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Gary Koop

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Joshua Chan & Gary Koop & Roberto Leon-Gonzalez & Rodney Strachan, 2011. "Time Varying Dimension Models," Working Papers 1116, University of Strathclyde Business School, Department of Economics.

    Mentioned in:

    1. Do not waste degrees of freedom with macro data
      by Economic Logician in Economic Logic on 2011-06-30 19:21:00
  2. Author Profile
    1. Top Forecasting Institutions and Researchers According to IDEAS!
      by Clive Jones in Business Forecasting on 2013-06-28 01:43:46
    2. Room for Improvement
      by Matthew Kahn in Environmental and Urban Economics on 2018-11-08 22:59:00

RePEc Biblio mentions

As found on the RePEc Biblio, the curated bibliography of Economics:
  1. Gary M. Koop, 2013. "Forecasting with Medium and Large Bayesian VARS," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(2), pages 177-203, March.

    Mentioned in:

    1. > Econometrics > Time Series Models > VAR Models > Bayesian Vector autoregressions (BVARs)
  2. Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2016. "Bayesian Compressed Vector Autoregressions," Working Papers 103, Brandeis University, Department of Economics and International Business School.

    Mentioned in:

    1. > Econometrics > Time Series Models > VAR Models > Bayesian Vector autoregressions (BVARs)
    2. > Econometrics > Big Data
  3. Nick Hanley & Robert Wright & Gary Koop, 2002. "Modelling Recreation Demand Using Choice Experiments: Climbing in Scotland," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 22(3), pages 449-466, July.

    Mentioned in:

    1. > Industrial Organization > Industry studies > Sports, recreation and tourism > Recreation
  4. Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2016. "Bayesian Compressed Vector Autoregressions," Working Papers 2016_09, Business School - Economics, University of Glasgow.

    Mentioned in:

    1. > Econometrics > Time Series Models > VAR Models > Bayesian Vector autoregressions (BVARs)
    2. > Econometrics > Big Data

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Koop, G, 1992. "Aggregate Shocks and Macroeconomic Fluctuations: A Bayesian Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(4), pages 395-411, Oct.-Dec..

    Mentioned in:

    1. Aggregate shocks and macroeconomic fluctuations: A bayesian approach (Journal of Applied Econometrics 1992) in ReplicationWiki ()
  2. Koop, Gary & Potter, Simon M., 2011. "Time varying VARs with inequality restrictions," Journal of Economic Dynamics and Control, Elsevier, vol. 35(7), pages 1126-1138, July.

    Mentioned in:

    1. Time varying VARs with inequality restrictions (JEDC 2011) in ReplicationWiki ()
  3. Koop, G & Poirier, D J, 1994. "Rank-Ordered Logit Models: An Empirical Analysis of Ontario Voter Preferences," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 9(4), pages 369-388, Oct.-Dec..

    Mentioned in:

    1. Rank-ordered logit models: An empirical analysis of Ontario voter preferences (Journal of Applied Econometrics 1994) in ReplicationWiki ()
  4. Koop, Gary, 1992. "Review of PCBRAP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(1), pages 105-107, Jan.-Marc.

    Mentioned in:

    1. Review of pcbrap (Journal of Applied Econometrics 1992) in ReplicationWiki ()
  5. Koop, Gary, 1999. "Bayesian Analysis, Computation and Communication Software," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(6), pages 677-689, Nov.-Dec..

    Mentioned in:

    1. Bayesian analysis, computation and communication software (Journal of Applied Econometrics 1999) in ReplicationWiki ()
  6. Koop, Gary & Tole, Lise, 1999. "Is there an environmental Kuznets curve for deforestation?," Journal of Development Economics, Elsevier, vol. 58(1), pages 231-244, February.

    Mentioned in:

    1. वनोन्मूलन in Wikipedia (Hindi)
    2. Krčenje gozdov in Wikipedia (Slovenian)
  7. Koop, Gary & Steel, Mark F J, 1991. "To Criticize the Critics: An Objective Bayesian Analysis of Stochastic Trends: A Comment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(4), pages 365-370, Oct.-Dec..

    Mentioned in:

    1. A comment on: ‘To criticize the critics: An objective bayesian analysis of stochastic trends’, By Peter C. B. Phillips (Journal of Applied Econometrics 1991) in ReplicationWiki ()
  8. Gary Koop & Simon M. Potter, 2007. "Estimation and Forecasting in Models with Multiple Breaks," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 74(3), pages 763-789.

    Mentioned in:

    1. Estimation and Forecasting in Models with Multiple Breaks (REStud 2007) in ReplicationWiki ()
  9. Joshua C. C. Chan & Gary Koop & Simon M. Potter, 2013. "A New Model of Trend Inflation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(1), pages 94-106, January.

    Mentioned in:

    1. A New Model of Trend Inflation (J Business & Econ Statistics 2013) in ReplicationWiki ()
  10. Koop, Gary, 1992. "'Objective' Bayesian Unit Root Tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(1), pages 65-82, Jan.-Marc.

    Mentioned in:

    1. ‘Objective’ bayesian unit root tests (Journal of Applied Econometrics 1992) in ReplicationWiki ()

Working papers

  1. Gary Koop & Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon & Ping Wu, 2023. "Incorporating Short Data into Large Mixed-Frequency VARs for Regional Nowcasting," Working Papers 23-09, Federal Reserve Bank of Cleveland.

    Cited by:

    1. Luca Barbaglia & Lorenzo Frattarolo & Niko Hauzenberger & Dominik Hirschbuehl & Florian Huber & Luca Onorante & Michael Pfarrhofer & Luca Tiozzo Pezzoli, 2024. "Nowcasting economic activity in European regions using a mixed-frequency dynamic factor model," Papers 2401.10054, arXiv.org.
    2. Josh Martin & Rebecca Riley, 2023. "Productivity measurement - Reassessing the production function from micro to macro," Working Papers 033, The Productivity Institute.

  2. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2022. "Reconciled Estimates of Monthly GDP in the US," Working Papers 22-01, Federal Reserve Bank of Cleveland.

    Cited by:

    1. Florens Odendahl & Barbara Rossi & Tatevik Sekhposyan, 2021. "Evaluating Forecast Performance with State Dependence," Working Papers 1295, Barcelona School of Economics.
    2. Ana Beatriz Galvão & James Mitchell, 2023. "Real‐Time Perceptions of Historical GDP Data Uncertainty," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 457-481, June.
    3. Chan, Joshua C.C. & Poon, Aubrey & Zhu, Dan, 2023. "High-dimensional conditionally Gaussian state space models with missing data," Journal of Econometrics, Elsevier, vol. 236(1).

  3. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2022. "Using stochastic hierarchical aggregation constraints to nowcast regional economic aggregates," Working Papers 22-06, Federal Reserve Bank of Cleveland.

    Cited by:

    1. George Athanasopoulos & Rob J Hyndman & Nikolaos Kourentzes & Anastasios Panagiotelis, 2023. "Forecast Reconciliation: A Review," Monash Econometrics and Business Statistics Working Papers 8/23, Monash University, Department of Econometrics and Business Statistics.

  4. Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino, 2022. "Forecasting US Inflation Using Bayesian Nonparametric Models," Papers 2202.13793, arXiv.org.

    Cited by:

    1. Petar Soric & Enric Monte & Salvador Torra & Oscar Claveria, 2022. ""Density forecasts of inflation using Gaussian process regression models"," IREA Working Papers 202210, University of Barcelona, Research Institute of Applied Economics, revised Jul 2022.
    2. Martin Gachter & Elias Hasler & Florian Huber, 2023. "A tale of two tails: 130 years of growth-at-risk," Papers 2302.08920, arXiv.org.
    3. Lenza, Michele & Moutachaker, Inès & Paredes, Joan, 2023. "Density forecasts of inflation: a quantile regression forest approach," Working Paper Series 2830, European Central Bank.
    4. Jan Pruser & Florian Huber, 2023. "Nonlinearities in Macroeconomic Tail Risk through the Lens of Big Data Quantile Regressions," Papers 2301.13604, arXiv.org, revised Sep 2023.
    5. Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2022. "Bayesian Forecasting in Economics and Finance: A Modern Review," Papers 2212.03471, arXiv.org, revised Jul 2023.
    6. Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.

  5. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2022. "Using hierarchical aggregation constraints to nowcast regional economic aggregates," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-04, Economic Statistics Centre of Excellence (ESCoE).

    Cited by:

    1. Luca Barbaglia & Lorenzo Frattarolo & Niko Hauzenberger & Dominik Hirschbuehl & Florian Huber & Luca Onorante & Michael Pfarrhofer & Luca Tiozzo Pezzoli, 2024. "Nowcasting economic activity in European regions using a mixed-frequency dynamic factor model," Papers 2401.10054, arXiv.org.
    2. George Athanasopoulos & Rob J Hyndman & Nikolaos Kourentzes & Anastasios Panagiotelis, 2023. "Forecast Reconciliation: A Review," Monash Econometrics and Business Statistics Working Papers 8/23, Monash University, Department of Econometrics and Business Statistics.

  6. Joshua C. C. Chan & Gary Koop & Xuewen Yu, 2021. "Large Order-Invariant Bayesian VARs with Stochastic Volatility," Papers 2111.07225, arXiv.org.

    Cited by:

    1. Joshua C. C. Chan & Xuewen Yu, 2022. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," Papers 2206.08438, arXiv.org.
    2. Chenghan Hou & Bao Nguyen & Bo Zhang, 2023. "Real‐time forecasting of the Australian macroeconomy using flexible Bayesian VARs," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 418-451, March.
    3. Florian Huber & Gary Koop, 2023. "Fast and Order-invariant Inference in Bayesian VARs with Non-Parametric Shocks," Papers 2305.16827, arXiv.org.
    4. Arias, Jonas E. & Rubio-Ramírez, Juan F. & Shin, Minchul, 2023. "Macroeconomic forecasting and variable ordering in multivariate stochastic volatility models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1054-1086.
    5. Ping Wu & Gary Koop, 2022. "Fast, Order-Invariant Bayesian Inference in VARs using the Eigendecomposition of the Error Covariance Matrix," Working Papers 2310, University of Strathclyde Business School, Department of Economics.
    6. Sune Karlsson & Stepan Mazur & Hoang Nguyen, 2021. "Vector autoregression models with skewness and heavy tails," Papers 2105.11182, arXiv.org.
    7. Wu, Ping & Koop, Gary, 2023. "Estimating the ordering of variables in a VAR using a Plackett–Luce prior," Economics Letters, Elsevier, vol. 230(C).
    8. Joshua Chan & Eric Eisenstat & Xuewen Yu, 2022. "Large Bayesian VARs with Factor Stochastic Volatility: Identification, Order Invariance and Structural Analysis," Papers 2207.03988, arXiv.org.
    9. Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2022. "Bayesian Forecasting in Economics and Finance: A Modern Review," Papers 2212.03471, arXiv.org, revised Jul 2023.
    10. Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
    11. Luis Gruber & Gregor Kastner, 2022. "Forecasting macroeconomic data with Bayesian VARs: Sparse or dense? It depends!," Papers 2206.04902, arXiv.org, revised Jul 2023.
    12. Prüser, Jan & Blagov, Boris, 2022. "Improving inference and forecasting in VAR models using cross-sectional information," Ruhr Economic Papers 960, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    13. Braun, Robin, 2021. "The importance of supply and demand for oil prices: evidence from non-Gaussianity," Bank of England working papers 957, Bank of England.

  7. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2021. "Nowcasting 'true' monthly US GDP during the pandemic," CAMA Working Papers 2021-14, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

    Cited by:

    1. Paul Ho, 2021. "Forecasting in the Absence of Precedent," Working Paper 21-10, Federal Reserve Bank of Richmond.
    2. Byron Botha & Rulof Burger & Kevin Kotze & Neil Rankin & Daan Steenkamp, 2022. "Big data forecasting of South African inflation," School of Economics Macroeconomic Discussion Paper Series 2022-03, School of Economics, University of Cape Town.

  8. Florian Huber & Gary Koop, 2021. "Subspace Shrinkage in Conjugate Bayesian Vector Autoregressions," Papers 2107.07804, arXiv.org.

    Cited by:

    1. Marcellino, Massimiliano & Clark, Todd & Huber, Florian & Koop, Gary, 2023. "Forecasting US Inflation Using Bayesian Nonparametric Models," CEPR Discussion Papers 18244, C.E.P.R. Discussion Papers.

  9. Martin Feldkircher & Florian Huber & Gary Koop & Michael Pfarrhofer, 2021. "Approximate Bayesian inference and forecasting in huge-dimensional multi-country VARs," Papers 2103.04944, arXiv.org, revised Feb 2022.

    Cited by:

    1. Dimitris Korobilis & Maximilian Schroder, 2023. "Monitoring multicountry macroeconomic risk," Papers 2305.09563, arXiv.org.
    2. Prüser, Jan & Blagov, Boris, 2022. "Improving inference and forecasting in VAR models using cross-sectional information," Ruhr Economic Papers 960, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.

  10. Jamie L. Cross & Chenghan Hou & Gary Koop, 2021. "Macroeconomic Forecasting with Large Stochastic Volatility in Mean VARs," Working Papers No 04/2021, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.

    Cited by:

    1. Matteo Iacopini & Francesco Ravazzolo & Luca Rossini, 2022. "Bayesian Multivariate Quantile Regression with alternative Time-varying Volatility Specifications," Papers 2211.16121, arXiv.org.
    2. Rub'en Loaiza-Maya & Didier Nibbering, 2022. "Efficient variational approximations for state space models," Papers 2210.11010, arXiv.org, revised Jun 2023.

  11. Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino & Michael Pfarrhofer, 2021. "Tail Forecasting with Multivariate Bayesian Additive Regression Trees," Working Papers 21-08R, Federal Reserve Bank of Cleveland, revised 12 Jul 2022.

    Cited by:

    1. Florian Huber & Josef Schreiner, 2023. "Are Phillips curves in CESEE still alive and well behaved?," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue Q3/23, pages 7-27.
    2. Tony Chernis & Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2023. "Predictive Density Combination Using a Tree-Based Synthesis Function," Working Papers 23-30, Federal Reserve Bank of Cleveland.
    3. Oyebayo Ridwan Olaniran & Ali Rashash R. Alzahrani, 2023. "On the Oracle Properties of Bayesian Random Forest for Sparse High-Dimensional Gaussian Regression," Mathematics, MDPI, vol. 11(24), pages 1-29, December.
    4. Jan Pruser & Florian Huber, 2023. "Nonlinearities in Macroeconomic Tail Risk through the Lens of Big Data Quantile Regressions," Papers 2301.13604, arXiv.org, revised Sep 2023.
    5. Philippe Goulet Coulombe & Mikael Frenette & Karin Klieber, 2023. "From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks," Papers 2311.16333, arXiv.org.
    6. Zhemkov, Michael, 2021. "Nowcasting Russian GDP using forecast combination approach," International Economics, Elsevier, vol. 168(C), pages 10-24.
    7. Joshua Chan, 2023. "BVARs and Stochastic Volatility," Papers 2310.14438, arXiv.org.
    8. Lenza, Michele & Moutachaker, Inès & Paredes, Joan, 2023. "Forecasting euro area inflation with machine-learning models," Research Bulletin, European Central Bank, vol. 112.
    9. Philippe Goulet Coulombe & Mikael Frenette & Karin Klieber, 2023. "From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks," Working Papers 23-04, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Nov 2023.

  12. Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino & Michael Pfarrhofer, 2021. "Investigating Growth at Risk Using a Multi-country Non-parametric Quantile Factor Model," Papers 2110.03411, arXiv.org.

    Cited by:

    1. Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    2. Dimitris Korobilis & Maximilian Schroder, 2023. "Monitoring multicountry macroeconomic risk," Papers 2305.09563, arXiv.org.
    3. Dimitris Korobilis & Maximilian Schröder, 2023. "Probabilistic Quantile Factor Analysis," Working Papers No 05/2023, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.

  13. Florian Huber & Gary Koop & Luca Onorante & Michael Pfarrhofer & Josef Schreiner, 2020. "Nowcasting in a Pandemic using Non-Parametric Mixed Frequency VARs," Papers 2008.12706, arXiv.org, revised Dec 2020.

    Cited by:

    1. Florian Huber & Josef Schreiner, 2023. "Are Phillips curves in CESEE still alive and well behaved?," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue Q3/23, pages 7-27.
    2. Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2023. "Bayesian Modeling of Time-Varying Parameters Using Regression Trees," Working Papers 23-05, Federal Reserve Bank of Cleveland.
    3. Eller, Markus & Hauzenberger, Niko & Huber, Florian & Schuberth, Helene & Vashold, Lukas, 2021. "The impact of macroprudential policies on capital flows in CESEE," Journal of International Money and Finance, Elsevier, vol. 119(C).
    4. David Kohns & Arnab Bhattacharjee, 2020. "Nowcasting Growth using Google Trends Data: A Bayesian Structural Time Series Model," Papers 2011.00938, arXiv.org, revised May 2022.
    5. Hwee Kwan Chow & Keen Meng Choy, 2023. "Economic forecasting in a pandemic: some evidence from Singapore," Empirical Economics, Springer, vol. 64(5), pages 2105-2124, May.
    6. Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2020. "Bayesian Modelling of TVP-VARs Using Regression Trees," Working Papers 2308, University of Strathclyde Business School, Department of Economics, revised Aug 2023.
    7. Martin Feldkircher & Florian Huber & Michael Pfarrhofer, 2020. "Measuring the Effectiveness of US Monetary Policy during the COVID-19 Recession," Papers 2007.15419, arXiv.org.
    8. Giovanni Ballarin & Petros Dellaportas & Lyudmila Grigoryeva & Marcel Hirt & Sophie van Huellen & Juan-Pablo Ortega, 2022. "Reservoir Computing for Macroeconomic Forecasting with Mixed Frequency Data," Papers 2211.00363, arXiv.org, revised Jan 2024.
    9. Florian Huber & Gary Koop, 2023. "Fast and Order-invariant Inference in Bayesian VARs with Non-Parametric Shocks," Papers 2305.16827, arXiv.org.
    10. Bobeica, Elena & Hartwig, Benny, 2023. "The COVID-19 shock and challenges for inflation modelling," International Journal of Forecasting, Elsevier, vol. 39(1), pages 519-539.
    11. Todd Clark & Florian Huber & Gary Koop & Massimiliano Marcellino & Michael Pfarrhofer, 2021. "Investigating Growth at Risk Using a Multi-country Non-parametric Quantile Factor Model," Working Papers 2307, University of Strathclyde Business School, Department of Economics.
    12. Paul Ho, 2021. "Forecasting in the Absence of Precedent," Working Paper 21-10, Federal Reserve Bank of Richmond.
    13. Karin Klieber, 2023. "Non-linear dimension reduction in factor-augmented vector autoregressions," Papers 2309.04821, arXiv.org.
    14. Serena Ng, 2021. "Modeling Macroeconomic Variations after Covid-19," NBER Working Papers 29060, National Bureau of Economic Research, Inc.
    15. Marcellino, Massimiliano & Clark, Todd & Huber, Florian & Koop, Gary & Pfarrhofer, Michael, 2022. "Tail Forecasting with Multivariate Bayesian Additive Regression Trees," CEPR Discussion Papers 17461, C.E.P.R. Discussion Papers.
    16. Richard Schnorrenberger & Aishameriane Schmidt & Guilherme Valle Moura, 2024. "Harnessing Machine Learning for Real-Time Inflation Nowcasting," Working Papers 806, DNB.
    17. Philippe Goulet Coulombe & Mikael Frenette & Karin Klieber, 2023. "From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks," Papers 2311.16333, arXiv.org.
    18. Martin Guth, 2022. "Predicting Default Probabilities for Stress Tests: A Comparison of Models," Papers 2202.03110, arXiv.org.
    19. Daniel Hopp, 2022. "Performance of long short-term memory artificial neural networks in nowcasting during the COVID-19 crisis," Papers 2203.11872, arXiv.org.
    20. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2021. "Addressing COVID-19 Outliers in BVARs with Stochastic Volatility," Working Papers 21-02R, Federal Reserve Bank of Cleveland, revised 09 Aug 2021.
    21. Hauzenberger, Niko & Huber, Florian & Klieber, Karin, 2023. "Real-time inflation forecasting using non-linear dimension reduction techniques," International Journal of Forecasting, Elsevier, vol. 39(2), pages 901-921.
    22. Niko Hauzenberger & Florian Huber & Karin Klieber & Massimiliano Marcellino, 2022. "Bayesian Neural Networks for Macroeconomic Analysis," Papers 2211.04752, arXiv.org, revised Apr 2024.
    23. Luca Barbaglia & Lorenzo Frattarolo & Niko Hauzenberger & Dominik Hirschbuehl & Florian Huber & Luca Onorante & Michael Pfarrhofer & Luca Tiozzo Pezzoli, 2024. "Nowcasting economic activity in European regions using a mixed-frequency dynamic factor model," Papers 2401.10054, arXiv.org.
    24. Iacopini, Matteo & Poon, Aubrey & Rossini, Luca & Zhu, Dan, 2023. "Bayesian mixed-frequency quantile vector autoregression: Eliciting tail risks of monthly US GDP," Journal of Economic Dynamics and Control, Elsevier, vol. 157(C).
    25. Tamás Kiss & Stepan Mazur & Hoang Nguyen & Pär Österholm, 2023. "Modeling the relation between the US real economy and the corporate bond‐yield spread in Bayesian VARs with non‐Gaussian innovations," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 347-368, March.
    26. Danilo Cascaldi-Garcia & Matteo Luciani & Michele Modugno, 2023. "Lessons from Nowcasting GDP across the World," International Finance Discussion Papers 1385, Board of Governors of the Federal Reserve System (U.S.).
    27. Zhemkov, Michael, 2021. "Nowcasting Russian GDP using forecast combination approach," International Economics, Elsevier, vol. 168(C), pages 10-24.
    28. Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2022. "Bayesian Forecasting in Economics and Finance: A Modern Review," Papers 2212.03471, arXiv.org, revised Jul 2023.
    29. Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
    30. Florian Huber & Massimiliano Marcellino, 2023. "Coarsened Bayesian VARs -- Correcting BVARs for Incorrect Specification," Papers 2304.07856, arXiv.org, revised May 2023.
    31. Kohns, David & Bhattacharjee, Arnab, 2023. "Nowcasting growth using Google Trends data: A Bayesian Structural Time Series model," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1384-1412.
    32. Barbaglia, Luca & Frattarolo, Lorenzo & Onorante, Luca & Pericoli, Filippo Maria & Ratto, Marco & Tiozzo Pezzoli, Luca, 2022. "Testing big data in a big crisis: Nowcasting under COVID-19," Working Papers 2022-06, Joint Research Centre, European Commission.
    33. Philippe Goulet Coulombe & Mikael Frenette & Karin Klieber, 2023. "From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks," Working Papers 23-04, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Nov 2023.
    34. Andrew J. Patton & Yasin Simsek, 2023. "Generalized Autoregressive Score Trees and Forests," Papers 2305.18991, arXiv.org.
    35. Kohns, David & Potjagailo, Galina, 2023. "Flexible Bayesian MIDAS: time‑variation, group‑shrinkage and sparsity," Bank of England working papers 1025, Bank of England.
    36. Hartwig, Benny, 2022. "Bayesian VARs and prior calibration in times of COVID-19," Discussion Papers 52/2022, Deutsche Bundesbank.
    37. Emilio Blanco & Fiorella Dogliolo & Lorena Garegnani, 2022. "Nowcasting during the Pandemic: Lessons from Argentina," BCRA Working Paper Series 202299, Central Bank of Argentina, Economic Research Department.

  14. Niko Hauzenberger & Florian Huber & Gary Koop, 2020. "Dynamic Shrinkage Priors for Large Time-varying Parameter Regressions using Scalable Markov Chain Monte Carlo Methods," Papers 2005.03906, arXiv.org, revised May 2023.

    Cited by:

    1. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    2. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.

  15. Galvao, Ana Beatriz & Owyang, Michael, 2020. "Forecasting Low Frequency Macroeconomic Events with High Frequency Data," EMF Research Papers 38, Economic Modelling and Forecasting Group.

    Cited by:

    1. Li, Dongxin & Zhang, Li & Li, Lihong, 2023. "Forecasting stock volatility with economic policy uncertainty: A smooth transition GARCH-MIDAS model," International Review of Financial Analysis, Elsevier, vol. 88(C).
    2. Serena Ng & Susannah Scanlan, 2023. "Constructing High Frequency Economic Indicators by Imputation," Papers 2303.01863, arXiv.org, revised Oct 2023.

  16. Florian Huber & Gary Koop & Michael Pfarrhofer, 2020. "Bayesian Inference in High-Dimensional Time-varying Parameter Models using Integrated Rotated Gaussian Approximations," Papers 2002.10274, arXiv.org.

    Cited by:

    1. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    2. Anna Pajor & Justyna Wróblewska, 2022. "Forecasting performance of Bayesian VEC-MSF models for financial data in the presence of long-run relationships," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(3), pages 427-448, September.
    3. Niko Hauzenberger & Florian Huber & Gary Koop, 2020. "Dynamic Shrinkage Priors for Large Time-varying Parameter Regressions using Scalable Markov Chain Monte Carlo Methods," Papers 2005.03906, arXiv.org, revised May 2023.
    4. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    5. Yousuf, Kashif & Ng, Serena, 2021. "Boosting high dimensional predictive regressions with time varying parameters," Journal of Econometrics, Elsevier, vol. 224(1), pages 60-87.
    6. Michael Pfarrhofer, 2020. "Forecasts with Bayesian vector autoregressions under real time conditions," Papers 2004.04984, arXiv.org.

  17. Deborah Gefang & Gary Koop & Aubrey Poon, 2019. "Variational Bayesian inference in large Vector Autoregressions with hierarchical shrinkage," CAMA Working Papers 2019-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

    Cited by:

    1. Joshua C. C. Chan & Xuewen Yu, 2022. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," Papers 2206.08438, arXiv.org.
    2. Deborah Gefang & Gary Koop & Aubrey Poon, 2020. "Computationally Efficient Inference in Large Bayesian Mixed Frequency VARs," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2020-07, Economic Statistics Centre of Excellence (ESCoE).
    3. Joshua C. C. Chan, 2019. "Large Bayesian vector autoregressions," CAMA Working Papers 2019-19, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    4. Michael W. McCracken & Serena Ng, 2021. "FRED-QD: A Quarterly Database for Macroeconomic Research," Review, Federal Reserve Bank of St. Louis, vol. 103(1), pages 1-44, January.
    5. Joshua C. C. Chan, 2019. "Minnesota-type adaptive hierarchical priors for large Bayesian VARs," CAMA Working Papers 2019-61, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    6. Mauro Bernardi & Daniele Bianchi & Nicolas Bianco, 2022. "Smoothing volatility targeting," Papers 2212.07288, arXiv.org.
    7. Matteo Iacopini & Luca Rossini, 2019. "Bayesian nonparametric graphical models for time-varying parameters VAR," Papers 1906.02140, arXiv.org.
    8. Mauro Bernardi & Daniele Bianchi & Nicolas Bianco, 2022. "Variational inference for large Bayesian vector autoregressions," Papers 2202.12644, arXiv.org, revised Jun 2023.

  18. Florian Huber & Gary Koop & Luca Onorante, 2019. "Inducing Sparsity and Shrinkage in Time-Varying Parameter Models," Papers 1905.10787, arXiv.org, revised Dec 2019.

    Cited by:

    1. Michael Pfarrhofer, 2019. "Measuring international uncertainty using global vector autoregressions with drifting parameters," Papers 1908.06325, arXiv.org, revised Dec 2019.
    2. Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2023. "Bayesian Modeling of Time-Varying Parameters Using Regression Trees," Working Papers 23-05, Federal Reserve Bank of Cleveland.
    3. David Kohns & Tibor Szendrei, 2021. "Decoupling Shrinkage and Selection for the Bayesian Quantile Regression," Papers 2107.08498, arXiv.org.
    4. Tsionas, Mike G. & Izzeldin, Marwan & Trapani, Lorenzo, 2022. "Estimation of large dimensional time varying VARs using copulas," European Economic Review, Elsevier, vol. 141(C).
    5. Martin Feldkircher & Florian Huber & Gary Koop & Michael Pfarrhofer, 2022. "APPROXIMATE BAYESIAN INFERENCE AND FORECASTING IN HUGE‐DIMENSIONAL MULTICOUNTRY VARs," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(4), pages 1625-1658, November.
    6. Niko Hauzenberger & Florian Huber & Luca Onorante, 2021. "Combining shrinkage and sparsity in conjugate vector autoregressive models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(3), pages 304-327, April.
    7. Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    8. David Kohns & Arnab Bhattacharjee, 2020. "Nowcasting Growth using Google Trends Data: A Bayesian Structural Time Series Model," Papers 2011.00938, arXiv.org, revised May 2022.
    9. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
    10. Ba Chu & Shafiullah Qureshi, 2021. "Comparing Out-of-Sample Performance of Machine Learning Methods to Forecast U.S. GDP Growth," Carleton Economic Papers 21-12, Carleton University, Department of Economics.
    11. Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2020. "Bayesian Modelling of TVP-VARs Using Regression Trees," Working Papers 2308, University of Strathclyde Business School, Department of Economics, revised Aug 2023.
    12. Mehmet Balcilar & Edmond Berisha & Rangan Gupta & Christian Pierdzioch, 2020. "Time-Varying Evidence of Predictability of Financial Stress in the United States over a Century: The Role of Inequality," Working Papers 202054, University of Pretoria, Department of Economics.
    13. Niko Hauzenberger & Florian Huber & Gary Koop, 2020. "Dynamic Shrinkage Priors for Large Time-varying Parameter Regressions using Scalable Markov Chain Monte Carlo Methods," Papers 2005.03906, arXiv.org, revised May 2023.
    14. Joseph P. Byrne & Boulis M. Ibrahim & Xiaoyu Zong, 2020. "Asset Prices and Capital Share Risks: Theory and Evidence," Papers 2006.14023, arXiv.org.
    15. Hu, Zhixiong & Prado, Raquel, 2023. "Fast Bayesian inference on spectral analysis of multivariate stationary time series," Computational Statistics & Data Analysis, Elsevier, vol. 178(C).
    16. Magnus Reif, 2021. "Time-Varying Dynamics of the German Business Cycle: A Comprehensive Investigation," CESifo Working Paper Series 9271, CESifo.
    17. Hauzenberger, Niko & Huber, Florian & Klieber, Karin, 2023. "Real-time inflation forecasting using non-linear dimension reduction techniques," International Journal of Forecasting, Elsevier, vol. 39(2), pages 901-921.
    18. Niko Hauzenberger & Florian Huber & Karin Klieber & Massimiliano Marcellino, 2022. "Bayesian Neural Networks for Macroeconomic Analysis," Papers 2211.04752, arXiv.org, revised Apr 2024.
    19. Crespo Cuaresma, Jesús & Huber, Florian & Onorante, Luca, 2020. "Fragility and the effect of international uncertainty shocks," Journal of International Money and Finance, Elsevier, vol. 108(C).
    20. Florian Huber & Gary Koop & Michael Pfarrhofer, 2020. "Bayesian Inference in High-Dimensional Time-varying Parameter Models using Integrated Rotated Gaussian Approximations," Papers 2002.10274, arXiv.org.
    21. Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2022. "Bayesian Forecasting in Economics and Finance: A Modern Review," Papers 2212.03471, arXiv.org, revised Jul 2023.
    22. Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
    23. Joshua C.C. Chan & Rodney W. Strachan, 2023. "Bayesian State Space Models In Macroeconometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 58-75, February.
    24. Michael Stanley Smith, 2021. "Implicit Copulas: An Overview," Papers 2109.04718, arXiv.org.
    25. Rub'en Loaiza-Maya & Didier Nibbering, 2022. "Efficient variational approximations for state space models," Papers 2210.11010, arXiv.org, revised Jun 2023.
    26. Florian Huber & Luca Rossini, 2020. "Inference in Bayesian Additive Vector Autoregressive Tree Models," Papers 2006.16333, arXiv.org, revised Mar 2021.
    27. Kohns, David & Bhattacharjee, Arnab, 2023. "Nowcasting growth using Google Trends data: A Bayesian Structural Time Series model," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1384-1412.
    28. Lin Liu, 2022. "Economic Uncertainty and Exchange Market Pressure: Evidence From China," SAGE Open, , vol. 12(1), pages 21582440211, January.
    29. Smith, Michael Stanley, 2023. "Implicit Copulas: An Overview," Econometrics and Statistics, Elsevier, vol. 28(C), pages 81-104.
    30. Cross, Jamie L. & Hou, Chenghan & Poon, Aubrey, 2020. "Macroeconomic forecasting with large Bayesian VARs: Global-local priors and the illusion of sparsity," International Journal of Forecasting, Elsevier, vol. 36(3), pages 899-915.
    31. Kohns, David & Potjagailo, Galina, 2023. "Flexible Bayesian MIDAS: time‑variation, group‑shrinkage and sparsity," Bank of England working papers 1025, Bank of England.

  19. Niko Hauzenberger & Florian Huber & Gary Koop & Luca Onorante, 2019. "Fast and Flexible Bayesian Inference in Time-varying Parameter Regression Models," Papers 1910.10779, arXiv.org, revised Sep 2021.

    Cited by:

    1. Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2023. "Bayesian Modeling of Time-Varying Parameters Using Regression Trees," Working Papers 23-05, Federal Reserve Bank of Cleveland.
    2. Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2020. "Bayesian Modelling of TVP-VARs Using Regression Trees," Working Papers 2308, University of Strathclyde Business School, Department of Economics, revised Aug 2023.
    3. Florian Huber & Gary Koop, 2023. "Fast and Order-invariant Inference in Bayesian VARs with Non-Parametric Shocks," Papers 2305.16827, arXiv.org.
    4. Niko Hauzenberger & Florian Huber & Gary Koop, 2020. "Dynamic Shrinkage Priors for Large Time-varying Parameter Regressions using Scalable Markov Chain Monte Carlo Methods," Papers 2005.03906, arXiv.org, revised May 2023.
    5. Fischer, Manfred M. & Hauzenberger, Niko & Huber, Florian & Pfarrhofer, Michael, 2022. "General Bayesian time-varying parameter VARs for modeling government bond yields," Working Papers in Regional Science 2021/01, WU Vienna University of Economics and Business.
    6. Hauzenberger, Niko & Huber, Florian & Klieber, Karin, 2023. "Real-time inflation forecasting using non-linear dimension reduction techniques," International Journal of Forecasting, Elsevier, vol. 39(2), pages 901-921.
    7. Peter Knaus & Sylvia Fruhwirth-Schnatter, 2023. "The Dynamic Triple Gamma Prior as a Shrinkage Process Prior for Time-Varying Parameter Models," Papers 2312.10487, arXiv.org.
    8. Florian Huber & Gary Koop & Michael Pfarrhofer, 2020. "Bayesian Inference in High-Dimensional Time-varying Parameter Models using Integrated Rotated Gaussian Approximations," Papers 2002.10274, arXiv.org.
    9. Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2022. "Bayesian Forecasting in Economics and Finance: A Modern Review," Papers 2212.03471, arXiv.org, revised Jul 2023.
    10. Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
    11. Manfred M. Fischer & Niko Hauzenberger & Florian Huber & Michael Pfarrhofer, 2021. "General Bayesian time-varying parameter VARs for predicting government bond yields," Papers 2102.13393, arXiv.org.
    12. Wenting Liao & Xin Sheng & Rangan Gupta & Sayar Karmakar, 2024. "Extreme Weather Shocks and State-Level Inflation of the United States," Working Papers 202402, University of Pretoria, Department of Economics.

  20. Joshua Chan & Luca Benati & Eric Eisenstat & Gary Koop, 2018. "Identifying Noise Shocks," Working Paper Series 41, Economics Discipline Group, UTS Business School, University of Technology, Sydney.

    Cited by:

    1. Luca Benati & Thomas A. Lubik, 2022. "Searching for Hysteresis," Working Paper 22-05, Federal Reserve Bank of Richmond.
    2. Ansgar Belke & Steffen Elstner & Svetlana Rujin, 2022. "Growth Prospects and the Trade Balance in Advanced Economies," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(5), pages 1209-1234, October.
    3. Luca Gambetti & Christoph Görtz & Dimitris Korobilis & John D. Tsoukalas & Francesco Zanetti, 2022. "The Effect of News Shocks and Monetary Policy," Advances in Econometrics, in: Essays in Honour of Fabio Canova, volume 44, pages 139-164, Emerald Group Publishing Limited.

  21. Koop, G & Korobilis, D, 2018. "Forecasting with High-Dimensional Panel VARs," Essex Finance Centre Working Papers 21329, University of Essex, Essex Business School.

    Cited by:

    1. Gefang, Deborah & Koop, Gary & Poon, Aubrey, 2023. "Forecasting using variational Bayesian inference in large vector autoregressions with hierarchical shrinkage," International Journal of Forecasting, Elsevier, vol. 39(1), pages 346-363.
    2. Deborah Gefang & Gary Koop & Aubrey Poon, 2019. "Variational Bayesian inference in large Vector Autoregressions with hierarchical shrinkage," CAMA Working Papers 2019-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    3. Malovaná, Simona & Frait, Jan, 2017. "Monetary policy and macroprudential policy: Rivals or teammates?," Journal of Financial Stability, Elsevier, vol. 32(C), pages 1-16.
    4. Camehl, Annika, 2023. "Penalized estimation of panel vector autoregressive models: A panel LASSO approach," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1185-1204.
    5. Schnücker, A.M., 2019. "Penalized Estimation of Panel Vector Autoregressive Models," Econometric Institute Research Papers EI-2019-33, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. Beckmann, Joscha & Czudaj, Robert, 2017. "Capital flows and GDP in emerging economies and the role of global spillovers," Journal of Economic Behavior & Organization, Elsevier, vol. 142(C), pages 140-163.
    7. Francesco Simone Lucidi, 2021. "The Misalignment of Fiscal Multipliers in Italian Regions," Working Papers in Public Economics 204, University of Rome La Sapienza, Department of Economics and Law.
    8. Bebonchu Atems, 2020. "Identifying the Dynamic Effects of Income Inequality on Crime," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(4), pages 751-782, August.
    9. David Martinez-Miera & Rafael Repullo, 2019. "Monetary Policy, Macroprudential Policy, and Financial Stability," Working Papers wp2019_1901, CEMFI.
    10. Florian Huber & Tam'as Krisztin & Michael Pfarrhofer, 2018. "A Bayesian panel VAR model to analyze the impact of climate change on high-income economies," Papers 1804.01554, arXiv.org, revised Feb 2021.
    11. Marcellino, Massimiliano & Bai, Yu & Carriero, Andrea & Clark, Todd, 2022. "Macroeconomic Forecasting in a Multi-country Context," CEPR Discussion Papers 16994, C.E.P.R. Discussion Papers.
    12. Marcellino, Massimiliano & Foroni, Claudia & Casarin, Roberto & Ravazzolo, Francesco, 2017. "Uncertainty Through the Lenses of A Mixed-Frequency Bayesian Panel Markov Switching Model," CEPR Discussion Papers 12339, C.E.P.R. Discussion Papers.
    13. Christou, Christina & Gupta, Rangan & Hassapis, Christis, 2017. "Does economic policy uncertainty forecast real housing returns in a panel of OECD countries? A Bayesian approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 65(C), pages 50-60.
    14. Florian Huber & Michael Pfarrhofer & Philipp Piribauer, 2020. "A multi-country dynamic factor model with stochastic volatility for euro area business cycle analysis," Papers 2001.03935, arXiv.org.
    15. Joan Costa-i-Font & Cristina Vilaplana-Prieto, 2022. "'Investing' in Care for Old Age? An Examination of Long-Term Care Expenditure Dynamics and Its Spillovers," CESifo Working Paper Series 9553, CESifo.
    16. Alexey Ponomarenko & Anna Rozhkova & Sergei Seleznev, 2018. "Macro-financial linkages: the role of liquidity dependence," BIS Working Papers 716, Bank for International Settlements.
    17. Basher, Syed Abul & Haug, Alfred A. & Sadorsky, Perry, 2019. "The impact of economic policy uncertainty and commodity prices on CARB country stock market volatility," MPRA Paper 96577, University Library of Munich, Germany.
    18. Christina Christou & Juncal Cunado & Rangan Gupta & Christis Hassapis, 2016. "Economic Policy Uncertainty and Stock Market Returns in Pacific-Rim Countries: Evidence based on a Bayesian Panel VAR Model," Working Papers 201661, University of Pretoria, Department of Economics.
    19. Camehl, Annika & von Schweinitz, Gregor, 2023. "What explains international interest rate co-movement?," IWH Discussion Papers 3/2023, Halle Institute for Economic Research (IWH), revised 2023.
    20. Florian Huber & Gary Koop, 2023. "Subspace shrinkage in conjugate Bayesian vector autoregressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 556-576, June.
    21. Laura Liu & Christian Matthes & Katerina Petrova & Jessica Sackett Romero, 2019. "Monetary Policy across Space and Time," Richmond Fed Economic Brief, Federal Reserve Bank of Richmond, issue August.
    22. Sheereen Fauzel* & Boopen Seetanah & RV Sannassee, 2015. "Foreign direct investment and welfare nexus in sub Saharan Africa," Journal of Developing Areas, Tennessee State University, College of Business, vol. 49(4), pages 271-283, October-D.
    23. Beechey, Meredith & Österholm, Pär & Poon, Aubrey, 2023. "Estimating the US trend short-term interest rate," Finance Research Letters, Elsevier, vol. 55(PA).
    24. Davidson, Sharada Nia, 2020. "Interdependence or contagion: A model switching approach with a focus on Latin America," Economic Modelling, Elsevier, vol. 85(C), pages 166-197.

  22. Joshua C.C. Chan & Eric Eisenstat & Chenghan Hou & Gary Koop, 2018. "Composite likelihood methods for large Bayesian VARs with stochastic volatility," CAMA Working Papers 2018-26, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

    Cited by:

    1. Miranda-Agrippino, Silvia & Ricco, Giovanni, 2018. "Bayesian vector autoregressions," LSE Research Online Documents on Economics 87393, London School of Economics and Political Science, LSE Library.
    2. Canova, Fabio & Matthes, Christian, 2018. "A composite likelihood approach for dynamic structural models," CEPR Discussion Papers 13245, C.E.P.R. Discussion Papers.
    3. Joshua C. C. Chan, 2022. "Comparing Stochastic Volatility Specifications for Large Bayesian VARs," Papers 2208.13255, arXiv.org.
    4. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
    5. Gunawan, David & Kohn, Robert & Nott, David, 2021. "Variational Bayes approximation of factor stochastic volatility models," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1355-1375.
    6. Jan Pruser & Florian Huber, 2023. "Nonlinearities in Macroeconomic Tail Risk through the Lens of Big Data Quantile Regressions," Papers 2301.13604, arXiv.org, revised Sep 2023.
    7. Laumer, Sebastian, 2020. "Government spending and heterogeneous consumption dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 114(C).
    8. Kerem Tuzcuoglu, 2019. "Composite Likelihood Estimation of an Autoregressive Panel Probit Model with Random Effects," Staff Working Papers 19-16, Bank of Canada.
    9. Raanju R. Sundararajan & Wagner Barreto‐Souza, 2023. "Student‐t stochastic volatility model with composite likelihood EM‐algorithm," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(1), pages 125-147, January.
    10. Gianluca Cubadda & Stefano Grassi & Barbara Guardabascio, 2024. "The Time-Varying Multivariate Autoregressive Index Model," CEIS Research Paper 571, Tor Vergata University, CEIS, revised 10 Jan 2024.
    11. Matteo Iacopini & Luca Rossini, 2019. "Bayesian nonparametric graphical models for time-varying parameters VAR," Papers 1906.02140, arXiv.org.
    12. Yuliya Rychalovska & Sergey Slobodyan & Rafael Wouters, 2023. "Professional Survey Forecasts and Expectations in DSGE Models," CERGE-EI Working Papers wp766, The Center for Economic Research and Graduate Education - Economics Institute, Prague.

  23. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2018. "Regional Output Growth in the United Kingdom: More Timely and Higher Frequency Estimates, 1970-2017," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-14, Economic Statistics Centre of Excellence (ESCoE).

    Cited by:

    1. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2022. "Reconciled Estimates of Monthly GDP in the US," Working Papers 22-01, Federal Reserve Bank of Cleveland.
    2. Florian, Huber & Koop, Gary & Onorante, Luca & Pfarrhofer, Michael & Schreiner, Josef, 2021. "Nowcasting in a Pandemic using Non-Parametric Mixed Frequency VARs," Working Papers 2021-01, Joint Research Centre, European Commission.
    3. Tony Chernis & Calista Cheung & Gabriella Velasco, 2017. "A Three-Frequency Dynamic Factor Model for Nowcasting Canadian Provincial GDP Growth," Discussion Papers 17-8, Bank of Canada.
    4. Sensier, Marianne & Devine, Fiona, 2020. "Understanding Regional Economic Performance And Resilience In The Uk: Trends Since The Global Financial Crisis," National Institute Economic Review, National Institute of Economic and Social Research, vol. 253, pages 18-28, August.
    5. Deborah Gefang & Gary Koop & Aubrey Poon, 2020. "Computationally Efficient Inference in Large Bayesian Mixed Frequency VARs," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2020-07, Economic Statistics Centre of Excellence (ESCoE).
    6. Luke Mosley & Idris A. Eckley & Alex Gibberd, 2022. "Sparse temporal disaggregation," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 2203-2233, October.
    7. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2020. "Regional output growth in the United Kingdom: More timely and higher frequency estimates from 1970," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(2), pages 176-197, March.
    8. Meredith M. Paker, 2020. "The Jobless Recovery After the 1980-1981 UK Recession," Oxford Economic and Social History Working Papers _182, University of Oxford, Department of Economics.
    9. María Gil & Danilo Leiva-Leon & Javier J. Pérez & Alberto Urtasun, 2019. "An application of dynamic factor models to nowcast regional economic activity in Spain," Occasional Papers 1904, Banco de España.
    10. Luke Mosley & Idris Eckley & Alex Gibberd, 2021. "Sparse Temporal Disaggregation," Papers 2108.05783, arXiv.org, revised Oct 2022.

  24. Gary Koop & Stuart McIntyre & James Mitchell, 2018. "UK Regional Nowcasting using a Mixed Frequency Vector Autoregressive Model," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-07, Economic Statistics Centre of Excellence (ESCoE).

    Cited by:

    1. Koop, Gary & McIntyre, Stuart & Mitchell, James & Poon, Aubrey, 2019. "Regional Output Growth in the United Kingdom: More Timely and Higher Frequency Estimates, 1970-2017," EMF Research Papers 20, Economic Modelling and Forecasting Group.
    2. Tony Chernis & Calista Cheung & Gabriella Velasco, 2017. "A Three-Frequency Dynamic Factor Model for Nowcasting Canadian Provincial GDP Growth," Discussion Papers 17-8, Bank of Canada.
    3. Concha Artola & María Gil & Javier J. Pérez & Alberto Urtasun & Alejandro Fiorito & Diego Vila, 2018. "Monitoring the Spanish economy from a regional perspective: main elements of analysis," Occasional Papers 1809, Banco de España.

  25. Gary Koop & Dimitris Korobilis, 2018. "Bayesian dynamic variable selection in high dimensions," Papers 1809.03031, arXiv.org, revised May 2020.

    Cited by:

    1. David T. Frazier & Gael M. Martin & Ruben Loaiza-Maya, 2022. "Variational Bayes in State Space Models: Inferential and Predictive Accuracy," Monash Econometrics and Business Statistics Working Papers 1/22, Monash University, Department of Econometrics and Business Statistics.
    2. Dimitris Korobilis & Kenichi Shimizu, 2021. "Bayesian Approaches to Shrinkage and Sparse Estimation," Working Papers 2021_19, Business School - Economics, University of Glasgow.
    3. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    4. Luo, Jiawen & Klein, Tony & Walther, Thomas & Ji, Qiang, 2021. "Forecasting Realized Volatility of Crude Oil Futures Prices based on Machine Learning," QBS Working Paper Series 2021/04, Queen's University Belfast, Queen's Business School.
    5. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    6. Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2020. "Point and Density Forecasting of Macroeconomic and Financial Uncertainties of the United States," Working Papers 202058, University of Pretoria, Department of Economics.
    7. Zhao, Jing, 2023. "Time-varying impact of geopolitical risk on natural resources prices: Evidence from the hybrid TVP-VAR model with large system," Resources Policy, Elsevier, vol. 82(C).
    8. Cepni, Oguzhan & Clements, Michael P., 2024. "How local is the local inflation factor? Evidence from emerging European countries," International Journal of Forecasting, Elsevier, vol. 40(1), pages 160-183.
    9. Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2021. "Point and density forecasting of macroeconomic and financial uncertainties of the USA," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(4), pages 700-707, July.
    10. Mauro Bernardi & Daniele Bianchi & Nicolas Bianco, 2022. "Smoothing volatility targeting," Papers 2212.07288, arXiv.org.
    11. Salisu, Afees A. & Tchankam, Jean Paul, 2022. "US Stock return predictability with high dimensional models," Finance Research Letters, Elsevier, vol. 45(C).
    12. Yousuf, Kashif & Ng, Serena, 2021. "Boosting high dimensional predictive regressions with time varying parameters," Journal of Econometrics, Elsevier, vol. 224(1), pages 60-87.

  26. Korobilis, Dimitris & Koop, Gary, 2018. "Variational Bayes inference in high-dimensional time-varying parameter models," Essex Finance Centre Working Papers 22665, University of Essex, Essex Business School.

    Cited by:

    1. Joshua C. C. Chan & Xuewen Yu, 2022. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," Papers 2206.08438, arXiv.org.
    2. Deborah Gefang & Gary Koop & Aubrey Poon, 2019. "Variational Bayesian inference in large Vector Autoregressions with hierarchical shrinkage," CAMA Working Papers 2019-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    3. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    4. Deborah Gefang & Gary Koop & Aubrey Poon, 2020. "Computationally Efficient Inference in Large Bayesian Mixed Frequency VARs," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2020-07, Economic Statistics Centre of Excellence (ESCoE).
    5. Gael M. Martin & David T. Frazier & Christian P. Robert, 2020. "Computing Bayes: Bayesian Computation from 1763 to the 21st Century," Monash Econometrics and Business Statistics Working Papers 14/20, Monash University, Department of Econometrics and Business Statistics.
    6. David T. Frazier & Ruben Loaiza-Maya & Gael M. Martin & Bonsoo Koo, 2021. "Loss-Based Variational Bayes Prediction," Monash Econometrics and Business Statistics Working Papers 8/21, Monash University, Department of Econometrics and Business Statistics.
    7. Badi Baltagi & Georges Bresson & Jean-Michel Etienne, 2020. "Growth Empirics: A Bayesian Semiparametric Model with Random Coefficients for a Panel of OECD Countries," Center for Policy Research Working Papers 229, Center for Policy Research, Maxwell School, Syracuse University.
    8. Reza Hajargasht, 2019. "Approximation Properties of Variational Bayes for Vector Autoregressions," Papers 1903.00617, arXiv.org.
    9. Dimitris Korobilis, 2018. "Machine Learning Macroeconometrics: A Primer," Working Paper series 18-30, Rimini Centre for Economic Analysis.
    10. Chaya Weerasinghe & Ruben Loaiza-Maya & Gael M. Martin & David T. Frazier, 2023. "ABC-based Forecasting in State Space Models," Monash Econometrics and Business Statistics Working Papers 12/23, Monash University, Department of Econometrics and Business Statistics.
    11. Florian Huber & Gary Koop & Michael Pfarrhofer, 2020. "Bayesian Inference in High-Dimensional Time-varying Parameter Models using Integrated Rotated Gaussian Approximations," Papers 2002.10274, arXiv.org.
    12. Barbara Rossi, 2019. "Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them," Economics Working Papers 1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
    13. Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2022. "Bayesian Forecasting in Economics and Finance: A Modern Review," Papers 2212.03471, arXiv.org, revised Jul 2023.
    14. Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
    15. Rub'en Loaiza-Maya & Didier Nibbering, 2022. "Efficient variational approximations for state space models," Papers 2210.11010, arXiv.org, revised Jun 2023.
    16. Matteo Iacopini & Luca Rossini, 2019. "Bayesian nonparametric graphical models for time-varying parameters VAR," Papers 1906.02140, arXiv.org.
    17. Gael M. Martin & David T. Frazier & Christian P. Robert, 2021. "Approximating Bayes in the 21st Century," Monash Econometrics and Business Statistics Working Papers 24/21, Monash University, Department of Econometrics and Business Statistics.

  27. Beckmann, J & Koop, G & Korobilis, D & Schüssler, R, 2017. "Exchange rate predictability and dynamic Bayesian learning," Essex Finance Centre Working Papers 20781, University of Essex, Essex Business School.

    Cited by:

    1. Hauzenberger, Niko & Huber, Florian, 2018. "Model instability in predictive exchange rate regressions," Department of Economics Working Paper Series 276, WU Vienna University of Economics and Business.
    2. Xin Sheng & Rangan Gupta & Afees A. Salisu & Elie Bouri, 2021. "OPEC News and Exchange Rate Forecasting Using Dynamic Bayesian Learning," Working Papers 202101, University of Pretoria, Department of Economics.
    3. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
    4. Knotek, Edward S. & Zaman, Saeed, 2023. "Real-time density nowcasts of US inflation: A model combination approach," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1736-1760.
    5. Svatopluk Kapounek & Evžen Kocenda & Zuzana Kucerová, 2021. "Selective Attention in Exchange Rate Forecasting," CESifo Working Paper Series 8901, CESifo.
    6. Nonejad, Nima, 2021. "Predicting equity premium using dynamic model averaging. Does the state–space representation matter?," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    7. Yuhyeon Bak & Cheolbeom Park, 2020. "Exchange Rate Predictability, Risk Premiums, and Predictive System," Discussion Paper Series 2006, Institute of Economic Research, Korea University.
    8. Hauzenberger, Niko & Huber, Florian & Klieber, Karin, 2023. "Real-time inflation forecasting using non-linear dimension reduction techniques," International Journal of Forecasting, Elsevier, vol. 39(2), pages 901-921.
    9. Niko Hauzenberger & Florian Huber & Karin Klieber & Massimiliano Marcellino, 2022. "Bayesian Neural Networks for Macroeconomic Analysis," Papers 2211.04752, arXiv.org, revised Apr 2024.
    10. Gianluca Cubadda & Stefano Grassi & Barbara Guardabascio, 2024. "The Time-Varying Multivariate Autoregressive Index Model," CEIS Research Paper 571, Tor Vergata University, CEIS, revised 10 Jan 2024.
    11. Yemba, Boniface P. & Otunuga, Olusegun Michael & Tang, Biyan & Biswas, Nabaneeta, 2023. "Nowcasting of the Short-run Euro-Dollar Exchange Rate with Economic Fundamentals and Time-varying Parameters," Finance Research Letters, Elsevier, vol. 52(C).
    12. Bruno P. C. Levy & Hedibert F. Lopes, 2021. "Dynamic Ordering Learning in Multivariate Forecasting," Papers 2101.04164, arXiv.org, revised Nov 2021.
    13. Nonejad, Nima, 2020. "Crude oil price volatility and equity return predictability: A comparative out-of-sample study," International Review of Financial Analysis, Elsevier, vol. 71(C).
    14. Niklas Valentin Lehmann, 2023. "Forecasting skill of a crowd-prediction platform: A comparison of exchange rate forecasts," Papers 2312.09081, arXiv.org.
    15. Davidson, Sharada Nia, 2020. "Interdependence or contagion: A model switching approach with a focus on Latin America," Economic Modelling, Elsevier, vol. 85(C), pages 166-197.

  28. Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2016. "Bayesian Compressed Vector Autoregressions," Working Papers 103, Brandeis University, Department of Economics and International Business School.

    Cited by:

    1. Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2023. "Large Time‐Varying Volatility Models for Hourly Electricity Prices," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 545-573, June.
    2. Gary Koop & Dimitris Korobilis, 2018. "Forecasting with High-Dimensional Panel VARs," Working Paper series 18-20, Rimini Centre for Economic Analysis.
    3. Miranda-Agrippino, Silvia & Ricco, Giovanni, 2018. "Bayesian vector autoregressions," LSE Research Online Documents on Economics 87393, London School of Economics and Political Science, LSE Library.
    4. Tsionas, Mike G. & Izzeldin, Marwan & Trapani, Lorenzo, 2022. "Estimation of large dimensional time varying VARs using copulas," European Economic Review, Elsevier, vol. 141(C).
    5. Martin Feldkircher & Florian Huber & Gary Koop & Michael Pfarrhofer, 2022. "APPROXIMATE BAYESIAN INFERENCE AND FORECASTING IN HUGE‐DIMENSIONAL MULTICOUNTRY VARs," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(4), pages 1625-1658, November.
    6. Daniel Felix Ahelegbey & Monica Billio & Roberto Casarin, 2020. "Modeling Turning Points In Global Equity Market," DEM Working Papers Series 195, University of Pavia, Department of Economics and Management.
    7. Matteo Mogliani & Anna Simoni, 2020. "Bayesian MIDAS penalized regressions: Estimation, selection, and prediction," Post-Print hal-03089878, HAL.
    8. Crespo Cuaresma, Jesus & Doppelhofer, Gernot & Feldkircher, Martin & Huber, Florian, 2018. "Spillovers from US monetary policy: Evidence from a time-varying parameter GVAR model," Working Papers in Economics 2018-6, University of Salzburg.
    9. Dimitris Korobilis & Kenichi Shimizu, 2021. "Bayesian Approaches to Shrinkage and Sparse Estimation," Working Papers 2021_19, Business School - Economics, University of Glasgow.
    10. Amaze Lusompa, 2021. "Local Projections, Autocorrelation, and Efficiency," Research Working Paper RWP 21-01, Federal Reserve Bank of Kansas City.
    11. Dimitris Korobilis & Davide Pettenuzzo, 2017. "Adaptive Hierarchical Priors for High-Dimensional Vector Autoregessions," Working Papers 115, Brandeis University, Department of Economics and International Business School.
    12. Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2020. "Large Time-Varying Volatility Models for Electricity Prices," Working Papers No 05/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    13. Jesús Crespo Cuaresma & Gernot Doppelhofer & Martin Feldkircher & Florian Huber, 2019. "Spillovers from US monetary policy: evidence from a time varying parameter global vector auto‐regressive model," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 182(3), pages 831-861, June.
    14. Dimitris Korobilis & Davide Pettenuzzo, 2020. "Machine Learning Econometrics: Bayesian algorithms and methods," Working Papers 2020_09, Business School - Economics, University of Glasgow.
    15. Boot, Tom & Nibbering, Didier, 2019. "Forecasting using random subspace methods," Journal of Econometrics, Elsevier, vol. 209(2), pages 391-406.
    16. Joshua C. C. Chan, 2019. "Large Bayesian vector autoregressions," CAMA Working Papers 2019-19, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    17. Mike G. Tsionas, 2016. "Alternatives to large VAR, VARMA and multivariate stochastic volatility models," Working Papers 217, Bank of Greece.
    18. Gregor Kastner & Florian Huber, 2020. "Sparse Bayesian vector autoregressions in huge dimensions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1142-1165, November.
    19. Roberto Casarin & Fausto Corradin & Francesco Ravazzolo & Nguyen Domenico Sartore, 2020. "A Scoring Rule for Factor and Autoregressive Models Under Misspecification," Advances in Decision Sciences, Asia University, Taiwan, vol. 24(2), pages 66-103, June.
    20. Spyros Makridakis & Andreas Merikas & Anna Merika & Mike G. Tsionas & Marwan Izzeldin, 2020. "A novel forecasting model for the Baltic dry index utilizing optimal squeezing," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(1), pages 56-68, January.
    21. Maximilian Bock & Martin Feldkircher & Pierre L. Siklos, 2020. "International effects of euro area forward guidance," CAMA Working Papers 2020-54, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    22. Emmanuel C. Mamatzakis & Steven Ongena & Mike G. Tsionas, 2023. "The response of household debt to COVID-19 using a neural networks VAR in OECD," Empirical Economics, Springer, vol. 65(1), pages 65-91, July.
    23. Assaf, A. George & Tsionas, Mike G., 2019. "Forecasting occupancy rate with Bayesian compression methods," Annals of Tourism Research, Elsevier, vol. 75(C), pages 439-449.
    24. Mike Tsionas & Marwan Izzeldin & Lorenzo Trapani, 2019. "Bayesian estimation of large dimensional time varying VARs using copulas," Papers 1912.12527, arXiv.org.
    25. Shabeer Khan & Mirzat Ullah & Mohammad Rahim Shahzad & Uzair Abdullah Khan & Umair Khan & Sayed M. Eldin & Abeer M. Alotaibi, 2022. "Spillover Connectedness among Global Uncertainties and Sectorial Indices of Pakistan: Evidence from Quantile Connectedness Approach," Sustainability, MDPI, vol. 14(23), pages 1-16, November.
    26. Rangan Gupta & Chi Keung Marco Lau & Vasilios Plakandaras & Wing-Keung Wong, 2018. "The Role of Housing Sentiment in Forecasting US Home Sales Growth: Evidence from a Bayesian Compressed Vector Autoregressive Model," Working Papers 201842, University of Pretoria, Department of Economics.
    27. Florian Huber & Gary Koop & Michael Pfarrhofer, 2020. "Bayesian Inference in High-Dimensional Time-varying Parameter Models using Integrated Rotated Gaussian Approximations," Papers 2002.10274, arXiv.org.
    28. Barbara Rossi, 2019. "Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them," Economics Working Papers 1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
    29. Carlos Carvalho & Jared D. Fisher & Davide Pettenuzzo, 2018. "Optimal Asset Allocation with Multivariate Bayesian Dynamic Linear Models," Working Papers 123, Brandeis University, Department of Economics and International Business School.
    30. Joshua C.C. Chan & Rodney W. Strachan, 2023. "Bayesian State Space Models In Macroeconometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 58-75, February.
    31. Florian Huber & Luca Rossini, 2020. "Inference in Bayesian Additive Vector Autoregressive Tree Models," Papers 2006.16333, arXiv.org, revised Mar 2021.
    32. Cross, Jamie, 2019. "On the reduced macroeconomic volatility of the Australian economy: Good policy or good luck?," Economic Modelling, Elsevier, vol. 77(C), pages 174-186.
    33. Dimitrios P. Louzis, 2019. "Steady‐state modeling and macroeconomic forecasting quality," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(2), pages 285-314, March.
    34. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano, 2019. "Large Bayesian vector autoregressions with stochastic volatility and non-conjugate priors," Journal of Econometrics, Elsevier, vol. 212(1), pages 137-154.
    35. Gupta, Rangan & Sun, Xiaojin, 2020. "Forecasting economic policy uncertainty of BRIC countries using Bayesian VARs," Economics Letters, Elsevier, vol. 186(C).
    36. Matteo Iacopini & Luca Rossini, 2019. "Bayesian nonparametric graphical models for time-varying parameters VAR," Papers 1906.02140, arXiv.org.
    37. Mike G. Tsionas, 2016. "Alternative Bayesian compression in Vector Autoregressions and related models," Working Papers 216, Bank of Greece.
    38. Sebastian Ankargren & Paulina Jon'eus, 2019. "Estimating Large Mixed-Frequency Bayesian VAR Models," Papers 1912.02231, arXiv.org.
    39. Yousuf, Kashif & Ng, Serena, 2021. "Boosting high dimensional predictive regressions with time varying parameters," Journal of Econometrics, Elsevier, vol. 224(1), pages 60-87.
    40. Minerva Mukhopadhyay & David B. Dunson, 2020. "Targeted Random Projection for Prediction From High-Dimensional Features," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(532), pages 1998-2010, December.
    41. Daniel Felix Ahelegbey & Luis Carvalho & Eric D. Kolaczyk, 2020. "A Bayesian Covariance Graph And Latent Position Model For Multivariate Financial Time Series," DEM Working Papers Series 181, University of Pavia, Department of Economics and Management.

  29. BAUWENS, Luc & KOOP, Gary & KOROBILIS, Dimitris & ROMBOUTS, Jeroen, 2015. "The Contribution of Structural Break Models to Forecating Macroeconomic Series," LIDAM Reprints CORE 2651, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Wensheng Kang & Jing Wang, 2018. "Oil shocks, policy uncertainty and earnings surprises," Review of Quantitative Finance and Accounting, Springer, vol. 51(2), pages 375-388, August.
    2. Markku Lanne & Jani Luoto, 2017. "A New Time‐Varying Parameter Autoregressive Model for U.S. Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 969-995, August.
    3. Timmermann, Allan & Pettenuzzo, Davide, 2016. "Forecasting Macroeconomic Variables under Model Instability," CEPR Discussion Papers 11355, C.E.P.R. Discussion Papers.
    4. Gary Koop & Dimitris Korobilis, 2018. "Forecasting with High-Dimensional Panel VARs," Working Paper series 18-20, Rimini Centre for Economic Analysis.
    5. Korobilis, Dimitris & Koop, Gary, 2020. "Bayesian dynamic variable selection in high dimensions," MPRA Paper 100164, University Library of Munich, Germany.
    6. Mark Fisher & Mark J. Jensen, 2018. "Bayesian Inference and Prediction of a Multiple-Change-Point Panel Model with Nonparametric Priors," FRB Atlanta Working Paper 2018-2, Federal Reserve Bank of Atlanta.
    7. Koop, Gary & Korobilis, Dimitris, 2018. "Variational Bayes inference in high-dimensional time-varying parameter models," MPRA Paper 87972, University Library of Munich, Germany.
    8. Kirsten Thompson & Renee Van Eyden & Rangan Gupta, 2015. "Identifying an index of financial conditions for South Africa," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 32(2), pages 256-274, June.
    9. Chiu, Ching-Wai (Jeremy) & Mumtaz, Haroon & Pintér, Gábor, 2017. "Forecasting with VAR models: Fat tails and stochastic volatility," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1124-1143.
    10. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    11. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
    12. Hou, Chenghan, 2017. "Infinite hidden markov switching VARs with application to macroeconomic forecast," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1025-1043.
    13. Dufays, Arnaud & Rombouts, Jeroen V.K., 2020. "Relevant parameter changes in structural break models," Journal of Econometrics, Elsevier, vol. 217(1), pages 46-78.
    14. Korobilis, D, 2017. "Forecasting with many predictors using message passing algorithms," Essex Finance Centre Working Papers 19565, University of Essex, Essex Business School.
    15. Nonejad, Nima, 2017. "Forecasting aggregate stock market volatility using financial and macroeconomic predictors: Which models forecast best, when and why?," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 131-154.
    16. Eo, Yunjong, 2015. "Structural Changes in Inflation Dynamics: Multiple Breaks at Different Dates for Different Parameters," Working Papers 2015-18, University of Sydney, School of Economics, revised Nov 2015.
    17. KOROBILIS, Dimitris, 2011. "VAR forecasting using Bayesian variable selection," LIDAM Discussion Papers CORE 2011022, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    18. Ewing, Bradley T. & Kang, Wensheng & Ratti, Ronald A., 2018. "The dynamic effects of oil supply shocks on the US stock market returns of upstream oil and gas companies," Energy Economics, Elsevier, vol. 72(C), pages 505-516.
    19. Markku Lanne & Jani Luoto, 2016. "Noncausal Bayesian Vector Autoregression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1392-1406, November.
    20. Franz Ruch & Mehmet Balcilar Author-Name-First Mehmet & Mampho P. Modise & Rangan Gupta, 2015. "Forecasting Core Inflation: The Case of South Africa," Working Papers 15-08, Eastern Mediterranean University, Department of Economics.
    21. Dimitris Korobilis, 2020. "High-dimensional macroeconomic forecasting using message passing algorithms," Papers 2004.11485, arXiv.org.
    22. Ardia, David & Dufays, Arnaud & Ordás Criado, Carlos, 2023. "Linking Frequentist and Bayesian Change-Point Methods," MPRA Paper 119486, University Library of Munich, Germany.
    23. Chen, Ji & Yang, Xinglin & Liu, Xiliang, 2022. "Learning, disagreement and inflation forecasting," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    24. Arnaud Dufays & Jeroen V.K. Rombouts, 2016. "Sparse Change-point HAR Models for Realized Variance," Cahiers de recherche 1607, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
    25. Nonejad Nima, 2015. "Particle Gibbs with ancestor sampling for stochastic volatility models with: heavy tails, in mean effects, leverage, serial dependence and structural breaks," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(5), pages 561-584, December.
    26. Yu Jeffrey Hu & Jeroen Rombouts & Ines Wilms, 2023. "Fast Forecasting of Unstable Data Streams for On-Demand Service Platforms," Papers 2303.01887, arXiv.org.
    27. C. Y. Tan & Y. B. Koh & K. H. Ng & K. H. Ng, 2019. "Structural Change Analysis of Active Cryptocurrency Market," Papers 1909.10679, arXiv.org.
    28. Pierre L. Siklos, 2020. "Looking into the Rear-View Mirror: Lessons from Japan for the Eurozone and the U.S?," IMES Discussion Paper Series 20-E-02, Institute for Monetary and Economic Studies, Bank of Japan.
    29. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    30. Gary Koop & Dimitris Korompilis, 2009. "UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So?," Working Papers 0917, University of Strathclyde Business School, Department of Economics.
    31. Czinkota, Thomas, 2012. "Das Halteproblem bei Strukturbrüchen in Finanzmarktzeitreihen [The Halting Problem applied to Structural Breaks in Financial Time Series]," MPRA Paper 37072, University Library of Munich, Germany.
    32. Luis Uzeda, 2018. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," Staff Working Papers 18-14, Bank of Canada.
    33. Kascha, Christian & Trenkler, Carsten, 2015. "Forecasting VARs, model selection, and shrinkage," Working Papers 15-07, University of Mannheim, Department of Economics.
    34. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    35. Elena Afanasyeva, 2020. "Can Forecast Errors Predict Financial Crises? Exploring the Properties of a New Multivariate Credit Gap," Finance and Economics Discussion Series 2020-045, Board of Governors of the Federal Reserve System (U.S.).
    36. BAUWENS, Luc & DE BACKER, Bruno & DUFAYS, Arnaud, 2014. "A Bayesian method of change-point estimation with recurrent regimes: application to GARCH models," LIDAM Reprints CORE 2641, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    37. Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2020. "Point and Density Forecasting of Macroeconomic and Financial Uncertainties of the United States," Working Papers 202058, University of Pretoria, Department of Economics.
    38. Hossein Hassani & Zara Ghodsi & Rangan Gupta & Mawuli K. Segnon, 2014. "Forecasting Home Sales in the Four Census Regions and the Aggregate US Economy Using Singular Spectrum Analysis," Working Papers 201482, University of Pretoria, Department of Economics.
    39. McKnight, Stephen & Mihailov, Alexander & Rumler, Fabio, 2020. "Inflation forecasting using the New Keynesian Phillips Curve with a time-varying trend," Economic Modelling, Elsevier, vol. 87(C), pages 383-393.
    40. Wensheng Kang & Ronald A. Ratti & Kyung Hwan Yoon, 2015. "Time-varying effect of oil market shocks on the stock market," CAMA Working Papers 2015-35, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    41. Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2021. "Point and density forecasting of macroeconomic and financial uncertainties of the USA," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(4), pages 700-707, July.
    42. Feiyu Jiang & Zifeng Zhao & Xiaofeng Shao, 2022. "Modelling the COVID‐19 infection trajectory: A piecewise linear quantile trend model," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(5), pages 1589-1607, November.
    43. Todd E. Clark & Taeyoung Doh, 2011. "A Bayesian evaluation of alternative models of trend inflation," Working Papers (Old Series) 1134, Federal Reserve Bank of Cleveland.
    44. Augustyniak, Maciej & Dufays, Arnaud, 2018. "Modeling macroeconomic series with regime-switching models characterized by a high-dimensional state space," Economics Letters, Elsevier, vol. 170(C), pages 122-126.
    45. Kirsten Thompson & Reneé van Eyden & Rangan Gupta, 2015. "Testing the Out-of-Sample Forecasting Ability of a Financial Conditions Index for South Africa," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 51(3), pages 486-501, May.
    46. Arnaud Dufays & Zhuo Li & Jeroen V.K. Rombouts & Yong Song, 2021. "Sparse change‐point VAR models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(6), pages 703-727, September.
    47. Eraslan, Sercan & Schröder, Maximilian, 2019. "Nowcasting GDP with a large factor model space," Discussion Papers 41/2019, Deutsche Bundesbank.
    48. Jiang, Feiyu & Zhao, Zifeng & Shao, Xiaofeng, 2023. "Time series analysis of COVID-19 infection curve: A change-point perspective," Journal of Econometrics, Elsevier, vol. 232(1), pages 1-17.
    49. Nonejad, Nima, 2020. "Crude oil price changes and the United Kingdom real gross domestic product growth rate: An out-of-sample investigation," The Journal of Economic Asymmetries, Elsevier, vol. 21(C).
    50. Sylvia Kaufmann, 2016. "Hidden Markov models in time series, with applications in economics," Working Papers 16.06, Swiss National Bank, Study Center Gerzensee.
    51. Dimitrios P. Louzis, 2016. "Macroeconomic forecasting and structural changes in steady states," Working Papers 204, Bank of Greece.

  30. Joshua C. C. Chan & Todd E. Clark & Gary Koop, 2015. "A New Model of Inflation, Trend Inflation, and Long-Run Inflation Expectations," Working Papers (Old Series) 1520, Federal Reserve Bank of Cleveland.

    Cited by:

    1. Bańbura, Marta & Leiva-Leon, Danilo & Menz, Jan-Oliver, 2021. "Do inflation expectations improve model-based inflation forecasts?," Working Paper Series 2604, European Central Bank.
    2. Geraldine Dany-Knedlik & Juan Angel Garcia, 2018. "Monetary Policy and Inflation Dynamics in ASEAN Economies," IMF Working Papers 2018/147, International Monetary Fund.
    3. Mengheng Li & Siem Jan Koopman, 2021. "Unobserved components with stochastic volatility: Simulation‐based estimation and signal extraction," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 614-627, August.
    4. Juan Angel Garcia & Sebastian Werner, 2018. "Inflation News and Euro Area Inflation Expectations," IMF Working Papers 2018/167, International Monetary Fund.
    5. Manuel M. F. Martins & Fabio Verona, 2020. "Forecasting Inflation with the New Keynesian Phillips Curve: Frequency Matters," CEF.UP Working Papers 2001, Universidade do Porto, Faculdade de Economia do Porto.
    6. Takushi Kurozumi & Willem Van Zandweghe, 2021. "Macroeconomic Changes with Declining Trend Inflation: Complementarity with the Superstar Firm Hypothesis," Bank of Japan Working Paper Series 21-E-13, Bank of Japan.
    7. Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    8. Marente Vlekke & Martin Mellens & Siem Jan Koopmans, 2020. "An assessment of the Phillips curve over time: evidence for the United States and the euro area," CPB Discussion Paper 416, CPB Netherlands Bureau for Economic Policy Analysis.
    9. Martins, Manuel Mota Freitas & Verona, Fabio, 2021. "Inflation dynamics and forecast: Frequency matters," Bank of Finland Research Discussion Papers 8/2021, Bank of Finland.
    10. Florian Huber & Daniel Kaufmann, 2015. "Trend Fundamentals and Exchange Rate Dynamics," KOF Working papers 15-393, KOF Swiss Economic Institute, ETH Zurich.
    11. Diegel, Max, 2022. "Time-varying credibility, anchoring and the Fed's inflation target," Discussion Papers 2022/9, Free University Berlin, School of Business & Economics.
    12. Francesca Rondina, 2018. "Estimating unobservable inflation expectations in the New Keynesian Phillips Curve," Working Papers 1804E, University of Ottawa, Department of Economics.
    13. Ellis W. Tallman & Saeed Zaman, 2015. "Forecasting Inflation: Phillips Curve Effects on Services Price Measures," Working Papers (Old Series) 1519, Federal Reserve Bank of Cleveland.
    14. Bańbura, Marta & Bobeica, Elena, 2023. "Does the Phillips curve help to forecast euro area inflation?," International Journal of Forecasting, Elsevier, vol. 39(1), pages 364-390.
    15. Dany-Knedlik, Geraldine & Holtemöller, Oliver, 2018. "Inflation dynamics during the Financial Crisis in Europe: cross-sectional identification of long-run inflation expectations," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181520, Verein für Socialpolitik / German Economic Association.
    16. Elizaveta Lukmanova & Katrin Rabitsch, 2018. "New VAR evidence on monetary transmission channels: temporary interest rate versus inflation target shocks," Working Papers of Department of Economics, Leuven 630040, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    17. Juan Angel Garcia & Aubrey Poon, 2018. "Trend Inflation and Inflation Compensation," IMF Working Papers 2018/154, International Monetary Fund.
    18. García, Juan Angel & Poon, Aubrey, 2019. "Inflation trends in Asia: implications for central banks," Working Paper Series 2338, European Central Bank.
    19. Arnoud Stevens & Joris Wauters, 2021. "Is euro area lowflation here to stay? Insights from a time‐varying parameter model with survey data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 566-586, August.
    20. Pär Österholm & Aubrey Poon, 2023. "Trend Inflation in Sweden," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 4707-4716, October.
    21. Chen, Ji & Yang, Xinglin & Liu, Xiliang, 2022. "Learning, disagreement and inflation forecasting," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    22. Christina Anderl & Guglielmo Maria Caporale, 2023. "Forecasting inflation with a zero lower bound or negative interest rates: Evidence from point and density forecasts," Manchester School, University of Manchester, vol. 91(3), pages 171-232, June.
    23. Marcelo Arbex & Sidney Caetano & Wilson Correa, 2018. "Macroeconomic Effects of Inflation Target Uncertainty Shocks," Working Papers 1804, University of Windsor, Department of Economics.
    24. Jmaes McNeil, 2020. "Monetary policy and the term structure of Inflation expectations with information frictions," Working Papers daleconwp2020-07, Dalhousie University, Department of Economics.
    25. Kamber, Güneş & Wong, Benjamin, 2020. "Global factors and trend inflation," Journal of International Economics, Elsevier, vol. 122(C).
    26. Andrew B. Martinez, 2020. "Extracting Information from Different Expectations," Working Papers 2020-008, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    27. Diegel, Max & Nautz, Dieter, 2021. "Long-term inflation expectations and the transmission of monetary policy shocks: Evidence from a SVAR analysis," Journal of Economic Dynamics and Control, Elsevier, vol. 130(C).
    28. Hauzenberger, Niko & Huber, Florian & Klieber, Karin, 2023. "Real-time inflation forecasting using non-linear dimension reduction techniques," International Journal of Forecasting, Elsevier, vol. 39(2), pages 901-921.
    29. Semmler, Willi & Gross, Marco, 2017. "Mind the output gap: the disconnect of growth and inflation during recessions and convex Phillips curves in the euro area," Working Paper Series 2004, European Central Bank.
    30. N. Kundan Kishor & Evan F. Koenig, 2016. "The roles of inflation expectations, core inflation, and slack in real-time inflation forecasting," Working Papers 1613, Federal Reserve Bank of Dallas.
    31. Saeed Zaman, 2021. "A Unified Framework to Estimate Macroeconomic Stars," Working Papers 21-23R, Federal Reserve Bank of Cleveland, revised 15 Aug 2022.
    32. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Working Papers 22-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    33. Richard K. Crump & Stefano Eusepi & Emanuel Moench & Bruce Preston, 2021. "The Term Structure of Expectations," Staff Reports 992, Federal Reserve Bank of New York.
    34. Hauber, Philipp & Schumacher, Christian, 2021. "Precision-based sampling with missing observations: A factor model application," Discussion Papers 11/2021, Deutsche Bundesbank.
    35. Andriantomanga, Zo, 2023. "The role of survey-based expectations in real-time forecasting of US inflation," MPRA Paper 119904, University Library of Munich, Germany.
    36. Lenza, Michele & Jarociński, Marek, 2016. "An inflation-predicting measure of the output gap in the euro area," Working Paper Series 1966, European Central Bank.
    37. Murasawa, Yasutomo, 2019. "Bayesian multivariate Beveridge--Nelson decomposition of I(1) and I(2) series with cointegration," MPRA Paper 91979, University Library of Munich, Germany.
    38. Bańbura, Marta & Bobeica, Elena, 2020. "PCCI – a data-rich measure of underlying inflation in the euro area," Statistics Paper Series 38, European Central Bank.
    39. Bowen Fu, Ivan Mendieta-Muñoz, 2023. "Structural shocks and trend inflation," Working Paper Series, Department of Economics, University of Utah 2023_04, University of Utah, Department of Economics.
    40. Beechey, Meredith & Österholm, Pär & Poon, Aubrey, 2023. "Estimating the US trend short-term interest rate," Finance Research Letters, Elsevier, vol. 55(PA).
    41. Martin Feldkircher & Pierre L. Siklos, 2018. "Global inflation dynamics and inflation expectations," CAMA Working Papers 2018-60, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    42. Jaromir Baxa & Miroslav Plasil & Borek Vasicek, 2013. "Inflation and the Steeplechase Between Economic Activity Variables," Working Papers 2013/15, Czech National Bank.
    43. Diegel, Max & Nautz, Dieter, 2020. "The role of long-term inflation expectations for the transmission of monetary policy shocks," Discussion Papers 2020/19, Free University Berlin, School of Business & Economics.
    44. Chew Lian Chua & Tim Robinson, 2018. "Why Has Australian Wages Growth Been So Low? A Phillips Curve Perspective," The Economic Record, The Economic Society of Australia, vol. 94(S1), pages 11-32, June.
    45. Cecchetti, Stephen & Feroli, Michael & Hooper, Peter & Kashyap, Anil & Schoenholtz, Kermit L., 2017. "Deflating Inflation Expectations: The Implications of Inflation’s Simple Dynamics," CEPR Discussion Papers 11925, C.E.P.R. Discussion Papers.
    46. Fu, Bowen, 2020. "Is the slope of the Phillips curve time-varying? Evidence from unobserved components models," Economic Modelling, Elsevier, vol. 88(C), pages 320-340.
    47. Kristin Forbes, 2019. "Has globalization changed the inflation process?," BIS Working Papers 791, Bank for International Settlements.
    48. Marta Banbura & Andries van Vlodrop, 2018. "Forecasting with Bayesian Vector Autoregressions with Time Variation in the Mean," Tinbergen Institute Discussion Papers 18-025/IV, Tinbergen Institute.
    49. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Papers 2202.04146, arXiv.org.
    50. Koester, Gerrit & Lis, Eliza & Nickel, Christiane & Osbat, Chiara & Smets, Frank, 2021. "Understanding low inflation in the euro area from 2013 to 2019: cyclical and structural drivers," Occasional Paper Series 280, European Central Bank.
    51. Helder Ferreira de Mendonça & Pedro Mendes Garcia & José Valentim Machado Vicente, 2021. "Rationality and anchoring of inflation expectations: An assessment from survey‐based and market‐based measures," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(6), pages 1027-1053, September.
    52. Aubrey Poon, 2018. "Assessing the Synchronicity and Nature of Australian State Business Cycles," The Economic Record, The Economic Society of Australia, vol. 94(307), pages 372-390, December.
    53. James Mitchell & Saeed Zaman, 2023. "The Distributional Predictive Content of Measures of Inflation Expectations," Working Papers 23-31, Federal Reserve Bank of Cleveland.
    54. Lukmanova, Elizaveta & Rabitsch, Katrin, 2023. "Evidence on monetary transmission and the role of imperfect information: Interest rate versus inflation target shocks," European Economic Review, Elsevier, vol. 158(C).

  31. Allan, Grant & Koop, Gary & McIntyre, Stuart & Smith, Paul, 2014. "Nowcasting Scottish GDP Growth," SIRE Discussion Papers 2015-08, Scottish Institute for Research in Economics (SIRE).

    Cited by:

    1. Knotek, Edward S. & Zaman, Saeed, 2023. "Real-time density nowcasts of US inflation: A model combination approach," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1736-1760.
    2. María Gil & Danilo Leiva-Leon & Javier J. Pérez & Alberto Urtasun, 2019. "An application of dynamic factor models to nowcast regional economic activity in Spain," Occasional Papers 1904, Banco de España.

  32. Koop, Gary & Korobilis, Dimitris, 2014. "Model Uncertainty in Panel Vector Autoregressive Models," SIRE Discussion Papers 2014-011, Scottish Institute for Research in Economics (SIRE).

    Cited by:

    1. Gefang, Deborah & Koop, Gary & Poon, Aubrey, 2023. "Forecasting using variational Bayesian inference in large vector autoregressions with hierarchical shrinkage," International Journal of Forecasting, Elsevier, vol. 39(1), pages 346-363.
    2. Gary Koop & Dimitris Korobilis, 2018. "Forecasting with High-Dimensional Panel VARs," Working Paper series 18-20, Rimini Centre for Economic Analysis.
    3. Thomas Goda, Santiago Sánchez, 2022. "Export Market Size Matters: The effect of the market size of export destinations on manufacturing growth," Documentos de Trabajo de Valor Público 20531, Universidad EAFIT.
    4. Deborah Gefang & Gary Koop & Aubrey Poon, 2019. "Variational Bayesian inference in large Vector Autoregressions with hierarchical shrinkage," CAMA Working Papers 2019-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    5. Martin Feldkircher & Florian Huber & Gary Koop & Michael Pfarrhofer, 2022. "APPROXIMATE BAYESIAN INFERENCE AND FORECASTING IN HUGE‐DIMENSIONAL MULTICOUNTRY VARs," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(4), pages 1625-1658, November.
    6. Georgios Magkonis & Simon Rudkin, 2019. "Does Trilemma Speak Chinese?," Working Papers in Economics & Finance 2019-01, University of Portsmouth, Portsmouth Business School, Economics and Finance Subject Group.
    7. Billio, Monica & Casarin, Roberto & Rossini, Luca, 2019. "Bayesian nonparametric sparse VAR models," Journal of Econometrics, Elsevier, vol. 212(1), pages 97-115.
    8. Joshua C.C. Chan & Eric Eisenstat & Chenghan Hou & Gary Koop, 2018. "Composite likelihood methods for large Bayesian VARs with stochastic volatility," CAMA Working Papers 2018-26, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    9. Camehl, Annika, 2023. "Penalized estimation of panel vector autoregressive models: A panel LASSO approach," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1185-1204.
    10. Dimitris Korobilis & Kenichi Shimizu, 2021. "Bayesian Approaches to Shrinkage and Sparse Estimation," Working Papers 2021_19, Business School - Economics, University of Glasgow.
    11. Schnücker, A.M., 2019. "Penalized Estimation of Panel Vector Autoregressive Models," Econometric Institute Research Papers EI-2019-33, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    12. Florian Huber & Daniel Kaufmann, 2015. "Trend Fundamentals and Exchange Rate Dynamics," KOF Working papers 15-393, KOF Swiss Economic Institute, ETH Zurich.
    13. Fang Ye, 2023. "The New Development Bank and the structure of the multilateral development financial system," Review of Development Economics, Wiley Blackwell, vol. 27(3), pages 1957-1972, August.
    14. Wang, Shengquan & Chen, Langnan & Xiong, Xiong, 2019. "Asset bubbles, banking stability and economic growth," Economic Modelling, Elsevier, vol. 78(C), pages 108-117.
    15. Florian Huber & Tam'as Krisztin & Michael Pfarrhofer, 2018. "A Bayesian panel VAR model to analyze the impact of climate change on high-income economies," Papers 1804.01554, arXiv.org, revised Feb 2021.
    16. Marcellino, Massimiliano & Bai, Yu & Carriero, Andrea & Clark, Todd, 2022. "Macroeconomic Forecasting in a Multi-country Context," CEPR Discussion Papers 16994, C.E.P.R. Discussion Papers.
    17. Anthony Orji & Jonathan E. Ogbuabor & Chiamaka F. Okolomike & Onyinye I. Anthony-Orji, 2022. "Do Capital Inflows and Financial Development, Influence Economic Growth in West Africa? Further Evidence from Transmission Mechanisms," Econometric Research in Finance, SGH Warsaw School of Economics, Collegium of Economic Analysis, vol. 7(1), pages 71-94.
    18. Till Weigt & Bernd Wilfling, 2018. "An approach to increasing forecast-combination accuracy through VAR error modeling," CQE Working Papers 6818, Center for Quantitative Economics (CQE), University of Muenster.
    19. Samuel F. Onipede & Nafiu A. Bashir & Jamaladeen Abubakar, 2023. "Small open economies and external shocks: an application of Bayesian global vector autoregression model," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(2), pages 1673-1699, April.
    20. Christou, Christina & Gupta, Rangan & Hassapis, Christis, 2017. "Does economic policy uncertainty forecast real housing returns in a panel of OECD countries? A Bayesian approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 65(C), pages 50-60.
    21. Mark F. J. Steel, 2020. "Model Averaging and Its Use in Economics," Journal of Economic Literature, American Economic Association, vol. 58(3), pages 644-719, September.
    22. Annalisa Marini & Steve McCorriston, 2019. "Price Transmission in Commodity Networks," Discussion Papers 1903, University of Exeter, Department of Economics.
    23. Schnücker, Annika, 2016. "Restrictions Search for Panel VARs," VfS Annual Conference 2016 (Augsburg): Demographic Change 145566, Verein für Socialpolitik / German Economic Association.
    24. Marini, Annalisa, 2020. "The Impact of Weather on Commodity Prices: A Warning for the Future," MPRA Paper 104572, University Library of Munich, Germany.
    25. Hazar Altınbaş & Vincenzo Pacelli & Edgardo Sica, 2022. "An Empirical Assessment of the Contagion Determinants in the Euro Area in a Period of Sovereign Debt Risk," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 8(2), pages 339-371, July.
    26. Ters, Kristyna & Urban, Jörg, 2018. "Intraday dynamics of credit risk contagion before and during the euro area sovereign debt crisis: Evidence from central Europe," International Review of Economics & Finance, Elsevier, vol. 54(C), pages 123-142.
    27. Matheus Koengkan & José Alberto Fuinhas, 2022. "The Interactions Between Renewable Energy Consumption, Economic Growth, and Globalisation: Fresh Evidence from the Mercosur Countries," Springer Books, in: Globalisation and Energy Transition in Latin America and the Caribbean, chapter 0, pages 63-99, Springer.
    28. Annika Schnücker, 2016. "Restrictions Search for Panel VARs," Discussion Papers of DIW Berlin 1612, DIW Berlin, German Institute for Economic Research.
    29. Ferry Syarifuddin, 2020. "Macroeconomic Consequences Of Foreign Exchange Futures," Working Papers WP/14/2020, Bank Indonesia.
    30. Huang, Yingying & Duan, Kun & Mishra, Tapas, 2021. "Is Bitcoin really more than a diversifier? A pre- and post-COVID-19 analysis," Finance Research Letters, Elsevier, vol. 43(C).
    31. Dimitris Korobilis., 2015. "Prior selection for panel vector autoregressions," Working Papers 2015_10, Business School - Economics, University of Glasgow.
    32. Renato Santiago & Matheus Koengkan & José Alberto Fuinhas & António Cardoso Marques, 2020. "The relationship between public capital stock, private capital stock and economic growth in the Latin American and Caribbean countries," International Review of Economics, Springer;Happiness Economics and Interpersonal Relations (HEIRS), vol. 67(3), pages 293-317, September.
    33. Ozcan, Burcu & Tzeremes, Panayiotis G. & Tzeremes, Nickolaos G., 2020. "Energy consumption, economic growth and environmental degradation in OECD countries," Economic Modelling, Elsevier, vol. 84(C), pages 203-213.
    34. Lubos Komarek & Kristyna Ters, 2016. "Intraday dynamics of euro area sovereign credit risk contagion," BIS Working Papers 573, Bank for International Settlements.
    35. Jesús Crespo Cuaresma & Martin Feldkircher & Florian Huber, 2016. "Forecasting with Global Vector Autoregressive Models: a Bayesian Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1371-1391, November.
    36. Antonio Pacifico, 2021. "Structural Panel Bayesian VAR with Multivariate Time-Varying Volatility to Jointly Deal with Structural Changes, Policy Regime Shifts, and Endogeneity Issues," Econometrics, MDPI, vol. 9(2), pages 1-35, May.
    37. Beckmann, Joscha & Davidson, Sharada Nia & Koop, Gary & Schüssler, Rainer, 2023. "Cross-country uncertainty spillovers: Evidence from international survey data," Journal of International Money and Finance, Elsevier, vol. 130(C).
    38. Michelle, Gilmartin, 2016. "A note on the identification and transmission of energy demand and supply shocks," MPRA Paper 76186, University Library of Munich, Germany.
    39. Joshua Chan, 2023. "BVARs and Stochastic Volatility," Papers 2310.14438, arXiv.org.
    40. Liao, Jun & Zong, Xianpeng & Zhang, Xinyu & Zou, Guohua, 2019. "Model averaging based on leave-subject-out cross-validation for vector autoregressions," Journal of Econometrics, Elsevier, vol. 209(1), pages 35-60.
    41. Christina Christou & Juncal Cunado & Rangan Gupta & Christis Hassapis, 2016. "Economic Policy Uncertainty and Stock Market Returns in Pacific-Rim Countries: Evidence based on a Bayesian Panel VAR Model," Working Papers 201661, University of Pretoria, Department of Economics.
    42. Camehl, Annika & von Schweinitz, Gregor, 2023. "What explains international interest rate co-movement?," IWH Discussion Papers 3/2023, Halle Institute for Economic Research (IWH), revised 2023.
    43. Syarifuddin, Ferry, 2020. "Macroeconomic Consequences of Foreign Exchange Futures Market for Inflation Targeting Economies," MPRA Paper 104810, University Library of Munich, Germany.
    44. Hongbo Liu & Shuanglu Liang & Qingbo Cui, 2020. "The Nexus between Economic Complexity and Energy Consumption under the Context of Sustainable Environment: Evidence from the LMC Countries," IJERPH, MDPI, vol. 18(1), pages 1-14, December.
    45. Prüser, Jan & Blagov, Boris, 2022. "Improving inference and forecasting in VAR models using cross-sectional information," Ruhr Economic Papers 960, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    46. Marszk, Adam & Lechman, Ewa, 2019. "New technologies and diffusion of innovative financial products: Evidence on exchange-traded funds in selected emerging and developed economies," Journal of Macroeconomics, Elsevier, vol. 62(C).
    47. Rasool Dehghanzadeh Shahabad & Mehmet Balcilar, 2022. "Modelling the Dynamic Interaction between Economic Policy Uncertainty and Commodity Prices in India: The Dynamic Autoregressive Distributed Lag Approach," Mathematics, MDPI, vol. 10(10), pages 1-21, May.
    48. Karol Szafranek & Marek Kwas & Grzegorz Szafrański & Zuzanna Wośko, 2020. "Common Determinants of Credit Default Swap Premia in the North American Oil and Gas Industry. A Panel BMA Approach," Energies, MDPI, vol. 13(23), pages 1-23, November.
    49. Roth, Markus, 2020. "Partial pooling with cross-country priors: An application to house price shocks," Discussion Papers 06/2020, Deutsche Bundesbank.
    50. Annika Camehl & Tomasz Wo'zniak, 2023. "Time-Varying Identification of Monetary Policy Shocks," Papers 2311.05883, arXiv.org, revised Nov 2023.
    51. Sharada Nia Davidson, 2022. "Regional Integration and Decoupling in the Asia Pacific: A Bayesian Panel VAR Approach," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 70(4), pages 773-807, December.
    52. Davidson, Sharada Nia, 2020. "Interdependence or contagion: A model switching approach with a focus on Latin America," Economic Modelling, Elsevier, vol. 85(C), pages 166-197.
    53. Huang, Yin-Siang & Chuang, Hui-Ching & Hasan, Iftekhar & Lin, Chih-Yung, 2021. "The effect of language on investing: Evidence from searches in Chinese versus English," Pacific-Basin Finance Journal, Elsevier, vol. 67(C).

  33. Chan, Joshua C.C. & Eisenstat, Eric & Koop, Gary, 2014. "Large Bayesian VARMAs," SIRE Discussion Papers 2015-06, Scottish Institute for Research in Economics (SIRE).

    Cited by:

    1. Leonardo Nogueira Ferreira & Silvia Miranda-Agrippino & Giovanni Ricco, 2023. "Bayesian Local Projections," Working Papers Series 581, Central Bank of Brazil, Research Department.
    2. Miranda-Agrippino, Silvia & Ricco, Giovanni, 2018. "Bayesian vector autoregressions," LSE Research Online Documents on Economics 87393, London School of Economics and Political Science, LSE Library.
    3. Tsionas, Mike G. & Izzeldin, Marwan & Trapani, Lorenzo, 2022. "Estimation of large dimensional time varying VARs using copulas," European Economic Review, Elsevier, vol. 141(C).
    4. Ricco, Giovanni & Miranda-Agrippino, Silvia, 2018. "The Transmission of Monetary Policy Shocks," CEPR Discussion Papers 13396, C.E.P.R. Discussion Papers.
    5. Joshua C. C. Chan, 2020. "Large Bayesian VARs: A Flexible Kronecker Error Covariance Structure," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(1), pages 68-79, January.
    6. Dufays, Arnaud & Rombouts, Jeroen V.K., 2020. "Relevant parameter changes in structural break models," Journal of Econometrics, Elsevier, vol. 217(1), pages 46-78.
    7. Joshua Chan & Luca Benati & Eric Eisenstat & Gary Koop, 2018. "Identifying Noise Shocks," Working Paper Series 41, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
    8. Joshua C. C. Chan, 2019. "Large Bayesian vector autoregressions," CAMA Working Papers 2019-19, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    9. Dias, Gustavo Fruet & Kapetanios, George, 2018. "Estimation and forecasting in vector autoregressive moving average models for rich datasets," Journal of Econometrics, Elsevier, vol. 202(1), pages 75-91.
    10. Kerem Tuzcuoglu, 2019. "Composite Likelihood Estimation of an Autoregressive Panel Probit Model with Random Effects," Staff Working Papers 19-16, Bank of Canada.
    11. Mike Tsionas & Marwan Izzeldin & Lorenzo Trapani, 2019. "Bayesian estimation of large dimensional time varying VARs using copulas," Papers 1912.12527, arXiv.org.
    12. Joshua C.C. Chan & Eric Eisenstat, 2015. "Efficient estimation of Bayesian VARMAs with time-varying coefficients," CAMA Working Papers 2015-19, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    13. Chan, Joshua C.C. & Poon, Aubrey & Zhu, Dan, 2023. "High-dimensional conditionally Gaussian state space models with missing data," Journal of Econometrics, Elsevier, vol. 236(1).
    14. Matteo Iacopini & Luca Rossini, 2019. "Bayesian nonparametric graphical models for time-varying parameters VAR," Papers 1906.02140, arXiv.org.

  34. Joshua C.C. Chan & Gary Koop, 2013. "Modelling Breaks and Clusters in the Steady States of Macroeconomic Variables," ANU Working Papers in Economics and Econometrics 2013-603, Australian National University, College of Business and Economics, School of Economics.

    Cited by:

    1. Louzis Dimitrios P., 2016. "Steady-state priors and Bayesian variable selection in VAR forecasting," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(5), pages 495-527, December.
    2. Tallman, Ellis W. & Zaman, Saeed, 2020. "Combining survey long-run forecasts and nowcasts with BVAR forecasts using relative entropy," International Journal of Forecasting, Elsevier, vol. 36(2), pages 373-398.
    3. Mark Fisher & Mark J. Jensen, 2018. "Bayesian Inference and Prediction of a Multiple-Change-Point Panel Model with Nonparametric Priors," FRB Atlanta Working Paper 2018-2, Federal Reserve Bank of Atlanta.
    4. Maximo Camacho & María Dolores Gadea & Ana Gómez Loscos, 2022. "A New Approach to Dating the Reference Cycle," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 66-81, January.
    5. Chiara Perricone, 2013. "Clustering Macroeconomic Variables," CEIS Research Paper 283, Tor Vergata University, CEIS, revised 11 Jun 2013.
    6. Dimitrios P. Louzis, 2019. "Steady‐state modeling and macroeconomic forecasting quality," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(2), pages 285-314, March.
    7. Dimitrios P. Louzis, 2016. "Macroeconomic forecasting and structural changes in steady states," Working Papers 204, Bank of Greece.

  35. Gary, Koop, 2013. "Using VARs and TVP-VARs with Many Macroeconomic Variables," SIRE Discussion Papers 2013-35, Scottish Institute for Research in Economics (SIRE).

    Cited by:

    1. Coşkun Akdeniz, 2021. "Construction of the Monetary Conditions Index with TVP-VAR Model: Empirical Evidence for Turkish Economy," Springer Books, in: Burcu Adıgüzel Mercangöz (ed.), Handbook of Research on Emerging Theories, Models, and Applications of Financial Econometrics, edition 1, pages 215-228, Springer.
    2. IWATA, Yasuharu & IIBOSHI, Hirokuni, 2023. "The Nexus between Public Debt and the Government Spending Multiplier: Fiscal Adjustments Matter," MPRA Paper 116355, University Library of Munich, Germany.
    3. Pajor Anna & Wróblewska Justyna, 2017. "VEC-MSF models in Bayesian analysis of short- and long-run relationships," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(3), pages 1-22, June.
    4. Damian Stelmasiak & Grzegorz Szafrański, 2016. "Forecasting the Polish Inflation Using Bayesian VAR Models with Seasonality," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 8(1), pages 21-42, March.
    5. Drachal, Krzysztof, 2021. "Forecasting crude oil real prices with averaging time-varying VAR models," Resources Policy, Elsevier, vol. 74(C).
    6. Drachal, Krzysztof, 2021. "Forecasting selected energy commodities prices with Bayesian dynamic finite mixtures," Energy Economics, Elsevier, vol. 99(C).
    7. IIBOSHI, Hirokuni & IWATA, Yasuharu, 2023. "The Nexus between Public Debt and the Government Spending Multiplier: Fiscal Adjustments Matter," MPRA Paper 116347, University Library of Munich, Germany.
    8. Dąbrowski, Marek A., 2021. "A novel approach to the estimation of an actively managed component of foreign exchange reserves," Economic Modelling, Elsevier, vol. 96(C), pages 83-95.

  36. Miguel, Belmonte & Gary, Koop, 2013. "Model Switching and Model Averaging in Time- Varying Parameter Regression Models," SIRE Discussion Papers 2013-34, Scottish Institute for Research in Economics (SIRE).

    Cited by:

    1. Hauzenberger, Niko & Huber, Florian, 2018. "Model instability in predictive exchange rate regressions," Department of Economics Working Paper Series 276, WU Vienna University of Economics and Business.
    2. Gary Koop, 2012. "Using VARs and TVP-VARs with Many Macroeconomic Variables," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 4(3), pages 143-167, September.
    3. Krzysztof Drachal, 2018. "Determining Time-Varying Drivers of Spot Oil Price in a Dynamic Model Averaging Framework," Energies, MDPI, vol. 11(5), pages 1-24, May.
    4. Niu, Linlin & Xu, Xiu & Chen, Ying, 2017. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," Economic Modelling, Elsevier, vol. 66(C), pages 201-213.
    5. Pierre Guérin & Danilo Leiva-Leon, 2015. "Model Averaging in Markov-Switching Models: Predicting National Recessions with Regional Data," Staff Working Papers 15-24, Bank of Canada.
    6. Jordi Maas, 2014. "Forecasting inflation using time-varying Bayesian model averaging," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 68(3), pages 149-182, August.
    7. Jaromir Baxa & Miroslav Plasil & Borek Vasicek, 2013. "Inflation and the Steeplechase Between Economic Activity Variables," Working Papers 2013/15, Czech National Bank.
    8. Krzysztof Drachal, 2018. "Some Novel Bayesian Model Combination Schemes: An Application to Commodities Prices," Sustainability, MDPI, vol. 10(8), pages 1-27, August.
    9. Wang, Yudong & Ma, Feng & Wei, Yu & Wu, Chongfeng, 2016. "Forecasting realized volatility in a changing world: A dynamic model averaging approach," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 136-149.

  37. Dickson, Alex & Jennings, Colin & Koop, Gary, 2013. "Domestic Violence and Football in Glasgow: Are Reference Points Relevant?," SIRE Discussion Papers 2013-33, Scottish Institute for Research in Economics (SIRE).

    Cited by:

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    1. Delle Monache, Davide & Petrella, Ivan, 2017. "Adaptive models and heavy tails with an application to inflation forecasting," International Journal of Forecasting, Elsevier, vol. 33(2), pages 482-501.
    2. Claudiu Tiberiu Albulescu & Aviral Kumar Tiwari & Stephen M. Miller & Rangan Gupta, 2016. "Time-Frequency Relationship between Inflation and Inflation Uncertainty for the U.S.: Evidence from Historical Data," Working papers 2016-12, University of Connecticut, Department of Economics.
    3. Markku Lanne & Jani Luoto, 2017. "A New Time‐Varying Parameter Autoregressive Model for U.S. Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 969-995, August.
    4. Joshua C.C. Chan & Angelia L. Grant, 2014. "Issues in Comparing Stochastic Volatility Models Using the Deviance Information Criterion," CAMA Working Papers 2014-51, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    5. Andreza A Palma, 2016. "Natural interest rate in Brazil: further evidence frThe main objective of this study is to estimate the natural interest rate for Brazil using a parsimonious AR-trend-bound model proposed by Chan, Koo," Economics Bulletin, AccessEcon, vol. 36(3), pages 1306-1314.
    6. Kabundi, Alain & Mlachila, Montfort, 2019. "The role of monetary policy credibility in explaining the decline in exchange rate pass-through in South Africa," Economic Modelling, Elsevier, vol. 79(C), pages 173-185.
    7. Mountford, Andrew, 2022. "Economic Growth Analysis When Balanced Growth Paths May Be Time Varying," MPRA Paper 114249, University Library of Munich, Germany.
    8. Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    9. Marente Vlekke & Martin Mellens & Siem Jan Koopmans, 2020. "An assessment of the Phillips curve over time: evidence for the United States and the euro area," CPB Discussion Paper 416, CPB Netherlands Bureau for Economic Policy Analysis.
    10. Timothy Cogley & Thomas J. Sargent, 2014. "Measuring Price-Level Uncertainty and Instability in the U.S., 1850-2012," Working Papers 2014-33, Economic Research Institute, Bank of Korea.
    11. Petrella, Ivan & Venditti, Fabrizio & Delle Monache, Davide, 2016. "Adaptive state space models with applications to the business cycle and financial stress," CEPR Discussion Papers 11599, C.E.P.R. Discussion Papers.
    12. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
    13. Behera, Harendra Kumar & Patra, Michael Debabrata, 2022. "Measuring trend inflation in India," Journal of Asian Economics, Elsevier, vol. 80(C).
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    22. Markku Lanne & Jani Luoto, 2016. "Noncausal Bayesian Vector Autoregression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1392-1406, November.
    23. Mónica Correa-López & Matías Pacce & Kathi Schlepper, 2019. "Exploring trend inFLation dynamics in Euro Area countries," Working Papers 1909, Banco de España.
    24. Cogley, Timothy & Sargent, Thomas J. & Surico, Paolo, 2015. "Price-level uncertainty and instability in the United Kingdom," Journal of Economic Dynamics and Control, Elsevier, vol. 52(C), pages 1-16.
    25. Nonejad, Nima, 2021. "Predicting equity premium using dynamic model averaging. Does the state–space representation matter?," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    26. Claudiu Tiberiu Albulescu & Aviral Kumar Tiwari & Stephen M. Miller & Rangan Gupta, 2019. "Time–frequency relationship between US inflation and inflation uncertainty: evidence from historical data," Scottish Journal of Political Economy, Scottish Economic Society, vol. 66(5), pages 673-702, November.
    27. Sbrana, Giacomo & Silvestrini, Andrea & Venditti, Fabrizio, 2017. "Short-term inflation forecasting: The M.E.T.A. approach," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1065-1081.
    28. De Schryder, Selien & Peersman, Gert & Wauters, Joris, 2020. "Wage indexation and the monetary policy regime," Journal of Macroeconomics, Elsevier, vol. 63(C).
    29. Jmaes McNeil, 2020. "Monetary policy and the term structure of Inflation expectations with information frictions," Working Papers daleconwp2020-07, Dalhousie University, Department of Economics.
    30. Hervé Le Bihan & Danilo Leiva-León & Matías Pacce, 2023. "Underlying inflation and asymetric risks," Working Papers 2319, Banco de España.
    31. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano & Mertens, Elmar, 2023. "Shadow-rate VARs," Discussion Papers 14/2023, Deutsche Bundesbank.
    32. Kamber, Güneş & Wong, Benjamin, 2020. "Global factors and trend inflation," Journal of International Economics, Elsevier, vol. 122(C).
    33. Forbes, Kristin & Kirkham, Lewis & Theodoridis, Konstantinos, 2018. "A Trendy Approach to UK Inflation Dynamics," CEPR Discussion Papers 12652, C.E.P.R. Discussion Papers.
    34. Eric Eisenstat & Rodney Strachan, 2014. "Modelling Inflation Volatility," Working Paper series 43_14, Rimini Centre for Economic Analysis.
    35. Luis Uzeda, 2018. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," Staff Working Papers 18-14, Bank of Canada.
    36. Terence D. Agbeyegbe, 2023. "The Link Between Output Growth and Output Growth Volatility: Barbados," Annals of Data Science, Springer, vol. 10(3), pages 787-804, June.
    37. Alex, Dony, 2021. "Anchoring of inflation expectations in large emerging economies," The Journal of Economic Asymmetries, Elsevier, vol. 23(C).
    38. Florian Kajuth, 2016. "NAIRU Estimates for Germany: New Evidence on the Inflation–Unemployment Tradeoff," German Economic Review, Verein für Socialpolitik, vol. 17(1), pages 104-125, February.
    39. Iacopini, Matteo & Poon, Aubrey & Rossini, Luca & Zhu, Dan, 2023. "Bayesian mixed-frequency quantile vector autoregression: Eliciting tail risks of monthly US GDP," Journal of Economic Dynamics and Control, Elsevier, vol. 157(C).
    40. Ricardo Gimeno & Alfredo Ibáñez, 2017. "The eurozone (expected) inflation: an option’s eyes view," Working Papers 1722, Banco de España.
    41. Jeremy J. Nalewaik, 2015. "Regime-Switching Models for Estimating Inflation Uncertainty," Finance and Economics Discussion Series 2015-93, Board of Governors of the Federal Reserve System (U.S.).
    42. Nonejad, Nima, 2021. "Predicting the return on the spot price of crude oil out-of-sample by conditioning on news-based uncertainty measures: Some new empirical results," Energy Economics, Elsevier, vol. 104(C).
    43. Claudiu Tiberiu Albulescu & Christian Aubin & Daniel Goyeau, 2016. "Stock prices, inflation and inflation uncertainty in the U.S.: Testing the long-run relationship considering Dow Jones sector indexes," Working Papers hal-01282481, HAL.
    44. Saeed Zaman, 2021. "A Unified Framework to Estimate Macroeconomic Stars," Working Papers 21-23R, Federal Reserve Bank of Cleveland, revised 15 Aug 2022.
    45. Yunjong Eo & Luis Uzeda & Benjamin Wong, 2022. "Understanding trend inflation through the lens of the goods and services sectors," CAMA Working Papers 2022-28, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    46. Franz Xaver Zobl & Martin Ertl, 2021. "The Condemned Live Longer – New Evidence of the New Keynesian Phillips Curve in Central and Eastern Europe," Open Economies Review, Springer, vol. 32(4), pages 671-699, September.
    47. Joshua C. C. Chan, 2017. "The Stochastic Volatility in Mean Model With Time-Varying Parameters: An Application to Inflation Modeling," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(1), pages 17-28, January.
    48. Hauber, Philipp & Schumacher, Christian, 2021. "Precision-based sampling with missing observations: A factor model application," Discussion Papers 11/2021, Deutsche Bundesbank.
    49. Günes Kamber & Benjamin Wong, 2016. "Testing an Interpretation of Core Inflation Measures in New Zealand," Reserve Bank of New Zealand Analytical Notes series AN2016/06, Reserve Bank of New Zealand.
    50. Stephen Wright & James Mitchell & Donald Robertson, 2018. "R2 bounds for predictive models: what univariate properties tell us about multivariate predictability," Birkbeck Working Papers in Economics and Finance 1804, Birkbeck, Department of Economics, Mathematics & Statistics.
    51. Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2022. "Bayesian Forecasting in Economics and Finance: A Modern Review," Papers 2212.03471, arXiv.org, revised Jul 2023.
    52. Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
    53. Joshua C.C. Chan & Rodney W. Strachan, 2023. "Bayesian State Space Models In Macroeconometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 58-75, February.
    54. Bo Zhang & Joshua C.C. Chan & Jamie L. Cross, 2018. "Stochastic volatility models with ARMA innovations: An application to G7 inflation forecasts," CAMA Working Papers 2018-32, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    55. Niko Hauzenberger & Daniel Kaufmann & Rebecca Stuart & Cédric Tille, 2022. "What Drives Long-Term Interest Rates? Evidence from the Entire Swiss Franc History 1852-2020," IRENE Working Papers 22-03, IRENE Institute of Economic Research.
    56. Chan, Joshua C.C. & Poon, Aubrey & Zhu, Dan, 2023. "High-dimensional conditionally Gaussian state space models with missing data," Journal of Econometrics, Elsevier, vol. 236(1).
    57. Markku Lanne & Jani Luoto & Henri Nyberg, 2014. "Is the Quantity Theory of Money Useful in Forecasting U.S. Inflation?," CREATES Research Papers 2014-26, Department of Economics and Business Economics, Aarhus University.
    58. Gong, Xiao-Li & Liu, Xi-Hua & Xiong, Xiong & Zhuang, Xin-Tian, 2018. "Modeling volatility dynamics using non-Gaussian stochastic volatility model based on band matrix routine," Chaos, Solitons & Fractals, Elsevier, vol. 114(C), pages 193-201.
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    1. Correa, Juan A. & Gómez, Marcos & Luengo, Andrés & Parro, Francisco, 2021. "Environmental misallocation in the copper industry," Resources Policy, Elsevier, vol. 71(C).

  41. Koop, Gary & Korobilis, Dimitris, 2012. "Large Time-Varying Parameter VARs," SIRE Discussion Papers 2012-14, Scottish Institute for Research in Economics (SIRE).

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    1. Ioannis Chatziantoniou & David Gabauer, 2019. "EMU-Risk Synchronisation and Financial Fragility Through the Prism of Dynamic Connectedness," Working Papers in Economics & Finance 2019-07, University of Portsmouth, Portsmouth Business School, Economics and Finance Subject Group.
    2. Bouri, Elie & Cepni, Oguzhan & Gabauer, David & Gupta, Rangan, 2021. "Return connectedness across asset classes around the COVID-19 outbreak," International Review of Financial Analysis, Elsevier, vol. 73(C).
    3. Punzi, Maria Teresa, 2016. "Financial cycles and co-movements between the real economy, finance and asset price dynamics in large-scale crises," FinMaP-Working Papers 61, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    4. Delle Monache, Davide & Petrella, Ivan, 2017. "Adaptive models and heavy tails with an application to inflation forecasting," International Journal of Forecasting, Elsevier, vol. 33(2), pages 482-501.
    5. Sungurtekin Hallam, Bahar, 2022. "Emerging market responses to external shocks: A cross-country analysis," Economic Modelling, Elsevier, vol. 115(C).
    6. Michael Pfarrhofer, 2019. "Measuring international uncertainty using global vector autoregressions with drifting parameters," Papers 1908.06325, arXiv.org, revised Dec 2019.
    7. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen M. Miller, 2015. "Was the recent downturn in US real GDP predictable?," Applied Economics, Taylor & Francis Journals, vol. 47(28), pages 2985-3007, June.
    8. Huber, Florian, 2016. "Density forecasting using Bayesian global vector autoregressions with stochastic volatility," International Journal of Forecasting, Elsevier, vol. 32(3), pages 818-837.
    9. Angela Abbate & Massimiliano Marcellino, 2017. "Macroeconomic activity and risk indicators: an unstable relationship," BAFFI CAREFIN Working Papers 1756, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    10. Joshua C. C. Chan & Xuewen Yu, 2022. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," Papers 2206.08438, arXiv.org.
    11. Tallman, Ellis W. & Zaman, Saeed, 2020. "Combining survey long-run forecasts and nowcasts with BVAR forecasts using relative entropy," International Journal of Forecasting, Elsevier, vol. 36(2), pages 373-398.
    12. Niko Hauzenberger & Florian Huber & Massimiliano Marcellino & Nico Petz, 2021. "Gaussian Process Vector Autoregressions and Macroeconomic Uncertainty," Papers 2112.01995, arXiv.org, revised Nov 2022.
    13. Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2023. "Bayesian Modeling of Time-Varying Parameters Using Regression Trees," Working Papers 23-05, Federal Reserve Bank of Cleveland.
    14. Gary Koop & Dimitris Korobilis, 2018. "Forecasting with High-Dimensional Panel VARs," Working Paper series 18-20, Rimini Centre for Economic Analysis.
    15. Annalisa Cadonna & Sylvia Fruhwirth-Schnatter & Peter Knaus, 2019. "Triple the gamma -- A unifying shrinkage prior for variance and variable selection in sparse state space and TVP models," Papers 1912.03100, arXiv.org.
    16. Deborah Gefang & Gary Koop & Aubrey Poon, 2019. "Variational Bayesian inference in large Vector Autoregressions with hierarchical shrinkage," CAMA Working Papers 2019-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    17. Čapek, Jan & Crespo Cuaresma, Jesús & Hauzenberger, Niko & Reichel, Vlastimil, 2023. "Macroeconomic forecasting in the euro area using predictive combinations of DSGE models," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1820-1838.
    18. Coşkun Akdeniz, 2021. "Construction of the Monetary Conditions Index with TVP-VAR Model: Empirical Evidence for Turkish Economy," Springer Books, in: Burcu Adıgüzel Mercangöz (ed.), Handbook of Research on Emerging Theories, Models, and Applications of Financial Econometrics, edition 1, pages 215-228, Springer.
    19. Tsionas, Mike G. & Izzeldin, Marwan & Trapani, Lorenzo, 2022. "Estimation of large dimensional time varying VARs using copulas," European Economic Review, Elsevier, vol. 141(C).
    20. Gary Koop, 2012. "Using VARs and TVP-VARs with Many Macroeconomic Variables," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 4(3), pages 143-167, September.
    21. Petrella, Ivan & Delle Monache, Davide & Venditti, Fabrizio, 2019. "Price Dividend Ratio and Long-Run Stock Returns: a Score Driven State Space Model," CEPR Discussion Papers 14107, C.E.P.R. Discussion Papers.
    22. Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2016. "Bayesian Compressed Vector Autoregressions," Working Papers 103, Brandeis University, Department of Economics and International Business School.
    23. KANAZAWA, Nobuyuki & 金澤, 伸幸, 2018. "Radial Basis Functions Neural Networks for Nonlinear Time Series Analysis and Time-Varying Effects of Supply Shocks," Discussion paper series HIAS-E-64, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    24. Michael S. Smith & Shaun P. Vahey, 2016. "Asymmetric Forecast Densities for U.S. Macroeconomic Variables from a Gaussian Copula Model of Cross-Sectional and Serial Dependence," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(3), pages 416-434, July.
    25. Chan, Joshua C.C. & Eisenstat, Eric & Strachan, Rodney W., 2020. "Reducing the state space dimension in a large TVP-VAR," Journal of Econometrics, Elsevier, vol. 218(1), pages 105-118.
    26. Philippe Goulet Coulombe, 2020. "The Macroeconomy as a Random Forest," Papers 2006.12724, arXiv.org, revised Mar 2021.
    27. Canova, Fabio & Ciccarelli, Matteo, 2013. "Panel Vector Autoregressive Models: A Survey," CEPR Discussion Papers 9380, C.E.P.R. Discussion Papers.
    28. Antonakakis, Nikolaos & Gabauer, David & Gupta, Rangan, 2019. "Greek economic policy uncertainty: Does it matter for Europe? Evidence from a dynamic connectedness decomposition approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    29. Eric Eisenstat & Joshua C.C. Chan & Rodney W. Strachan, 2014. "Stochastic Model Specification Search for Time-Varying Parameter VARs," CAMA Working Papers 2014-23, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    30. Billio, Monica & Casarin, Roberto & Rossini, Luca, 2019. "Bayesian nonparametric sparse VAR models," Journal of Econometrics, Elsevier, vol. 212(1), pages 97-115.
    31. Giacomo Rella, 2021. "The Fed, housing and household debt over time," Department of Economics University of Siena 850, Department of Economics, University of Siena.
    32. Vasilios Plakandaras & Periklis Gogas & Theophilos Papadimitriou & Rangan Gupta, 2017. "The Informational Content of the Term Spread in Forecasting the US Inflation Rate: A Nonlinear Approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(2), pages 109-121, March.
    33. Joseph P. Byrne & Shuo Cao. & Dimitris Korobilis., 2015. "Term Structure Dynamics, Macro-Finance Factors and Model Uncertainty," Working Papers 2015_08, Business School - Economics, University of Glasgow.
    34. Karol Szafranek & Michał Rubaszek & Gazi Salah Uddin, 2023. "The role of uncertainty and sentiment for intraday volatility connectedness between oil and financial markets," KAE Working Papers 2023-095, Warsaw School of Economics, Collegium of Economic Analysis.
    35. Petrella, Ivan & Venditti, Fabrizio & Delle Monache, Davide, 2016. "Adaptive state space models with applications to the business cycle and financial stress," CEPR Discussion Papers 11599, C.E.P.R. Discussion Papers.
    36. Joshua C. C. Chan, 2020. "Large Bayesian VARs: A Flexible Kronecker Error Covariance Structure," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(1), pages 68-79, January.
    37. Amaze Lusompa, 2021. "Local Projections, Autocorrelation, and Efficiency," Research Working Paper RWP 21-01, Federal Reserve Bank of Kansas City.
    38. Petrova, Katerina, 2019. "A quasi-Bayesian local likelihood approach to time varying parameter VAR models," Journal of Econometrics, Elsevier, vol. 212(1), pages 286-306.
    39. Lasha Kavtaradze & Manouchehr Mokhtari, 2018. "Factor Models And Time†Varying Parameter Framework For Forecasting Exchange Rates And Inflation: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 302-334, April.
    40. Joshua C. C. Chan, 2022. "Comparing Stochastic Volatility Specifications for Large Bayesian VARs," Papers 2208.13255, arXiv.org.
    41. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
    42. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    43. Gregor Kastner, 2016. "Sparse Bayesian time-varying covariance estimation in many dimensions," Papers 1608.08468, arXiv.org, revised Nov 2017.
    44. Li, Shaoyu & Zhu, Chunhui & Shang, Yuhuang, 2023. "Hedging demand and near-zero swap spreads: Evidence from the Chinese interest rate swap market," The Quarterly Review of Economics and Finance, Elsevier, vol. 91(C), pages 170-185.
    45. Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2020. "Bayesian Modelling of TVP-VARs Using Regression Trees," Working Papers 2308, University of Strathclyde Business School, Department of Economics, revised Aug 2023.
    46. Antonio M. Conti & Andrea Nobili & Federico M. Signoretti, 2018. "Bank capital constraints, lending supply and economic activity," Temi di discussione (Economic working papers) 1199, Bank of Italy, Economic Research and International Relations Area.
    47. Rick Bohte & Luca Rossini, 2019. "Comparing the Forecasting of Cryptocurrencies by Bayesian Time-Varying Volatility Models," JRFM, MDPI, vol. 12(3), pages 1-18, September.
    48. Dufays, Arnaud & Rombouts, Jeroen V.K., 2020. "Relevant parameter changes in structural break models," Journal of Econometrics, Elsevier, vol. 217(1), pages 46-78.
    49. Vugar Ahmadov & Salman Huseynov & Shaig Adigozalov & Fuad Mammadov & Vugar Rahimov, 2018. "Forecasting inflation in post-oil boom years: A case for regime switches?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 42(2), pages 369-385, April.
    50. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015. "Large Vector Autoregressions with Asymmetric Priors," Working Papers 759, Queen Mary University of London, School of Economics and Finance.
    51. Moura, Guilherme V. & Noriller, Mateus R., 2019. "Maximum likelihood estimation of a TVP-VAR," Economics Letters, Elsevier, vol. 174(C), pages 78-83.
    52. Florian Huber, 2014. "Density Forecasting using Bayesian Global Vector Autoregressions with Common Stochastic Volatility," Department of Economics Working Papers wuwp179, Vienna University of Economics and Business, Department of Economics.
    53. Zhang, Yaojie & Wahab, M.I.M. & Wang, Yudong, 2023. "Forecasting crude oil market volatility using variable selection and common factor," International Journal of Forecasting, Elsevier, vol. 39(1), pages 486-502.
    54. Davide Delle Monache & Ivan Petrella, 2014. "Adaptive Models and Heavy Tails," Working Papers 720, Queen Mary University of London, School of Economics and Finance.
    55. Chen, Hongyi & Cao, Shuo, 2019. "Exchange Rate Movements and Fundamentals: Impact of Oil Prices and the People’s Republic of China’s Growth," ADBI Working Papers 938, Asian Development Bank Institute.
    56. Andrea Carriero & Galvao, Ana Beatriz & Kapetanios, George, 2016. "A comprehensive evaluation of macroeconomic forecasting methods," EMF Research Papers 10, Economic Modelling and Forecasting Group.
    57. Laurent Callot & Johannes Tang Kristensen, 2014. "Vector Autoregressions with parsimoniously Time Varying Parameters and an Application to Monetary Policy," Tinbergen Institute Discussion Papers 14-145/III, Tinbergen Institute, revised 09 Apr 2015.
    58. Stefano Grassi & Nima Nonejad & Paolo Santucci de Magistris, 2014. "Forecasting with the Standardized Self-Perturbed Kalman Filter," CREATES Research Papers 2014-12, Department of Economics and Business Economics, Aarhus University.
    59. Akbulut Nesrin & Ari Yakup, 2023. "TVP-VAR Frequency Connectedness Between the Foreign Exchange Rates of Non-Euro Area Member Countries," Folia Oeconomica Stetinensia, Sciendo, vol. 23(2), pages 1-23, December.
    60. Yunhan Zhang & Qiang Ji & David Gabauer & Rangan Gupta, 2024. "How Connected is the Oil-Bank Network? Firm-Level and High-Frequency Evidence," Working Papers 202405, University of Pretoria, Department of Economics.
    61. Hwang, Youngjin, 2019. "Forecasting recessions with time-varying models," Journal of Macroeconomics, Elsevier, vol. 62(C).
    62. Shuo Cao, 2018. "Learning about Term Structure Predictability under Uncertainty," GRU Working Paper Series GRU_2018_006, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
    63. Vugar Ahmadov & Shaig Adigozalov & Salman Huseynov & Fuad Mammadov & Vugar Rahimov, 2016. "Forecasting inflation in post-oil boom years: A case for non-linear models?," Working Papers 1601, Central Bank of Azerbaijan Republic.
    64. Luis A. Gil-Alana & Rangan Gupta & Olusanya E. Olubusoye & OlaOluwa S. Yaya, 2015. "Time Series Analysis of Persistence in Crude Oil Price Volatility across Bull and Bear Regimes," Working Papers 201580, University of Pretoria, Department of Economics.
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    66. Marcellino, Massimiliano & Carriero, Andrea & Tornese, Tommaso, 2022. "Blended Identification in Structural VARs," CEPR Discussion Papers 17640, C.E.P.R. Discussion Papers.
    67. Catania, Leopoldo & Grassi, Stefano & Ravazzolo, Francesco, 2019. "Forecasting cryptocurrencies under model and parameter instability," International Journal of Forecasting, Elsevier, vol. 35(2), pages 485-501.
    68. Marcellino, Massimiliano & Aastveit, Knut Are & Carriero, Andrea & Clark, Todd, 2016. "Have Standard VARs Remained Stable Since the Crisis?," CEPR Discussion Papers 11558, C.E.P.R. Discussion Papers.
    69. Simionescu, Mihaela, 2014. "Bayesian Forecasts Combination To Improve The Romanian Inflation Predictions Based On Econometric Models," UTMS Journal of Economics, University of Tourism and Management, Skopje, Macedonia, vol. 5(2), pages 131-140.
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    226. Leopoldo Catania & Stefano Grassi & Francesco Ravazzolo, 2018. "Forecasting Cryptocurrencies Financial Time Series," Working Papers No 5/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    227. Niall O’Sullivan & Sheng Zhu & Jason Foran, 2019. "Sentiment versus liquidity pricing effects in the cross-section of UK stock returns," Journal of Asset Management, Palgrave Macmillan, vol. 20(4), pages 317-329, July.
    228. Lyu, Chenyan & Scholtens, Bert, 2022. "Is the Global Carbon Market Integrated? Return and Volatility Connectedness in ETS Systems," Working Papers 7-2022, Copenhagen Business School, Department of Economics, revised 08 Jun 2022.
    229. Philippe Goulet Coulombe, 2020. "Time-Varying Parameters as Ridge Regressions," Papers 2009.00401, arXiv.org, revised Apr 2023.
    230. Arı, Yakup, 2022. "USD/TRY and foreign banks in Turkey: Evidence by TVP-VAR," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 67, pages 5-26.
    231. Cobb, Marcus P A, 2017. "Aggregate Density Forecasting from Disaggregate Components Using Large VARs," MPRA Paper 76849, University Library of Munich, Germany.
    232. Camba-Méndez, Gonzalo, 2020. "On the inflation risks embedded in sovereign bond yields," Working Paper Series 2423, European Central Bank.
    233. Byrne, Joseph P. & Cao, Shuo & Korobilis, Dimitris, 2017. "Forecasting the term structure of government bond yields in unstable environments," Journal of Empirical Finance, Elsevier, vol. 44(C), pages 209-225.
    234. Michael Pfarrhofer, 2020. "Forecasts with Bayesian vector autoregressions under real time conditions," Papers 2004.04984, arXiv.org.
    235. Joscha Beckmann & Rainer Schüssler, 2014. "Forecasting Equity Premia using Bayesian Dynamic Model Averaging," CQE Working Papers 2914, Center for Quantitative Economics (CQE), University of Muenster.

  42. Joshua C C Chan & Gary Koop & Simon M Potter, 2012. "A Bounded Model of Time Variation in Trend Inflation, NAIRU and the Phillips Curve," ANU Working Papers in Economics and Econometrics 2012-590, Australian National University, College of Business and Economics, School of Economics.

    Cited by:

    1. Kabundi, Alain & Poon, Aubrey & Wu, Ping, 2023. "A time-varying Phillips curve with global factors: Are global factors important?," Economic Modelling, Elsevier, vol. 126(C).
    2. Mallick, Debdulal, 2019. "Policy regimes and the shape of the Phillips curve in Australia," Journal of Policy Modeling, Elsevier, vol. 41(6), pages 1077-1094.
    3. Karlsson, Sune & Österholm, Pär, 2018. "Is the US Phillips Curve Stable? Evidence from Bayesian VARs," Working Papers 2018:5, Örebro University, School of Business.
    4. Tino Berger & Gerdie Everaert & Hauke Vierke, 2015. "Testing for time variation in an unobserved components model for the U.S. economy," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 15/903, Ghent University, Faculty of Economics and Business Administration.
    5. Knüppel, Malte & Krüger, Fabian, 2017. "Forecast Uncertainty, Disagreement, and Linear Pools of Density Forecasts," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168294, Verein für Socialpolitik / German Economic Association.
    6. Kim, Insu & Yie, Myung-Soo, 2016. "Trend inflation, firms' backward-looking behavior, and inflation gap persistence," Economic Modelling, Elsevier, vol. 58(C), pages 116-125.
    7. N. Cordemans & J. Wauters, 2018. "Are inflation and economic activity out of sync in the euro area?," Economic Review, National Bank of Belgium, issue i, pages 79-96, June.
    8. Florian Huber & Daniel Kaufmann, 2015. "Trend Fundamentals and Exchange Rate Dynamics," KOF Working papers 15-393, KOF Swiss Economic Institute, ETH Zurich.
    9. Abhishek K. Umrawal & Joshua C. C. Chan, 2021. "On Parameter Estimation in Unobserved Components Models subject to Linear Inequality Constraints," Papers 2110.12149, arXiv.org, revised Feb 2023.
    10. Consolo, Agostino & Da Silva, António Dias, 2019. "The euro area labour market through the lens of the Beveridge curve," Economic Bulletin Articles, European Central Bank, vol. 4.
    11. Sune Karlsson & Pär Österholm, 2020. "A note on the stability of the Swedish Phillips curve," Empirical Economics, Springer, vol. 59(6), pages 2573-2612, December.
    12. Bańbura, Marta & Bobeica, Elena, 2023. "Does the Phillips curve help to forecast euro area inflation?," International Journal of Forecasting, Elsevier, vol. 39(1), pages 364-390.
    13. Mallick, Debdulal, 2014. "A Spectral Representation of the Phillips Curve in Australia," MPRA Paper 59794, University Library of Munich, Germany.
    14. Dany-Knedlik, Geraldine & Holtemöller, Oliver, 2018. "Inflation dynamics during the Financial Crisis in Europe: cross-sectional identification of long-run inflation expectations," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181520, Verein für Socialpolitik / German Economic Association.
    15. Arnoud Stevens & Joris Wauters, 2021. "Is euro area lowflation here to stay? Insights from a time‐varying parameter model with survey data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 566-586, August.
    16. Michal Andrle & Miroslav Plašil, 2016. "System Priors for Econometric Time Series," IMF Working Papers 2016/231, International Monetary Fund.
    17. Philippe Goulet Coulombe & Mikael Frenette & Karin Klieber, 2023. "From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks," Papers 2311.16333, arXiv.org.
    18. Hervé Le Bihan & Danilo Leiva-León & Matías Pacce, 2023. "Underlying inflation and asymetric risks," Working Papers 2319, Banco de España.
    19. Karlsson, Sune & Österholm, Pär, 2019. "Volatilities, drifts and the relation between treasury yields and the corporate bond yield spread in australia," Finance Research Letters, Elsevier, vol. 30(C), pages 378-384.
    20. Kamber, Güneş & Wong, Benjamin, 2020. "Global factors and trend inflation," Journal of International Economics, Elsevier, vol. 122(C).
    21. Joshua C.C. Chan, 2015. "Specification tests for time-varying parameter models with stochastic volatility," CAMA Working Papers 2015-42, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    22. McKnight, Stephen & Mihailov, Alexander & Rumler, Fabio, 2020. "Inflation forecasting using the New Keynesian Phillips Curve with a time-varying trend," Economic Modelling, Elsevier, vol. 87(C), pages 383-393.
    23. Saeed Zaman, 2021. "A Unified Framework to Estimate Macroeconomic Stars," Working Papers 21-23R, Federal Reserve Bank of Cleveland, revised 15 Aug 2022.
    24. Yunjong Eo & Luis Uzeda & Benjamin Wong, 2022. "Understanding trend inflation through the lens of the goods and services sectors," CAMA Working Papers 2022-28, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    25. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Working Papers 22-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    26. Jinho Choi & Juan Carlos Escanciano & Junjie Guo, 2022. "Generalized band spectrum estimation with an application to the New Keynesian Phillips curve," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 1055-1078, August.
    27. Hauber, Philipp & Schumacher, Christian, 2021. "Precision-based sampling with missing observations: A factor model application," Discussion Papers 11/2021, Deutsche Bundesbank.
    28. Lenza, Michele & Jarociński, Marek, 2016. "An inflation-predicting measure of the output gap in the euro area," Working Paper Series 1966, European Central Bank.
    29. Jaeho Kim & Sora Chon, 2022. "Bayesian estimation of the long-run trend of the US economy," Empirical Economics, Springer, vol. 62(2), pages 461-485, February.
    30. Joshua C.C. Chan & Rodney W. Strachan, 2023. "Bayesian State Space Models In Macroeconometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 58-75, February.
    31. Raïsa Basselier & David de Antonio Liedo & Jana Jonckheere & Geert Langenus, 2018. "Can inflation expectations in business or consumer surveys improve inflation forecasts?," Working Paper Research 348, National Bank of Belgium.
    32. Bowen Fu, Ivan Mendieta-Muñoz, 2023. "Structural shocks and trend inflation," Working Paper Series, Department of Economics, University of Utah 2023_04, University of Utah, Department of Economics.
    33. Andrle, Michal & Plašil, Miroslav, 2018. "Econometrics with system priors," Economics Letters, Elsevier, vol. 172(C), pages 134-137.
    34. Jaromir Baxa & Miroslav Plasil & Borek Vasicek, 2013. "Inflation and the Steeplechase Between Economic Activity Variables," Working Papers 2013/15, Czech National Bank.
    35. Philippe Goulet Coulombe & Mikael Frenette & Karin Klieber, 2023. "From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks," Working Papers 23-04, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Nov 2023.
    36. Fu, Bowen, 2020. "Is the slope of the Phillips curve time-varying? Evidence from unobserved components models," Economic Modelling, Elsevier, vol. 88(C), pages 320-340.
    37. Roberto Duncan & Enrique Martínez‐García, 2023. "Forecasting inflation in open economies: What can a NOEM model do?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(3), pages 481-513, April.
    38. Joshua C.C. Chan & Todd E. Clark & Gary Koop, 2018. "A New Model of Inflation, Trend Inflation, and Long‐Run Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(1), pages 5-53, February.
    39. Michael O’Grady, 2019. "Estimating the Output, Inflation and Unemployment Gaps in Ireland using Bayesian Model Averaging," The Economic and Social Review, Economic and Social Studies, vol. 50(1), pages 35-76.
    40. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Papers 2202.04146, arXiv.org.
    41. Chu Shiou-Yen & Shane Christopher, 2017. "Using the hybrid Phillips curve with memory to forecast US inflation," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(4), pages 1-16, September.
    42. Malte Knüppel & Fabian Krüger, 2022. "Forecast uncertainty, disagreement, and the linear pool," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 23-41, January.
    43. Grant, Angelia L., 2018. "The Great Recession and Okun's law," Economic Modelling, Elsevier, vol. 69(C), pages 291-300.

  43. Koop, Gary & Gefang, Deborah & Campolieti, Michele, 2012. "Time Variation in the Dynamics of Worker Flows: Evidence from the US and Canada," SIRE Discussion Papers 2012-69, Scottish Institute for Research in Economics (SIRE).

    Cited by:

    1. Campolieti, Michele & Gefang, Deborah & Koop, Gary, 2014. "A new look at variation in employment growth in Canada: The role of industry, provincial, national and external factors," Journal of Economic Dynamics and Control, Elsevier, vol. 41(C), pages 257-275.
    2. Michele Campolieti & Deborah Gefang & Gary Koop, 2013. "A new look at variation in employment growth in Canada," Working Papers 26145565, Lancaster University Management School, Economics Department.

  44. Onorante, Luca & Koop, Gary, 2012. "Estimating Phillips curves in turbulent times using the ECB's survey of professional forecasters," Working Paper Series 1422, European Central Bank.

    Cited by:

    1. Chletsos, Michael & Drosou, Vasiliki & Roupakias, Stelios, 2016. "Can Phillips curve explain the recent behavior of inflation? Further evidence from USA and Canada," The Journal of Economic Asymmetries, Elsevier, vol. 14(PA), pages 20-28.
    2. Yingying XU & Zhixin LIU & Jaime ORTIZ, 2018. "Actual and Expected Inflation in the U.S.: A Time-Frequency View," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 42-62, December.
    3. Sophocles Mavroeidis & Mikkel Plagborg-Møller & James H. Stock, 2014. "Empirical Evidence on Inflation Expectations in the New Keynesian Phillips Curve," Journal of Economic Literature, American Economic Association, vol. 52(1), pages 124-188, March.
    4. Mohammed Saiful Islam & Riduanul Mustafa, 2017. "Quest for a Valid Phillips Curve in the Long Run: An Empirical Approach," International Business Research, Canadian Center of Science and Education, vol. 10(4), pages 191-198, April.
    5. Hauzenberger Niko & Huber Florian & Pfarrhofer Michael & Zörner Thomas O., 2021. "Stochastic model specification in Markov switching vector error correction models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(2), pages 1-17, April.
    6. Moretti, Laura & Onorante, Luca & Zakipour-Saber, Shayan, 2019. "Phillips curves in the euro area," Research Technical Papers 8/RT/19, Central Bank of Ireland.
    7. Pierre Guérin & Danilo Leiva-Leon, 2015. "Model Averaging in Markov-Switching Models: Predicting National Recessions with Regional Data," Staff Working Papers 15-24, Bank of Canada.
    8. Schleer, Frauke & Kappler, Marcus, 2014. "The Phillips Curve: (In)stability, the role of credit, and implications for potential output measurement," ZEW Discussion Papers 14-067, ZEW - Leibniz Centre for European Economic Research.
    9. Oinonen, Sami & Paloviita, Maritta & Vilmi, Lauri, 2013. "How have inflation dynamics changed over time? Evidence from the euro area and USA," Bank of Finland Research Discussion Papers 6/2013, Bank of Finland.
    10. Choi, Yoonseok & Kim, Sunghyun, 2016. "Testing an alternative price-setting behavior in the new Keynesian Phillips curve: Extrapolative price-setting mechanism," International Review of Economics & Finance, Elsevier, vol. 44(C), pages 253-265.
    11. Baxa, Jaromír & Plašil, Miroslav & Vašíček, Bořek, 2015. "Changes in inflation dynamics under inflation targeting? Evidence from Central European countries," Economic Modelling, Elsevier, vol. 44(C), pages 116-130.
    12. Croonenbroeck, Carsten & Stadtmann, Georg, 2012. "Evaluating Phillips curve based inflation forecasts in Europe: A note," Discussion Papers 329, European University Viadrina Frankfurt (Oder), Department of Business Administration and Economics.
    13. Lanne, Markku & Luoto, Jani, 2011. "Autoregression-Based Estimation of the New Keynesian Phillips Curve," MPRA Paper 29801, University Library of Munich, Germany.
    14. López Pérez, Víctor, 2015. "Do professional forecasters behave as if they believed in the new Keynesian Phillips Curve for the euro area?," Working Paper Series 1763, European Central Bank.
    15. Johanna Amberger & Ralf Fendel, 2017. "Understanding inflation dynamics in the Euro Area: deviants and commonalities across member countries," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 44(2), pages 261-293, May.
    16. Johanna Amberger & Ralf Fendel, 2017. "The Slope of the Euro Area Phillips Curve: Always and Everywhere the Same?," Applied Economics and Finance, Redfame publishing, vol. 4(3), pages 77-88, May.
    17. Jaromir Baxa & Miroslav Plasil & Borek Vasicek, 2013. "Inflation and the Steeplechase Between Economic Activity Variables," Working Papers 2013/15, Czech National Bank.
    18. Víctor López-Pérez, 2017. "Do professional forecasters behave as if they believed in the New Keynesian Phillips Curve for the euro area?," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 44(1), pages 147-174, February.

  45. Luc Bauwens & Gary Koop & Dimitris Korobilis & Jeroen Rombouts, 2011. "A Comparison of Forecasting Procedures For Macroeconomic Series: The Contribution of Structural Break Models," CIRANO Working Papers 2011s-13, CIRANO.

    Cited by:

    1. Wensheng Kang & Jing Wang, 2018. "Oil shocks, policy uncertainty and earnings surprises," Review of Quantitative Finance and Accounting, Springer, vol. 51(2), pages 375-388, August.
    2. Markku Lanne & Jani Luoto, 2017. "A New Time‐Varying Parameter Autoregressive Model for U.S. Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 969-995, August.
    3. Timmermann, Allan & Pettenuzzo, Davide, 2016. "Forecasting Macroeconomic Variables under Model Instability," CEPR Discussion Papers 11355, C.E.P.R. Discussion Papers.
    4. Gary Koop & Dimitris Korobilis, 2018. "Forecasting with High-Dimensional Panel VARs," Working Paper series 18-20, Rimini Centre for Economic Analysis.
    5. Korobilis, Dimitris & Koop, Gary, 2020. "Bayesian dynamic variable selection in high dimensions," MPRA Paper 100164, University Library of Munich, Germany.
    6. Mark Fisher & Mark J. Jensen, 2018. "Bayesian Inference and Prediction of a Multiple-Change-Point Panel Model with Nonparametric Priors," FRB Atlanta Working Paper 2018-2, Federal Reserve Bank of Atlanta.
    7. Koop, Gary & Korobilis, Dimitris, 2018. "Variational Bayes inference in high-dimensional time-varying parameter models," MPRA Paper 87972, University Library of Munich, Germany.
    8. Kirsten Thompson & Renee Van Eyden & Rangan Gupta, 2015. "Identifying an index of financial conditions for South Africa," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 32(2), pages 256-274, June.
    9. Chiu, Ching-Wai (Jeremy) & Mumtaz, Haroon & Pintér, Gábor, 2017. "Forecasting with VAR models: Fat tails and stochastic volatility," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1124-1143.
    10. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    11. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
    12. Hou, Chenghan, 2017. "Infinite hidden markov switching VARs with application to macroeconomic forecast," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1025-1043.
    13. Dufays, Arnaud & Rombouts, Jeroen V.K., 2020. "Relevant parameter changes in structural break models," Journal of Econometrics, Elsevier, vol. 217(1), pages 46-78.
    14. Korobilis, D, 2017. "Forecasting with many predictors using message passing algorithms," Essex Finance Centre Working Papers 19565, University of Essex, Essex Business School.
    15. Nonejad, Nima, 2017. "Forecasting aggregate stock market volatility using financial and macroeconomic predictors: Which models forecast best, when and why?," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 131-154.
    16. Eo, Yunjong, 2015. "Structural Changes in Inflation Dynamics: Multiple Breaks at Different Dates for Different Parameters," Working Papers 2015-18, University of Sydney, School of Economics, revised Nov 2015.
    17. KOROBILIS, Dimitris, 2011. "VAR forecasting using Bayesian variable selection," LIDAM Discussion Papers CORE 2011022, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    18. Ewing, Bradley T. & Kang, Wensheng & Ratti, Ronald A., 2018. "The dynamic effects of oil supply shocks on the US stock market returns of upstream oil and gas companies," Energy Economics, Elsevier, vol. 72(C), pages 505-516.
    19. Markku Lanne & Jani Luoto, 2016. "Noncausal Bayesian Vector Autoregression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1392-1406, November.
    20. Franz Ruch & Mehmet Balcilar Author-Name-First Mehmet & Mampho P. Modise & Rangan Gupta, 2015. "Forecasting Core Inflation: The Case of South Africa," Working Papers 15-08, Eastern Mediterranean University, Department of Economics.
    21. Dimitris Korobilis, 2020. "High-dimensional macroeconomic forecasting using message passing algorithms," Papers 2004.11485, arXiv.org.
    22. Ardia, David & Dufays, Arnaud & Ordás Criado, Carlos, 2023. "Linking Frequentist and Bayesian Change-Point Methods," MPRA Paper 119486, University Library of Munich, Germany.
    23. Chen, Ji & Yang, Xinglin & Liu, Xiliang, 2022. "Learning, disagreement and inflation forecasting," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    24. Arnaud Dufays & Jeroen V.K. Rombouts, 2016. "Sparse Change-point HAR Models for Realized Variance," Cahiers de recherche 1607, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
    25. Nonejad Nima, 2015. "Particle Gibbs with ancestor sampling for stochastic volatility models with: heavy tails, in mean effects, leverage, serial dependence and structural breaks," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(5), pages 561-584, December.
    26. Yu Jeffrey Hu & Jeroen Rombouts & Ines Wilms, 2023. "Fast Forecasting of Unstable Data Streams for On-Demand Service Platforms," Papers 2303.01887, arXiv.org.
    27. C. Y. Tan & Y. B. Koh & K. H. Ng & K. H. Ng, 2019. "Structural Change Analysis of Active Cryptocurrency Market," Papers 1909.10679, arXiv.org.
    28. Pierre L. Siklos, 2020. "Looking into the Rear-View Mirror: Lessons from Japan for the Eurozone and the U.S?," IMES Discussion Paper Series 20-E-02, Institute for Monetary and Economic Studies, Bank of Japan.
    29. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    30. Gary Koop & Dimitris Korompilis, 2009. "UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So?," Working Papers 0917, University of Strathclyde Business School, Department of Economics.
    31. Czinkota, Thomas, 2012. "Das Halteproblem bei Strukturbrüchen in Finanzmarktzeitreihen [The Halting Problem applied to Structural Breaks in Financial Time Series]," MPRA Paper 37072, University Library of Munich, Germany.
    32. Luis Uzeda, 2018. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," Staff Working Papers 18-14, Bank of Canada.
    33. Kascha, Christian & Trenkler, Carsten, 2015. "Forecasting VARs, model selection, and shrinkage," Working Papers 15-07, University of Mannheim, Department of Economics.
    34. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    35. Elena Afanasyeva, 2020. "Can Forecast Errors Predict Financial Crises? Exploring the Properties of a New Multivariate Credit Gap," Finance and Economics Discussion Series 2020-045, Board of Governors of the Federal Reserve System (U.S.).
    36. BAUWENS, Luc & DE BACKER, Bruno & DUFAYS, Arnaud, 2014. "A Bayesian method of change-point estimation with recurrent regimes: application to GARCH models," LIDAM Reprints CORE 2641, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    37. Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2020. "Point and Density Forecasting of Macroeconomic and Financial Uncertainties of the United States," Working Papers 202058, University of Pretoria, Department of Economics.
    38. Hossein Hassani & Zara Ghodsi & Rangan Gupta & Mawuli K. Segnon, 2014. "Forecasting Home Sales in the Four Census Regions and the Aggregate US Economy Using Singular Spectrum Analysis," Working Papers 201482, University of Pretoria, Department of Economics.
    39. McKnight, Stephen & Mihailov, Alexander & Rumler, Fabio, 2020. "Inflation forecasting using the New Keynesian Phillips Curve with a time-varying trend," Economic Modelling, Elsevier, vol. 87(C), pages 383-393.
    40. Wensheng Kang & Ronald A. Ratti & Kyung Hwan Yoon, 2015. "Time-varying effect of oil market shocks on the stock market," CAMA Working Papers 2015-35, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    41. Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2021. "Point and density forecasting of macroeconomic and financial uncertainties of the USA," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(4), pages 700-707, July.
    42. Feiyu Jiang & Zifeng Zhao & Xiaofeng Shao, 2022. "Modelling the COVID‐19 infection trajectory: A piecewise linear quantile trend model," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(5), pages 1589-1607, November.
    43. Todd E. Clark & Taeyoung Doh, 2011. "A Bayesian evaluation of alternative models of trend inflation," Working Papers (Old Series) 1134, Federal Reserve Bank of Cleveland.
    44. Augustyniak, Maciej & Dufays, Arnaud, 2018. "Modeling macroeconomic series with regime-switching models characterized by a high-dimensional state space," Economics Letters, Elsevier, vol. 170(C), pages 122-126.
    45. Kirsten Thompson & Reneé van Eyden & Rangan Gupta, 2015. "Testing the Out-of-Sample Forecasting Ability of a Financial Conditions Index for South Africa," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 51(3), pages 486-501, May.
    46. Arnaud Dufays & Zhuo Li & Jeroen V.K. Rombouts & Yong Song, 2021. "Sparse change‐point VAR models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(6), pages 703-727, September.
    47. Eraslan, Sercan & Schröder, Maximilian, 2019. "Nowcasting GDP with a large factor model space," Discussion Papers 41/2019, Deutsche Bundesbank.
    48. Jiang, Feiyu & Zhao, Zifeng & Shao, Xiaofeng, 2023. "Time series analysis of COVID-19 infection curve: A change-point perspective," Journal of Econometrics, Elsevier, vol. 232(1), pages 1-17.
    49. Nonejad, Nima, 2020. "Crude oil price changes and the United Kingdom real gross domestic product growth rate: An out-of-sample investigation," The Journal of Economic Asymmetries, Elsevier, vol. 21(C).
    50. Sylvia Kaufmann, 2016. "Hidden Markov models in time series, with applications in economics," Working Papers 16.06, Swiss National Bank, Study Center Gerzensee.
    51. Dimitrios P. Louzis, 2016. "Macroeconomic forecasting and structural changes in steady states," Working Papers 204, Bank of Greece.

  46. Koop, Gary & Leon-Gonzalez, Roberto & Strachan, Rodney, 2011. "Bayesian Model Averaging in the Instrumental Variable Regression Model," SIRE Discussion Papers 2011-23, Scottish Institute for Research in Economics (SIRE).

    Cited by:

    1. Iftekhar Hasan & Roman Horvath & Jan Mares, 2018. "Finance and Wealth Inequality," Working Papers IES 2018/35, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Dec 2018.
    2. San Ahmed, Arsalan & Holloway, Garth John, 2017. "Calories, conflict and correlates: Redistributive food security in post-conflict Iraq," Food Policy, Elsevier, vol. 68(C), pages 89-99.
    3. Meyer-Gohde, Alexander & Neuhoff, Daniel, 2018. "Generalized exogenous processes in DSGE: A Bayesian approach," IMFS Working Paper Series 125, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
    4. Temple, Jonathan & Rockey, James, 2015. "Growth Econometrics for Agnostics and True Believers," CEPR Discussion Papers 10590, C.E.P.R. Discussion Papers.
    5. Chan, Joshua C.C. & Eisenstat, Eric & Strachan, Rodney W., 2020. "Reducing the state space dimension in a large TVP-VAR," Journal of Econometrics, Elsevier, vol. 218(1), pages 105-118.
    6. Pham, Thi Hong Hanh, 2017. "Impacts of globalization on the informal sector: Empirical evidence from developing countries," Economic Modelling, Elsevier, vol. 62(C), pages 207-218.
    7. Hedibert F. Lopes & Nicholas G. Polson, 2014. "Bayesian Instrumental Variables: Priors and Likelihoods," Econometric Reviews, Taylor & Francis Journals, vol. 33(1-4), pages 100-121, June.
    8. TANAKA Kiyoyasu, 2015. "The Impact of Foreign Firms on Industrial Productivity: A Bayesian-model averaging approach," Discussion papers 15009, Research Institute of Economy, Trade and Industry (RIETI).
    9. Rodney W. Strachan & Herman K. Van Dijk, 2013. "Evidence On Features Of A Dsge Business Cycle Model From Bayesian Model Averaging," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 54(1), pages 385-402, February.
    10. Maribel Serna Rodríguez & Andrés Ramírez Hassan & Alexander Coad, 2019. "Uncovering Value Drivers of High Performance Soccer Players," Journal of Sports Economics, , vol. 20(6), pages 819-849, August.
    11. Roberto Leon-Gonzalez & Daniel Montolio, 2012. "Endogeneity and Panel Data in Growth Regressions: A Bayesian Model Averaging Approach," GRIPS Discussion Papers 12-08, National Graduate Institute for Policy Studies.
    12. Eric Eisenstat & Joshua C.C. Chan & Rodney W. Strachan, 2018. "Reducing Dimensions in a Large TVP-VAR," Working Paper Series 43, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
    13. Adam Slez, 2019. "The Difference Between Instability and Uncertainty: Comment on Young and Holsteen (2017)," Sociological Methods & Research, , vol. 48(2), pages 400-430, May.
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    15. Ampaabeng, Samuel K. & Tan, Chih Ming, 2013. "The long-term cognitive consequences of early childhood malnutrition: The case of famine in Ghana," Journal of Health Economics, Elsevier, vol. 32(6), pages 1013-1027.
    16. Samuel K. Ampaabeng & Chih Ming Tang, 2012. "The Long-Term Cognitive Consequences of Early Childhood Malnutrition: The Case of Famine in Ghana," Working Paper series 64_12, Rimini Centre for Economic Analysis.
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    19. Pedro Saramago & Karl Claxton & Nicky J. Welton & Marta Soares, 2020. "Bayesian econometric modelling of observational data for cost‐effectiveness analysis: establishing the value of negative pressure wound therapy in the healing of open surgical wounds," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1575-1593, October.
    20. Andros Kourtellos & Alex Lenkoski & Kyriakos Petrou, 2017. "Measuring the Strength of the Theories of Government Size," University of Cyprus Working Papers in Economics 11-2017, University of Cyprus Department of Economics.
    21. Andros Kourtellos & Charalambos G. Tsangarides, 2022. "Robust Correlates of Growth Spells: Do Inequality and Redistribution Matter?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(6), pages 1302-1328, December.
    22. Roman Horváth, 2012. "Does Trust Promote Growth?," Working Papers 319, Leibniz Institut für Ost- und Südosteuropaforschung (Institute for East and Southeast European Studies).
    23. Cameron Fen & Samir Undavia, 2022. "Improving Macroeconomic Model Validity and Forecasting Performance with Pooled Country Data using Structural, Reduced Form, and Neural Network Model," Papers 2203.06540, arXiv.org.
    24. Sajad Rahimian, 2021. "The Determinants of Democracy Revisited: An Instrumental Variable Bayesian Model Averaging Approach," Papers 2103.04255, arXiv.org.
    25. Zuzana Irsova & Hristos Doucouliagos & Tomas Havranek & T. D. Stanley, 2023. "Meta-Analysis of Social Science Research: A Practitioner´s Guide," Working Papers IES 2023/25, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2023.
    26. Narayan Bulusu & Pierre Guérin, 2018. "What Drives Interbank Loans? Evidence from Canada," Staff Working Papers 18-5, Bank of Canada.
    27. Tanaka, Kiyoyasu, 2015. "The impact of foreign firms on industrial productivity : evidence from Japan," IDE Discussion Papers 533, Institute of Developing Economies, Japan External Trade Organization(JETRO).
    28. Michael Jetter & Christopher F. Parmeter, 2016. "Uncovering the determinants of corruption," Working Papers 2016-02, University of Miami, Department of Economics.
    29. Jaroslava Hlouskova & Martin Wagner, 2013. "The Determinants of Long-Run Economic Growth: A Conceptually and Computationally Simple Approach," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 149(IV), pages 445-492, December.
    30. Jetter, Michael & Parmeter, Christopher F., 2018. "Sorting through global corruption determinants: Institutions and education matter – Not culture," World Development, Elsevier, vol. 109(C), pages 279-294.
    31. Martins, Luis F. & Gabriel, Vasco J., 2014. "Linear instrumental variables model averaging estimation," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 709-724.

  47. BELMONTE, Miguel A.G. & KOOP, Gary & KOROBILIS, Dimitris, 2011. "Hierarchical shrinkage in time-varying parameter models," LIDAM Discussion Papers CORE 2011036, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

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    1. Michael Pfarrhofer, 2019. "Measuring international uncertainty using global vector autoregressions with drifting parameters," Papers 1908.06325, arXiv.org, revised Dec 2019.
    2. Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2023. "Bayesian Modeling of Time-Varying Parameters Using Regression Trees," Working Papers 23-05, Federal Reserve Bank of Cleveland.
    3. Annalisa Cadonna & Sylvia Fruhwirth-Schnatter & Peter Knaus, 2019. "Triple the gamma -- A unifying shrinkage prior for variance and variable selection in sparse state space and TVP models," Papers 1912.03100, arXiv.org.
    4. Florian Huber & Gregor Kastner & Martin Feldkircher, 2016. "Should I stay or should I go? A latent threshold approach to large-scale mixture innovation models," Papers 1607.04532, arXiv.org, revised Jul 2018.
    5. Korobilis, Dimitris & Koop, Gary, 2020. "Bayesian dynamic variable selection in high dimensions," MPRA Paper 100164, University Library of Munich, Germany.
    6. Miranda-Agrippino, Silvia & Ricco, Giovanni, 2018. "Bayesian vector autoregressions," LSE Research Online Documents on Economics 87393, London School of Economics and Political Science, LSE Library.
    7. Prüser, Jan, 2017. "Forecasting US inflation using Markov dimension switching," Ruhr Economic Papers 710, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    8. Koop, Gary & Korobilis, Dimitris, 2018. "Variational Bayes inference in high-dimensional time-varying parameter models," MPRA Paper 87972, University Library of Munich, Germany.
    9. Maheu, John M & Song, Yong, 2017. "An Efficient Bayesian Approach to Multiple Structural Change in Multivariate Time Series," MPRA Paper 79211, University Library of Munich, Germany.
    10. Simon Beyeler, 2019. "Streamlining Time-varying VAR with a Factor Structure in the Parameters," Working Papers 19.03, Swiss National Bank, Study Center Gerzensee.
    11. Niko Hauzenberger & Florian Huber & Gary Koop & Luca Onorante, 2019. "Fast and Flexible Bayesian Inference in Time-varying Parameter Regression Models," Papers 1910.10779, arXiv.org, revised Sep 2021.
    12. Chan, Joshua C.C. & Eisenstat, Eric & Strachan, Rodney W., 2020. "Reducing the state space dimension in a large TVP-VAR," Journal of Econometrics, Elsevier, vol. 218(1), pages 105-118.
    13. Eric Eisenstat & Joshua C.C. Chan & Rodney W. Strachan, 2014. "Stochastic Model Specification Search for Time-Varying Parameter VARs," CAMA Working Papers 2014-23, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    14. David Kohns & Arnab Bhattacharjee, 2020. "Nowcasting Growth using Google Trends Data: A Bayesian Structural Time Series Model," Papers 2011.00938, arXiv.org, revised May 2022.
    15. Dimitris Korobilis & Kenichi Shimizu, 2021. "Bayesian Approaches to Shrinkage and Sparse Estimation," Working Papers 2021_19, Business School - Economics, University of Glasgow.
    16. Adam, Marc C. & Jansson, Walter, 2019. "Credit constraints and the propagation of the Great Depression in Germany," Discussion Papers 2019/12, Free University Berlin, School of Business & Economics.
    17. Lasha Kavtaradze & Manouchehr Mokhtari, 2018. "Factor Models And Time†Varying Parameter Framework For Forecasting Exchange Rates And Inflation: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 302-334, April.
    18. Joscha Beckmann & Rainer Schüssler, 2014. "Forecasting Exchange Rates under Model and Parameter Uncertainty," CQE Working Papers 3214, Center for Quantitative Economics (CQE), University of Muenster.
    19. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    20. Gregor Kastner, 2016. "Sparse Bayesian time-varying covariance estimation in many dimensions," Papers 1608.08468, arXiv.org, revised Nov 2017.
    21. Dufays, Arnaud & Rombouts, Jeroen V.K., 2020. "Relevant parameter changes in structural break models," Journal of Econometrics, Elsevier, vol. 217(1), pages 46-78.
    22. Korobilis, D, 2017. "Forecasting with many predictors using message passing algorithms," Essex Finance Centre Working Papers 19565, University of Essex, Essex Business School.
    23. Bitto, Angela & Frühwirth-Schnatter, Sylvia, 2019. "Achieving shrinkage in a time-varying parameter model framework," Journal of Econometrics, Elsevier, vol. 210(1), pages 75-97.
    24. Annalisa Cadonna & Sylvia Frühwirth-Schnatter & Peter Knaus, 2020. "Triple the Gamma—A Unifying Shrinkage Prior for Variance and Variable Selection in Sparse State Space and TVP Models," Econometrics, MDPI, vol. 8(2), pages 1-36, May.
    25. Macias, Paweł & Stelmasiak, Damian & Szafranek, Karol, 2023. "Nowcasting food inflation with a massive amount of online prices," International Journal of Forecasting, Elsevier, vol. 39(2), pages 809-826.
    26. Damian Stelmasiak & Grzegorz Szafrański, 2016. "Forecasting the Polish Inflation Using Bayesian VAR Models with Seasonality," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 8(1), pages 21-42, March.
    27. Beckmann, Joscha & Schüssler, Rainer, 2016. "Forecasting exchange rates under parameter and model uncertainty," Journal of International Money and Finance, Elsevier, vol. 60(C), pages 267-288.
    28. Dimitris Korobilis, 2020. "High-dimensional macroeconomic forecasting using message passing algorithms," Papers 2004.11485, arXiv.org.
    29. Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2012. "Prior Selection for Vector Autoregressions," NBER Working Papers 18467, National Bureau of Economic Research, Inc.
    30. Sylvia Fruhwirth-Schnatter & Peter Knaus, 2022. "Sparse Bayesian State-Space and Time-Varying Parameter Models," Papers 2207.12147, arXiv.org.
    31. Martin Feldkircher & Nico Hauzenberger, 2019. "How useful are time-varying parameter models for forecasting economic growth in CESEE?," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue Q1/19, pages 29-48.
    32. Igor Ferreira Batista Martins & Hedibert Freitas Lopes, 2023. "Stochastic volatility models with skewness selection," Papers 2312.00282, arXiv.org.
    33. Feldkircher, Martin & Kastner, Gregor & Huber, Florian, 2018. "Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian VARs?," Department of Economics Working Paper Series 260, WU Vienna University of Economics and Business.
    34. Karol Szafranek, 2017. "Bagged artificial neural networks in forecasting inflation: An extensive comparison with current modelling frameworks," NBP Working Papers 262, Narodowy Bank Polski.
    35. Florian Huber & Michael Pfarrhofer & Philipp Piribauer, 2020. "A multi-country dynamic factor model with stochastic volatility for euro area business cycle analysis," Papers 2001.03935, arXiv.org.
    36. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    37. Joshua C.C. Chan, 2015. "Specification tests for time-varying parameter models with stochastic volatility," CAMA Working Papers 2015-42, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    38. Rangan Gupta & Mampho P. Modise & Josine Uwilingiye, 2011. "Out-of-Sample Equity Premium Predictability in South Africa: Evidence from a Large Number of Predictors," Working Papers 201122, University of Pretoria, Department of Economics.
    39. Yang Aijun & Xiang Ju & Yang Hongqiang & Lin Jinguan, 2018. "Sparse Bayesian Variable Selection in Probit Model for Forecasting U.S. Recessions Using a Large Set of Predictors," Computational Economics, Springer;Society for Computational Economics, vol. 51(4), pages 1123-1138, April.
    40. Matei, Florin, 2014. "An empirical examination of stock market integration in EMU," MPRA Paper 60717, University Library of Munich, Germany.
    41. Hauzenberger, Niko & Huber, Florian & Klieber, Karin, 2023. "Real-time inflation forecasting using non-linear dimension reduction techniques," International Journal of Forecasting, Elsevier, vol. 39(2), pages 901-921.
    42. Joshua C. C. Chan & Eric Eisenstat, 2018. "Bayesian model comparison for time‐varying parameter VARs with stochastic volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(4), pages 509-532, June.
    43. Niko Hauzenberger & Florian Huber & Karin Klieber & Massimiliano Marcellino, 2022. "Bayesian Neural Networks for Macroeconomic Analysis," Papers 2211.04752, arXiv.org, revised Apr 2024.
    44. Stefano Grassi & Miguel Leon-Ledesma & Filippo Ferroni, 2016. "Fundamental shock selection in DSGE models," 2016 Meeting Papers 47, Society for Economic Dynamics.
    45. Yuntong Liu & Yu Wei & Yi Liu & Wenjuan Li, 2020. "Forecasting Oil Price by Hierarchical Shrinkage in Dynamic Parameter Models," Discrete Dynamics in Nature and Society, Hindawi, vol. 2020, pages 1-12, December.
    46. Niaz Bashiri Behmiri, Maryam Ahmadi, Juha-Pekka Junttila, and Matteo Manera, 2021. "Financial Stress and Basis in Energy Markets," The Energy Journal, International Association for Energy Economics, vol. 0(Number 5).
    47. Peter Knaus & Sylvia Fruhwirth-Schnatter, 2023. "The Dynamic Triple Gamma Prior as a Shrinkage Process Prior for Time-Varying Parameter Models," Papers 2312.10487, arXiv.org.
    48. Florian Huber & Gary Koop & Michael Pfarrhofer, 2020. "Bayesian Inference in High-Dimensional Time-varying Parameter Models using Integrated Rotated Gaussian Approximations," Papers 2002.10274, arXiv.org.
    49. Michelle, Gilmartin, 2016. "A note on the identification and transmission of energy demand and supply shocks," MPRA Paper 76186, University Library of Munich, Germany.
    50. Kalli, Maria & Griffin, Jim E., 2014. "Time-varying sparsity in dynamic regression models," Journal of Econometrics, Elsevier, vol. 178(2), pages 779-793.
    51. Christian Hotz-Behofsits & Florian Huber & Thomas O. Zorner, 2018. "Predicting crypto-currencies using sparse non-Gaussian state space models," Papers 1801.06373, arXiv.org, revised Feb 2018.
    52. Joshua C.C. Chan & Rodney W. Strachan, 2023. "Bayesian State Space Models In Macroeconometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 58-75, February.
    53. Dimitris Korobilis, 2014. "Data-based priors for vector autoregressions with drifting coefficients," Working Papers 2014_04, Business School - Economics, University of Glasgow.
    54. Peter Knaus & Angela Bitto-Nemling & Annalisa Cadonna & Sylvia Fruhwirth-Schnatter, 2019. "Shrinkage in the Time-Varying Parameter Model Framework Using the R Package shrinkTVP," Papers 1907.07065, arXiv.org, revised Nov 2020.
    55. Belomestny, Denis & Krymova, Ekaterina & Polbin, Andrey, 2021. "Bayesian TVP-VARX models with time invariant long-run multipliers," Economic Modelling, Elsevier, vol. 101(C).
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    57. Dufays, A. & Rombouts, V., 2015. "Sparse Change-Point Time Series Models," LIDAM Discussion Papers CORE 2015032, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    58. Dimitrios P. Louzis, 2019. "Steady‐state modeling and macroeconomic forecasting quality," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(2), pages 285-314, March.
    59. Wang, Zongrun & Zhou, Ling & Mi, Yunlong & Shi, Yong, 2022. "Measuring dynamic pandemic-related policy effects: A time-varying parameter multi-level dynamic factor model approach," Journal of Economic Dynamics and Control, Elsevier, vol. 139(C).
    60. Kohns, David & Bhattacharjee, Arnab, 2023. "Nowcasting growth using Google Trends data: A Bayesian Structural Time Series model," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1384-1412.
    61. Rangan Gupta & Shawkat Hammoudeh & Beatrice D. Simo-Kengne & Soodabeh Sarafrazi, 2013. "Can the Sharia-Based Islamic Stock Market Returns be Forecasted Using Large Number of Predictors and Models?," Working Papers 201381, University of Pretoria, Department of Economics.
    62. Joshua C.C. Chan & Angelia L. Grant, 2014. "Fast Computation of the Deviance Information Criterion for Latent Variable Models," CAMA Working Papers 2014-09, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    63. Fu, Zhonghao & Hong, Yongmiao & Su, Liangjun & Wang, Xia, 2023. "Specification tests for time-varying coefficient models," Journal of Econometrics, Elsevier, vol. 235(2), pages 720-744.
    64. Matteo Iacopini & Luca Rossini, 2019. "Bayesian nonparametric graphical models for time-varying parameters VAR," Papers 1906.02140, arXiv.org.
    65. Jan Prüser, 2021. "Forecasting US inflation using Markov dimension switching," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 481-499, April.
    66. Bäurle Gregor & Kaufmann Daniel & Kaufmann Sylvia & Strachan Rodney, 2020. "Constrained interest rates and changing dynamics at the zero lower bound," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(2), pages 1-26, April.
    67. Felix Abramovich & Vadim Grinshtein, 2013. "Estimation of a sparse group of sparse vectors," Biometrika, Biometrika Trust, vol. 100(2), pages 355-370.
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    69. Lopes, Hedibert F. & McCulloch, Robert E. & Tsay, Ruey S., 2022. "Parsimony inducing priors for large scale state–space models," Journal of Econometrics, Elsevier, vol. 230(1), pages 39-61.
    70. Fu, Bowen, 2020. "Is the slope of the Phillips curve time-varying? Evidence from unobserved components models," Economic Modelling, Elsevier, vol. 88(C), pages 320-340.
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    72. Marta Banbura & Andries van Vlodrop, 2018. "Forecasting with Bayesian Vector Autoregressions with Time Variation in the Mean," Tinbergen Institute Discussion Papers 18-025/IV, Tinbergen Institute.
    73. Malefaki, Valia, 2015. "On Flexible Linear Factor Stochastic Volatility Models," MPRA Paper 62216, University Library of Munich, Germany.
    74. Philippe Goulet Coulombe, 2020. "Time-Varying Parameters as Ridge Regressions," Papers 2009.00401, arXiv.org, revised Apr 2023.
    75. Sakaria, D.K. & Griffin, J.E., 2017. "On efficient Bayesian inference for models with stochastic volatility," Econometrics and Statistics, Elsevier, vol. 3(C), pages 23-33.

  48. Gefang, Deborah & Koop, Gary & Potter, Simon M., 2011. "Understanding Liquidity and Credit Risks in the Financial Crisis," SIRE Discussion Papers 2011-26, Scottish Institute for Research in Economics (SIRE).

    Cited by:

    1. Soedarmono, Wahyoe & Machrouh, Fouad & Tarazi, Amine, 2013. "Bank competition, crisis and risk taking: Evidence from emerging markets in Asia," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 23(C), pages 196-221.
    2. Mark D. Flood & John C. Liechty & Thomas Piontek, 2015. "Systemwide Commonalities in Market Liquidity," Working Papers 15-11, Office of Financial Research, US Department of the Treasury.
    3. Thomas B. King & Kurt F. Lewis, 2020. "Credit Risk, Liquidity, and Lies," International Journal of Central Banking, International Journal of Central Banking, vol. 16(5), pages 219-267, October.
    4. Azusa Takeyama & Naoshi Tsuchida, 2015. "The Interaction between Funding Liquidity and Market Liquidity: Evidence from Subprime and European Crises," IMES Discussion Paper Series 15-E-14, Institute for Monetary and Economic Studies, Bank of Japan.
    5. Mesias Alfeus & Martino Grasselli & Erik Schlögl, 2017. "A Consistent Stochastic Model of the Term Structure of Interest Rates for Multiple Tenors," Research Paper Series 384, Quantitative Finance Research Centre, University of Technology, Sydney.
    6. Sheng Huang & Jonathan Williams & Ru Xie, 2017. "The Future of Money: Liquidity co-movement between financial institutions and real estate firms: evidence from China," Working Papers 17004, Bangor Business School, Prifysgol Bangor University (Cymru / Wales).
    7. Tu, Anthony H. & Chen, Cathy Yi-Hsuan, 2018. "A factor-based approach of bond portfolio value-at-risk: The informational roles of macroeconomic and financial stress factors," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 243-268.
    8. James J. McAndrews & Asani Sarkar & Zhenyu Wang, 2008. "The effect of the Term Auction Facility on the London inter-bank offered rate," Staff Reports 335, Federal Reserve Bank of New York.
    9. Muto, Ichiro, 2012. "A Simple Interest Rate Model with Unobserved Components: The Role of the Interbank Reference Rate," MPRA Paper 43220, University Library of Munich, Germany.
    10. Wolfgang Aussenegg & Lukas Goetz & Ranko Jelic, 2015. "Common Factors in the Performance of European Corporate Bonds – Evidence before and after the Financial Crisis," European Financial Management, European Financial Management Association, vol. 21(2), pages 265-308, March.
    11. Rim Boussaada & Abdelaziz Hakimi & Majdi Karmani, 2022. "Is there a threshold effect in the liquidity risk–non‐performing loans relationship? A PSTR approach for MENA banks," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 1886-1898, April.
    12. Gerhart, Christoph & Lütkebohmert, Eva, 2020. "Empirical analysis and forecasting of multiple yield curves," Insurance: Mathematics and Economics, Elsevier, vol. 95(C), pages 59-78.
    13. Alfred Wong & Jiayue Zhang, 2018. "Breakdown of covered interest parity: mystery or myth?," BIS Papers chapters, in: Bank for International Settlements (ed.), The price, real and financial effects of exchange rates, volume 96, pages 57-78, Bank for International Settlements.
    14. Vladyslav Sushko & Claudio Borio & Robert Neil McCauley & Patrick McGuire, 2016. "The failure of covered interest parity: FX hedging demand and costly balance sheets," BIS Working Papers 590, Bank for International Settlements.
    15. Smales, Lee A., 2016. "News sentiment and bank credit risk," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 37-61.
    16. Gunay, Samet, 2020. "Seeking causality between liquidity risk and credit risk: TED-OIS spreads and CDS indexes," Research in International Business and Finance, Elsevier, vol. 52(C).
    17. Alfred Wong & David Leung & Calvin Ng, 2016. "Risk-adjusted Covered Interest Parity: Theory and Evidence," Working Papers 162016, Hong Kong Institute for Monetary Research.
    18. Goldstein, Michael A. & Namin, Elmira Shekari, 2023. "Corporate bond liquidity and yield spreads: A review," Research in International Business and Finance, Elsevier, vol. 65(C).
    19. Hassan, M. Kabir & Khan, Ashraf & Paltrinieri, Andrea, 2019. "Liquidity risk, credit risk and stability in Islamic and conventional banks," Research in International Business and Finance, Elsevier, vol. 48(C), pages 17-31.
    20. Yoldas, Emre & Senyuz, Zeynep, 2018. "Financial stress and equilibrium dynamics in term interbank funding markets," Journal of Financial Stability, Elsevier, vol. 34(C), pages 136-149.
    21. Alfred Wong & Jiayue Zhang, 2018. "Breakdown of covered interest parity: mystery or myth?," FIW Working Paper series 182, FIW.
    22. Thomas B. King & Kurt F. Lewis, 2014. "What Drives Bank Funding Spreads?," Working Paper Series WP-2014-23, Federal Reserve Bank of Chicago.
    23. Pedro Pires Ribeiro & José Dias Curto, 2017. "Volatility spillover effects in interbank money markets," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 153(1), pages 105-136, February.
    24. Casavecchia, Lorenzo & Loudon, Geoffrey F. & Wu, Eliza, 2018. "What moves benchmark money market rates? Evidence from the BBSW market," Pacific-Basin Finance Journal, Elsevier, vol. 51(C), pages 137-154.
    25. Cottrell, Simon & Yu, Xiao & Delpachitra, Sarath & Ma, Yihong, 2021. "What determines wholesale funding costs of the global systemically important banks?," Journal of Banking & Finance, Elsevier, vol. 132(C).
    26. Gallitschke, Janek & Seifried (née Müller), Stefanie & Seifried, Frank Thomas, 2017. "Interbank interest rates: Funding liquidity risk and XIBOR basis spreads," Journal of Banking & Finance, Elsevier, vol. 78(C), pages 142-152.
    27. Andreas Schrimpf & Vladyslav Sushko, 2019. "Beyond LIBOR: a primer on the new benchmark rates," BIS Quarterly Review, Bank for International Settlements, March.
    28. Alfred Wong & David Leung & Calvin Ng, 2016. "How do housing purchase limits affect firm default risks in Mainland China?," Working Papers 172016, Hong Kong Institute for Monetary Research.
    29. Anthony H. Tu & Cathy Yi-Hsuan Chen, 2016. "What Derives the Bond Portfolio Value-at-Risk: Information Roles of Macroeconomic and Financial Stress Factors," SFB 649 Discussion Papers SFB649DP2016-006, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    30. Carpenter, Seth B. & Demiralp, Selva & Senyuz, Zeynep, 2016. "Volatility in the federal funds market and money market spreads during the financial crisis," Journal of Financial Stability, Elsevier, vol. 25(C), pages 225-233.
    31. Prokopczuk, Marcel & Siewert, Jan B. & Vonhoff, Volker, 2013. "Credit risk in covered bonds," Journal of Empirical Finance, Elsevier, vol. 21(C), pages 102-120.
    32. José Da Fonseca & Peiming Wang, 2016. "A joint analysis of market indexes in credit default swap, volatility and stock markets," Applied Economics, Taylor & Francis Journals, vol. 48(19), pages 1767-1784, April.
    33. Nikolaos Karouzakis, 2021. "The role of time‐varying risk premia in international interbank markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5720-5745, October.
    34. Cui, Jin & In, Francis & Maharaj, Elizabeth Ann, 2016. "What drives the Libor–OIS spread? Evidence from five major currency Libor–OIS spreads," International Review of Economics & Finance, Elsevier, vol. 45(C), pages 358-375.

  49. Koop, G. & Pesaran, M.H. & Smith, R., 2011. "On Identification of Bayesian DSGE Models," Cambridge Working Papers in Economics 1131, Faculty of Economics, University of Cambridge.

    Cited by:

    1. F. Canova & F. Ferroni & C. Matthes, 2015. "Approximating time varying structural models with time invariant structures," Working papers 578, Banque de France.
    2. Andrzej Kocięcki & Marcin Kolasa, 2022. "A solution to the global identification problem in DSGE models," Working Papers 2022-01, Faculty of Economic Sciences, University of Warsaw.
    3. Francesco Zanetti & Christoph Görtz & John D. Tsoukalas, 2016. "News Shocks under Financial Frictions," Economics Series Working Papers 813, University of Oxford, Department of Economics.
    4. Kamber, Gunes & McDonald, Chris & Sander, Nick & Theodoridis, Konstantinos, 2016. "Modelling the business cycle of a small open economy: The Reserve Bank of New Zealand's DSGE model," Economic Modelling, Elsevier, vol. 59(C), pages 546-569.
    5. Yunus Aksoy & Henrique S. Basso & Ron P. Smith & Tobias Grasl, 2019. "Demographic Structure and Macroeconomic Trends," American Economic Journal: Macroeconomics, American Economic Association, vol. 11(1), pages 193-222, January.
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    11. Chadha, Jagjit S. & Shibayama, Katsuyuki, 2018. "Bayesian estimation of DSGE models: Identification using a diagnostic indicator," Journal of Economic Dynamics and Control, Elsevier, vol. 95(C), pages 172-186.
    12. Adjemian, Michael K. & Bruno, Valentina G. & Robe, Michel A., 2016. "Forward‐Looking USDA Price Forecasts," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235931, Agricultural and Applied Economics Association.
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    14. Chen, Xiaoshan & Kirsanova, Tatiana & Leith, Campbell, 2017. "An empirical assessment of Optimal Monetary Policy in the Euro area," European Economic Review, Elsevier, vol. 100(C), pages 95-115.
    15. Willi Mutschler, 2014. "Identification of DSGE Models - the Effect of Higher-Order Approximation and Pruning," CQE Working Papers 3314, Center for Quantitative Economics (CQE), University of Muenster.
    16. Chatelain, Jean-Bernard & Ralf, Kirsten, 2018. "Publish and Perish: Creative Destruction and Macroeconomic Theory," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 46(2), pages 65-101.
    17. Chih‐Sheng Hsieh & Lung‐Fei Lee & Vincent Boucher, 2020. "Specification and estimation of network formation and network interaction models with the exponential probability distribution," Quantitative Economics, Econometric Society, vol. 11(4), pages 1349-1390, November.
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    22. Pablo A. Guerrón-Quintana & James M. Nason, 2013. "Bayesian estimation of DSGE models," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 21, pages 486-512, Edward Elgar Publishing.
    23. Güneş Kamber & Chris McDonald & Nicholas Sander & Konstantinos Theodoridis, 2015. "A structural model for policy analysis and forecasting: NZSIM," Reserve Bank of New Zealand Discussion Paper Series DP2015/05, Reserve Bank of New Zealand.
    24. Wickens, Michael R. & Pagan, Adrian, 2019. "Checking if the Straitjacket Fits," CEPR Discussion Papers 14140, C.E.P.R. Discussion Papers.
    25. Lenhle Dlamini & Harold Ngalawa, 2022. "Macroprudential policy and house prices in an estimated Dynamic Stochastic General Equilibrium model for South Africa," Australian Economic Papers, Wiley Blackwell, vol. 61(2), pages 304-336, June.
    26. Ivashchenko, Sergey & Mutschler, Willi, 2020. "The effect of observables, functional specifications, model features and shocks on identification in linearized DSGE models," Economic Modelling, Elsevier, vol. 88(C), pages 280-292.
    27. Zhu, Yanyuan & Feng, Xiao, 2014. "China's national production function since 1997: A reinvestigation," Working Papers in Economics 2014,2, Bundeswehr University Munich, Economic Research Group.
    28. Claire A. Reicher, 2016. "A Note on the Identification of Dynamic Economic Models with Generalized Shock Processes," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(3), pages 412-423, June.
    29. X. Liu & A.R. Pagan & T. Robinson, 2018. "Critically assessing estimated DSGE models: A case study of a multi-sector model," CAMA Working Papers 2018-04, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    30. Ho, Paul, 2023. "Global robust Bayesian analysis in large models," Journal of Econometrics, Elsevier, vol. 235(2), pages 608-642.
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    32. Kai Liu, 2014. "Public Finances, Business Cycles and Structural Fiscal Balances," Cambridge Working Papers in Economics 1411, Faculty of Economics, University of Cambridge.
    33. Alfred Stiassny & Christina Uhl, 2014. "Does Elderly Employment have an Impact on Youth Employment? A General Equilibrium Approach," Department of Economics Working Papers wuwp178, Vienna University of Economics and Business, Department of Economics.
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  50. Gefang, Deborah & Koop, Gary & Potter, Simon M., 2011. "The Dynamics of UK and US Inflation Expectations," SIRE Discussion Papers 2011-47, Scottish Institute for Research in Economics (SIRE).

    Cited by:

    1. Speck, Christian, 2016. "Inflation Anchoring in the Euro Area," VfS Annual Conference 2016 (Augsburg): Demographic Change 145697, Verein für Socialpolitik / German Economic Association.
    2. Petra Gerlach-Kristen & Richhild Mössner, 2014. "Inflation Expectations, Central Bank Credibility and the Global Financial Crisis," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 150(II), pages 55-87, June.
    3. J. Easaw & R. Golinelli & M. Malgarini, 2012. "Do Households Anchor their Inflation Expectations? Theory and Evidence from a Household Survey," Working Papers wp842, Dipartimento Scienze Economiche, Universita' di Bologna.
    4. Buono, Ines & Formai, Sara, 2018. "New evidence on the evolution of the anchoring of inflation expectations," Journal of Macroeconomics, Elsevier, vol. 57(C), pages 39-54.
    5. Speck, Christian, 2017. "Inflation anchoring in the euro area," Working Paper Series 1998, European Central Bank.
    6. Nyberg, Henri & Saikkonen, Pentti, 2012. "Forecasting with a noncausal VAR model," Bank of Finland Research Discussion Papers 33/2012, Bank of Finland.
    7. Till Strohsal & Lars Winkelmann, 2012. "Assessing the Anchoring of Inflation Expectations," SFB 649 Discussion Papers SFB649DP2012-022, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    8. José Vicente Romero & Sara Naranjo-Saldarriaga, 2022. "Weather Shocks and Inflation Expectations in Semi-Structural Models," Borradores de Economia 1218, Banco de la Republica de Colombia.
    9. Strohsal, Till & Winkelmann, Lars, 2015. "Assessing the anchoring of inflation expectations," Journal of International Money and Finance, Elsevier, vol. 50(C), pages 33-48.
    10. Suh, Sangwon & Kim, Daehwan, 2021. "Inflation targeting and expectation anchoring: Evidence from developed and emerging market economies," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    11. James Yetman, 2020. "Pass-through from short-horizon to long-horizon inflation expectations, and the anchoring of inflation expectations," BIS Working Papers 895, Bank for International Settlements.
    12. Inês da Cunha Cabral & Pedro Pires Ribeiro & João Nicolau, 2022. "Changes in inflation compensation and oil prices: short-term and long-term dynamics," Empirical Economics, Springer, vol. 62(2), pages 581-603, February.
    13. Speck, Christian, 2016. "Inflation anchoring in the euro area," Discussion Papers 04/2016, Deutsche Bundesbank.
    14. Hossein Hassani & Jan Coreman & Saeed Heravi & Joshy Easaw, 2018. "Forecasting Inflation Rate: Professional Against Academic, Which One is More Accurate," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(3), pages 631-646, September.
    15. James Yetman, 2020. "The pass-through from short-horizon to long-horizon inflation expectations," BIS Papers chapters, in: Bank for International Settlements (ed.), Inflation dynamics in Asia and the Pacific, volume 111, pages 55-66, Bank for International Settlements.
    16. Helder Ferreira de Mendonça & Pedro Mendes Garcia & José Valentim Machado Vicente, 2021. "Rationality and anchoring of inflation expectations: An assessment from survey‐based and market‐based measures," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(6), pages 1027-1053, September.

  51. Koop, Gary & Onorante, Luca, 2011. "Estimating Phillips Curves in Turbulent Times using the ECB’s Survey of Professional Forecasters," SIRE Discussion Papers 2011-19, Scottish Institute for Research in Economics (SIRE).

    Cited by:

    1. Sophocles Mavroeidis & Mikkel Plagborg-Møller & James H. Stock, 2014. "Empirical Evidence on Inflation Expectations in the New Keynesian Phillips Curve," Journal of Economic Literature, American Economic Association, vol. 52(1), pages 124-188, March.
    2. Baxa, Jaromír & Plašil, Miroslav & Vašíček, Bořek, 2015. "Changes in inflation dynamics under inflation targeting? Evidence from Central European countries," Economic Modelling, Elsevier, vol. 44(C), pages 116-130.
    3. Lanne, Markku & Luoto, Jani, 2011. "Autoregression-Based Estimation of the New Keynesian Phillips Curve," MPRA Paper 29801, University Library of Munich, Germany.

  52. Koop, Gary, 2011. "Forecasting with Medium and Large Bayesian VARs," SIRE Discussion Papers 2011-38, Scottish Institute for Research in Economics (SIRE).

    Cited by:

    1. Koop, Gary & Korobilis, Dimitris, 2016. "Model uncertainty in Panel Vector Autoregressive models," European Economic Review, Elsevier, vol. 81(C), pages 115-131.
    2. Joshua C.C. Chan & Angelia L. Grant, 2016. "Reconciling output gaps: unobserved components model and Hodrick-Prescott filter," CAMA Working Papers 2016-44, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    3. Anastasios Evgenidis & Stephanos Papadamou, 2021. "The impact of unconventional monetary policy in the euro area. Structural and scenario analysis from a Bayesian VAR," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5684-5703, October.
    4. Huber, Florian, 2016. "Density forecasting using Bayesian global vector autoregressions with stochastic volatility," International Journal of Forecasting, Elsevier, vol. 32(3), pages 818-837.
    5. Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2020. "Efficient selection of hyperparameters in large Bayesian VARs using automatic differentiation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 934-943, September.
    6. Louzis Dimitrios P., 2016. "Steady-state priors and Bayesian variable selection in VAR forecasting," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(5), pages 495-527, December.
    7. Joshua C. C. Chan & Xuewen Yu, 2022. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," Papers 2206.08438, arXiv.org.
    8. Tallman, Ellis W. & Zaman, Saeed, 2020. "Combining survey long-run forecasts and nowcasts with BVAR forecasts using relative entropy," International Journal of Forecasting, Elsevier, vol. 36(2), pages 373-398.
    9. Gefang, Deborah & Koop, Gary & Poon, Aubrey, 2023. "Forecasting using variational Bayesian inference in large vector autoregressions with hierarchical shrinkage," International Journal of Forecasting, Elsevier, vol. 39(1), pages 346-363.
    10. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2022. "Using hierarchical aggregation constraints to nowcast regional economic aggregates," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-04, Economic Statistics Centre of Excellence (ESCoE).
    11. Scott Brave & R. Andrew Butters & Alejandro Justiniano, 2016. "Forecasting Economic Activity with Mixed Frequency Bayesian VARs," Working Paper Series WP-2016-5, Federal Reserve Bank of Chicago.
    12. Karlsson, Sune, 2012. "Forecasting with Bayesian Vector Autoregressions," Working Papers 2012:12, Örebro University, School of Business.
    13. Deborah Gefang & Gary Koop & Aubrey Poon, 2019. "Variational Bayesian inference in large Vector Autoregressions with hierarchical shrinkage," CAMA Working Papers 2019-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    14. Berger, Tino & Richter, Julia & Wong, Benjamin, 2021. "A unified approach for jointly estimating the business and financial cycle, and the role of financial factors," University of Göttingen Working Papers in Economics 415, University of Goettingen, Department of Economics.
    15. Bańbura, Marta & Giannone, Domenico & Lenza, Michele, 2015. "Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections," International Journal of Forecasting, Elsevier, vol. 31(3), pages 739-756.
    16. Koop, Gary & McIntyre, Stuart & Mitchell, James & Poon, Aubrey, 2019. "Regional Output Growth in the United Kingdom: More Timely and Higher Frequency Estimates, 1970-2017," EMF Research Papers 20, Economic Modelling and Forecasting Group.
    17. Cross, Jamie L. & Hou, Chenghan & Koop, Gary & Poon, Aubrey, 2023. "Large stochastic volatility in mean VARs," Journal of Econometrics, Elsevier, vol. 236(1).
    18. Marco Centoni & Gianluca Cubadda, 2015. "Common Feature Analysis of Economic Time Series: An Overview and Recent Developments," CEIS Research Paper 355, Tor Vergata University, CEIS, revised 05 Oct 2015.
    19. Knüppel, Malte & Krüger, Fabian & Pohle, Marc-Oliver, 2022. "Score-based calibration testing for multivariate forecast distributions," Discussion Papers 50/2022, Deutsche Bundesbank.
    20. Edward S. Knotek & Saeed Zaman, 2017. "Financial Nowcasts and Their Usefulness in Macroeconomic Forecasting," Working Papers (Old Series) 1702, Federal Reserve Bank of Cleveland.
    21. Gary Koop, 2012. "Using VARs and TVP-VARs with Many Macroeconomic Variables," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 4(3), pages 143-167, September.
    22. Niko Hauzenberger & Florian Huber & Luca Onorante, 2021. "Combining shrinkage and sparsity in conjugate vector autoregressive models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(3), pages 304-327, April.
    23. Brave, Scott A. & Butters, R. Andrew & Justiniano, Alejandro, 2019. "Forecasting economic activity with mixed frequency BVARs," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1692-1707.
    24. Michael W. McCracken & Joseph McGillicuddy, 2017. "An Empirical Investigation of Direct and Iterated Multistep Conditional Forecasts," Working Papers 2017-40, Federal Reserve Bank of St. Louis.
    25. Berg Tim Oliver, 2017. "Forecast accuracy of a BVAR under alternative specifications of the zero lower bound," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(2), pages 1-29, April.
    26. Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2016. "Bayesian Compressed Vector Autoregressions," Working Papers 103, Brandeis University, Department of Economics and International Business School.
    27. Alain Kabundi & Deniz Igan & Francisco N. de Simone & Natalia Tamirisa, 2013. "Monetary Policy and Balance Sheets," Working Papers 364, Economic Research Southern Africa.
    28. Giannoni, Marc & Boivin, Jean & Stevanovic, Dalibor, 2013. "Dynamic Effects of Credit Shocks in a Data-Rich Environment," CEPR Discussion Papers 9470, C.E.P.R. Discussion Papers.
    29. Gary Koop & Dimitris Korobilis, 2012. "Large Time-Varying Parameter VARs," Working Paper series 11_12, Rimini Centre for Economic Analysis.
    30. Chan, Joshua C.C. & Eisenstat, Eric & Strachan, Rodney W., 2020. "Reducing the state space dimension in a large TVP-VAR," Journal of Econometrics, Elsevier, vol. 218(1), pages 105-118.
    31. Reichlin, Lucrezia & Giannone, Domenico & Modugno, Michele & Banbura, Marta, 2012. "Now-casting and the real-time data flow," CEPR Discussion Papers 9112, C.E.P.R. Discussion Papers.
    32. Andrejs Bessonovs, 2015. "Suite of Latvia's GDP forecasting models," Working Papers 2015/01, Latvijas Banka.
    33. Stefański, Maciej, 2022. "Macroeconomic effects and transmission channels of quantitative easing," Economic Modelling, Elsevier, vol. 114(C).
    34. Chin, Kuo-Hsuan & Li, Xue, 2019. "Bayesian forecast combination in VAR-DSGE models," Journal of Macroeconomics, Elsevier, vol. 59(C), pages 278-298.
    35. Eric Eisenstat & Joshua C.C. Chan & Rodney W. Strachan, 2014. "Stochastic Model Specification Search for Time-Varying Parameter VARs," CAMA Working Papers 2014-23, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    36. Billio, Monica & Casarin, Roberto & Rossini, Luca, 2019. "Bayesian nonparametric sparse VAR models," Journal of Econometrics, Elsevier, vol. 212(1), pages 97-115.
    37. Bernardini, Emmanuela & Cubadda, Gianluca, 2015. "Macroeconomic forecasting and structural analysis through regularized reduced-rank regression," International Journal of Forecasting, Elsevier, vol. 31(3), pages 682-691.
    38. Joshua C.C. Chan & Eric Eisenstat & Chenghan Hou & Gary Koop, 2018. "Composite likelihood methods for large Bayesian VARs with stochastic volatility," CAMA Working Papers 2018-26, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    39. Everett Grant, 2018. "The Double-Edged Sword of Global Integration: Robustness, Fragility \& Contagion in the International Firm Network," 2018 Meeting Papers 506, Society for Economic Dynamics.
    40. Camehl, Annika, 2023. "Penalized estimation of panel vector autoregressive models: A panel LASSO approach," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1185-1204.
    41. Joshua C. C. Chan, 2020. "Large Bayesian VARs: A Flexible Kronecker Error Covariance Structure," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(1), pages 68-79, January.
    42. Gächter, Martin & Huber, Florian & Meier, Martin, 2022. "A shot for the US economy," Finance Research Letters, Elsevier, vol. 47(PA).
    43. Petrova, Katerina, 2019. "A quasi-Bayesian local likelihood approach to time varying parameter VAR models," Journal of Econometrics, Elsevier, vol. 212(1), pages 286-306.
    44. Joshua C. C. Chan, 2022. "Comparing Stochastic Volatility Specifications for Large Bayesian VARs," Papers 2208.13255, arXiv.org.
    45. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
    46. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    47. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2014. "No Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates," CEPR Discussion Papers 9848, C.E.P.R. Discussion Papers.
    48. Michaelides, Panayotis G. & Tsionas, Efthymios G. & Konstantakis, Konstantinos N., 2018. "Debt Crisis in Europe (2001-2015): A Network General Equilibrium GVAR approach," MPRA Paper 89998, University Library of Munich, Germany.
    49. Konstantakis, Konstantinos N. & Michaelides, Panayotis G. & Tsionas, Efthymios G. & Minou, Chrysanthi, 2015. "System estimation of GVAR with two dominants and network theory: Evidence for BRICs," Economic Modelling, Elsevier, vol. 51(C), pages 604-616.
    50. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015. "Large Vector Autoregressions with Asymmetric Priors," Working Papers 759, Queen Mary University of London, School of Economics and Finance.
    51. Cristina Fuentes-Albero & Leonardo Melosi, 2011. "Methods for Computing Marginal Data Densities from the Gibbs Output," Departmental Working Papers 201131, Rutgers University, Department of Economics.
    52. Thomas Horvath & Peter Huber & Ulrike Huemer & Helmut Mahringer & Philipp Piribauer & Mark Sommer & Stefan Weingärtner, 2022. "Mittelfristige Beschäftigungsprognose für Österreich und die Bundesländer. Berufliche und sektorale Veränderungen 2021 bis 2028," WIFO Studies, WIFO, number 70720, Juni.
    53. Joshua Chan & Luca Benati & Eric Eisenstat & Gary Koop, 2018. "Identifying Noise Shocks," Working Paper Series 41, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
    54. Chenghan Hou & Bao Nguyen & Bo Zhang, 2023. "Real‐time forecasting of the Australian macroeconomy using flexible Bayesian VARs," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 418-451, March.
    55. Marian Fink & Thomas Horvath & Peter Huber & Ulrike Huemer & Mathias Kirchner & Helmut Mahringer & Philipp Piribauer, 2017. "Mittelfristige Beschäftigungsprognose für Österreich und die Bundesländer. Berufliche und sektorale Veränderungen 2016 bis 2023," WIFO Studies, WIFO, number 60948, Juni.
    56. Andrea Carriero & Galvao, Ana Beatriz & Kapetanios, George, 2016. "A comprehensive evaluation of macroeconomic forecasting methods," EMF Research Papers 10, Economic Modelling and Forecasting Group.
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    58. Joshua C C Chan & Eric Eisenstat & Gary Koop, 2014. "Large Bayesian VARMAs," Working Papers 1409, University of Strathclyde Business School, Department of Economics.
    59. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
    60. Luis A. Gil-Alana & Rangan Gupta & Olusanya E. Olubusoye & OlaOluwa S. Yaya, 2015. "Time Series Analysis of Persistence in Crude Oil Price Volatility across Bull and Bear Regimes," Working Papers 201580, University of Pretoria, Department of Economics.
    61. Todd E. Clark & Michael W. McCracken, 2014. "Evaluating Conditional Forecasts from Vector Autoregressions," Working Papers 2014-25, Federal Reserve Bank of St. Louis.
    62. De Gooijer, Jan G. & Zerom, Dawit, 2019. "Semiparametric quantile averaging in the presence of high-dimensional predictors," International Journal of Forecasting, Elsevier, vol. 35(3), pages 891-909.
    63. Maiorova, Ksenia & Fokin, Nikita, 2020. "Наукастинг Темпов Роста Стоимостных Объемов Экспорта И Импорта По Товарным Группам [Nowcasting the growth rates of the export and import by commodity groups]," MPRA Paper 109557, University Library of Munich, Germany.
    64. Damian Stelmasiak & Grzegorz Szafrański, 2016. "Forecasting the Polish Inflation Using Bayesian VAR Models with Seasonality," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 8(1), pages 21-42, March.
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    68. Pestova, Anna & Mamonov, Mikhail, 2019. "Should we care? The economic effects of financial sanctions on the Russian economy," BOFIT Discussion Papers 13/2019, Bank of Finland Institute for Emerging Economies (BOFIT).
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  53. Koop, Gary & Korobilis, Dimitris, 2011. "UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So?," SIRE Discussion Papers 2011-39, Scottish Institute for Research in Economics (SIRE).

    Cited by:

    1. Goodness C. Aye & Rangan Gupta & Shawkat Hammoudeh & Won Joong Kim, 2014. "Forecasting the Price of Gold Using Dynamic Model Averaging," Working Papers 201415, University of Pretoria, Department of Economics.
    2. Goodness C. Aye & Stephen M. Miller & Rangan Gupta & Mehmet Balcilar, 2013. "Forecasting the US Real Private Residential Fixed Investment Using Large Number of Predictors," Working Papers 201348, University of Pretoria, Department of Economics.
    3. Mihaela Simionescu (Bratu), 2014. "The Performance of Predictions Based on the Dobrescu Macromodel for the Romanian Economy," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 179-195, October.
    4. Davide Pettenuzzo & Francesco Ravazzolo, 2014. "Optimal portfolio choice under decision-based model combinations," Working Paper 2014/15, Norges Bank.
    5. Jan Prüser, 2019. "Adaptive learning from model space," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(1), pages 29-38, January.
    6. Mehmet Balcilar & Rangan Gupta & Clement Kyei & Mark Wohar, 2015. "Does Economic Policy Uncertainty Predict Exchange Rate Returns and Volatility? Evidence from a Nonparametric Causality-in-Quantiles Test," Working Papers 201599, University of Pretoria, Department of Economics.
    7. Afees A. Salisu & Kazeem Isah, 2017. "Predicting US CPI-Inflation in the presence of asymmetries, persistence, endogeneity, and conditional heteroscedasticity," Working Papers 026, Centre for Econometric and Allied Research, University of Ibadan.
    8. Rangan Gupta & Shawkat Hammoudeh & Won Joong Kim & Beatrice D. Simo-Kengne, 2013. "Forecasting China’s Foreign Exchange Reserves Using Dynamic Model Averaging: The Role of Macroeconomic Fundamentals, Financial Stress and Economic Uncertainty," Working Papers 201338, University of Pretoria, Department of Economics.
    9. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
    10. Zhang, Yaojie & Wahab, M.I.M. & Wang, Yudong, 2023. "Forecasting crude oil market volatility using variable selection and common factor," International Journal of Forecasting, Elsevier, vol. 39(1), pages 486-502.
    11. Ouysse, Rachida, 2016. "Bayesian model averaging and principal component regression forecasts in a data rich environment," International Journal of Forecasting, Elsevier, vol. 32(3), pages 763-787.
    12. Drachal, Krzysztof, 2019. "Forecasting prices of selected metals with Bayesian data-rich models," Resources Policy, Elsevier, vol. 64(C).
    13. Catania, Leopoldo & Grassi, Stefano & Ravazzolo, Francesco, 2019. "Forecasting cryptocurrencies under model and parameter instability," International Journal of Forecasting, Elsevier, vol. 35(2), pages 485-501.
    14. Hyeyoen Kim & Doojin Ryu, 2013. "Forecasting Exchange Rate from Combination Taylor Rule Fundamental," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 49(S4), pages 81-92, September.
    15. Naser, Hanan, 2016. "Estimating and forecasting the real prices of crude oil: A data rich model using a dynamic model averaging (DMA) approach," Energy Economics, Elsevier, vol. 56(C), pages 75-87.
    16. Danglun Luo & Qianwei Ying, 2014. "Political Connections and Bank Lines of Credit," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 50(03), pages 5-21, May.
    17. MeiChi Huang, 2019. "A Nationwide or Localized Housing Crisis? Evidence from Structural Instability in US Housing Price and Volume Cycles," Computational Economics, Springer;Society for Computational Economics, vol. 53(4), pages 1547-1563, April.
    18. Tomás Marinozzi, 2023. "Forecasting Inflation in Argentina: A Probabilistic Approach," Ensayos Económicos, Central Bank of Argentina, Economic Research Department, vol. 1(81), pages 81-110, May.
    19. Pierre Guérin & Danilo Leiva-Leon, 2015. "Model Averaging in Markov-Switching Models: Predicting National Recessions with Regional Data," Staff Working Papers 15-24, Bank of Canada.
    20. Nonejad, Nima, 2021. "Predicting equity premium using dynamic model averaging. Does the state–space representation matter?," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    21. Katarzyna Maciejowska & Bartosz Uniejewski & Tomasz Serafin, 2020. "PCA forecast averaging - predicting day-ahead and intraday electricity prices," WORking papers in Management Science (WORMS) WORMS/20/02, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    22. Nombulelo Gumata & Alain Kabundi & Eliphas Ndou, 2013. "Important channels of transmission of monetary policy shock in South Africa," Working Papers 6021, South African Reserve Bank.
    23. Pallara, Kevin, 2016. "The dynamic effects of government spending: a FAVAR approach," MPRA Paper 92283, University Library of Munich, Germany.
    24. Nuri Hacıevliyagil & Krzysztof Drachal & Ibrahim Halil Eksi, 2022. "Predicting House Prices Using DMA Method: Evidence from Turkey," Economies, MDPI, vol. 10(3), pages 1-27, March.
    25. Nicholas Apergis & Ghassen El Montasser & Emmanuel Owusu-Sekyere & Ahdi N. Ajmi & Rangan Gupta, 2014. "Dutch Disease Effect of Oil Rents on Agriculture Value Added in MENA Countries," Working Papers 201408, University of Pretoria, Department of Economics.
    26. Matei, Florin, 2014. "An empirical examination of stock market integration in EMU," MPRA Paper 60717, University Library of Munich, Germany.
    27. Kola Akinsomi & Goodness C. Aye & Vassilios Babalos & Fotini Economou & Rangan Gupta, 2014. "Real Estate Returns Predictability Revisited: Novel Evidence from the US REITs Market," Working Papers 201454, University of Pretoria, Department of Economics.
    28. Behnamian, Mehdi & Shojaee, Abdul Nasser & Haji, Gholamali, 2021. "Investigating the Effective Factors in the Growth of Private Sector Investment in Iran," Quarterly Journal of Applied Theories of Economics, Faculty of Economics, Management and Business, University of Tabriz, vol. 7(4), pages 84-57, February.
    29. Dong, Xiyong & Yoon, Seong-Min, 2019. "What global economic factors drive emerging Asian stock market returns? Evidence from a dynamic model averaging approach," Economic Modelling, Elsevier, vol. 77(C), pages 204-215.
    30. Mohsen Khezri & Seyed Ehsan Hosseinidoust & Mohammad Kazem Naziri, 2019. "Investigating the Temporary and Permanent Influential Variables on Iran Inflation Using TVP-DMA Models," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 23(1), pages 209-234, Winter.
    31. Konstantin Styrin, 2019. "Forecasting Inflation in Russia Using Dynamic Model Averaging," Russian Journal of Money and Finance, Bank of Russia, vol. 78(1), pages 3-18, March.
    32. Konstantin Styrin, 2018. "Forecasting inflation in Russia by Dynamic Model Averaging," Bank of Russia Working Paper Series wps39, Bank of Russia.
    33. Zhemkov, Michael, 2021. "Nowcasting Russian GDP using forecast combination approach," International Economics, Elsevier, vol. 168(C), pages 10-24.
    34. Michelle, Gilmartin, 2016. "A note on the identification and transmission of energy demand and supply shocks," MPRA Paper 76186, University Library of Munich, Germany.
    35. Joshua C.C. Chan & Rodney W. Strachan, 2023. "Bayesian State Space Models In Macroeconometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 58-75, February.
    36. Wang, Tiantian & Qu, Wan & Zhang, Dayong & Ji, Qiang & Wu, Fei, 2022. "Time-varying determinants of China's liquefied natural gas import price: A dynamic model averaging approach," Energy, Elsevier, vol. 259(C).
    37. Wei, Yu & Liu, Jing & Lai, Xiaodong & Hu, Yang, 2017. "Which determinant is the most informative in forecasting crude oil market volatility: Fundamental, speculation, or uncertainty?," Energy Economics, Elsevier, vol. 68(C), pages 141-150.
    38. Naser, Hanan & Alaali, Fatema, 2015. "Can Oil Prices Help Predict US Stock Market Returns: An Evidence Using a DMA Approach," MPRA Paper 65295, University Library of Munich, Germany, revised 25 Jun 2015.
    39. Wang, TianTian & Zhang, Dayong & Clive Broadstock, David, 2019. "Financialization, fundamentals, and the time-varying determinants of US natural gas prices," Energy Economics, Elsevier, vol. 80(C), pages 707-719.
    40. Eraslan, Sercan & Schröder, Maximilian, 2019. "Nowcasting GDP with a large factor model space," Discussion Papers 41/2019, Deutsche Bundesbank.
    41. Hanan Naser & Fatema Alaali, 2018. "Can oil prices help predict US stock market returns? Evidence using a dynamic model averaging (DMA) approach," Empirical Economics, Springer, vol. 55(4), pages 1757-1777, December.
    42. Lin, Boqiang & Su, Tong, 2021. "Do China's macro-financial factors determine the Shanghai crude oil futures market?," International Review of Financial Analysis, Elsevier, vol. 78(C).
    43. Eraslan, Sercan & Schröder, Maximilian, 2023. "Nowcasting GDP with a pool of factor models and a fast estimation algorithm," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1460-1476.
    44. Wei, Yu & Cao, Yang, 2017. "Forecasting house prices using dynamic model averaging approach: Evidence from China," Economic Modelling, Elsevier, vol. 61(C), pages 147-155.
    45. Sakar Hasan Hamza & Qingna Li, 2023. "The Dynamics of US Gasoline Demand and Its Prediction: An Extended Dynamic Model Averaging Approach," Energies, MDPI, vol. 16(12), pages 1-13, June.
    46. Martin Hodula & Simona Malovana & Jan Frait, 2019. "Introducing a New Index of Households' Macroeconomic Conditions," Working Papers 2019/10, Czech National Bank.
    47. Zhongxin Ni & Xing Lu & Wenjun Xue, 2021. "Does the belt and road initiative resolve the steel overcapacity in China? Evidence from a dynamic model averaging approach," Empirical Economics, Springer, vol. 61(1), pages 279-307, July.
    48. Tata Subba Rao & Granville Tunnicliffe Wilson & Ngai Hang Chan & Ye Lu & Chun Yip Yau, 2017. "Factor Modelling for High-Dimensional Time Series: Inference and Model Selection," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(2), pages 285-307, March.
    49. Fasanya, Ismail & Adekoya, Oluwasegun & Oyewole, Oluwatomisin & Adegboyega, Soliu, 2022. "Investor sentiment and energy futures predictability: Evidence from Feasible Quasi Generalized Least Squares," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    50. Naik, Prasad A., 2015. "Marketing Dynamics: A Primer on Estimation and Control," Foundations and Trends(R) in Marketing, now publishers, vol. 9(3), pages 175-266, December.
    51. Leopoldo Catania & Stefano Grassi & Francesco Ravazzolo, 2018. "Forecasting Cryptocurrencies Financial Time Series," Working Papers No 5/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    52. Krzysztof Drachal, 2018. "Some Novel Bayesian Model Combination Schemes: An Application to Commodities Prices," Sustainability, MDPI, vol. 10(8), pages 1-27, August.
    53. Afees A. Salisu & Kazeem Isah, 2017. "Predicting US Inflation: Evidence from a New Approach," Working Papers 039, Centre for Econometric and Allied Research, University of Ibadan.
    54. Simona Malovaná & Martin Hodula & Jan Frait, 2021. "What Does Really Drive Consumer Confidence?," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 155(3), pages 885-913, June.

  54. Koop, Gary & Tole, Lise, 2011. "Forecasting the European Carbon Market," SIRE Discussion Papers 2011-20, Scottish Institute for Research in Economics (SIRE).

    Cited by:

    1. Zhu, Bangzhu & Ye, Shunxin & Han, Dong & Wang, Ping & He, Kaijian & Wei, Yi-Ming & Xie, Rui, 2019. "A multiscale analysis for carbon price drivers," Energy Economics, Elsevier, vol. 78(C), pages 202-216.
    2. Andrea Bastianin & Elisabetta Mirto & Yan Qin & Luca Rossini, 2024. "What drives the European carbon market? Macroeconomic factors and forecasts," Working Papers 2024.02, Fondazione Eni Enrico Mattei.
    3. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
    4. Koch, Nicolas & Fuss, Sabine & Grosjean, Godefroy & Edenhofer, Ottmar, 2014. "Causes of the EU ETS price drop: Recession, CDM, renewable policies or a bit of everything?—New evidence," Energy Policy, Elsevier, vol. 73(C), pages 676-685.
    5. Bastianin, Andrea & Mirto, Elisabetta & Qin, Yan & Rossini, Luca, 2024. "What drives the European carbon market? Macroeconomic factors and forecasts," FEEM Working Papers 339740, Fondazione Eni Enrico Mattei (FEEM).
    6. Po Yun & Chen Zhang & Yaqi Wu & Xianzi Yang & Zulfiqar Ali Wagan, 2020. "A Novel Extended Higher-Order Moment Multi-Factor Framework for Forecasting the Carbon Price: Testing on the Multilayer Long Short-Term Memory Network," Sustainability, MDPI, vol. 12(5), pages 1-16, March.
    7. Naser, Hanan, 2016. "Estimating and forecasting the real prices of crude oil: A data rich model using a dynamic model averaging (DMA) approach," Energy Economics, Elsevier, vol. 56(C), pages 75-87.
    8. Yusupova, Alisa & Pavlidis, Nicos G. & Pavlidis, Efthymios G., 2023. "Dynamic linear models with adaptive discounting," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1925-1944.
    9. Koch, Nicolas & Grosjean, Godefroy & Fuss, Sabine & Edenhofer, Ottmar, 2016. "Politics matters: Regulatory events as catalysts for price formation under cap-and-trade," Journal of Environmental Economics and Management, Elsevier, vol. 78(C), pages 121-139.
    10. Koop, Gary & Tole, Lise, 2013. "Modeling the relationship between European carbon permits and certified emission reductions," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 166-181.
    11. Miguel, Belmonte & Gary, Koop, 2013. "Model Switching and Model Averaging in Time- Varying Parameter Regression Models," SIRE Discussion Papers 2013-34, Scottish Institute for Research in Economics (SIRE).
    12. Pierre Guérin & Danilo Leiva-Leon, 2015. "Model Averaging in Markov-Switching Models: Predicting National Recessions with Regional Data," Staff Working Papers 15-24, Bank of Canada.
    13. Lei, Heng & Xue, Minggao & Liu, Huiling, 2022. "Probability distribution forecasting of carbon allowance prices: A hybrid model considering multiple influencing factors," Energy Economics, Elsevier, vol. 113(C).
    14. Xu, Hua & Wang, Minggang & Jiang, Shumin & Yang, Weiguo, 2020. "Carbon price forecasting with complex network and extreme learning machine," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    15. Liu, Li & Ma, Feng & Wang, Yudong, 2015. "Forecasting excess stock returns with crude oil market data," Energy Economics, Elsevier, vol. 48(C), pages 316-324.
    16. Risse, Marian & Ohl, Ludwig, 2017. "Using dynamic model averaging in state space representation with dynamic Occam’s window and applications to the stock and gold market," Journal of Empirical Finance, Elsevier, vol. 44(C), pages 158-176.
    17. Pan, Zhiyuan & Wang, Qing & Wang, Yudong & Yang, Li, 2018. "Forecasting U.S. real GDP using oil prices: A time-varying parameter MIDAS model," Energy Economics, Elsevier, vol. 72(C), pages 177-187.
    18. Zhu, Bangzhu & Wan, Chunzhuo & Wang, Ping, 2022. "Interval forecasting of carbon price: A novel multiscale ensemble forecasting approach," Energy Economics, Elsevier, vol. 115(C).
    19. Alisa Yusupova & Nicos G. Pavlidis & Efthymios G. Pavlidis, 2019. "Adaptive Dynamic Model Averaging with an Application to House Price Forecasting," Papers 1912.04661, arXiv.org.
    20. Simone Borghesi & Giulio Cainelli & Massimiliano Mazzanti, 2012. "Brown Sunsets and Green Dawns in the Industrial Sector: Environmental Innovations, Firm Behavior and the European Emission Trading," Working Papers 2012.03, Fondazione Eni Enrico Mattei.
    21. Cainelli, Giulio & Mazzanti, Massimiliano, 2013. "Environmental innovations in services: Manufacturing–services integration and policy transmissions," Research Policy, Elsevier, vol. 42(9), pages 1595-1604.
    22. Jonathan Berrisch & Florian Ziel, 2021. "CRPS Learning," Papers 2102.00968, arXiv.org, revised Nov 2021.
    23. Zhu, Bangzhu & Huang, Liqing & Yuan, Lili & Ye, Shunxin & Wang, Ping, 2020. "Exploring the risk spillover effects between carbon market and electricity market: A bidimensional empirical mode decomposition based conditional value at risk approach," International Review of Economics & Finance, Elsevier, vol. 67(C), pages 163-175.
    24. Quande Qin & Huangda He & Li Li & Ling-Yun He, 2020. "A Novel Decomposition-Ensemble Based Carbon Price Forecasting Model Integrated with Local Polynomial Prediction," Computational Economics, Springer;Society for Computational Economics, vol. 55(4), pages 1249-1273, April.
    25. Jian Liu & Ziting Zhang & Lizhao Yan & Fenghua Wen, 2021. "Forecasting the volatility of EUA futures with economic policy uncertainty using the GARCH-MIDAS model," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-19, December.
    26. Venmans, Frank, 2012. "A literature-based multi-criteria evaluation of the EU ETS," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(8), pages 5493-5510.
    27. Zhu, Bangzhu & Han, Dong & Chevallier, Julien & Wei, Yi-Ming, 2017. "Dynamic multiscale interactions between European carbon and electricity markets during 2005–2016," Energy Policy, Elsevier, vol. 107(C), pages 309-322.
    28. Zhu, Bangzhu & Ye, Shunxin & Wang, Ping & He, Kaijian & Zhang, Tao & Wei, Yi-Ming, 2018. "A novel multiscale nonlinear ensemble leaning paradigm for carbon price forecasting," Energy Economics, Elsevier, vol. 70(C), pages 143-157.
    29. Ren, Xiaohang & Duan, Kun & Tao, Lizhu & Shi, Yukun & Yan, Cheng, 2022. "Carbon prices forecasting in quantiles," Energy Economics, Elsevier, vol. 108(C).
    30. Jianguo Zhou & Qiqi Wang, 2021. "Forecasting Carbon Price with Secondary Decomposition Algorithm and Optimized Extreme Learning Machine," Sustainability, MDPI, vol. 13(15), pages 1-17, July.
    31. Bent Jesper Christensen & Nabanita Datta Gupta & Paolo Santucci de Magistris, 2021. "Measuring the impact of clean energy production on CO2 abatement in Denmark: Upper bound estimation and forecasting," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(1), pages 118-149, January.
    32. Hyeonho Kim & Yujin Kim & Yongho Ko & Seungwoo Han, 2022. "Performance Comparison of Predictive Methodologies for Carbon Emission Credit Price in the Korea Emission Trading System," Sustainability, MDPI, vol. 14(13), pages 1-20, July.
    33. Krzysztof Jajuga & Lucjan T. Orlowski & Karsten Staehr (ed.), 2017. "Contemporary Trends and Challenges in Finance," Springer Proceedings in Business and Economics, Springer, number 978-3-319-54885-2, March.
    34. Po Yun & Chen Zhang & Yaqi Wu & Yu Yang, 2022. "Forecasting Carbon Dioxide Price Using a Time-Varying High-Order Moment Hybrid Model of NAGARCHSK and Gated Recurrent Unit Network," IJERPH, MDPI, vol. 19(2), pages 1-19, January.
    35. Huang, Yumeng & Dai, Xingyu & Wang, Qunwei & Zhou, Dequn, 2021. "A hybrid model for carbon price forecastingusing GARCH and long short-term memory network," Applied Energy, Elsevier, vol. 285(C).
    36. Andrea Bastianin & Elisabetta Mirto & Yan Qin & Luca Rossini, 2024. "What drives the European carbon market? Macroeconomic factors and forecasts," Papers 2402.04828, arXiv.org, revised Feb 2024.
    37. Yang Liu & Xueqing Yang & Mei Wang, 2021. "Global Transmission of Returns among Financial, Traditional Energy, Renewable Energy and Carbon Markets: New Evidence," Energies, MDPI, vol. 14(21), pages 1-32, November.
    38. Krzysztof Drachal, 2018. "Some Novel Bayesian Model Combination Schemes: An Application to Commodities Prices," Sustainability, MDPI, vol. 10(8), pages 1-27, August.
    39. Giulio Cainelli & Massimiliano Mazzanti & Simone Borghesi, 2012. "The European Emission Trading Scheme and environmental innovation diffusion: Empirical analyses using Italian CIS data," Working Papers 201201, University of Ferrara, Department of Economics.
    40. Tan, Xueping & Sirichand, Kavita & Vivian, Andrew & Wang, Xinyu, 2022. "Forecasting European carbon returns using dimension reduction techniques: Commodity versus financial fundamentals," International Journal of Forecasting, Elsevier, vol. 38(3), pages 944-969.
    41. Liu, Li & Wang, Yudong & Yang, Li, 2018. "Predictability of crude oil prices: An investor perspective," Energy Economics, Elsevier, vol. 75(C), pages 193-205.
    42. Jianguo Zhou & Xuejing Huo & Xiaolei Xu & Yushuo Li, 2019. "Forecasting the Carbon Price Using Extreme-Point Symmetric Mode Decomposition and Extreme Learning Machine Optimized by the Grey Wolf Optimizer Algorithm," Energies, MDPI, vol. 12(5), pages 1-22, March.
    43. Wang, Minggang & Zhu, Mengrui & Tian, Lixin, 2022. "A novel framework for carbon price forecasting with uncertainties," Energy Economics, Elsevier, vol. 112(C).

  55. Jochmann, Markus & Koop, Gary, 2011. "Regime-Switching Cointegration," SIRE Discussion Papers 2011-36, Scottish Institute for Research in Economics (SIRE).

    Cited by:

    1. Miranda-Agrippino, Silvia & Ricco, Giovanni, 2018. "Bayesian vector autoregressions," LSE Research Online Documents on Economics 87393, London School of Economics and Political Science, LSE Library.
    2. Maheu, John M & Song, Yong, 2017. "An Efficient Bayesian Approach to Multiple Structural Change in Multivariate Time Series," MPRA Paper 79211, University Library of Munich, Germany.
    3. Jochmann, Markus & Koop, Gary, 2011. "Regime-Switching Cointegration," SIRE Discussion Papers 2011-60, Scottish Institute for Research in Economics (SIRE).
    4. Hou, Chenghan, 2017. "Infinite hidden markov switching VARs with application to macroeconomic forecast," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1025-1043.
    5. Dark, Jonathan, 2015. "Futures hedging with Markov switching vector error correction FIEGARCH and FIAPARCH," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 269-285.
    6. Hauzenberger Niko & Huber Florian & Pfarrhofer Michael & Zörner Thomas O., 2021. "Stochastic model specification in Markov switching vector error correction models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(2), pages 1-17, April.
    7. Katsuhiro Sugita, 2016. "Bayesian inference in Markov switching vector error correction model," Economics Bulletin, AccessEcon, vol. 36(3), pages 1534-1546.
    8. Beckmann, Joscha & Czudaj, Robert, 2014. "Effective exchange rates, current accounts and global imbalances," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100364, Verein für Socialpolitik / German Economic Association.
    9. Li, Leon, 2022. "The dynamic interrelations of oil-equity implied volatility indexes under low and high volatility-of-volatility risk," Energy Economics, Elsevier, vol. 105(C).
    10. Huber, Florian & Zörner, Thomas O., 2019. "Threshold cointegration in international exchange rates:A Bayesian approach," International Journal of Forecasting, Elsevier, vol. 35(2), pages 458-473.
    11. Inoue,Tomoo & Kaya,Demet & Ohshige,Hitoshi, 2015. "The impact of China?s slowdown on the Asia Pacific region : an application of the GVAR model," Policy Research Working Paper Series 7442, The World Bank.
    12. Christou, Christina & Gupta, Rangan & Nyakabawo, Wendy & Wohar, Mark E., 2018. "Do house prices hedge inflation in the US? A quantile cointegration approach," International Review of Economics & Finance, Elsevier, vol. 54(C), pages 15-26.
    13. Knezevic, David & Nordström, Martin & Österholm, Pär, 2019. "The Relation between Municipal and Government Bond Yields in an Era of Unconventional Monetary Policy," Working Papers 2019:6, Örebro University, School of Business.
    14. Chew Lian Chua & Sarantis Tsiaplias, 2014. "A Bayesian Approach to Modelling Bivariate Time-Varying Cointegration and Cointegrating Rank," Melbourne Institute Working Paper Series wp2014n27, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    15. Joscha Beckmann & Dionysius Glycopantis & Keith Pilbeam, 2018. "The dollar–euro exchange rate and monetary fundamentals," Empirical Economics, Springer, vol. 54(4), pages 1389-1410, June.

  56. Koop, Gary & Korobilis, Dimitris, 2010. "Forecasting Inflation Using Dynamic Model Averaging," SIRE Discussion Papers 2010-113, Scottish Institute for Research in Economics (SIRE).

    Cited by:

    1. Goodness C. Aye & Rangan Gupta & Shawkat Hammoudeh & Won Joong Kim, 2014. "Forecasting the Price of Gold Using Dynamic Model Averaging," Working Papers 201415, University of Pretoria, Department of Economics.
    2. Caldeira, João F. & Moura, Guilherme V. & Santos, André A.P., 2016. "Bond portfolio optimization using dynamic factor models," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 128-158.
    3. Daniel L. Tortorice, 2014. "Equity Return Predictability, Time Varying Volatility and Learning About the Permanence of Shocks," Working Papers 70, Brandeis University, Department of Economics and International Business School.
    4. Asai, Manabu & Gupta, Rangan & McAleer, Michael, 2020. "Forecasting volatility and co-volatility of crude oil and gold futures: Effects of leverage, jumps, spillovers, and geopolitical risks," International Journal of Forecasting, Elsevier, vol. 36(3), pages 933-948.
    5. Davide Pettenuzzo & Francesco Ravazzolo, 2014. "Optimal portfolio choice under decision-based model combinations," Working Paper 2014/15, Norges Bank.
    6. Florian Huber & Gregor Kastner & Martin Feldkircher, 2016. "Should I stay or should I go? A latent threshold approach to large-scale mixture innovation models," Papers 1607.04532, arXiv.org, revised Jul 2018.
    7. Miguel A.G. Belmonte & Gary Koop & Dimitris Korobilis, 2014. "Hierarchical Shrinkage in Time‐Varying Parameter Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(1), pages 80-94, January.
    8. Jan Prüser, 2019. "Adaptive learning from model space," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(1), pages 29-38, January.
    9. Čapek, Jan & Crespo Cuaresma, Jesús & Hauzenberger, Niko & Reichel, Vlastimil, 2023. "Macroeconomic forecasting in the euro area using predictive combinations of DSGE models," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1820-1838.
    10. Korobilis, Dimitris & Koop, Gary, 2020. "Bayesian dynamic variable selection in high dimensions," MPRA Paper 100164, University Library of Munich, Germany.
    11. David Kohns & Tibor Szendrei, 2021. "Decoupling Shrinkage and Selection for the Bayesian Quantile Regression," Papers 2107.08498, arXiv.org.
    12. João F. Caldeira & Guilherme V. Moura & Francisco J. Nogales & André A. P. Santos, 2017. "Combining Multivariate Volatility Forecasts: An Economic-Based Approach," Journal of Financial Econometrics, Oxford University Press, vol. 15(2), pages 247-285.
    13. Prüser, Jan, 2017. "Forecasting US inflation using Markov dimension switching," Ruhr Economic Papers 710, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
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  57. Joshua C.C. Chan & Garry Koop & Roberto Leon Gonzales & Rodney W. Strachan, 2010. "Time Varying Dimension Models," ANU Working Papers in Economics and Econometrics 2010-523, Australian National University, College of Business and Economics, School of Economics.

    Cited by:

    1. Korobilis, Dimitris & Koop, Gary, 2020. "Bayesian dynamic variable selection in high dimensions," MPRA Paper 100164, University Library of Munich, Germany.
    2. Prüser, Jan, 2017. "Forecasting US inflation using Markov dimension switching," Ruhr Economic Papers 710, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    3. Koop, Gary & Korobilis, Dimitris, 2018. "Variational Bayes inference in high-dimensional time-varying parameter models," MPRA Paper 87972, University Library of Munich, Germany.
    4. Gary Koop & Dimitris Korobilis, 2012. "Large Time-Varying Parameter VARs," Working Paper series 11_12, Rimini Centre for Economic Analysis.
    5. Chan, Joshua C.C. & Eisenstat, Eric & Strachan, Rodney W., 2020. "Reducing the state space dimension in a large TVP-VAR," Journal of Econometrics, Elsevier, vol. 218(1), pages 105-118.
    6. Tino Berger & Gerdie Everaert & Hauke Vierke, 2015. "Testing for time variation in an unobserved components model for the U.S. economy," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 15/903, Ghent University, Faculty of Economics and Business Administration.
    7. Eric Eisenstat & Joshua C.C. Chan & Rodney W. Strachan, 2014. "Stochastic Model Specification Search for Time-Varying Parameter VARs," CAMA Working Papers 2014-23, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    8. Dimitris Korobilis & Kenichi Shimizu, 2021. "Bayesian Approaches to Shrinkage and Sparse Estimation," Working Papers 2021_19, Business School - Economics, University of Glasgow.
    9. Lasha Kavtaradze & Manouchehr Mokhtari, 2018. "Factor Models And Time†Varying Parameter Framework For Forecasting Exchange Rates And Inflation: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 302-334, April.
    10. Joscha Beckmann & Rainer Schüssler, 2014. "Forecasting Exchange Rates under Model and Parameter Uncertainty," CQE Working Papers 3214, Center for Quantitative Economics (CQE), University of Muenster.
    11. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    12. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
    13. Dufays, Arnaud & Rombouts, Jeroen V.K., 2020. "Relevant parameter changes in structural break models," Journal of Econometrics, Elsevier, vol. 217(1), pages 46-78.
    14. Korobilis, D, 2017. "Forecasting with many predictors using message passing algorithms," Essex Finance Centre Working Papers 19565, University of Essex, Essex Business School.
    15. Chan, Joshua C.C., 2013. "Moving average stochastic volatility models with application to inflation forecast," Journal of Econometrics, Elsevier, vol. 176(2), pages 162-172.
    16. Hang Qian, 2014. "A Flexible State Space Model And Its Applications," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(2), pages 79-88, March.
    17. Ripamonti, Alexandre, 2013. "Rational Valuation Formula (RVF) and Time Variability in Asset Rates of Return," MPRA Paper 79460, University Library of Munich, Germany.
    18. Qian, Hang, 2012. "A Flexible State Space Model and its Applications," MPRA Paper 38455, University Library of Munich, Germany.
    19. KOROBILIS, Dimitris, 2011. "VAR forecasting using Bayesian variable selection," LIDAM Discussion Papers CORE 2011022, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    20. Beckmann, Joscha & Schüssler, Rainer, 2016. "Forecasting exchange rates under parameter and model uncertainty," Journal of International Money and Finance, Elsevier, vol. 60(C), pages 267-288.
    21. Dimitris Korobilis, 2020. "High-dimensional macroeconomic forecasting using message passing algorithms," Papers 2004.11485, arXiv.org.
    22. Joshua C C Chan & Cody Y L Hsiao, 2013. "Estimation of Stochastic Volatility Models with Heavy Tails and Serial Dependence," CAMA Working Papers 2013-74, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    23. Miguel, Belmonte & Gary, Koop, 2013. "Model Switching and Model Averaging in Time- Varying Parameter Regression Models," SIRE Discussion Papers 2013-34, Scottish Institute for Research in Economics (SIRE).
    24. Pierre Guérin & Danilo Leiva-Leon, 2015. "Model Averaging in Markov-Switching Models: Predicting National Recessions with Regional Data," Staff Working Papers 15-24, Bank of Canada.
    25. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    26. Joshua C.C. Chan, 2015. "Specification tests for time-varying parameter models with stochastic volatility," CAMA Working Papers 2015-42, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    27. Jouchi Nakajima & Mike West, 2013. "Bayesian Analysis of Latent Threshold Dynamic Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(2), pages 151-164, April.
    28. Schlösser, Alexander, 2020. "Forecasting industrial production in Germany: The predictive power of leading indicators," Ruhr Economic Papers 838, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    29. Joshua C. C. Chan & Eric Eisenstat, 2018. "Bayesian model comparison for time‐varying parameter VARs with stochastic volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(4), pages 509-532, June.
    30. Prüser, Jan, 2023. "Data-based priors for vector error correction models," International Journal of Forecasting, Elsevier, vol. 39(1), pages 209-227.
    31. Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2019. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Working Paper 2019/2, Norges Bank.
    32. Florian Huber & Gary Koop & Michael Pfarrhofer, 2020. "Bayesian Inference in High-Dimensional Time-varying Parameter Models using Integrated Rotated Gaussian Approximations," Papers 2002.10274, arXiv.org.
    33. Joshua C. C. Chan, 2017. "The Stochastic Volatility in Mean Model With Time-Varying Parameters: An Application to Inflation Modeling," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(1), pages 17-28, January.
    34. Joshua C.C. Chan & Eric Eisenstat, 2015. "Efficient estimation of Bayesian VARMAs with time-varying coefficients," CAMA Working Papers 2015-19, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    35. Kalli, Maria & Griffin, Jim E., 2014. "Time-varying sparsity in dynamic regression models," Journal of Econometrics, Elsevier, vol. 178(2), pages 779-793.
    36. Joshua C.C. Chan & Rodney W. Strachan, 2023. "Bayesian State Space Models In Macroeconometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 58-75, February.
    37. Luke Hartigan, 2015. "Changes in the Factor Structure of the U.S. Economy: Permanent Breaks or Business Cycle Regimes?," Discussion Papers 2015-17, School of Economics, The University of New South Wales.
    38. Kimura Takeshi & Nakajima Jouchi, 2016. "Identifying conventional and unconventional monetary policy shocks: a latent threshold approach," The B.E. Journal of Macroeconomics, De Gruyter, vol. 16(1), pages 277-300, January.
    39. Rodríguez, Gabriel & Vassallo, Renato & Castillo B., Paul, 2023. "Effects of external shocks on macroeconomic fluctuations in Pacific Alliance countries," Economic Modelling, Elsevier, vol. 124(C).
    40. Jordi Maas, 2014. "Forecasting inflation using time-varying Bayesian model averaging," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 68(3), pages 149-182, August.
    41. Jan Prüser, 2021. "Forecasting US inflation using Markov dimension switching," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 481-499, April.
    42. Felix Abramovich & Vadim Grinshtein, 2013. "Estimation of a sparse group of sparse vectors," Biometrika, Biometrika Trust, vol. 100(2), pages 355-370.
    43. Gabriel Rodríguez & Renato Vassallo, 2022. "Time Evolution of External Shocks on Macroeconomic Fluctuations in Pacific Alliance Countries: Empirical Application using TVP-VAR-SV Models," Documentos de Trabajo / Working Papers 2022-508, Departamento de Economía - Pontificia Universidad Católica del Perú.
    44. Yousuf, Kashif & Ng, Serena, 2021. "Boosting high dimensional predictive regressions with time varying parameters," Journal of Econometrics, Elsevier, vol. 224(1), pages 60-87.
    45. Joshua C.C. Chan & Eric Eisenstat, 2013. "Gibbs Samplers for VARMA and Its Extensions," ANU Working Papers in Economics and Econometrics 2013-604, Australian National University, College of Business and Economics, School of Economics.
    46. Fu, Bowen, 2020. "Is the slope of the Phillips curve time-varying? Evidence from unobserved components models," Economic Modelling, Elsevier, vol. 88(C), pages 320-340.
    47. Joshua C.C. Chan & Eric Eisenstat, 2018. "Comparing hybrid time-varying parameter VARs," CAMA Working Papers 2018-31, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    48. Cross, Jamie & Poon, Aubrey, 2016. "Forecasting structural change and fat-tailed events in Australian macroeconomic variables," Economic Modelling, Elsevier, vol. 58(C), pages 34-51.

  58. Deborah Gefang & Gary Koop & Simon M. Potter, 2010. "Technical Appendix to: Understanding Liquidity and Credit Risks in the Financial Crisis," Working Paper series 46_10, Rimini Centre for Economic Analysis.

    Cited by:

    1. Casavecchia, Lorenzo & Loudon, Geoffrey F. & Wu, Eliza, 2018. "What moves benchmark money market rates? Evidence from the BBSW market," Pacific-Basin Finance Journal, Elsevier, vol. 51(C), pages 137-154.
    2. Andreas Schrimpf & Vladyslav Sushko, 2019. "Beyond LIBOR: a primer on the new benchmark rates," BIS Quarterly Review, Bank for International Settlements, March.

  59. Gary Koop & Simon Potter, 2010. "A flexible approach to parametric inference in nonlinear and time varying time series models," Post-Print hal-00732535, HAL.

    Cited by:

    1. Joshua C.C. Chan & Angelia L. Grant, 2015. "Pitfalls of Estimating the Marginal Likelihood Using the Modified Harmonic Mean," CAMA Working Papers 2015-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    2. Claudio Morana, 2012. "The Oil price-Macroeconomy Relationship since the Mid- 1980s: A global perspective," Working Papers 2012.28, Fondazione Eni Enrico Mattei.
    3. Knotek, Edward S. & Zaman, Saeed, 2021. "Asymmetric responses of consumer spending to energy prices: A threshold VAR approach," Energy Economics, Elsevier, vol. 95(C).
    4. Philipp Piribauer, 2016. "Heterogeneity in spatial growth clusters," Empirical Economics, Springer, vol. 51(2), pages 659-680, September.
    5. Banu Kurtaran, 2015. "Re-examining the PPP Hypothesis via Nonlinearity and Smooth Breaks," Econometrics Letters, Bilimsel Mektuplar Organizasyonu (Scientific letters), vol. 2(1), pages 1-21.
    6. Omay, Tolga & Hasanov, Mubariz & Emirmahmutoglu, Furkan, 2014. "Structural Break, Nonlinearity, and Asymmetry: A re-examination of PPP proposition," MPRA Paper 62335, University Library of Munich, Germany.
    7. Markus Jochmann & Gary Koop & Simon M. Potter, 2009. "Modeling the Dynamics of Inflation Compensation," Working Paper series 15_09, Rimini Centre for Economic Analysis.
    8. Joshua C.C. Chan & Rodney W. Strachan, 2023. "Bayesian State Space Models In Macroeconometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 58-75, February.
    9. Aue, Alexander & Horváth, Lajos & Hušková, Marie, 2012. "Segmenting mean-nonstationary time series via trending regressions," Journal of Econometrics, Elsevier, vol. 168(2), pages 367-381.

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    1. Wensheng Kang & Ronald A. Ratti & Joaquin L. Vespignani, 2017. "Global Commodity Prices and Global Stock Volatility Shocks: Effects across Countries," Globalization Institute Working Papers 311, Federal Reserve Bank of Dallas.
    2. Joshua C. C. Chan & Gary Koop & Simon M. Potter, 2016. "A Bounded Model of Time Variation in Trend Inflation, Nairu and the Phillips Curve," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(3), pages 551-565, April.
    3. Joris de Wind, 2014. "Time variation in the dynamic effects of unanticipated changes in tax policy," CPB Discussion Paper 271, CPB Netherlands Bureau for Economic Policy Analysis.
    4. Bogdan DIMA & Ştefana Maria DIMA & Flavia BARNA, 2019. "Inflation Contagion Effects in the Baltic Countries: A Time-varying Coefficients VAR with Stochastic Volatility Analysis," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 72-87, March.
    5. Lenarčič, Črt & Zorko, Robert & Herman, Uroš & Savšek, Simon, 2016. "A Primer on Slovene House Prices Forecast," MPRA Paper 103552, University Library of Munich, Germany.
    6. Leonardo Nogueira Ferreira & Silvia Miranda-Agrippino & Giovanni Ricco, 2023. "Bayesian Local Projections," Working Papers Series 581, Central Bank of Brazil, Research Department.
    7. Tomas Konecny & Oxana Babecka-Kucharcukova, 2016. "Credit Spreads and the Links between the Financial and Real Sectors in a Small Open Economy: The Case of the Czech Republic," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(4), pages 302-321, August.
    8. Florian Eckert & Nina Mühlebach, 2021. "Global and Local Components of Output Gaps," KOF Working papers 21-497, KOF Swiss Economic Institute, ETH Zurich.
    9. Yvonne Adema & Kees Folmer & Gerrit Hugo Heuvelen & Sonny Kuijpers & Rob Luginbuhl & Bas Scheer, 2020. "Unemployment Forecasts: Room for Improvement?," De Economist, Springer, vol. 168(3), pages 403-417, September.
    10. Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2020. "Efficient selection of hyperparameters in large Bayesian VARs using automatic differentiation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 934-943, September.
    11. Mayer, Eric & Rüth, Sebastian & Scharler, Johann, 2016. "Total factor productivity and the propagation of shocks: Empirical evidence and implications for the business cycle," Journal of Macroeconomics, Elsevier, vol. 50(C), pages 335-346.
    12. Patrick A. Imam, 2015. "Shock from Graying: Is the Demographic Shift Weakening Monetary Policy Effectiveness," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 20(2), pages 138-154, March.
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    16. Sebastian Ankargren & Mårten Bjellerup & Hovick Shahnazarian, 2017. "The importance of the financial system for the real economy," Empirical Economics, Springer, vol. 53(4), pages 1553-1586, December.
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    18. Wen Xu, 2016. "Estimation of Dynamic Panel Data Models with Stochastic Volatility Using Particle Filters," Econometrics, MDPI, vol. 4(4), pages 1-13, October.
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    21. Jakub Matějů, 2019. "What Drives the Strength of Monetary Policy Transmission?," International Journal of Central Banking, International Journal of Central Banking, vol. 15(3), pages 59-87, September.
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    37. Mirriam Chitalu Chama-Chiliba & Rangan Gupta & Nonophile Nkambule & Naomi Tlotlego, 2011. "Forecasting Key Macroeconomic Variables of the South African Economy Using Bayesian Variable Selection," Working Papers 201132, University of Pretoria, Department of Economics.
    38. Jensen, Mark J. & Maheu, John M., 2013. "Bayesian semiparametric multivariate GARCH modeling," Journal of Econometrics, Elsevier, vol. 176(1), pages 3-17.
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    41. Gary Koop, 2012. "Using VARs and TVP-VARs with Many Macroeconomic Variables," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 4(3), pages 143-167, September.
    42. Allayioti, Anastasia & Venditti, Fabrizio, 2024. "The role of comovement and time-varying dynamics in forecasting commodity prices," Working Paper Series 2901, European Central Bank.
    43. Hachula, Michael & Rieth, Malte & Piffer, Michele, 2016. "Unconventional Monetary Policy, Fiscal Side Effects and Euro Area (Im)balances," VfS Annual Conference 2016 (Augsburg): Demographic Change 145790, Verein für Socialpolitik / German Economic Association.
    44. Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2016. "Bayesian Compressed Vector Autoregressions," Working Papers 103, Brandeis University, Department of Economics and International Business School.
    45. KANAZAWA, Nobuyuki & 金澤, 伸幸, 2018. "Radial Basis Functions Neural Networks for Nonlinear Time Series Analysis and Time-Varying Effects of Supply Shocks," Discussion paper series HIAS-E-64, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    46. Michael S. Smith & Shaun P. Vahey, 2016. "Asymmetric Forecast Densities for U.S. Macroeconomic Variables from a Gaussian Copula Model of Cross-Sectional and Serial Dependence," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(3), pages 416-434, July.
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    48. Alain Kabundi & Deniz Igan & Francisco N. de Simone & Natalia Tamirisa, 2013. "Monetary Policy and Balance Sheets," Working Papers 364, Economic Research Southern Africa.
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    50. Gary Koop & Dimitris Korobilis, 2012. "Large Time-Varying Parameter VARs," Working Paper series 11_12, Rimini Centre for Economic Analysis.
    51. Mehmet Balcilar & Rangan Gupta & Kevin Kotze, 2013. "Forecasting South African Macroeconomic Data with a Nonlinear DSGE Model," Working Papers 201313, University of Pretoria, Department of Economics.
    52. Tomáš Jeřábek & Jakub Trojan & Radka Šperková, 2013. "Predictive performance of DSGE model for small open economy - the case study of Czech Republic," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 61(7), pages 2229-2238.
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    55. Ellington, Michael & Martin, Chris & Wang, Bingsong, 2019. "Search Frictions and Evolving Labour Market Dynamics," The Warwick Economics Research Paper Series (TWERPS) 1195, University of Warwick, Department of Economics.
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    76. Canova, Fabio & Dallari, Pietro, 2013. "How important is tourism for the international transmission of cyclical fluctuations? Evidence from the Mediterranean," Working Paper Series 1553, European Central Bank.
    77. Nils Jannsen & Galina Potjagailo & Maik H. Wolters, 2019. "Monetary Policy during Financial Crises: Is the Transmission Mechanism Impaired?," International Journal of Central Banking, International Journal of Central Banking, vol. 15(4), pages 81-126, October.
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    403. Thomas A. Lubik & Christian Matthes, 2015. "Time-Varying Parameter Vector Autoregressions: Specification, Estimation, and an Application," Economic Quarterly, Federal Reserve Bank of Richmond, issue 4Q, pages 323-352.
    404. Chak Hung Jack Cheng & Nopphol Witvorapong, 2021. "Health care policy uncertainty, real health expenditures and health care inflation in the USA," Empirical Economics, Springer, vol. 60(4), pages 2083-2103, April.
    405. Nicolas Eterovic & Dalibor Eterovic, 2022. "Stocks, Bonds and the US Dollar - Measuring Domestic and International Market Developments in an Emerging Market," Working Papers Central Bank of Chile 964, Central Bank of Chile.
    406. Karamanis, Dimitrios & Kechrinioti, Alexandra, 2023. "The Greek-Turkish rivalry: A Bayesian VAR approach," MPRA Paper 116827, University Library of Munich, Germany.
    407. Cussen, Mary & O'Brien, Martin & Onorante, Luca & O'Reilly, Gerard, 2015. "Assessing the impact of macroprudential measures," Economic Letters 03/EL/15, Central Bank of Ireland.
    408. Nguyen, BH & Zhang, Bo, 2022. "Forecasting oil Prices: can large BVARs help?," Working Papers 2022-04, University of Tasmania, Tasmanian School of Business and Economics.
    409. Kunovac, Davor & Palenzuela, Diego Rodriguez & Sun, Yiqiao, 2022. "A new optimum currency area index for the euro area," Working Paper Series 2730, European Central Bank.
    410. Paul Viefers, 2011. "Bayesian Inference for the Mixed-Frequency VAR Model," Discussion Papers of DIW Berlin 1172, DIW Berlin, German Institute for Economic Research.
    411. Chatterjee, Ujjal & French, Joseph J., 2022. "A note on tweeting and equity markets before and during the Covid-19 pandemic," Finance Research Letters, Elsevier, vol. 46(PA).
    412. Leopoldo Catania & Stefano Grassi & Francesco Ravazzolo, 2018. "Forecasting Cryptocurrencies Financial Time Series," Working Papers No 5/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    413. Michele Campolieti & Deborah Gefang & Gary Koop, 2013. "A new look at variation in employment growth in Canada," Working Papers 26145565, Lancaster University Management School, Economics Department.
    414. Malte Knüppel & Fabian Krüger, 2022. "Forecast uncertainty, disagreement, and the linear pool," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 23-41, January.
    415. Clark, Todd E. & Doh, Taeyoung, 2014. "Evaluating alternative models of trend inflation," International Journal of Forecasting, Elsevier, vol. 30(3), pages 426-448.
    416. Carrera, César & Pérez-Forero, Fernando & Ramírez-Rondán, Nelson, 2014. "Effects of the U.S. quantitative easing on the Peruvian economy," Working Papers 2014-017, Banco Central de Reserva del Perú.
    417. Mikhail Mamonov & Anna Pestova, 2023. "The Price of War: Macroeconomic and Cross-Sectional Effects of Sanctions on Russia," CERGE-EI Working Papers wp756, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    418. Akbar, Muhammad & Iqbal, Farhan & Noor, Farzana, 2019. "Bayesian analysis of dynamic linkages among gold price, stock prices, exchange rate and interest rate in Pakistan," Resources Policy, Elsevier, vol. 62(C), pages 154-164.
    419. Irfan Akbar Kazi & Hakimzadi Wagan & Farhan Akbar, 2012. "The changing international transmission of US monetary policy shocks: is there evidence of contagion effect on OECD countries," Working Papers hal-04141067, HAL.
    420. Ramazan EKİNCİ & Osman TÜZÜN & Fatih CEYLAN & Hakan KAHYAOĞLU, 2017. "Dışa Açıklık ile İşsizlik Arasındaki İlişki: Seçilmiş AB Ülkeleri ve Türkiye Üzerine Zamana Göre Değişen Parametreli Bir Analiz Algıları," Sosyoekonomi Journal, Sosyoekonomi Society, issue 25(31).
    421. Guevara, Carlos & Rodríguez, Gabriel, 2020. "The role of credit supply shocks in pacific alliance countries: A TVP-VAR-SV approach," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    422. Borus Jungbacker & Siem Jan Koopman, 2015. "Likelihood‐based dynamic factor analysis for measurement and forecasting," Econometrics Journal, Royal Economic Society, vol. 18(2), pages 1-21, June.
    423. Florian Eckert & Nina Mühlebach, 2023. "Global and local components of output gaps," Empirical Economics, Springer, vol. 65(5), pages 2301-2331, November.
    424. Eric Jondeau & Michael Rockinger, 2019. "Predicting Long‐Term Financial Returns: VAR versus DSGE Model—A Horse Race," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 51(8), pages 2239-2291, December.
    425. Jesús Crespo Cuaresma & Martin Feldkircher & Florian Huber, 2014. "Forecasting with Bayesian Global Vector Autoregressive Models: A Comparison of Priors," Working Papers 189, Oesterreichische Nationalbank (Austrian Central Bank).
    426. Borus Jungbacker & Siem Jan Koopman, 2008. "Likelihood-based Analysis for Dynamic Factor Models," Tinbergen Institute Discussion Papers 08-007/4, Tinbergen Institute, revised 20 Mar 2014.
    427. Teye, Alfred Larm & Ahelegbey, Daniel Felix, 2017. "Detecting spatial and temporal house price diffusion in the Netherlands: A Bayesian network approach," Regional Science and Urban Economics, Elsevier, vol. 65(C), pages 56-64.
    428. Eiji Goto, 2020. "Industry Impacts of Unconventional Monetary Policy," 2020 Papers pgo873, Job Market Papers.
    429. James P. LeSage & Daniel Hendrikz, 2019. "Large Bayesian vector autoregressive forecasting for regions: A comparison of methods based on alternative disturbance structures," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 62(3), pages 563-599, June.

  61. Markus Jochmann & Gary Koop & Simon M. Potter, 2009. "Modeling the Dynamics of Inflation Compensation," Working Paper series 15_09, Rimini Centre for Economic Analysis.

    Cited by:

    1. Łyziak, Tomasz & Paloviita, Maritta, 2016. "Anchoring of inflation expectations in the euro area: recent evidence based on survey data," Working Paper Series 1945, European Central Bank.
    2. Carlos Medel, 2018. "Econometric Analysis on Survey-data-based Anchoring of Inflation Expectations in Chile," Working Papers Central Bank of Chile 825, Central Bank of Chile.
    3. Speck, Christian, 2016. "Inflation Anchoring in the Euro Area," VfS Annual Conference 2016 (Augsburg): Demographic Change 145697, Verein für Socialpolitik / German Economic Association.
    4. Gabriele Galati & Richhild Moessner & Maarten van Rooij, 2020. "The anchoring of long-term inflation expectations of consumers: insights from a new survey," Working Papers 688, DNB.
    5. Joshua C.C. Chan & Angelia L. Grant, 2015. "Pitfalls of Estimating the Marginal Likelihood Using the Modified Harmonic Mean," CAMA Working Papers 2015-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    6. Hachula, Michael & Nautz, Dieter, 2017. "The dynamic impact of macroeconomic news on long-term inflation expectations," Discussion Papers 2017/12, Free University Berlin, School of Business & Economics.
    7. Ciccarelli, Matteo & García, Juan Angel & Montes-Galdón, Carlos, 2017. "Unconventional monetary policy and the anchoring of inflation expectations," Working Paper Series 1995, European Central Bank.
    8. Buono, Ines & Formai, Sara, 2018. "New evidence on the evolution of the anchoring of inflation expectations," Journal of Macroeconomics, Elsevier, vol. 57(C), pages 39-54.
    9. Speck, Christian, 2017. "Inflation anchoring in the euro area," Working Paper Series 1998, European Central Bank.
    10. Michael J. Lamla & Lena Draeger, 2013. "Anchoring of Consumers' Inflation Expectations," KOF Working papers 13-339, KOF Swiss Economic Institute, ETH Zurich.
    11. Till Strohsal & Lars Winkelmann, 2012. "Assessing the Anchoring of Inflation Expectations," SFB 649 Discussion Papers SFB649DP2012-022, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    12. Strohsal, Till & Winkelmann, Lars, 2015. "Assessing the anchoring of inflation expectations," Journal of International Money and Finance, Elsevier, vol. 50(C), pages 33-48.
    13. Czudaj, Robert L., 2023. "Expectation Formation and the Phillips Curve Revisited," MPRA Paper 119478, University Library of Munich, Germany.
    14. Joshua C C Chan & Yong Song, 2017. "Measuring inflation expectations uncertainty using high-frequency data," CAMA Working Papers 2017-61, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    15. Till Strohsal & Rafi Melnick & Dieter Nautz, 2015. "The Time-Varying Degree of Inflation Expectations Anchoring," SFB 649 Discussion Papers SFB649DP2015-028, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    16. Juan Angel García & Sebastian E. V. Werner, 2021. "Inflation News and Euro-Area Inflation Expectations," International Journal of Central Banking, International Journal of Central Banking, vol. 17(3), pages 1-60, September.
    17. Alturki, Sultan & Olson, Eric, 2022. "Oil sentiment and the U.S. inflation premium," Energy Economics, Elsevier, vol. 114(C).
    18. Deborah Gefang & Gary Koop & Simon Potter, 2011. "The Dynamics of UK and US Inflation Expectations," Working Papers 1120, University of Strathclyde Business School, Department of Economics.
    19. Lemke, Wolfgang & Strohsal, Till, 2013. "What Can Break-Even Inflation Rates Tell Us about the Anchoring of Inflation Expectations in the Euro Area?," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79794, Verein für Socialpolitik / German Economic Association.
    20. Todd E. Clark & Troy Davig, 2008. "An empirical assessment of the relationships among inflation and short- and long-term expectations," Research Working Paper RWP 08-05, Federal Reserve Bank of Kansas City.
    21. Suh, Sangwon & Kim, Daehwan, 2021. "Inflation targeting and expectation anchoring: Evidence from developed and emerging market economies," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    22. Nautz, Dieter & Strohsal, Till & Netšunajev, Aleksei, 2019. "The Anchoring Of Inflation Expectations In The Short And In The Long Run," Macroeconomic Dynamics, Cambridge University Press, vol. 23(5), pages 1959-1977, July.
    23. James Yetman, 2020. "Pass-through from short-horizon to long-horizon inflation expectations, and the anchoring of inflation expectations," BIS Working Papers 895, Bank for International Settlements.
    24. Inês da Cunha Cabral & Pedro Pires Ribeiro & João Nicolau, 2022. "Changes in inflation compensation and oil prices: short-term and long-term dynamics," Empirical Economics, Springer, vol. 62(2), pages 581-603, February.
    25. Speck, Christian, 2016. "Inflation anchoring in the euro area," Discussion Papers 04/2016, Deutsche Bundesbank.
    26. Czudaj, Robert L., 2023. "Anchoring of Inflation Expectations and the Role of Monetary Policy and Cost-Push Factors," MPRA Paper 119029, University Library of Munich, Germany.
    27. Duran, Murat & Gülşen, Eda, 2013. "Estimating inflation compensation for Turkey using yield curves," Economic Modelling, Elsevier, vol. 32(C), pages 592-601.
    28. Ciccarelli, Matteo & García, Juan Angel, 2021. "Expectation spillovers and the return of inflation," Economics Letters, Elsevier, vol. 209(C).
    29. Lena Dräger & Michael Lamla, 2018. "Is the Anchoring of Consumers' Inflation Expectations Shaped by Inflational Experience?," CESifo Working Paper Series 7042, CESifo.
    30. Dieter Nautz & Aleksei Netsunajev & Till Strohsal, 2016. "Aggregate Employment, Job Polarization and Inequalities: A Transatlantic Perspective," SFB 649 Discussion Papers SFB649DP2016-015, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    31. Swinkels, Laurens, 2018. "Simulating historical inflation-linked bond returns," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 374-389.
    32. Dräger, Lena & Lamla, Michael, 2013. "Anchoring of Consumers' Inflation Expectations: Evidence from Microdata," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79889, Verein für Socialpolitik / German Economic Association.
    33. Aleksei Netšunajev & Lars Winkelmann, 2016. "International dynamics of inflation expectations," SFB 649 Discussion Papers SFB649DP2016-019, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    34. Helder Ferreira de Mendonça & Pedro Mendes Garcia & José Valentim Machado Vicente, 2021. "Rationality and anchoring of inflation expectations: An assessment from survey‐based and market‐based measures," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(6), pages 1027-1053, September.
    35. Gabriele Galati & Richhild Moessner & Maarten van Rooij, 2021. "Anchoring of consumers’ long-term euro area inflation expectations during the pandemic," Working Papers 715, DNB.
    36. Dash, Pradyumna & Rohit, Abhishek Kumar & Devaguptapu, Adviti, 2020. "Assessing the (de-)anchoring of households’ long-term inflation expectations in the US," Journal of Macroeconomics, Elsevier, vol. 63(C).

  62. Jochmann, Markus & Koop, Gary & Leon-Gonzalez & Strachan, Rodney W., 2009. "Stochastic Search Variable Selection in Vector Error Correction Models with an Application to a Model of the UK Macroeconomy," SIRE Discussion Papers 2009-44, Scottish Institute for Research in Economics (SIRE).

    Cited by:

    1. Jochmann, Markus & Koop, Gary, 2011. "Regime-Switching Cointegration," SIRE Discussion Papers 2011-60, Scottish Institute for Research in Economics (SIRE).
    2. Michael S. Smith & Shaun P. Vahey, 2016. "Asymmetric Forecast Densities for U.S. Macroeconomic Variables from a Gaussian Copula Model of Cross-Sectional and Serial Dependence," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(3), pages 416-434, July.
    3. SENBETA, Sisay Regassa, 2012. "How important are external shocks in explaining growth in Sub-Saharan Africa? Evidence from a Bayesian VAR," Working Papers 2012010, University of Antwerp, Faculty of Business and Economics.
    4. Smith, Michael Stanley, 2015. "Copula modelling of dependence in multivariate time series," International Journal of Forecasting, Elsevier, vol. 31(3), pages 815-833.
    5. Niko Hauzenberger & Michael Pfarrhofer & Luca Rossini, 2020. "Sparse time-varying parameter VECMs with an application to modeling electricity prices," Papers 2011.04577, arXiv.org, revised Apr 2023.
    6. Wensheng Kang & Ronald A. Ratti & Kyung Hwan Yoon, 2015. "Time-varying effect of oil market shocks on the stock market," CAMA Working Papers 2015-35, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    7. Smith, Simon C. & Timmermann, Allan, 2022. "Have risk premia vanished?," Journal of Financial Economics, Elsevier, vol. 145(2), pages 553-576.

  63. Koop, Gary & Leon-Gonzalez, Roberto & Strachan, Rodney W., 2008. "Bayesian Inference in the Time Varying Cointegration Model," SIRE Discussion Papers 2008-60, Scottish Institute for Research in Economics (SIRE).

    Cited by:

    1. Punzi, Maria Teresa, 2016. "Financial cycles and co-movements between the real economy, finance and asset price dynamics in large-scale crises," FinMaP-Working Papers 61, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    2. Cross, Jamie & Nguyen, Bao H., 2017. "The relationship between global oil price shocks and China's output: A time-varying analysis," Energy Economics, Elsevier, vol. 62(C), pages 79-91.
    3. Costola, Michele & Iacopini, Matteo, 2023. "Measuring sovereign bond fragmentation in the Eurozone," Finance Research Letters, Elsevier, vol. 51(C).
    4. Miranda-Agrippino, Silvia & Ricco, Giovanni, 2018. "Bayesian vector autoregressions," LSE Research Online Documents on Economics 87393, London School of Economics and Political Science, LSE Library.
    5. Maheu, John M & Song, Yong, 2017. "An Efficient Bayesian Approach to Multiple Structural Change in Multivariate Time Series," MPRA Paper 79211, University Library of Munich, Germany.
    6. Karolina Konopczak & Aleksander Łożykowski, 2021. "Efekt fiskalny uszczelniania systemu podatkowego w Polsce: próba oszacowania w zakresie podatku CIT," Ekonomista, Polskie Towarzystwo Ekonomiczne, issue 1, pages 25-55.
    7. Jochmann, Markus & Koop, Gary, 2011. "Regime-Switching Cointegration," SIRE Discussion Papers 2011-60, Scottish Institute for Research in Economics (SIRE).
    8. Xianguo HUANG & Roberto LEON-GONZALEZ & Somrasri YUPHO, 2013. "Financial Integration from a Time-Varying Cointegration Perspective," Asian Journal of Empirical Research, Asian Economic and Social Society, vol. 3(12), pages 1473-1487.
    9. Michele Costola & Matteo Iacopini & Carlo R. M. A. Santagiustina, 2021. "On the "mementum" of Meme Stocks," Papers 2106.03691, arXiv.org.
    10. Panopoulou, Ekaterini & Pantelidis, Theologos, 2016. "The Fisher effect in the presence of time-varying coefficients," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 495-511.
    11. Rodney W. Strachan & Herman K. Van Dijk, 2013. "Evidence On Features Of A Dsge Business Cycle Model From Bayesian Model Averaging," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 54(1), pages 385-402, February.
    12. Funashima, Yoshito, 2020. "Money stock versus monetary base in time–frequency exchange rate determination," Journal of International Money and Finance, Elsevier, vol. 104(C).
    13. Joshua Chan & Arnaud Doucet & Roberto Leon-Gonzalez & Rodney W. Strachan, 2018. "Multivariate Stochastic Volatility with Co-Heteroscedasticity," GRIPS Discussion Papers 18-12, National Graduate Institute for Policy Studies.
    14. Ripamonti, Alexandre, 2013. "Rational Valuation Formula (RVF) and Time Variability in Asset Rates of Return," MPRA Paper 79460, University Library of Munich, Germany.
    15. Anna Pajor & Justyna Wróblewska, 2022. "Forecasting performance of Bayesian VEC-MSF models for financial data in the presence of long-run relationships," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(3), pages 427-448, September.
    16. Czudaj, Robert L., 2019. "Dynamics between trading volume, volatility and open interest in agricultural futures markets: A Bayesian time-varying coefficient approach," Econometrics and Statistics, Elsevier, vol. 12(C), pages 78-145.
    17. Hauzenberger Niko & Huber Florian & Pfarrhofer Michael & Zörner Thomas O., 2021. "Stochastic model specification in Markov switching vector error correction models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(2), pages 1-17, April.
    18. Shaun P Vahey & Elizabeth C Wakerly, 2013. "Moving towards probability forecasting," BIS Papers chapters, in: Bank for International Settlements (ed.), Globalisation and inflation dynamics in Asia and the Pacific, volume 70, pages 3-8, Bank for International Settlements.
    19. Kapetanios, George & Millard, Stephen & Petrova, Katerina & Price, Simon, 2019. "Time-varying cointegration and the UK great ratios," Bank of England working papers 789, Bank of England.
    20. Niko Hauzenberger & Michael Pfarrhofer & Luca Rossini, 2020. "Sparse time-varying parameter VECMs with an application to modeling electricity prices," Papers 2011.04577, arXiv.org, revised Apr 2023.
    21. Peter McAdam & Kostas Mouratidis & Theodore Panagiotidis & Georgios Papapanagiotou, 2023. "European Trade & Growth Imbalances: An Analysis using a Sign-Restriction Bayesian-GVAR with Stochastic Volatility," Working Paper series 23-12, Rimini Centre for Economic Analysis.
    22. Barigozzi, Matteo, 2018. "On the stability of euro area money demand and its implications for monetary policy," LSE Research Online Documents on Economics 87283, London School of Economics and Political Science, LSE Library.
    23. Karolina Konopczak, 2020. "Kwantyfikacja zmian luki VAT: podejście ekonometryczne," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 2, pages 25-42.
    24. Pooyan Amir-Ahmadi & Christian Matthes & Mu-Chun Wang, 2016. "Choosing Prior Hyperparameters," Working Paper 16-9, Federal Reserve Bank of Richmond.
    25. Huber, Florian & Zörner, Thomas O., 2019. "Threshold cointegration in international exchange rates:A Bayesian approach," International Journal of Forecasting, Elsevier, vol. 35(2), pages 458-473.
    26. Hong Li & Yanlin Shi, 2022. "Robust information share measures with an application on the international crude oil markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(4), pages 555-579, April.
    27. Xiaojie Xu, 2019. "Price dynamics in corn cash and futures markets: cointegration, causality, and forecasting through a rolling window approach," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 33(2), pages 155-181, June.
    28. Lips Johannes, 2017. "Do They Still Matter? – Impact of Fossil Fuels on Electricity Prices in the Light of Increased Renewable Generation," Journal of Time Series Econometrics, De Gruyter, vol. 9(2), pages 1-30, July.
    29. Martin Falk & Xiang Lin, 2018. "Income elasticity of overnight stays over seven decades," Tourism Economics, , vol. 24(8), pages 1015-1028, December.
    30. Joshua C.C. Chan & Rodney W. Strachan, 2023. "Bayesian State Space Models In Macroeconometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 58-75, February.
    31. Nalan Basturk & Lennart Hoogerheide & Herman K. van Dijk, 2017. "Bayesian Analysis of Boundary and Near-Boundary Evidence in Econometric Models with Reduced Rank," Tinbergen Institute Discussion Papers 17-058/III, Tinbergen Institute.
    32. Xiaojie Xu, 2015. "Cointegration among regional corn cash prices," Economics Bulletin, AccessEcon, vol. 35(4), pages 2581-2594.
    33. Miroslav Plasil & Stepan Radkovsky & Pavel Rezabek, 2013. "Modelling bank loans to non-financial corporations," Occasional Publications - Chapters in Edited Volumes, in: CNB Financial Stability Report 2012/2013, chapter 0, pages 128-136, Czech National Bank.
    34. Chew Lian Chua & Sarantis Tsiaplias, 2014. "A Bayesian Approach to Modelling Bivariate Time-Varying Cointegration and Cointegrating Rank," Melbourne Institute Working Paper Series wp2014n27, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.

  64. Markus Jochmann & Gary Koop & Rodney W. Strachan, 2008. "Bayesian Forecasting using Stochastic Search Variable Selection in a VAR Subject to Breaks," Working Paper series 19_08, Rimini Centre for Economic Analysis.

    Cited by:

    1. Dimitris, Korobilis, 2013. "Forecasting with Factor Models: A Bayesian Model Averaging Perspective," MPRA Paper 52724, University Library of Munich, Germany.
    2. Wilson, Kevin J., 2017. "An investigation of dependence in expert judgement studies with multiple experts," International Journal of Forecasting, Elsevier, vol. 33(1), pages 325-336.
    3. Markus Jochmann & Gary Koop & Roberto Leon-Gonzalez & Rodney W. Strachan, 2009. "Stochastic Search Variable Selection in Vector Error Correction Models with an Application to a Model of the UK Macroeconomy," Working Paper series 44_09, Rimini Centre for Economic Analysis.
    4. Gary Koop, 2011. "Forecasting with Medium and Large Bayesian VARs," Working Papers 1117, University of Strathclyde Business School, Department of Economics.
    5. Knut Are Aastveit & Anne Sofie Jore & Francesco Ravazzolo, 2014. "Forecasting recessions in real time," Working Paper 2014/02, Norges Bank.
    6. Karlsson, Sune, 2012. "Forecasting with Bayesian Vector Autoregressions," Working Papers 2012:12, Örebro University, School of Business.
    7. Daniel Felix Ahelegbey & Monica Billio & Roberto Casarin, 2020. "Modeling Turning Points In Global Equity Market," DEM Working Papers Series 195, University of Pavia, Department of Economics and Management.
    8. Nikolaus Hautsch & Fuyu Yang, 2014. "Bayesian Stochastic Search for the Best Predictors: Nowcasting GDP Growth," University of East Anglia Applied and Financial Economics Working Paper Series 056, School of Economics, University of East Anglia, Norwich, UK..
    9. Gary Koop & Dimitris Korobilis, 2012. "Large Time-Varying Parameter VARs," Working Paper series 11_12, Rimini Centre for Economic Analysis.
    10. Joshua C.C. Chan & Gary Koop, 2013. "Modelling Breaks and Clusters in the Steady States of Macroeconomic Variables," ANU Working Papers in Economics and Econometrics 2013-603, Australian National University, College of Business and Economics, School of Economics.
    11. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2011. "Combination Schemes for Turning Point Predictions," Tinbergen Institute Discussion Papers 11-123/4, Tinbergen Institute.
    12. Macias, Paweł & Stelmasiak, Damian & Szafranek, Karol, 2023. "Nowcasting food inflation with a massive amount of online prices," International Journal of Forecasting, Elsevier, vol. 39(2), pages 809-826.
    13. KOROBILIS, Dimitris, 2011. "VAR forecasting using Bayesian variable selection," LIDAM Discussion Papers CORE 2011022, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    14. Kim, Young Min & Lee, Seojin, 2020. "Exchange rate predictability: A variable selection perspective," International Review of Economics & Finance, Elsevier, vol. 70(C), pages 117-134.
    15. SENBETA, Sisay Regassa, 2012. "How important are external shocks in explaining growth in Sub-Saharan Africa? Evidence from a Bayesian VAR," Working Papers 2012010, University of Antwerp, Faculty of Business and Economics.
    16. Paul Hofmarcher & Jesús Crespo Cuaresma & Bettina Grün & Kurt Hornik, 2015. "Last Night a Shrinkage Saved My Life: Economic Growth, Model Uncertainty and Correlated Regressors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(2), pages 133-144, March.
    17. Stephen G. Hall & Heather D. Gibson & G. S. Tavlas & Mike G. Tsionas, 2020. "A Monte Carlo Study of Time Varying Coefficient (TVC) Estimation," Computational Economics, Springer;Society for Computational Economics, vol. 56(1), pages 115-130, June.
    18. Smith, Simon C. & Timmermann, Allan & Zhu, Yinchu, 2019. "Variable selection in panel models with breaks," Journal of Econometrics, Elsevier, vol. 212(1), pages 323-344.
    19. Ahlem DAHEM, 2016. "Short-Term Bayesian Inflation Forecasting For Tunisia: Some Empirical Evidence," EcoForum, "Stefan cel Mare" University of Suceava, Romania, Faculty of Economics and Public Administration - Economy, Business Administration and Tourism Department., vol. 5(1), pages 1-47, January.
    20. Schnücker, Annika, 2016. "Restrictions Search for Panel VARs," VfS Annual Conference 2016 (Augsburg): Demographic Change 145566, Verein für Socialpolitik / German Economic Association.
    21. Karol Szafranek, 2017. "Bagged artificial neural networks in forecasting inflation: An extensive comparison with current modelling frameworks," NBP Working Papers 262, Narodowy Bank Polski.
    22. Rangan Gupta & Rudi Steinbach, 2010. "Forecasting Key Macroeconomic Variables of the South African Economy: A Small Open Economy New Keynesian DSGE-VAR Model," Working Papers 201019, University of Pretoria, Department of Economics.
    23. Annika Schnücker, 2016. "Restrictions Search for Panel VARs," Discussion Papers of DIW Berlin 1612, DIW Berlin, German Institute for Economic Research.
    24. Wensheng Kang & Ronald A. Ratti & Kyung Hwan Yoon, 2015. "Time-varying effect of oil market shocks on the stock market," CAMA Working Papers 2015-35, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    25. Gupta, Rangan & Steinbach, Rudi, 2013. "A DSGE-VAR model for forecasting key South African macroeconomic variables," Economic Modelling, Elsevier, vol. 33(C), pages 19-33.
    26. P.A.V.B. Swamy & Stephen G. Hall & George S. Tavlas & I-Lok Chang & Heather D. Gibson & William H. Greene & Jatinder S. Mehta, 2016. "A Method for Measuring Treatment Effects on the Treated without Randomization," Econometrics, MDPI, vol. 4(2), pages 1-23, March.
    27. Li, Zili & Washington, Simon P. & Zheng, Zuduo & Prato, Carlo G., 2023. "A Bayesian hierarchical approach to the joint modelling of Revealed and stated choices," Journal of choice modelling, Elsevier, vol. 47(C).
    28. Jiang, Yu & Song, Zhe & Kusiak, Andrew, 2013. "Very short-term wind speed forecasting with Bayesian structural break model," Renewable Energy, Elsevier, vol. 50(C), pages 637-647.
    29. Dahem, Ahlem, 2015. "Short term Bayesian inflation forecasting for Tunisia," MPRA Paper 66702, University Library of Munich, Germany.
    30. Kien C. Tran & Mike G. Tsionas, 2022. "Instrumental Variables Estimation without Outside Instruments," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(3), pages 489-506, September.
    31. Zhang, Bo & Nguyen, Bao H., 2020. "Real-time forecasting of the Australian macroeconomy using Bayesian VARs," Working Papers 2020-12, University of Tasmania, Tasmanian School of Business and Economics.

  65. Gary Koop & Roberto Leon-Gonzalez & Rodney W. Strachan, 2008. "Dynamic probabilities of restrictions in state space models: An application to the Phillips curve," Working Paper series 26_08, Rimini Centre for Economic Analysis.

    Cited by:

    1. Joshua C.C. Chan & Garry Koop & Roberto Leon Gonzales & Rodney W. Strachan, 2010. "Time Varying Dimension Models," ANU Working Papers in Economics and Econometrics 2010-523, Australian National University, College of Business and Economics, School of Economics.
    2. Geraci, Marco Valerio & Gnabo, Jean-Yves, 2018. "Measuring Interconnectedness between Financial Institutions with Bayesian Time-Varying Vector Autoregressions," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(3), pages 1371-1390, June.
    3. Yerali Gandica & Marco Valerio Geraci & Sophie Béreau & Jean-Yves Gnabo, 2018. "Fragmentation, integration and macroprudential surveillance of the US financial industry: Insights from network science," PLOS ONE, Public Library of Science, vol. 13(4), pages 1-23, April.
    4. Koop, Gary & Tole, Lise, 2013. "Modeling the relationship between European carbon permits and certified emission reductions," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 166-181.
    5. Koop, Gary & Potter, Simon M., 2011. "Time varying VARs with inequality restrictions," Journal of Economic Dynamics and Control, Elsevier, vol. 35(7), pages 1126-1138, July.
    6. Joshua C.C. Chan, 2015. "Specification tests for time-varying parameter models with stochastic volatility," CAMA Working Papers 2015-42, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    7. Eric Eisenstat & Rodney Strachan, 2014. "Modelling Inflation Volatility," Working Paper series 43_14, Rimini Centre for Economic Analysis.
    8. Terence D. Agbeyegbe, 2023. "The Link Between Output Growth and Output Growth Volatility: Barbados," Annals of Data Science, Springer, vol. 10(3), pages 787-804, June.
    9. Joshua C. C. Chan, 2017. "The Stochastic Volatility in Mean Model With Time-Varying Parameters: An Application to Inflation Modeling," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(1), pages 17-28, January.
    10. Benjamin Wong, 2013. "The Evolution of the U.S. Output-Inflation Tradeoff," CAMA Working Papers 2013-70, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    11. Jansson, Walter, 2018. "Stock markets, banks and economic growth in the UK, 1850–1913," Financial History Review, Cambridge University Press, vol. 25(3), pages 263-296, December.
    12. Qian, Hang, 2015. "Inequality Constrained State Space Models," MPRA Paper 66447, University Library of Munich, Germany.
    13. Joshua C.C. Chan & Rodney W. Strachan, 2023. "Bayesian State Space Models In Macroeconometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 58-75, February.
    14. Nonejad Nima, 2016. "Particle Markov Chain Monte Carlo Techniques of Unobserved Component Time Series Models Using Ox," Journal of Time Series Econometrics, De Gruyter, vol. 8(1), pages 55-90, January.
    15. Han, Xiaoyi & Hsieh, Chih-Sheng & Lee, Lung-fei, 2017. "Estimation and model selection of higher-order spatial autoregressive model: An efficient Bayesian approach," Regional Science and Urban Economics, Elsevier, vol. 63(C), pages 97-120.
    16. Apergis, Nicholas, 2015. "Policy risks, technological risks and stock returns: New evidence from the US stock market," Economic Modelling, Elsevier, vol. 51(C), pages 359-365.
    17. Marco Valerio Geraci & Jean-Yves Gnabo, 2015. "Measuring Interconnectedness between Financial Institutions with Bayesian Time-Varying VARS," Working Papers ECARES ECARES 2015-51, ULB -- Universite Libre de Bruxelles.
    18. Grant, Angelia L., 2018. "The Great Recession and Okun's law," Economic Modelling, Elsevier, vol. 69(C), pages 291-300.

  66. Koop, Gary M & Poirier, Dale J & Tobias, Justin, 2007. "Bayesian Econometric Methods," Staff General Research Papers Archive 12722, Iowa State University, Department of Economics.

    Cited by:

    1. Haider, Adnan & Khan, Safdar Ullah, 2008. "A Small Open Economy DSGE Model for Pakistan," MPRA Paper 12977, University Library of Munich, Germany, revised 17 Jan 2009.
    2. Danaf, Mazen & Guevara, C. Angelo & Ben-Akiva, Moshe, 2023. "A control-function correction for endogeneity in random coefficients models: The case of choice-based recommender systems," Journal of choice modelling, Elsevier, vol. 46(C).
    3. Cross, Jamie & Nguyen, Bao H., 2017. "The relationship between global oil price shocks and China's output: A time-varying analysis," Energy Economics, Elsevier, vol. 62(C), pages 79-91.
    4. Qian, Hang, 2012. "Essays on statistical inference with imperfectly observed data," ISU General Staff Papers 201201010800003618, Iowa State University, Department of Economics.
    5. Richard S. J. Tol & In Chang Hwang & Frédéric Reynès, 2012. "The Effect of Learning on Climate Policy under Fat-tailed Uncertainty," Working Paper Series 5312, Department of Economics, University of Sussex Business School.
    6. Joshua C. C. Chan & Xuewen Yu, 2022. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," Papers 2206.08438, arXiv.org.
    7. Xiaodong Du & David A. Hennessy & Cindy L. Yu, 2012. "Testing Day's Conjecture that More Nitrogen Decreases Crop Yield Skewness," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 94(1), pages 225-237.
    8. Abidoye, Babatunde O. & Marlene, Labuschagne, 2012. "The Transmission of World Maize Price to South African Maize Market: A Threshold Cointegration Approach," Working Papers 206515, University of Pretoria, Department of Agricultural Economics, Extension and Rural Development.
    9. Jed Cohen, Klaus Moeltner, Johannes Reichl and Michael Schmidthaler, 2016. "An Empirical Analysis of Local Opposition to New Transmission Lines Across the EU-27," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    10. Iftekhar Hasan & Roman Horvath & Jan Mares, 2018. "Finance and Wealth Inequality," Working Papers IES 2018/35, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Dec 2018.
    11. Koop, Gary & McIntyre, Stuart & Mitchell, James & Poon, Aubrey, 2019. "Regional Output Growth in the United Kingdom: More Timely and Higher Frequency Estimates, 1970-2017," EMF Research Papers 20, Economic Modelling and Forecasting Group.
    12. Chih-Sheng Hsieh & Michael D. König & Xiaodong Liu & Christian Zimmermann, 2020. "Collaboration in Bipartite Networks, with an Application to Coauthorship Networks," Working Papers 2020-030, Federal Reserve Bank of St. Louis.
    13. Martinovici, A., 2019. "Revealing attention - how eye movements predict brand choice and moment of choice," Other publications TiSEM 7dca38a5-9f78-4aee-bd81-c, Tilburg University, School of Economics and Management.
    14. Katharina Hauck & Xiaohui Zhang, 2016. "Heterogeneity in the Effect of Common Shocks on Healthcare Expenditure Growth," Health Economics, John Wiley & Sons, Ltd., vol. 25(9), pages 1090-1103, September.
    15. Horvath, Roman, 2011. "Research & development and growth: A Bayesian model averaging analysis," Economic Modelling, Elsevier, vol. 28(6), pages 2669-2673.
    16. Robin C. Sickles & Jiaqi Hao & Chenjun Shang, 2014. "Panel data and productivity measurement: an analysis of Asian productivity trends," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 12(3), pages 211-231, August.
    17. Nikolaus Hautsch & Fuyu Yang, 2014. "Bayesian Stochastic Search for the Best Predictors: Nowcasting GDP Growth," University of East Anglia Applied and Financial Economics Working Paper Series 056, School of Economics, University of East Anglia, Norwich, UK..
    18. Sickles, Robin C. & Hao, Jiaqi & Shang, Chenjun, 2015. "Panel Data and Productivity Measurement," Working Papers 15-018, Rice University, Department of Economics.
    19. Angelia L. Grant & Joshua C.C. Chan, 2017. "A Bayesian Model Comparison for Trend‐Cycle Decompositions of Output," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(2-3), pages 525-552, March.
    20. Mountford, Andrew, 2022. "Economic Growth Analysis When Balanced Growth Paths May Be Time Varying," MPRA Paper 114249, University Library of Munich, Germany.
    21. Abidoye, Babatunde Oluwakayode, 2010. "Bayesian inference in modeling recreation demand," ISU General Staff Papers 201001010800002496, Iowa State University, Department of Economics.
    22. Hong Wang & Catherine S. Forbes & Jean-Pierre Fenech & John Vaz, 2018. "The determinants of bank loan recovery rates in good times and bad - new evidence," Papers 1804.07022, arXiv.org.
    23. Herriges, Joseph A. & Kling, Catherine L. & Liu, Chih-Chen & Tobias, Justin, 2009. "What Are the Consequences of Consequentiality?," Staff General Research Papers Archive 13034, Iowa State University, Department of Economics.
    24. Chih-Sheng Hsieh & Michael D König & Xiaodong Liu & Christian Zimmermann, 2022. "Collaboration in Bipartite Networks," Working Papers 2202, National Taiwan University, Department of Economics, revised Feb 2022.
    25. Li, Mingliang & Tobias, Justin L., 2011. "Bayesian inference in a correlated random coefficients model: Modeling causal effect heterogeneity with an application to heterogeneous returns to schooling," Journal of Econometrics, Elsevier, vol. 162(2), pages 345-361, June.
    26. David Kohns & Arnab Bhattacharjee, 2020. "Nowcasting Growth using Google Trends Data: A Bayesian Structural Time Series Model," Papers 2011.00938, arXiv.org, revised May 2022.
    27. Chih-Sheng Hsieh & Michael D. König & Xiaodong Liu & Christian Zimmermann, 2018. "Superstar Economists: Coauthorship networks and research output," Working Papers 2018-28, Federal Reserve Bank of St. Louis.
    28. Agbeyegbe, Terence D., 2020. "Bayesian analysis of output gap in Barbados," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 1(1).
    29. Niu, Linlin & Xu, Xiu & Chen, Ying, 2017. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," Economic Modelling, Elsevier, vol. 66(C), pages 201-213.
    30. Maeng, Kyuho & Jeon, Seung Ryong & Park, Taeho & Cho, Youngsang, 2021. "Network effects of connected and autonomous vehicles in South Korea: A consumer preference approach," Research in Transportation Economics, Elsevier, vol. 90(C).
    31. Maria Chiara D'Errico & Carlo Andrea Bollino, 2015. "Bayesian Analysis of Demand Elasticity in the Italian Electricity Market," Sustainability, MDPI, vol. 7(9), pages 1-22, September.
    32. Francesco Furlanetto & Francesco Ravazzolo & Samad Sarferaz, 2014. "Identification of financial factors in economic fluctuations," KOF Working papers 14-364, KOF Swiss Economic Institute, ETH Zurich.
    33. Joshua C. C. Chan, 2022. "Comparing Stochastic Volatility Specifications for Large Bayesian VARs," Papers 2208.13255, arXiv.org.
    34. Nurmakhanova, Mira, 2008. "Essays on fall fertilizer application," ISU General Staff Papers 2008010108000016739, Iowa State University, Department of Economics.
    35. Igari, Ryosuke & Hoshino, Takahiro, 2018. "A Bayesian data combination approach for repeated durations under unobserved missing indicators: Application to interpurchase-timing in marketing," Computational Statistics & Data Analysis, Elsevier, vol. 126(C), pages 150-166.
    36. Odusola, Ayodele & Abidoye, Babatunde, 2015. "Effects of Temperature and Rainfall Shocks on Economic Growth in Africa," UNDP Africa Research Discussion Papers 267028, United Nations Development Programme (UNDP).
    37. Ishdorj, Ariun, 2008. "Essays on food assistance program participation and demand for food," ISU General Staff Papers 2008010108000016750, Iowa State University, Department of Economics.
    38. Marcin Błażejowski & Paweł Kufel & Jacek Kwiatkowski, 2020. "Model simplification and variable selection: A replication of the UK inflation model by Hendry (2001)," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(5), pages 645-652, August.
    39. Koop, Gary & Korobilis, Dimitris, 2010. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(4), pages 267-358, July.
    40. Mario Cerrato & John Crosby & Muhammad Kaleem, 2011. "Measuring the economic significance of structural exchange rate models," Working Papers 2011_17, Business School - Economics, University of Glasgow.
    41. Adnan Haider & Asad Jan & Kalim Hyder, 2013. "On the (Ir)Relevance of Monetary Aggregate Targeting in Pakistan: An Eclectic View," Lahore Journal of Economics, Department of Economics, The Lahore School of Economics, vol. 18(2), pages 65-119, July-Dec.
    42. Christopher Moore & Daniel Phaneuf & Walter Thurman, 2011. "A Bayesian Bioeconometric Model of Invasive Species Control: The Case of the Hemlock Woolly Adelgid," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 50(1), pages 1-26, September.
    43. Baştürk, Nalan & Grassi, Stefano & Hoogerheide, Lennart & Opschoor, Anne & van Dijk, Herman K., 2017. "The R Package MitISEM: Efficient and Robust Simulation Procedures for Bayesian Inference," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 79(i01).
    44. Horvath, Roman & Rusnak, Marek & Smidkova, Katerina & Zapal, Jan, 2011. "Dissent voting behavior of central bankers: what do we really know?," MPRA Paper 34638, University Library of Munich, Germany.
    45. Blazejowski, Marcin & Kwiatkowski, Jacek, 2020. "Bayesian Model Averaging for Autoregressive Distributed Lag (BMA_ADL) in gretl," MPRA Paper 98387, University Library of Munich, Germany.
    46. Liu, De-Chih & Chang, Yu-Chien, 2022. "Systematic variations in exchange rate returns," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 569-583.
    47. Mohammad Arshad Rahman & Angela Vossmeyer, 2019. "Estimation and Applications of Quantile Regression for Binary Longitudinal Data," Papers 1909.05560, arXiv.org.
    48. Nikhil Patel, 2016. "International Trade Finance and the Cost Channel of Monetary Policy in Open Economies," BIS Working Papers 539, Bank for International Settlements.
    49. Colson, Gregory & Rousu, Matthew C. & Huffman, Wallace E., 2008. "Consumers' Willingness to Pay for New Genetically Modified Food Products: Evidence from Experimental Auctions of Intragenic and Transgenic Foods," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6407, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    50. Obryan Poyser, 2017. "Exploring the determinants of Bitcoin's price: an application of Bayesian Structural Time Series," Papers 1706.01437, arXiv.org.
    51. Daeseok Han, 2021. "Heterogeneous Deterioration Process and Risk of Deficiencies of Aging Bridges for Transportation Asset Management," Sustainability, MDPI, vol. 13(13), pages 1-16, June.
    52. Caio Waisman & Harikesh S. Nair & Carlos Carrion, 2019. "Online Causal Inference for Advertising in Real-Time Bidding Auctions," Papers 1908.08600, arXiv.org, revised Feb 2024.
    53. Helmut Herwartz & Christian Ochsner & Hannes Rohloff, 2021. "The Credit Composition of Global Liquidity," MAGKS Papers on Economics 202115, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    54. Joshua C C Chan & Cody Y L Hsiao, 2013. "Estimation of Stochastic Volatility Models with Heavy Tails and Serial Dependence," CAMA Working Papers 2013-74, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    55. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2014. "On the Rise of Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 14-085/III, Tinbergen Institute, revised 04 Sep 2014.
    56. Rob Luginbuhl, 2020. "Estimation of the Financial Cycle with a Rank-Reduced Multivariate State-Space Model," CPB Discussion Paper 409, CPB Netherlands Bureau for Economic Policy Analysis.
    57. Du, Xiaodong & Carriquiry, Miguel A., 2013. "Spatiotemporal analysis of ethanol market penetration," Energy Economics, Elsevier, vol. 38(C), pages 128-135.
    58. Ahn, Hie Joo, 2023. "Duration structure of unemployment hazards and the trend unemployment rate," Journal of Economic Dynamics and Control, Elsevier, vol. 151(C).
    59. Guangjie Li, 2015. "Consistency in Estimation and Model Selection of Dynamic Panel Data Models with Fixed Effects," Econometrics, MDPI, vol. 3(3), pages 1-31, July.
    60. Ahlem DAHEM, 2016. "Short-Term Bayesian Inflation Forecasting For Tunisia: Some Empirical Evidence," EcoForum, "Stefan cel Mare" University of Suceava, Romania, Faculty of Economics and Public Administration - Economy, Business Administration and Tourism Department., vol. 5(1), pages 1-47, January.
    61. Danaf, Mazen & Guevara, Angelo & Atasoy, Bilge & Ben-Akiva, Moshe, 2020. "Endogeneity in adaptive choice contexts: Choice-based recommender systems and adaptive stated preferences surveys," Journal of choice modelling, Elsevier, vol. 34(C).
    62. Li, Phillip, 2010. "Estimation of Sample Selection Models With Two Selection Mechanisms," University of California Transportation Center, Working Papers qt0h97w9x2, University of California Transportation Center.
    63. Baltagi, Badi H. & Bresson, Georges & Chaturvedi, Anoop & Lacroix, Guy, 2022. "Robust Dynamic Space-Time Panel Data Models Using ?-Contamination: An Application to Crop Yields and Climate Change," IZA Discussion Papers 15815, Institute of Labor Economics (IZA).
    64. Klaus Moeltner & James J. Murphy & John K. Stranlund & Maria Alejandra Velez, 2013. "Institutional heterogeneity in social dilemma games: a Bayesian examination," Chapters, in: John A. List & Michael K. Price (ed.), Handbook on Experimental Economics and the Environment, chapter 2, pages 67-88, Edward Elgar Publishing.
    65. Bin Jiang & Anastasios Panagiotelis & George Athanasopoulos & Rob Hyndman & Farshid Vahid, 2016. "Bayesian Rank Selection in Multivariate Regression," Monash Econometrics and Business Statistics Working Papers 6/16, Monash University, Department of Econometrics and Business Statistics.
    66. Joshua C.C. Chan, 2015. "Specification tests for time-varying parameter models with stochastic volatility," CAMA Working Papers 2015-42, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    67. Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2022. "An automated prior robustness analysis in Bayesian model comparison," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 583-602, April.
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    76. Hakobyana, Zaruhi & Koulovatianos, Christos, 2019. "Populism and polarization in social media without fake news: The vicious circle of biases, beliefs and network homophily," CFS Working Paper Series 626, Center for Financial Studies (CFS).
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    84. Gardebroek, Cornelis & Oude Lansink, Alfons G.J.M., 2008. "Dynamic Microeconometric Approaches To Analysing Agricultural Policy," 107th Seminar, January 30-February 1, 2008, Sevilla, Spain 6592, European Association of Agricultural Economists.
    85. Ishdorj, Ariun & Jensen, Helen H., 2010. "Demand For Breakfast Cereals: Whole Grains Guidance And Food Choice," 115th Joint EAAE/AAEA Seminar, September 15-17, 2010, Freising-Weihenstephan, Germany 116445, European Association of Agricultural Economists.
    86. Herriges, Joseph A. & Phaneuf, Daniel J. & Tobias, Justin, 2008. "Estimating Demand Systems when Outcomes Are Correlated Count," Staff General Research Papers Archive 12934, Iowa State University, Department of Economics.
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    112. C. Glocker & G. Sestieri & P. Towbin, 2017. "Time-varying fiscal spending multipliers in the UK," Working papers 643, Banque de France.
    113. Mengheng Li & Marcel Scharth, 2022. "Leverage, Asymmetry, and Heavy Tails in the High-Dimensional Factor Stochastic Volatility Model," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 285-301, January.
    114. Bernardi Mauro & Della Corte Giuseppe & Proietti Tommaso, 2011. "Extracting the Cyclical Component in Hours Worked," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(3), pages 1-28, May.
    115. Christopher N. Boyer & Dayton M. Lambert & Charles C. Martinez & Joshua G. Maples, 2023. "Beef and pork processing plant labor costs," Agribusiness, John Wiley & Sons, Ltd., vol. 39(3), pages 691-702, July.
    116. Parley Ruogu Yang, 2021. "Forecasting high-frequency financial time series: an adaptive learning approach with the order book data," Papers 2103.00264, arXiv.org.
    117. Dogan, Osman & Taspinar, Suleyman, 2016. "Bayesian Inference in Spatial Sample Selection Models," MPRA Paper 82829, University Library of Munich, Germany.
    118. Peter Lenk, 2014. "Bayesian estimation of random utility models," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 20, pages 457-497, Edward Elgar Publishing.
    119. Saqib Amin & Ruhamah Yousaf & Muhammad Awais Anwar & Noman Arshed, 2022. "Assessing the impact of diversity and ageing population on health expenditure of United States," International Journal of Health Planning and Management, Wiley Blackwell, vol. 37(2), pages 913-929, March.
    120. Jiaying Deng & Hossein Ghasemkhani & Yong Tan & Arvind K Tripathi, 2023. "Actions speak louder than words: Imputing users’ reputation from transaction history," Production and Operations Management, Production and Operations Management Society, vol. 32(4), pages 1096-1111, April.
    121. Han, Xiaoyi & Hsieh, Chih-Sheng & Lee, Lung-fei, 2017. "Estimation and model selection of higher-order spatial autoregressive model: An efficient Bayesian approach," Regional Science and Urban Economics, Elsevier, vol. 63(C), pages 97-120.
    122. Mihaela Simionescu (Bratu), 2014. "The Bayesian Modelling Of Inflation Rate In Romania," Romanian Statistical Review, Romanian Statistical Review, vol. 62(2), pages 147-160, June.
    123. David, Bounie & Abel, François & Patrick, Waelbroeck, 2016. "Debit card and demand for cash," Journal of Banking & Finance, Elsevier, vol. 73(C), pages 55-66.
    124. Xiaodong Du & Fengxia Dong, 2016. "Responses to market information and the impact on price volatility and trading volume: the case of Class III milk futures," Empirical Economics, Springer, vol. 50(2), pages 661-678, March.
    125. Park, Yuri & Koo, Yoonmo, 2016. "An empirical analysis of switching cost in the smartphone market in South Korea," Telecommunications Policy, Elsevier, vol. 40(4), pages 307-318.
    126. Damien, Paul & Fuentes-García, Ruth & Mena, Ramsés H. & Zarnikau, Jay, 2019. "Impacts of day-ahead versus real-time market prices on wholesale electricity demand in Texas," Energy Economics, Elsevier, vol. 81(C), pages 259-272.
    127. Qian, Hang, 2010. "Linear regression using both temporally aggregated and temporally disaggregated data: Revisited," MPRA Paper 32686, University Library of Munich, Germany.
    128. Colson, Gregory, 2009. "Improving nutrient content through genetic modification: Evidence from experimental auctions on consumer acceptance and willingness to pay for intragenic foods," ISU General Staff Papers 200901010800001872, Iowa State University, Department of Economics.
    129. Altman, Edward I. & Kalotay, Egon A., 2014. "Ultimate recovery mixtures," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 116-129.
    130. Florian Huber & Luca Onorante & Michael Pfarrhofer, 2022. "Forecasting euro area inflation using a huge panel of survey expectations," Papers 2207.12225, arXiv.org.
    131. Gary Cornwall & Jeffrey A. Mills & Beau A. Sauley & Huibin Weng, 2018. "Predictive Testing for Granger Causality via Posterior Simulation and Cross Validation," BEA Working Papers 0156, Bureau of Economic Analysis.
    132. Nataliia Ostapenko, 2022. "Do output gap estimates improve inflation forecasts in Slovakia?," Working and Discussion Papers WP 4/2022, Research Department, National Bank of Slovakia.
    133. James R. Bland, 2019. "Measuring and Comparing Two Kinds of Rationalizable Opportunity Cost in Mixture Models," Games, MDPI, vol. 11(1), pages 1-27, December.
    134. Moisés Carrasco Garcés & Felipe Vasquez-Lavin & Roberto D. Ponce Oliva & José Luis Bustamante Oporto & Manuel Barrientos & Arcadio A. Cerda, 2021. "Embedding effect and the consequences of advanced disclosure: evidence from the valuation of cultural goods," Empirical Economics, Springer, vol. 61(2), pages 1039-1062, August.
    135. Yi-Chun (Chad) Ho & Junjie Wu & Yong Tan, 2017. "Disconfirmation Effect on Online Rating Behavior: A Structural Model," Information Systems Research, INFORMS, vol. 28(3), pages 626-642, September.

  67. Gary Koop & Lise Tole, 2007. "What is the Environmental Performance of Firms Overseas?: An Empirical Investigation of the Global Gold Mining Industry," Working Paper series 26_07, Rimini Centre for Economic Analysis.

    Cited by:

    1. Hosseinzadeh, Ahmad & Smyth, Russell & Valadkhani, Abbas & Le, Viet, 2016. "Analyzing the efficiency performance of major Australian mining companies using bootstrap data envelopment analysis," Economic Modelling, Elsevier, vol. 57(C), pages 26-35.
    2. Shahbaz, Muhammad, 2013. "Does financial instability increase environmental degradation? Fresh evidence from Pakistan," Economic Modelling, Elsevier, vol. 33(C), pages 537-544.
    3. Anthony Glass & Karligash Kenjegalieva & Robin Sickles, 2013. "How efficiently do U.S. cities manage roadway congestion?," Journal of Productivity Analysis, Springer, vol. 40(3), pages 407-428, December.
    4. Magambo, Isaiah Hubert & Dikgang, Johane & Gelo, Dambala & Tregenna, Fiona, 2021. "Dynamic Technical and Environmental Efficiency Performance of Large Gold Mines in Developing Countries," EconStor Preprints 235859, ZBW - Leibniz Information Centre for Economics.
    5. Kukenova, Madina & Monteiro, Jose-Antonio, 2008. "Does Lax Environmental Regulation Attract FDI when accounting for "third-country" effects?," MPRA Paper 11321, University Library of Munich, Germany, revised Sep 2008.
    6. Dong, Feng & Li, Yangfan & Li, Kun & Zhu, Jiao & Zheng, Lu, 2022. "Can smart city construction improve urban ecological total factor energy efficiency in China? Fresh evidence from generalized synthetic control method," Energy, Elsevier, vol. 241(C).
    7. Morakinyo Adetutu & Anthony Glass & Karligash Kenjegalieva & Robin Sickles, 2015. "The effects of efficiency and TFP growth on pollution in Europe: a multistage spatial analysis," Journal of Productivity Analysis, Springer, vol. 43(3), pages 307-326, June.
    8. Yan Wang & Tao Zhou & Hao Chen & Zhihai Rong, 2019. "Environmental Homogenization or Heterogenization? The Effects of Globalization on Carbon Dioxide Emissions, 1970–2014," Sustainability, MDPI, vol. 11(10), pages 1-23, May.

  68. Anthony Garratt & Gary Koop & Emi Mise & Shaun P Vahey, 2007. "Real-time Prediction with UK Monetary Aggregates in the Presence of Model Uncertainty," Birkbeck Working Papers in Economics and Finance 0714, Birkbeck, Department of Economics, Mathematics & Statistics.

    Cited by:

    1. Oleg Korenok & Stanislav Radchenko & Norman R. Swanson, 2010. "International evidence on the efficacy of new‐Keynesian models of inflation persistence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 31-54, January.
    2. Andres Fernandez & Norman R. Swanson, 2009. "Real-time datasets really do make a difference: definitional change, data release, and forecasting," Working Papers 09-28, Federal Reserve Bank of Philadelphia.
    3. Ratti, Ronald A. & Vespignani, Joaquin L., 2015. "Commodity prices and BRIC and G3 liquidity: A SFAVEC approach," Journal of Banking & Finance, Elsevier, vol. 53(C), pages 18-33.
    4. Chris McDonald & Craig Thamotheram & Shaun P. Vahey & Elizabeth C. Wakerly, 2016. "Assessing the economic value of probabilistic forecasts in the presence of an inflation target," Reserve Bank of New Zealand Discussion Paper Series DP2016/10, Reserve Bank of New Zealand.
    5. Lanne, Markku & Luoma, Arto & Luoto, Jani, 2008. "A Naïve Sticky Information Model of Households’ Inflation Expectations," MPRA Paper 8663, University Library of Munich, Germany.
    6. Cobham, David, 2012. "The past, present and future of central banking," SIRE Discussion Papers 2012-50, Scottish Institute for Research in Economics (SIRE).
    7. Robert J. Tetlow, 2010. "Real-time model uncertainty in the United States: 'Robust' policies put to the test," Finance and Economics Discussion Series 2010-15, Board of Governors of the Federal Reserve System (U.S.).
    8. Ratti, Ronald A. & Vespignani, Joaquin L., 2016. "Oil prices and global factor macroeconomic variables," Energy Economics, Elsevier, vol. 59(C), pages 198-212.
    9. Alex Nikolsko-Rzhevskyy, 2011. "Monetary Policy Estimation in Real Time: Forward-Looking Taylor Rules without Forward-Looking Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43(5), pages 871-897, August.
    10. Anne Sofie Jore & James Mitchell & Shaun Vahey, 2008. "Combining Forecast Densities from VARs with Uncertain Instabilities," Reserve Bank of New Zealand Discussion Paper Series DP2008/18, Reserve Bank of New Zealand.
    11. Vespignani, Joaquin L. & Ratti, Ronald A., 2016. "Not all international monetary shocks are alike for the Japanese economy," Economic Modelling, Elsevier, vol. 52(PB), pages 822-837.
    12. Schumacher, Christian, 2009. "Factor forecasting using international targeted predictors: the case of German GDP," Discussion Paper Series 1: Economic Studies 2009,10, Deutsche Bundesbank.
    13. Jiang, Lei, 2014. "Stock liquidity and the Taylor rule," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 202-214.
    14. KOROBILIS, Dimitris, 2011. "VAR forecasting using Bayesian variable selection," LIDAM Discussion Papers CORE 2011022, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    15. Kim, Young Min & Lee, Seojin, 2020. "Exchange rate predictability: A variable selection perspective," International Review of Economics & Finance, Elsevier, vol. 70(C), pages 117-134.
    16. Anthony Garratt & James Mitchell & Shaun P. Vahey & Elizabeth C. Wakerly, 2010. "Real-time Inflation Forecast Densities from Ensemble Phillips Curves," CAMA Working Papers 2010-34, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    17. Dean Croushore, 2008. "Frontiers of real-time data analysis," Working Papers 08-4, Federal Reserve Bank of Philadelphia.
    18. Shaun P Vahey & Elizabeth C Wakerly, 2013. "Moving towards probability forecasting," BIS Papers chapters, in: Bank for International Settlements (ed.), Globalisation and inflation dynamics in Asia and the Pacific, volume 70, pages 3-8, Bank for International Settlements.
    19. Nikolsko-Rzhevskyy, Alex, 2008. "Monetary Policy Evaluation in Real Time: Forward-Looking Taylor Rules Without Forward-Looking Data," MPRA Paper 11352, University Library of Munich, Germany.
    20. Kuzin, Vladimir N. & Marcellino, Massimiliano & Schumacher, Christian, 2009. "Pooling versus model selection for nowcasting with many predictors: an application to German GDP," Discussion Paper Series 1: Economic Studies 2009,03, Deutsche Bundesbank.
    21. Smith, Michael Stanley, 2015. "Copula modelling of dependence in multivariate time series," International Journal of Forecasting, Elsevier, vol. 31(3), pages 815-833.
    22. Chang, Ming-Jen & Matsuki, Takashi, 2022. "Exchange rate forecasting with real-time data: Evidence from Western offshoots," Research in International Business and Finance, Elsevier, vol. 59(C).
    23. Dr. James Mitchell, 2009. "Measuring Output Gap Uncertainty," National Institute of Economic and Social Research (NIESR) Discussion Papers 342, National Institute of Economic and Social Research.
    24. David Cobham, 2012. "From Bretton Woods to inflation targeting: financial change and monetary policy evolution in Europe," Heriot-Watt University Economics Discussion Papers 1203, Department of Economics, School of Management and Languages, Heriot Watt University.
    25. Timmermann, Allan, 2006. "Forecast Combinations," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 4, pages 135-196, Elsevier.
    26. Garratt, Anthony & Mitchell, James & Vahey, Shaun, 2013. "Measuring Output Gap Nowcast Uncertainty," EMF Research Papers 01, Economic Modelling and Forecasting Group.
    27. Khiabani, Nasser, 2010. "How Important are Oil and Money Shocks in Explaining Housing Market Fluctuations in an Oil-exporting Country?: Evidence from Iran," MPRA Paper 34041, University Library of Munich, Germany, revised 01 Mar 2011.
    28. Bo Zhang, 2019. "Real‐time inflation forecast combination for time‐varying coefficient models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(3), pages 175-191, April.
    29. Dimitris Korobilis, 2018. "Machine Learning Macroeconometrics: A Primer," Working Paper series 18-30, Rimini Centre for Economic Analysis.
    30. Luoto, Jani, 2011. "Aggregate infrastructure capital stock and long-run growth: Evidence from Finnish data," Journal of Development Economics, Elsevier, vol. 94(2), pages 181-191, March.
    31. Kevin Lee, Nilss Olekalns, Kalvinder Shields and Zheng Wang, 2011. "The Australian Real?Time Datbase: An Overview and an Illustration of its Use in Business Cycle Analysis," Department of Economics - Working Papers Series 1132, The University of Melbourne.
    32. Buncic, Daniel & Müller, Oliver, 2017. "Measuring the output gap in Switzerland with linear opinion pools," Economic Modelling, Elsevier, vol. 64(C), pages 153-171.
    33. Antipa, Pamfili & Barhoumi, Karim & Brunhes-Lesage, Véronique & Darné, Olivier, 2012. "Nowcasting German GDP: A comparison of bridge and factor models," Journal of Policy Modeling, Elsevier, vol. 34(6), pages 864-878.
    34. Chris Florakis & Gianluigi Giorgioni & Alexandros Kostakis & Costas Milas, 2012. "The Impact of Stock Market Illiquidity on Real UK GDP Growth," Working Paper series 65_12, Rimini Centre for Economic Analysis.
    35. Wolden Bache, Ida & Sofie Jore, Anne & Mitchell, James & Vahey, Shaun P., 2011. "Combining VAR and DSGE forecast densities," Journal of Economic Dynamics and Control, Elsevier, vol. 35(10), pages 1659-1670, October.
    36. Garratt, Anthony & Koop, Gary & Mise, Emi & Vahey, Shaun P., 2009. "Real-Time Prediction With U.K. Monetary Aggregates in the Presence of Model Uncertainty," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 480-491.
    37. Wojciech Charemza & Carlos Diaz Vela & Svetlana Makarova, 2013. "Inflation fan charts, monetary policy and skew normal distribution," Discussion Papers in Economics 13/06, Division of Economics, School of Business, University of Leicester.
    38. Katharina Glass, 2018. "Predictability of Euro Area Revisions," Macroeconomics and Finance Series 201801, University of Hamburg, Department of Socioeconomics.
    39. Groen, Jan J.J. & Kapetanios, George & Price, Simon, 2009. "A real time evaluation of Bank of England forecasts of inflation and growth," International Journal of Forecasting, Elsevier, vol. 25(1), pages 74-80.
    40. Zhang, Bo & Nguyen, Bao H., 2020. "Real-time forecasting of the Australian macroeconomy using Bayesian VARs," Working Papers 2020-12, University of Tasmania, Tasmanian School of Business and Economics.
    41. Gary Koop & Dimitris Korobilis, 2013. "A new index of financial conditions," Working Papers 1307, University of Strathclyde Business School, Department of Economics.
    42. Erick Lahura, 2017. "Monetary Aggregates and Monetary Policy in Peru," BCAM Working Papers 1704, Birkbeck Centre for Applied Macroeconomics.
    43. Khiabani, Nasser, 2015. "Oil inflows and housing market fluctuations in an oil-exporting country: Evidence from Iran," Journal of Housing Economics, Elsevier, vol. 30(C), pages 59-76.
    44. Anthony Garratt & Ivan Petrella, 2022. "Commodity prices and inflation risk," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 392-414, March.
    45. Enrique Moral-Benito, 2015. "Model Averaging In Economics: An Overview," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 46-75, February.
    46. Florackis, Chris & Giorgioni, Gianluigi & Kostakis, Alexandros & Milas, Costas, 2014. "On stock market illiquidity and real-time GDP growth," Journal of International Money and Finance, Elsevier, vol. 44(C), pages 210-229.

  69. Anthony Garratt & Gary Koop & Shaun P. Vahey, 2006. "Forecasting Substantial Data Revisions in the Presence of Model Uncertainty," Birkbeck Working Papers in Economics and Finance 0617, Birkbeck, Department of Economics, Mathematics & Statistics.

    Cited by:

    1. Yu-Fan Huang & Sui Luo, 2018. "Potential output and inflation dynamics after the Great Recession," Empirical Economics, Springer, vol. 55(2), pages 495-517, September.
    2. Todd E. Clark & Michael W. McCracken, 2010. "Averaging forecasts from VARs with uncertain instabilities," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 5-29.
    3. Alex Nikolsko-Rzhevskyy, 2011. "Monetary Policy Estimation in Real Time: Forward-Looking Taylor Rules without Forward-Looking Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43(5), pages 871-897, August.
    4. Anne Sofie Jore & James Mitchell & Shaun Vahey, 2008. "Combining Forecast Densities from VARs with Uncertain Instabilities," Reserve Bank of New Zealand Discussion Paper Series DP2008/18, Reserve Bank of New Zealand.
    5. Anthony Garratt & Gary Koop & Shaun P. Vahey, 2008. "Forecasting Substantial Data Revisions in the Presence of Model Uncertainty," Economic Journal, Royal Economic Society, vol. 118(530), pages 1128-1144, July.
    6. James M. Nason & Shaun P. Vahey, 2011. "UK World War I and interwar data for business cycle and growth analysis," Working Papers 11-10, Federal Reserve Bank of Philadelphia.
    7. Grammig, Joachim & Kehrle, Kerstin, 2008. "A new marked point process model for the federal funds rate target: Methodology and forecast evaluation," Journal of Economic Dynamics and Control, Elsevier, vol. 32(7), pages 2370-2396, July.
    8. Döhrn, Roland, 2020. "Are German national accounts informational efficient?," Ruhr Economic Papers 880, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    9. Akram, Q. Farooq, 2011. "Policy analysis in real time using IMF's monetary model," Economic Modelling, Elsevier, vol. 28(4), pages 1696-1709, July.
    10. Nikolsko-Rzhevskyy, Alex, 2008. "Monetary Policy Evaluation in Real Time: Forward-Looking Taylor Rules Without Forward-Looking Data," MPRA Paper 11352, University Library of Munich, Germany.
    11. Christopher Adam & David Cobham, 2009. "Using Real-Time Output Gaps To Examine Past And Future Policy Choices," National Institute Economic Review, National Institute of Economic and Social Research, vol. 210(1), pages 98-110, October.
    12. Li, Z. & Hurn, A.S. & Clements, A.E., 2017. "Forecasting quantiles of day-ahead electricity load," Energy Economics, Elsevier, vol. 67(C), pages 60-71.
    13. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    14. Cath Sleeman, 2006. "Analysis of revisions to quarterly GDP - a real-time database," Reserve Bank of New Zealand Bulletin, Reserve Bank of New Zealand, vol. 69, pages 1-44., March.
    15. Wolden Bache, Ida & Sofie Jore, Anne & Mitchell, James & Vahey, Shaun P., 2011. "Combining VAR and DSGE forecast densities," Journal of Economic Dynamics and Control, Elsevier, vol. 35(10), pages 1659-1670, October.
    16. Mahadeva, Lavan, 2007. "Monetary Policy and Data Uncertainty: A Case Study of Distribution, Hotels and Catering Growth," Discussion Papers 19, Monetary Policy Committee Unit, Bank of England.
    17. Garratt, Anthony & Koop, Gary & Mise, Emi & Vahey, Shaun P., 2009. "Real-Time Prediction With U.K. Monetary Aggregates in the Presence of Model Uncertainty," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 480-491.
    18. Katharina Glass, 2018. "Predictability of Euro Area Revisions," Macroeconomics and Finance Series 201801, University of Hamburg, Department of Socioeconomics.
    19. Roland Döhrn, 2023. "Are German National Accounts informationally efficient?," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 19(1), pages 23-42, March.
    20. Chanont Banternghansa & Michael W. McCracken, 2010. "Real-time forecast averaging with ALFRED," Working Papers 2010-033, Federal Reserve Bank of St. Louis.
    21. Richard G. Anderson & Charles S. Gascon, 2009. "Estimating U.S. output growth with vintage data in a state-space framework," Review, Federal Reserve Bank of St. Louis, vol. 91(Jul), pages 349-370.

  70. Koop, Gary M & Tobias, Justin, 2006. "Semiparametric Bayesian Inference in Smooth Coefficient Models," Staff General Research Papers Archive 12202, Iowa State University, Department of Economics.

    Cited by:

    1. Dorfman, Jeffrey H. & Karali, Berna, 2008. "Do Farmers Hedge Optimally or by Habit? A Bayesian Partial-Adjustment Model of Farmer Hedging," 2008 Conference, April 21-22, 2008, St. Louis, Missouri 37596, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    2. Dorfman, Jeffrey H. & Patridge, Mark D. & Galloway, Hamilton, 2008. "Are High-Tech Employment and Natural Amenities Linked?: Answers from a Smoothed Bayesian Spatial Model," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6459, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    3. Berna Karali & Jeffrey H. Dorfman & Walter N. Thurman, 2010. "Do volatility determinants vary across futures contracts? Insights from a smoothed Bayesian estimator," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 30(3), pages 257-277, March.
    4. William H. Greene & David A. Hensher, 2008. "Modeling Ordered Choices: A Primer and Recent Developments," Working Papers 08-26, New York University, Leonard N. Stern School of Business, Department of Economics.
    5. Scott E. Atkinson & Jeffrey H. Dorfman, 2009. "Feasible estimation of firm-specific allocative inefficiency through Bayesian numerical methods," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(4), pages 675-697.
    6. Huang, Ho-Chuan (River) & Lin, Shu-Chin, 2008. "Smooth-time-varying Okun's coefficients," Economic Modelling, Elsevier, vol. 25(2), pages 363-375, March.
    7. Myeong Jun Kim & Stanley I. M. Ko & Sung Y. Park, 2021. "On time and frequency-varying Okun’s coefficient: a new approach based on ensemble empirical mode decomposition," Empirical Economics, Springer, vol. 61(3), pages 1151-1188, September.
    8. Bacolod, Marigee P. & Tobias, Justin L., 2006. "Schools, school quality and achievement growth: Evidence from the Philippines," Economics of Education Review, Elsevier, vol. 25(6), pages 619-632, December.
    9. Amin Mugera & Michael Langemeier & Allen Featherstone, 2012. "Labor productivity convergence in the Kansas farm sector: a three-stage procedure using data envelopment analysis and semiparametric regression analysis," Journal of Productivity Analysis, Springer, vol. 38(1), pages 63-79, August.
    10. Suzanna-Maria Paleologou, 2016. "The long-run tendency of government expenditure: a semi-parametric modelling approach," Empirical Economics, Springer, vol. 50(3), pages 753-776, May.
    11. Agee, Mark D. & Atkinson, Scott E. & Crocker, Thomas D. & Williams, Jonathan W., 2014. "Non-separable pollution control: Implications for a CO2 emissions cap and trade system," Resource and Energy Economics, Elsevier, vol. 36(1), pages 64-82.
    12. Murat K. Munkin, 2022. "Count Roy model with finite mixtures," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1160-1181, September.
    13. Luca Brugnolini & Giuseppe Ragusa, 2022. "Euro Area Deflationary Pressure Index," Computational Economics, Springer;Society for Computational Economics, vol. 60(3), pages 883-900, October.
    14. Zheng, Xiaoyong, 2008. "Semiparametric Bayesian estimation of mixed count regression models," Economics Letters, Elsevier, vol. 100(3), pages 435-438, September.

  71. Gary Koop & Roberto Leon-Gonzalez & Rodney Strachan, 2006. "Bayesian Inference in a Cointegrating Panel Data Model," Discussion Papers in Economics 06/2, Division of Economics, School of Business, University of Leicester.

    Cited by:

    1. Jochmann, Markus & Koop, Gary, 2011. "Regime-Switching Cointegration," SIRE Discussion Papers 2011-60, Scottish Institute for Research in Economics (SIRE).
    2. Tareq Sadeq, 2008. "Bayesian Analysis of DSGE models: A Panel Approach," Documents de recherche 08-03, Centre d'Études des Politiques Économiques (EPEE), Université d'Evry Val d'Essonne.
    3. Michael L. Polemis & Mike G. Tsionas, 2023. "The environmental consequences of blockchain technology: A Bayesian quantile cointegration analysis for Bitcoin," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 1602-1621, April.

  72. Gary Koop & Simon M. Potter & Rodney W. Strachan, 2005. "Reexamining the consumption-wealth relationship: the role of model uncertainty," Staff Reports 202, Federal Reserve Bank of New York.

    Cited by:

    1. Markus Jochmann & Gary Koop & Roberto Leon-Gonzalez & Rodney W. Strachan, 2009. "Stochastic Search Variable Selection in Vector Error Correction Models with an Application to a Model of the UK Macroeconomy," Working Paper series 44_09, Rimini Centre for Economic Analysis.
    2. Chen, Jie, 2006. "Housing Wealth and Aggregate Consumption in Sweden," Working Paper Series 2006:16, Uppsala University, Department of Economics.
    3. Jochmann, Markus & Koop, Gary, 2011. "Regime-Switching Cointegration," SIRE Discussion Papers 2011-60, Scottish Institute for Research in Economics (SIRE).
    4. Todd E. Clark & Michael W. McCracken, 2010. "Averaging forecasts from VARs with uncertain instabilities," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 5-29.
    5. Olivier Allain, 2011. "The impact of income distribution on consumption: a reassessment," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00712657, HAL.
    6. Chen, Jie, 2006. "Re-evaluating the association between housing wealth and aggregate consumption: New evidence from Sweden," Journal of Housing Economics, Elsevier, vol. 15(4), pages 321-348, December.
    7. Iscan, Talan B., 2011. "Productivity growth and the U.S. saving rate," Economic Modelling, Elsevier, vol. 28(1-2), pages 501-514, January.
    8. Frank Schmid, 2013. "Wealth Effects on Consumption in Switzerland," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 149(I), pages 87-110, March.
    9. Yang, Zan & Wang, S.T., 2012. "Permanent and transitory shocks in owner-occupied housing: A common trend model of price dynamics," Journal of Housing Economics, Elsevier, vol. 21(4), pages 336-346.
    10. Boysen-Hogrefe, Jens & Dovern, Jonas & Gern, Klaus-Jürgen & Jannsen, Nils & Van Roye, Björn & Sander, Birgit & Scheide, Joachim & Boss, Alfred & Meier, Carsten-Patrick, 2008. "Weltkonjunktur und deutsche Konjunktur im Winter 2008," Kiel Discussion Papers 459/460, Kiel Institute for the World Economy (IfW Kiel).
    11. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    12. Maltritz, Dominik & Molchanov, Alexander, 2014. "Country credit risk determinants with model uncertainty," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 224-234.
    13. Márquez, Elena & Martínez-Cañete, Ana R. & Pérez-Soba, Inés, 2013. "Wealth shocks, credit conditions and asymmetric consumption response: Empirical evidence for the UK," Economic Modelling, Elsevier, vol. 33(C), pages 357-366.
    14. Justyna Wróblewska, 2009. "Bayesian Model Selection in the Analysis of Cointegration," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 1(1), pages 57-69, March.
    15. Maltritz, Dominik, 2012. "Determinants of sovereign yield spreads in the Eurozone: A Bayesian approach," Journal of International Money and Finance, Elsevier, vol. 31(3), pages 657-672.
    16. Maltritz, Dominik & Molchanov, Alexander, 2013. "Analyzing determinants of bond yield spreads with Bayesian Model Averaging," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5275-5284.
    17. Ren, Yu & Yuan, Yufei & Zhang, Yang, 2014. "Human capital, household capital and asset returns," Journal of Banking & Finance, Elsevier, vol. 42(C), pages 11-22.
    18. Mattias Villani, 2009. "Steady-state priors for vector autoregressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(4), pages 630-650.

  73. Koop, G. & Strachan, R.W. & van Dijk, H.K. & Villani, M., 2005. "Bayesian approaches to cointegratrion," Econometric Institute Research Papers EI 2005-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Karlsson, Sune, 2012. "Forecasting with Bayesian Vector Autoregressions," Working Papers 2012:12, Örebro University, School of Business.
    2. SILVESTRINI, Andrea, 2010. "Testing fiscal sustainability in Poland: a Bayesian analysis of cointegration," LIDAM Reprints CORE 2220, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Gareth W. Peters & Balakrishnan Kannan & Ben Lasscock & Chris Mellen, 2010. "Model Selection and Adaptive Markov chain Monte Carlo for Bayesian Cointegrated VAR model," Papers 1004.3830, arXiv.org.
    4. Cristina Fuentes-Albero & Leonardo Melosi, 2011. "Methods for Computing Marginal Data Densities from the Gibbs Output," Departmental Working Papers 201131, Rutgers University, Department of Economics.
    5. Primiceri, Giorgio & Giannone, Domenico & Lenza, Michele, 2016. "Priors for the Long Run," CEPR Discussion Papers 11261, C.E.P.R. Discussion Papers.
    6. Ciobotaru, Corina & Mazza, Christian, 2022. "Consistency and asymptotic normality of M-estimates of scatter on Grassmann manifolds," Journal of Multivariate Analysis, Elsevier, vol. 190(C).
    7. Helmut Luetkepohl, 2007. "Econometric Analysis with Vector Autoregressive Models," Economics Working Papers ECO2007/11, European University Institute.
    8. Sugita, Katsuhiro & 杉田, 勝弘, 2006. "Bayesian Analysis of Dynamic Multivariate Models with Multiple Structural Breaks," Discussion Papers 2006-14, Graduate School of Economics, Hitotsubashi University.
    9. Kociecki, Andrzej, 2012. "Orbital Priors for Time-Series Models," MPRA Paper 42804, University Library of Munich, Germany.
    10. Villani, Mattias, 2005. "Bayesian Inference of General Linear Restrictions on the Cointegration Space," Working Paper Series 189, Sveriges Riksbank (Central Bank of Sweden).
    11. Sugita, Katsuhiro & 杉田, 勝弘, 2006. "Time Series Analysis of the Expectations Hypothesis for the Japanese Term Structure of Interest Rates in the Presence of Multiple Structural Breaks," Discussion Papers 2006-15, Graduate School of Economics, Hitotsubashi University.

  74. Gary Koop & Roberto León-González & Rodney W. Strachan, 2005. "Efficient Posterior Simulation for Cointegrated Models with Priors On the Cointegration Space," Discussion Papers in Economics 05/13, Division of Economics, School of Business, University of Leicester, revised Apr 2006.

    Cited by:

    1. Gary Koop & Roberto Leon-Gonzalez & Rodney Strachan, 2011. "Bayesian Inference in the Time Varying Cointegration Model," Working Papers 1121, University of Strathclyde Business School, Department of Economics.
    2. Luca Benati & Thomas A. Lubik, 2022. "Searching for Hysteresis," Working Paper 22-05, Federal Reserve Bank of Richmond.
    3. Karlsson, Sune, 2012. "Forecasting with Bayesian Vector Autoregressions," Working Papers 2012:12, Örebro University, School of Business.
    4. Koop, Gary & Leon-Gonzalez, Roberto & Strachan, Rodney, 2012. "Bayesian model averaging in the instrumental variable regression model," Journal of Econometrics, Elsevier, vol. 171(2), pages 237-250.
    5. Jacek Osiewalski & Justyna Wróblewska & Kamil Makieła, 2020. "Bayesian comparison of production function-based and time-series GDP models," Empirical Economics, Springer, vol. 58(3), pages 1355-1380, March.
    6. Jochmann, Markus & Koop, Gary, 2011. "Regime-Switching Cointegration," SIRE Discussion Papers 2011-60, Scottish Institute for Research in Economics (SIRE).
    7. Chan, Joshua C.C. & Eisenstat, Eric & Strachan, Rodney W., 2020. "Reducing the state space dimension in a large TVP-VAR," Journal of Econometrics, Elsevier, vol. 218(1), pages 105-118.
    8. Katsuhiro Sugita, 2017. "Time Series Analysis of the US Term Structure of Interest Rates Using a Bayesian Markov Switching Cointegration Model," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 9(3), pages 49-56, March.
    9. Rodney W. Strachan & Herman K. Van Dijk, 2013. "Evidence On Features Of A Dsge Business Cycle Model From Bayesian Model Averaging," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 54(1), pages 385-402, February.
    10. Tsay, Ruey S. & Ando, Tomohiro, 2012. "Bayesian panel data analysis for exploring the impact of subprime financial crisis on the US stock market," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3345-3365.
    11. Anna Pajor & Justyna Wróblewska, 2022. "Forecasting performance of Bayesian VEC-MSF models for financial data in the presence of long-run relationships," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(3), pages 427-448, September.
    12. Eric Eisenstat & Joshua C.C. Chan & Rodney W. Strachan, 2018. "Reducing Dimensions in a Large TVP-VAR," Working Paper Series 43, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
    13. Krzysztof Osiewalski & Jacek Osiewalski, 2013. "A Long-Run Relationship between Daily Prices on Two Markets: The Bayesian VAR(2)–MSF-SBEKK Model," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 5(1), pages 65-83, March.
    14. Justyna Wróblewska, 2012. "Bayesian Analysis of Weak Form Polynomial Reduced Rank Structures in VEC Models," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 4(4), pages 253-267, December.
    15. Dąbrowski, Marek A. & Wróblewska, Justyna, 2019. "Insulating property of the flexible exchange rate regime: A case of Central and Eastern European countries," MPRA Paper 93813, University Library of Munich, Germany.
    16. Peter McAdam & Kostas Mouratidis & Theodore Panagiotidis & Georgios Papapanagiotou, 2023. "European Trade & Growth Imbalances: An Analysis using a Sign-Restriction Bayesian-GVAR with Stochastic Volatility," Working Paper series 23-12, Rimini Centre for Economic Analysis.
    17. Dąbrowski, Marek A. & Wróblewska, Justyna, 2016. "Exchange rate as a shock absorber in Poland and Slovakia: Evidence from Bayesian SVAR models with common serial correlation," Economic Modelling, Elsevier, vol. 58(C), pages 249-262.
    18. Heather M Anderson & Farshid Vahid, 2010. "VARs, Cointegration and Common Cycle Restrictions," Monash Econometrics and Business Statistics Working Papers 14/10, Monash University, Department of Econometrics and Business Statistics.
    19. Sylvia Kaufmann & Johann Scharler, 2013. "Bank-Lending Standards, Loan Growth and the Business Cycle in the Euro Area," Working Papers 2013-34, Faculty of Economics and Statistics, Universität Innsbruck.
    20. Justyna Wróblewska & Anna Pajor, 2019. "One-period joint forecasts of Polish inflation, unemployment and interest rate using Bayesian VEC-MSF models," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 11(1), pages 23-45, March.
    21. Murasawa, Yasutomo, 2019. "Bayesian multivariate Beveridge--Nelson decomposition of I(1) and I(2) series with cointegration," MPRA Paper 91979, University Library of Munich, Germany.
    22. Justyna Wróblewska, 2015. "Common Trends and Common Cycles – Bayesian Approach," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 7(2), pages 91-110, June.
    23. Justyna Wróblewska, 2009. "Bayesian Model Selection in the Analysis of Cointegration," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 1(1), pages 57-69, March.
    24. Dąbrowski, Marek A. & Wróblewska, Justyna, 2015. "Exchange rate as a shock absorber or a shock propagator in Poland and Slovakia - an approach based on Bayesian SVAR models with common serial correlation," MPRA Paper 61441, University Library of Munich, Germany.
    25. Justyna Wróblewska, 2011. "Bayesian Analysis of Weak Form Reduced Rank Structure in VEC Models," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 3(3), pages 169-186, September.

  75. Koop, Gary M & Poirier, Dale J & Tobias, Justin, 2005. "Semiparametric Bayesian Inference in Multiple Equation Models," Staff General Research Papers Archive 12009, Iowa State University, Department of Economics.

    Cited by:

    1. Alexandra Ferreira‐Lopes & Luís Filipe Martins & Ruben Espanhol, 2020. "The relationship between tax rates and tax revenues in eurozone member countries ‐ exploring the Laffer curve," Bulletin of Economic Research, Wiley Blackwell, vol. 72(2), pages 121-145, April.
    2. Bin Zhou & Qinfeng Xu & Jinhong You, 2011. "Efficient estimation for error component seemingly unrelated nonparametric regression models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 73(1), pages 121-138, January.
    3. Marianna Belloc & Ugo Pagano, 2009. "Politics-Business Interaction Paths," CESifo Working Paper Series 2883, CESifo.
    4. Nicholas Apergis & Christina Christou & Stephen Miller, 2012. "Convergence patterns in financial development: evidence from club convergence," Empirical Economics, Springer, vol. 43(3), pages 1011-1040, December.
    5. Bresson Georges & Chaturvedi Anoop & Rahman Mohammad Arshad & Shalabh, 2021. "Seemingly unrelated regression with measurement error: estimation via Markov Chain Monte Carlo and mean field variational Bayes approximation," The International Journal of Biostatistics, De Gruyter, vol. 17(1), pages 75-97, May.
    6. Alan T. K. Wan & Jinhong You & Riquan Zhang, 2016. "A Seemingly Unrelated Nonparametric Additive Model with Autoregressive Errors," Econometric Reviews, Taylor & Francis Journals, vol. 35(5), pages 894-928, May.
    7. Manuel Wiesenfarth & Carlos Matías Hisgen & Thomas Kneib & Carmen Cadarso-Suarez, 2012. "Bayesian Nonparametric Instrumental Variable Regression based on Penalized Splines and Dirichlet Process Mixtures," Courant Research Centre: Poverty, Equity and Growth - Discussion Papers 127, Courant Research Centre PEG.
    8. Huang, Ho-Chuan (River) & Lin, Shu-Chin, 2008. "Smooth-time-varying Okun's coefficients," Economic Modelling, Elsevier, vol. 25(2), pages 363-375, March.
    9. Myeong Jun Kim & Stanley I. M. Ko & Sung Y. Park, 2021. "On time and frequency-varying Okun’s coefficient: a new approach based on ensemble empirical mode decomposition," Empirical Economics, Springer, vol. 61(3), pages 1151-1188, September.
    10. Joshua C.C. Chan & Angelia L. Grant, 2014. "Fast Computation of the Deviance Information Criterion for Latent Variable Models," CAMA Working Papers 2014-09, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    11. Panayotis Michaelides & Mike Tsionas & Panos Xidonas, 2020. "A Bayesian Signals Approach for the Detection of Crises," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(3), pages 551-585, September.
    12. Panagiotelis, Anastasios & Smith, Michael, 2008. "Bayesian identification, selection and estimation of semiparametric functions in high-dimensional additive models," Journal of Econometrics, Elsevier, vol. 143(2), pages 291-316, April.

  76. Gary Koop & Lise Tole, 2004. "An Investigation of Thresholds in Air Pollution-Mortality Effects," Discussion Papers in Economics 04/20, Division of Economics, School of Business, University of Leicester.

    Cited by:

    1. Roberto Leon-Gonzalez & Thanabalasingam Vinayagathasan, 2015. "Robust Determinants of Growth in Asian Developing Economies: A Bayesian Panel Data Model Averaging Approach," GRIPS Discussion Papers 15-15, National Graduate Institute for Policy Studies.

  77. Koop, Gary M & Tobias, Justin, 2004. "Learning About Heterogeneity in Returns to Schooling," Staff General Research Papers Archive 12008, Iowa State University, Department of Economics.

    Cited by:

    1. Ruiqi Liu & Ben Boukai & Zuofeng Shang, 2019. "Statistical Inference on Partially Linear Panel Model under Unobserved Linearity," Papers 1911.08830, arXiv.org.
    2. Victor Iturra & Mauricio Sarrias, 2023. "Amenities and individual heterogeneity in the return to schooling," Letters in Spatial and Resource Sciences, Springer, vol. 16(1), pages 1-15, December.
    3. Dolton, Peter & Sandi, Matteo, 2017. "Returning to returns: Revisiting the British education evidence," Labour Economics, Elsevier, vol. 48(C), pages 87-104.
    4. Li, Mingliang & Tobias, Justin L., 2011. "Bayesian inference in a correlated random coefficients model: Modeling causal effect heterogeneity with an application to heterogeneous returns to schooling," Journal of Econometrics, Elsevier, vol. 162(2), pages 345-361, June.
    5. Marianna Belloc & Ugo Pagano, 2009. "Politics-Business Interaction Paths," CESifo Working Paper Series 2883, CESifo.
    6. Holloway, Garth J. & Lacombe, Donald J. & LeSage, James P., 2006. "Spatial Econometric Issues for Bio-Economic and Land-Use Modeling," 2006 Annual Meeting, August 12-18, 2006, Queensland, Australia 25525, International Association of Agricultural Economists.
    7. Henderson, Daniel J. & Houtenville, Andrew & Wang, Le, 2017. "The Distribution of Returns to Education for People with Disabilities," IZA Discussion Papers 10747, Institute of Labor Economics (IZA).
    8. Sandeep Mohapatra & Bruno Wichmann & Philippe Marcoul, 2018. "Removing The “Veil Of Ignorance”: Nonlinearities In Education Effects On Gender Wage Inequalities," Contemporary Economic Policy, Western Economic Association International, vol. 36(4), pages 644-666, October.
    9. Tran, Tuyen Quang & Hung Pham, Hiep & Thi Vo, Hoa & Thuy Luu, Hong & Mai Nguyen, Huong, 2019. "Local governance, education and occupation-education mismatch: Heterogeneous effects on wages in a lower middle income economy," International Journal of Educational Development, Elsevier, vol. 71(C).
    10. Luca Favero & Andreina Fucci, 2017. "The Erasmus effect on earnings: a panel analysis from Siena," Department of Economics University of Siena 762, Department of Economics, University of Siena.
    11. Ozabaci, Deniz & Henderson, Daniel J., 2014. "Additive Kernel Estimates of Returns to Schooling," IZA Discussion Papers 8736, Institute of Labor Economics (IZA).
    12. Cui, Yuling & Nahm, Daehoon & Tani, Massimiliano, 2013. "Earnings Differentials and Returns to Education in China, 1995-2008," IZA Discussion Papers 7349, Institute of Labor Economics (IZA).
    13. Henderson, Daniel J. & Polachek, Solomon & Wang, Le, 2011. "Heterogeneity in Schooling Rates of Return," IZA Discussion Papers 5662, Institute of Labor Economics (IZA).
    14. Mohitosh Kejriwal & Xiaoxiao Li & Evan Totty, 2018. "Multidimensional Skills and the Returns to Schooling: Evidence from an Interactive Fixed Effects Approach and a Linked Survey-Administrative Dataset," Purdue University Economics Working Papers 1309, Purdue University, Department of Economics.
    15. Simone Balestra & Uschi Backes-Gellner, 2013. "Heterogeneous Returns to Education Over Wage Distribution: Who Profits the Most?," Economics of Education Working Paper Series 0091, University of Zurich, Department of Business Administration (IBW), revised Dec 2013.
    16. Biewen, Martin & (neé Tapalaga), Madalina Thiele, 2020. "Early tracking, academic vs. vocational training, and the value of ‘second-chance’ options," Labour Economics, Elsevier, vol. 66(C).
    17. Joshua C. C. Chan, 2005. "Replication of the results in 'learning about heterogeneity in returns to schooling'," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(3), pages 439-443.
    18. Patrawart, Kraiyos, 2008. "Can Equality in Education Be A New Anti-Corruption Tool?: Cross-Country Evidence (1990-2005)," MPRA Paper 9665, University Library of Munich, Germany.
    19. Koop, Gary M & Tobias, Justin, 2006. "Semiparametric Bayesian Inference in Smooth Coefficient Models," Staff General Research Papers Archive 12202, Iowa State University, Department of Economics.
    20. Mohitosh Kejriwal & Xiaoxiao Li & Evan Totty, 2019. "Multidemsional Skills and Returns to Schooling: Evidence from an Interactive Fixed Effects Aproach and a Linked Survey-Administrative Dataset," Purdue University Economics Working Papers 1316, Purdue University, Department of Economics.
    21. Mohitosh Kejriwal & Xiaoxiao Li & Linh Nguyen & Evan Totty, 2024. "The efficacy of ability proxies for estimating the returns to schooling: A factor model‐based evaluation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 3-21, January.
    22. Tsionas, Efthymios G., 2012. "Maximum likelihood estimation of stochastic frontier models by the Fourier transform," Journal of Econometrics, Elsevier, vol. 170(1), pages 234-248.
    23. Mingliang Li, 2006. "High school completion and future youth unemployment: new evidence from High School and Beyond," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 23-53, January.
    24. Aleksey Oshchepkov & Anna Shirokanova, 2020. "Multilevel Modeling For Economists: Why, When And How," HSE Working papers WP BRP 233/EC/2020, National Research University Higher School of Economics.
    25. Rémi Piatek & Pia Pinger, 2016. "Maintaining (Locus of) Control? Data Combination for the Identification and Inference of Factor Structure Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(4), pages 734-755, June.
    26. Dolton, Peter & Sandi, Matteo, 2017. "Returning to returns: revisiting the British education evidence," LSE Research Online Documents on Economics 85152, London School of Economics and Political Science, LSE Library.

  78. Gary Koop & Simon M. Potter, 2004. "Prior elicitation in multiple change-point models," Staff Reports 197, Federal Reserve Bank of New York.

    Cited by:

    1. Pesaran, M.H. & Pettenuzzo, D. & Timmermann, A., 2006. "Learning, Structural Instability and Present Value Calculations," Cambridge Working Papers in Economics 0602, Faculty of Economics, University of Cambridge.
    2. Kul B Luintel & Khan Mosahid & Leon-Gonzalez Roberto & Li Guangjie, 2016. "Financial Development, Structure and Growth : New Data, Method and Results," GRIPS Discussion Papers 15-27, National Graduate Institute for Policy Studies.
    3. Giordani, Paolo & Villani, Mattias, 2009. "Forecasting Macroeconomic Time Series With Locally Adaptive Signal Extraction," Working Paper Series 234, Sveriges Riksbank (Central Bank of Sweden).
    4. Daniel Felix Ahelegbey & Monica Billio & Roberto Casarin, 2020. "Modeling Turning Points In Global Equity Market," DEM Working Papers Series 195, University of Pavia, Department of Economics and Management.
    5. Jochmann, Markus & Koop, Gary & Strachan, Rodney W., 2010. "Bayesian forecasting using stochastic search variable selection in a VAR subject to breaks," International Journal of Forecasting, Elsevier, vol. 26(2), pages 326-347, April.
    6. Gary Koop & Simon M. Potter, 2004. "Forecasting and estimating multiple change-point models with an unknown number of change points," Staff Reports 196, Federal Reserve Bank of New York.
    7. Giordani, Paolo & Kohn, Robert, 2008. "Efficient Bayesian Inference for Multiple Change-Point and Mixture Innovation Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 66-77, January.
    8. Geweke, John F. & Horowitz, Joel L. & Pesaran, M. Hashem, 2006. "Econometrics: A Bird's Eye View," IZA Discussion Papers 2458, Institute of Labor Economics (IZA).
    9. Ruggieri, Eric & Antonellis, Marcus, 2016. "An exact approach to Bayesian sequential change point detection," Computational Statistics & Data Analysis, Elsevier, vol. 97(C), pages 71-86.
    10. Mehmet Balcilar & Riza Demirer & Festus V. Bekun, 2021. "Flexible Time-Varying Betas in a Novel Mixture Innovation Factor Model with Latent Threshold," Mathematics, MDPI, vol. 9(8), pages 1-20, April.
    11. Venkata Jandhyala & Stergios Fotopoulos & Ian MacNeill & Pengyu Liu, 2013. "Inference for single and multiple change-points in time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(4), pages 423-446, July.
    12. Lu Shaochuan, 2023. "Scalable Bayesian Multiple Changepoint Detection via Auxiliary Uniformisation," International Statistical Review, International Statistical Institute, vol. 91(1), pages 88-113, April.
    13. Chun Liu & John M. Maheu, 2008. "Are There Structural Breaks in Realized Volatility?," Journal of Financial Econometrics, Oxford University Press, vol. 6(3), pages 326-360, Summer.
    14. Hinoveanu, Laurentiu C. & Leisen, Fabrizio & Villa, Cristiano, 2019. "Bayesian loss-based approach to change point analysis," Computational Statistics & Data Analysis, Elsevier, vol. 129(C), pages 61-78.
    15. Petros Dellaportas & David G. T. Denison & Chris Holmes, 2007. "Flexible Threshold Models for Modelling Interest Rate Volatility," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 419-437.
    16. Guangjie Li, 2015. "A stochastic frontier model with structural breaks in efficiency and technology," Empirical Economics, Springer, vol. 49(1), pages 131-159, August.

  79. Gary Koop & Simon M. Potter, 2004. "Forecasting and estimating multiple change-point models with an unknown number of change points," Staff Reports 196, Federal Reserve Bank of New York.

    Cited by:

    1. Pesaran, M.H. & Pettenuzzo, D. & Timmermann, A., 2006. "Learning, Structural Instability and Present Value Calculations," Cambridge Working Papers in Economics 0602, Faculty of Economics, University of Cambridge.
    2. Gary Koop & Simon M. Potter, 2009. "Prior Elicitation In Multiple Change-Point Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 50(3), pages 751-772, August.
    3. Todd E. Clark & Michael W. McCracken, 2010. "Averaging forecasts from VARs with uncertain instabilities," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 5-29.
    4. Giordani, Paolo & Kohn, Robert, 2008. "Efficient Bayesian Inference for Multiple Change-Point and Mixture Innovation Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 66-77, January.
    5. Vosseler, Alexander, 2016. "Bayesian model selection for unit root testing with multiple structural breaks," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 616-630.
    6. Geweke, John F. & Horowitz, Joel L. & Pesaran, M. Hashem, 2006. "Econometrics: A Bird's Eye View," IZA Discussion Papers 2458, Institute of Labor Economics (IZA).
    7. Petros Dellaportas & David G. T. Denison & Chris Holmes, 2007. "Flexible Threshold Models for Modelling Interest Rate Volatility," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 419-437.
    8. Ravazzolo, F. & van Dijk, D.J.C. & Paap, R. & Franses, Ph.H.B.F., 2006. "Bayesian Model Averaging in the Presence of Structural Breaks," Econometric Institute Research Papers EI 2006-33, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    9. Jaehee Kim & Sooyoung Cheon, 2010. "Bayesian multiple change-point estimation with annealing stochastic approximation Monte Carlo," Computational Statistics, Springer, vol. 25(2), pages 215-239, June.

  80. Gary Koop & Dale Poirier & Justin Tobias, 2003. "Bayesian Semiparametric Inference in Multiple Equation Models," Discussion Papers in Economics 04/17, Division of Economics, School of Business, University of Leicester.

    Cited by:

    1. Marianna Belloc & Ugo Pagano, 2009. "Politics-Business Interaction Paths," CESifo Working Paper Series 2883, CESifo.

  81. Carmen Fernandez & Gary Koop & Mark F J Steel, 2003. "Alternative efficiency measures for multiple-output production," Edinburgh School of Economics Discussion Paper Series 65, Edinburgh School of Economics, University of Edinburgh.

    Cited by:

    1. Holtkamp, A.M. & Brummer, B., 2018. "Environmental efficiency of smallholder rubber production," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277518, International Association of Agricultural Economists.
    2. Walheer, Barnabé & Zhang, Linjia, 2018. "Profit Luenberger and Malmquist-Luenberger indexes for multi-activity decision making units: the case of the star-rated hotel industry in China," RIEI Working Papers 2018-06, Xi'an Jiaotong-Liverpool University, Research Institute for Economic Integration.
    3. Patricia Tecles & Benjamin M. Tabak, 2010. "Determinants of Bank Efficiency: the Case of Brazil," Working Papers Series 210, Central Bank of Brazil, Research Department.
    4. Malikov, Emir, 2016. "Estimating Multi-Product Production Functions and Productivity using Control Functions," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235108, Agricultural and Applied Economics Association.
    5. Guohua Feng & Chuan Wang & Apostolos Serletis, 2018. "Shadow prices of $$\hbox {CO}_{2}$$ CO 2 emissions at US electric utilities: a random-coefficient, random-directional-vector directional output distance function approach," Empirical Economics, Springer, vol. 54(1), pages 231-258, February.
    6. Tsionas, Efthymios & Assaf, A. George & Gillen, David & Mattila, Anna S., 2017. "Modeling technical and service efficiency," Transportation Research Part B: Methodological, Elsevier, vol. 96(C), pages 113-125.
    7. Ferreira, Jose T.A.S. & Steel, Mark F.J., 2007. "Model comparison of coordinate-free multivariate skewed distributions with an application to stochastic frontiers," Journal of Econometrics, Elsevier, vol. 137(2), pages 641-673, April.
    8. K Hervé Dakpo, 2016. "On modeling pollution-generating technologies: a new formulation of the by-production approach," Working Papers SMART 16-06, INRAE UMR SMART.
    9. Alphonse Singbo & Bruno Larue, 2016. "Scale Economies, Technical Efficiency, and the Sources of Total Factor Productivity Growth of Quebec Dairy Farms," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 64(2), pages 339-363, June.
    10. Luis Antonio Galiano Bastarrica & Eva M. Buitrago Esquinas & María Ángeles Caraballo Pou & Rocío Yñiguez Ovando, 2023. "Environmental adjustment of the EU27 GDP: an econometric quantitative model," Environment Systems and Decisions, Springer, vol. 43(1), pages 115-128, March.
    11. Kortelainen, Mika, 2008. "Estimation of semiparametric stochastic frontiers under shape constraints with application to pollution generating technologies," MPRA Paper 9257, University Library of Munich, Germany.
    12. Levent Kutlu, 2020. "Greenhouse Gas Emission Efficiencies of World Countries," IJERPH, MDPI, vol. 17(23), pages 1-11, November.
    13. Subal C. Kumbhakar & Emir Malikov, 2018. "Good modeling of bad outputs: editors’ introduction," Empirical Economics, Springer, vol. 54(1), pages 1-6, February.
    14. Anthony Glass & Karligash Kenjegalieva & Robin Sickles, 2013. "How efficiently do U.S. cities manage roadway congestion?," Journal of Productivity Analysis, Springer, vol. 40(3), pages 407-428, December.
    15. Koop G., 2002. "Comparing the Performance of Baseball Players: A Multiple-Output Approach," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 710-720, September.
    16. Kumbhakar, Subal C. & Tsionas, Efthymios G., 2016. "The good, the bad and the technology: Endogeneity in environmental production models," Journal of Econometrics, Elsevier, vol. 190(2), pages 315-327.
    17. Sickles, Robin C., 2005. "Panel estimators and the identification of firm-specific efficiency levels in parametric, semiparametric and nonparametric settings," Journal of Econometrics, Elsevier, vol. 126(2), pages 305-334, June.
    18. Emir Malikov & Raushan Bokusheva & Subal C. Kumbhakar, 2018. "A hedonic-output-index-based approach to modeling polluting technologies," Empirical Economics, Springer, vol. 54(1), pages 287-308, February.
    19. Areal, Francisco J & Tiffin, Richard & Balcombe, Kelvin, 2010. "Provision of an environmental output within a multi-output distance function approach," MPRA Paper 25051, University Library of Munich, Germany.
    20. Neophyta Empora & Theofanis Mamuneas, 2011. "The Effect of Emissions on U.S. State Total Factor Productivity Growth," Review of Economic Analysis, Digital Initiatives at the University of Waterloo Library, vol. 3(2), pages 149-172, October.
    21. Gbemay Singbo, Alphonse & Larue, Bruno, 2014. "Scale Economies and Technical Efficiency of Quebec Dairy Farms," Working Papers 182482, University of Laval, Center for Research on the Economics of the Environment, Agri-food, Transports and Energy (CREATE).
    22. Malikov, Emir & Kumbhakar, Subal C. & Tsionas, Efthymios G., 2015. "Bayesian Approach to Disentangling Technical and Environmental Productivity," MPRA Paper 64877, University Library of Munich, Germany.
    23. Collier, Trevor & Johnson, Andrew L. & Ruggiero, John, 2011. "Technical efficiency estimation with multiple inputs and multiple outputs using regression analysis," European Journal of Operational Research, Elsevier, vol. 208(2), pages 153-160, January.
    24. Gary Koop & Lise Tole, 2008. "What is the environmental performance of firms overseas? An empirical investigation of the global gold mining industry," Journal of Productivity Analysis, Springer, vol. 30(2), pages 129-143, October.
    25. Emir Malikov & Gudbrand Lien, 2021. "Proxy Variable Estimation of Multiproduct Production Functions," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(5), pages 1878-1902, October.
    26. Carta, Alessandro & Steel, Mark F.J., 2012. "Modelling multi-output stochastic frontiers using copulas," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3757-3773.
    27. Morakinyo Adetutu & Anthony Glass & Karligash Kenjegalieva & Robin Sickles, 2015. "The effects of efficiency and TFP growth on pollution in Europe: a multistage spatial analysis," Journal of Productivity Analysis, Springer, vol. 43(3), pages 307-326, June.
    28. Dakpo, K Hervé, 2016. "On modeling pollution-generating technologies: a new formulation of the by-production approach," Working Papers 245191, Institut National de la recherche Agronomique (INRA), Departement Sciences Sociales, Agriculture et Alimentation, Espace et Environnement (SAE2).
    29. Yu, Biying & Tian, Yaming & Zhang, Junyi, 2015. "A dynamic active energy demand management system for evaluating the effect of policy scheme on household energy consumption behavior," Energy, Elsevier, vol. 91(C), pages 491-506.
    30. de Mendonça, Mário Jorge Cardoso & Pereira, Amaro Olimpio & Bellido, Marlon Max H. & Medrano, Luis Alberto & Pessanha, José Francisco Moreira, 2023. "Service quality performance indicators for electricity distribution in Brazil," Utilities Policy, Elsevier, vol. 80(C).
    31. Atkinson, Scott E. & Tsionas, Mike G., 2016. "Directional distance functions: Optimal endogenous directions," Journal of Econometrics, Elsevier, vol. 190(2), pages 301-314.
    32. Pantelis Kalaitzidakis & Theofanis P. Mamuneas & Thanasis Stengos, 2018. "Greenhouse Emissions and Productivity Growth," JRFM, MDPI, vol. 11(3), pages 1-14, July.
    33. Lambarraa, Fatima, 2011. "Dynamic Efficiency Analysis of Spanish Outdoor and Greenhouse Horticulture Sector," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114408, European Association of Agricultural Economists.
    34. Neophyta Empora, 2017. "Air pollution spillovers and U.S. state productivity growth," University of Cyprus Working Papers in Economics 06-2017, University of Cyprus Department of Economics.
    35. Alphonse G. Singbo & Bruno Larue, 2014. "Scale Economies and Technical Efficiency of Quebec Dairy Farms," Cahiers de recherche CREATE 2014-7, CREATE.

  82. Gary Koop & Simon M. Potter, 2003. "Forecasting in large macroeconomic panels using Bayesian Model Averaging," Staff Reports 163, Federal Reserve Bank of New York.

    Cited by:

    1. Maurin, Laurent & Drechsel, Katja, 2008. "Flow of conjunctural information and forecast of euro area economic activity," Working Paper Series 925, European Central Bank.
    2. Luis F. Melo Velandia & Rubén A. Loaiza Maya & Mauricio Villamizar-Villegas, 2014. "Bayesian Combination for Inflation Forecasts: The Effects of a Prior Based on Central Banks’ Estimates," Borradores de Economia 853, Banco de la Republica de Colombia.
    3. David O. Cushman, 2012. "Mankiw vs. DeLong and Krugman on the CEA's Real GDP Forecasts in Early 2009: What Might a Time Series Econometrician Have Said?," Econ Journal Watch, Econ Journal Watch, vol. 9(3), pages 309-349, September.
    4. Li, Gang & Li, Yong, 2015. "Forecasting copper futures volatility under model uncertainty," Resources Policy, Elsevier, vol. 46(P2), pages 167-176.
    5. George Kapetanios & Vincent Labhard & Simon Price, 2006. "Forecasting Using Predictive Likelihood Model Averaging," Working Papers 567, Queen Mary University of London, School of Economics and Finance.
    6. Faust, Jon & Wright, Jonathan H., 2013. "Forecasting Inflation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 2-56, Elsevier.
    7. George Kapetanios & Vincent Labhard & Simon Price, 2007. "Forecast combination and the Bank of England’s suite of statistical forecasting models," Bank of England working papers 323, Bank of England.
    8. Jonathan H. Wright, 2003. "Bayesian Model Averaging and exchange rate forecasts," International Finance Discussion Papers 779, Board of Governors of the Federal Reserve System (U.S.).
    9. Jon Faust & Jonathan H. Wright, 2007. "Comparing Greenbook and Reduced Form Forecasts using a Large Realtime Dataset," NBER Working Papers 13397, National Bureau of Economic Research, Inc.
    10. Todd E. Clark & Michael W. McCracken, 2006. "Forecasting of small macroeconomic VARs in the presence of instabilities," Research Working Paper RWP 06-09, Federal Reserve Bank of Kansas City.
    11. George Kapetanios & Vincent Labhard & Simon Price, 2005. "Forecasting using Bayesian and information theoretic model averaging: an application to UK inflation," Bank of England working papers 268, Bank of England.
    12. Ando, Tomohiro & Tsay, Ruey, 2010. "Predictive likelihood for Bayesian model selection and averaging," International Journal of Forecasting, Elsevier, vol. 26(4), pages 744-763, October.
    13. Badi H. Baltagi, 2008. "Forecasting with panel data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(2), pages 153-173.
    14. Eliana González, 2010. "Bayesian Model Averaging. An Application to Forecast Inflation in Colombia," Borradores de Economia 7015, Banco de la Republica.
    15. João Valle e Azevedo & Inês Maria Gonçalves, 2015. "Macroeconomic Forecasting Starting from Survey Nowcasts," Working Papers w201502, Banco de Portugal, Economics and Research Department.
    16. Baltagi, Badi H., 2013. "Panel Data Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 995-1024, Elsevier.
    17. Chew Lian Chua & Sandy Suardi & Sarantis Tsiaplias, 2011. "Predicting Short-Term Interest Rates: Does Bayesian Model Averaging Provide Forecast Improvement?," Melbourne Institute Working Paper Series wp2011n01, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    18. Todd E. Clark & Michael W. McCracken, 2008. "Improving forecast accuracy by combining recursive and rolling forecasts," Working Papers 2008-028, Federal Reserve Bank of St. Louis.
    19. Clark, Todd E. & McCracken, Michael W., 2005. "The power of tests of predictive ability in the presence of structural breaks," Journal of Econometrics, Elsevier, vol. 124(1), pages 1-31, January.
    20. Reichlin, Lucrezia & Giannone, Domenico & De Mol, Christine, 2006. "Forecasting Using a Large Number of Predictors: Is Bayesian Regression a Valid Alternative to Principal Components?," CEPR Discussion Papers 5829, C.E.P.R. Discussion Papers.
    21. Chotikapanich, D. & Griffiths, W.E. & Rao, D.S.P., 2001. "Averaging Income Distributions," Department of Economics - Working Papers Series 798, The University of Melbourne.
    22. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    23. João Valle e Azevedo, 2013. "Macroeconomic Forecasting Using Low-Frequency Filters," Working Papers w201301, Banco de Portugal, Economics and Research Department.
    24. Wang, Xiaoqian & Hyndman, Rob J. & Li, Feng & Kang, Yanfei, 2023. "Forecast combinations: An over 50-year review," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1518-1547.
    25. Chua, Chew Lian & Suardi, Sandy & Tsiaplias, Sarantis, 2013. "Predicting short-term interest rates using Bayesian model averaging: Evidence from weekly and high frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 442-455.
    26. John Galbraith & Greg Tkacz, 2007. "How Far Can Forecasting Models Forecast? Forecast Content Horizons for Some Important Macroeconomic Variables," Staff Working Papers 07-1, Bank of Canada.
    27. Taha Zaghdoudi, 2016. "Banking Crisis Early Warning Model based on a Bayesian Model Averaging Approach," Acta Universitatis Danubius. OEconomica, Danubius University of Galati, issue 12(4), pages 275-288, October.
    28. Luis Fernando Melo & Rubén Albeiro Loaiza Maya, 2012. "Bayesian Forecast Combination for Inflation Using Rolling Windows: An Emerging Country Case," Borradores de Economia 9511, Banco de la Republica.
    29. Kilian, Lutz & Inoue, Atsushi, 2005. "How Useful is Bagging in Forecasting Economic Time Series? A Case Study of US CPI Inflation," CEPR Discussion Papers 5304, C.E.P.R. Discussion Papers.
    30. Matteo Luciani & Libero Monteforte, 2012. "Uncertainty and Heterogeneity in factor models forecasting," Working Papers 5, Department of the Treasury, Ministry of the Economy and of Finance.
    31. Alonso Fernández, Andrés Modesto & Bastos, Guadalupe & García-Martos, Carolina, 2017. "Electricity prices forecasting by averaging dynamic factor models," DES - Working Papers. Statistics and Econometrics. WS 24028, Universidad Carlos III de Madrid. Departamento de Estadística.
    32. Andrés M. Alonso & Guadalupe Bastos & Carolina García-Martos, 2016. "Electricity Price Forecasting by Averaging Dynamic Factor Models," Energies, MDPI, vol. 9(8), pages 1-21, July.
    33. Rumi Masih & A. Mansur M. Masih & Kilian Mie, 2010. "Model uncertainty and asset return predictability: an application of Bayesian model averaging," Applied Economics, Taylor & Francis Journals, vol. 42(15), pages 1963-1972.
    34. Yu-chin Chen & Kenneth Rogoff, 2006. "Are the Commodity Currencies an Exception to the Rule?," Working Papers UWEC-2006-28, University of Washington, Department of Economics, revised Mar 2012.
    35. Tevdovski, Dragan & Petrevski, Goran & Bogoev, Jane, 2016. "The effects of macroeconomic policies under fixed exchange rates: A Bayesian VAR analysis," MPRA Paper 73461, University Library of Munich, Germany, revised 21 Jun 2016.
    36. Jonathan H. Wright, 2003. "Forecasting U.S. inflation by Bayesian Model Averaging," International Finance Discussion Papers 780, Board of Governors of the Federal Reserve System (U.S.).
    37. Petrevski, Goran & Exterkate, Peter & Tevdovski, Dragan & Bogoev, Jane, 2015. "The transmission of foreign shocks to South Eastern European economies: A Bayesian VAR approach," Economic Systems, Elsevier, vol. 39(4), pages 632-643.
    38. Zaghdoudi, Taha, 2014. "Modèle d’alerte des crises bancaires basé sur une approche bayésienne [Banking crisis early warning model based on a bayesian model averaging approach]," MPRA Paper 69262, University Library of Munich, Germany.
    39. Garett Jones & W. Schneider, 2006. "Intelligence, Human Capital, and Economic Growth: A Bayesian Averaging of Classical Estimates (BACE) Approach," Journal of Economic Growth, Springer, vol. 11(1), pages 71-93, March.

  83. Carmen Fernandez & Mark F J Steel & Gary Koop, 2002. "Multiple-output production with undesirable output: An application to nitrogen surplus in agriculture," Edinburgh School of Economics Discussion Paper Series 34, Edinburgh School of Economics, University of Edinburgh.

    Cited by:

    1. Holtkamp, A.M. & Brummer, B., 2018. "Environmental efficiency of smallholder rubber production," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277518, International Association of Agricultural Economists.
    2. Mamardashvili, Phatima & Jan, Pierrick, 2014. "Environmentally harmful by-products in efficiency analysis: An example of nitrogen surplus on Swiss dairy farms," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182962, European Association of Agricultural Economists.
    3. William C. Horrace & Kurt E. Schnier, 2008. "Fixed-Effect Estimation of Highly-Mobile Production Technologies," Center for Policy Research Working Papers 87, Center for Policy Research, Maxwell School, Syracuse University.
    4. Walheer, Barnabé & Zhang, Linjia, 2018. "Profit Luenberger and Malmquist-Luenberger indexes for multi-activity decision making units: the case of the star-rated hotel industry in China," RIEI Working Papers 2018-06, Xi'an Jiaotong-Liverpool University, Research Institute for Economic Integration.
    5. Shiyi Chen & Wolfgang K. Härdle & Li Wang, 2020. "Estimation and determinants of Chinese banks’ total factor efficiency: a new vision based on unbalanced development of Chinese banks and their overall risk," Computational Statistics, Springer, vol. 35(2), pages 427-468, June.
    6. Malikov, Emir, 2016. "Estimating Multi-Product Production Functions and Productivity using Control Functions," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235108, Agricultural and Applied Economics Association.
    7. Alfonso Flores-Lagunes & William C. Horrace & Kurt E. Schnier, 2007. "Identifying technically efficient fishing vessels: a non-empty, minimal subset approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(4), pages 729-745.
    8. William Horrace & Seth Richards-Shubik, 2013. "Expected Efficiency Ranks From Parametric Stochastic Fronteir Models," Center for Policy Research Working Papers 153, Center for Policy Research, Maxwell School, Syracuse University.
    9. Khor, Ling Yee & Zeller, Manfred, 2012. "Doubts on input quality: The effect of inaccurate fertilizer content on the estimation of production functions and technical efficiency," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 126212, International Association of Agricultural Economists.
    10. Ho-chuan Huang, 2004. "Estimation of Technical Inefficiencies with Heterogeneous Technologies," Journal of Productivity Analysis, Springer, vol. 21(3), pages 277-296, May.
    11. Figge, Frank & Hahn, Tobias & Barkemeyer, Ralf, 2014. "The If, How and Where of assessing sustainable resource use," Ecological Economics, Elsevier, vol. 105(C), pages 274-283.
    12. Tateishi, Henrique Ryosuke & Bragagnolo, Cassiano & de Faria, Rosane Nunes, 2020. "Economic and environmental efficiencies of greenhouse gases’ emissions under institutional influence," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    13. Ball, E. & Fare, R. & Grosskopf, S. & Zaim, O., 2005. "Accounting for externalities in the measurement of productivity growth: the Malmquist cost productivity measure," Structural Change and Economic Dynamics, Elsevier, vol. 16(3), pages 374-394, September.
    14. Ferreira, Jose T.A.S. & Steel, Mark F.J., 2007. "Model comparison of coordinate-free multivariate skewed distributions with an application to stochastic frontiers," Journal of Econometrics, Elsevier, vol. 137(2), pages 641-673, April.
    15. Marconi, G. & Ritzen, J., 2014. "Money counts for a Times Higher Education top-rank," Research Memorandum 015, Maastricht University, Graduate School of Business and Economics (GSBE).
    16. K Hervé Dakpo, 2016. "On modeling pollution-generating technologies: a new formulation of the by-production approach," Working Papers SMART 16-06, INRAE UMR SMART.
    17. Alphonse Singbo & Bruno Larue, 2016. "Scale Economies, Technical Efficiency, and the Sources of Total Factor Productivity Growth of Quebec Dairy Farms," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 64(2), pages 339-363, June.
    18. Horrace, William C., 2005. "On ranking and selection from independent truncated normal distributions," Journal of Econometrics, Elsevier, vol. 126(2), pages 335-354, June.
    19. Kortelainen, Mika, 2008. "Estimation of semiparametric stochastic frontiers under shape constraints with application to pollution generating technologies," MPRA Paper 9257, University Library of Munich, Germany.
    20. Levent Kutlu, 2020. "Greenhouse Gas Emission Efficiencies of World Countries," IJERPH, MDPI, vol. 17(23), pages 1-11, November.
    21. Subal C. Kumbhakar & Emir Malikov, 2018. "Good modeling of bad outputs: editors’ introduction," Empirical Economics, Springer, vol. 54(1), pages 1-6, February.
    22. Koop G., 2002. "Comparing the Performance of Baseball Players: A Multiple-Output Approach," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 710-720, September.
    23. Jim Griffin & Mark Steel, 2005. "Bayesian Stochastic Frontier Analysis Using WinBUGS," Econometrics 0509004, University Library of Munich, Germany.
    24. Kumbhakar, Subal C. & Tsionas, Efthymios G., 2016. "The good, the bad and the technology: Endogeneity in environmental production models," Journal of Econometrics, Elsevier, vol. 190(2), pages 315-327.
    25. Stern, David I., 2004. "The Rise and Fall of the Environmental Kuznets Curve," World Development, Elsevier, vol. 32(8), pages 1419-1439, August.
    26. Benjamin Hampf, 2018. "Measuring inefficiency in the presence of bad outputs: Does the disposability assumption matter?," Empirical Economics, Springer, vol. 54(1), pages 101-127, February.
    27. Njuki, Eric & Bravo-Ureta, Boris, 2014. "A Bayesian Approach to Analyzing the Economic Costs of Environmental Regulation in U.S. Dairy Farming," Working Papers 33, University of Connecticut, Department of Agricultural and Resource Economics, Charles J. Zwick Center for Food and Resource Policy.
    28. Magambo, Isaiah & Dikgang, Johane & Gelo, Dambala & Tregenna, Fiona, 2021. "Environmental and Technical Efficiency in Large Gold Mines in Developing Countries," MPRA Paper 108068, University Library of Munich, Germany.
    29. Efthymios G. Tsionas, 2006. "Inference in dynamic stochastic frontier models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 669-676, July.
    30. Magambo, Isaiah Hubert & Dikgang, Johane & Gelo, Dambala & Tregenna, Fiona, 2021. "Dynamic Technical and Environmental Efficiency Performance of Large Gold Mines in Developing Countries," EconStor Preprints 235859, ZBW - Leibniz Information Centre for Economics.
    31. Emir Malikov & Raushan Bokusheva & Subal C. Kumbhakar, 2018. "A hedonic-output-index-based approach to modeling polluting technologies," Empirical Economics, Springer, vol. 54(1), pages 287-308, February.
    32. Gbemay Singbo, Alphonse & Larue, Bruno, 2014. "Scale Economies and Technical Efficiency of Quebec Dairy Farms," Working Papers 182482, University of Laval, Center for Research on the Economics of the Environment, Agri-food, Transports and Energy (CREATE).
    33. Malikov, Emir & Kumbhakar, Subal C. & Tsionas, Efthymios G., 2015. "Bayesian Approach to Disentangling Technical and Environmental Productivity," MPRA Paper 64877, University Library of Munich, Germany.
    34. Chien-Ming Chen & Magali A. Delmas, 2012. "Measuring Eco-Inefficiency: A New Frontier Approach," Operations Research, INFORMS, vol. 60(5), pages 1064-1079, October.
    35. Guohua Feng & Apostolos Serletis, "undated". "Undesirable Outputs and a Primal Divisia Productivity Index Based on the Directional Output Distance Function," Working Papers 2013-15, Department of Economics, University of Calgary.
    36. Assaf, A. George & Tsionas, Mike G., 2019. "A review of research into performance modeling in tourism research - Launching the Annals of Tourism Research curated collection on performance modeling in tourism research," Annals of Tourism Research, Elsevier, vol. 76(C), pages 266-277.
    37. Tsionas, Mike G., 2016. "Notes on technical efficiency estimation with multiple inputs and outputs," European Journal of Operational Research, Elsevier, vol. 249(2), pages 784-788.
    38. Carmen Fernandez & Gary Koop & Mark F J Steel, 2003. "Alternative efficiency measures for multiple-output production," Edinburgh School of Economics Discussion Paper Series 65, Edinburgh School of Economics, University of Edinburgh.
    39. Graham, Mary, 2008. "Biophysical Modelling and Performance Measurement," 2008 Conference (52nd), February 5-8, 2008, Canberra, Australia 6773, Australian Agricultural and Resource Economics Society.
    40. William C. Horrace & Seth O. Richards, 2007. "A Monte Carlo Study of Efficiency Estimates from Frontier Models," Center for Policy Research Working Papers 97, Center for Policy Research, Maxwell School, Syracuse University.
    41. Graham, Mary, 2009. "Developing a social perspective to farm performance analysis," Ecological Economics, Elsevier, vol. 68(8-9), pages 2390-2398, June.
    42. J. Griffin & M. Steel, 2008. "Flexible mixture modelling of stochastic frontiers," Journal of Productivity Analysis, Springer, vol. 29(1), pages 33-50, February.
    43. Gary Koop & Lise Tole, 2008. "What is the environmental performance of firms overseas? An empirical investigation of the global gold mining industry," Journal of Productivity Analysis, Springer, vol. 30(2), pages 129-143, October.
    44. Emir Malikov & Gudbrand Lien, 2021. "Proxy Variable Estimation of Multiproduct Production Functions," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(5), pages 1878-1902, October.
    45. Carta, Alessandro & Steel, Mark F.J., 2012. "Modelling multi-output stochastic frontiers using copulas," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3757-3773.
    46. Bhattacharyya, Aditi & Kutlu, Levent & Sickles, Robin C., 2018. "Pricing Inputs and Outputs: Market prices versus shadow prices, market power, and welfare analysis," Working Papers 18-009, Rice University, Department of Economics.
    47. Subal Kumbhakar & Raquel Ortega-Argilés & Lesley Potters & Marco Vivarelli & Peter Voigt, 2012. "Corporate R&D and firm efficiency: evidence from Europe’s top R&D investors," Journal of Productivity Analysis, Springer, vol. 37(2), pages 125-140, April.
    48. Riera, Félix Sebastián & Brümmer, Bernhard, 2022. "Environmental efficiency of wine grape production in Mendoza, Argentina," Agricultural Water Management, Elsevier, vol. 262(C).
    49. George Assaf, A. & Matousek, Roman & Tsionas, Efthymios G., 2013. "Turkish bank efficiency: Bayesian estimation with undesirable outputs," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 506-517.
    50. Dakpo, K Hervé, 2016. "On modeling pollution-generating technologies: a new formulation of the by-production approach," Working Papers 245191, Institut National de la recherche Agronomique (INRA), Departement Sciences Sociales, Agriculture et Alimentation, Espace et Environnement (SAE2).
    51. Lota D. Tamini & Bruno Larue & Gale West, 2012. "Technical and environmental efficiencies and best management practices in agriculture," Applied Economics, Taylor & Francis Journals, vol. 44(13), pages 1659-1672, May.
    52. Luis R. Murillo‐Zamorano, 2004. "Economic Efficiency and Frontier Techniques," Journal of Economic Surveys, Wiley Blackwell, vol. 18(1), pages 33-77, February.
    53. Khor, Ling Yee & Zeller, Manfred, 2014. "Inaccurate fertilizer content and its effect on the estimation of production functions," China Economic Review, Elsevier, vol. 30(C), pages 123-132.
    54. Huang, Wei & Bruemmer, Bernhard, 2017. "Balancing economic revenue and grazing pressure of livestock grazing on the Qinghai–Tibetan–Plateau," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 61(4), October.
    55. Fujii, Hidemichi & Managi, Shunsuke & Matousek, Roman, 2014. "Indian bank efficiency and productivity changes with undesirable outputs: A disaggregated approach," Journal of Banking & Finance, Elsevier, vol. 38(C), pages 41-50.
    56. Matousek, Roman & Rughoo, Aarti & Sarantis, Nicholas & George Assaf, A., 2015. "Bank performance and convergence during the financial crisis: Evidence from the ‘old’ European Union and Eurozone," Journal of Banking & Finance, Elsevier, vol. 52(C), pages 208-216.
    57. Hampf, Benjamin, 2015. "Estimating the materials balance condition: A stochastic frontier approach," Darmstadt Discussion Papers in Economics 226, Darmstadt University of Technology, Department of Law and Economics.
    58. Shiyi Chen & Wolfgang K. Härdle & Li Wang, 2014. "Estimation and Determinants of Chinese Banks’ Total Factor Efficiency: A New Vision Based on Unbalanced Development of Chinese Banks and Their Overall Risk," SFB 649 Discussion Papers SFB649DP2014-068, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    59. Lota D. Tamini & Bruno Larue & Gale E. West & Moise K.Ndegue Fongue, 2016. "Agricultural production and pollutant runoffs in QuŽbecÕs Chaudi re river watershed: what are the potential environmental gains?," Cahiers de recherche CREATE 2016-2, CREATE.
    60. Louhichi, Awatef & Boujelbene, Younes, 2020. "Credit risk pricing and the rationality of lending decision-making within dual banking systems: A parametric approach," Economic Systems, Elsevier, vol. 44(1).
    61. Alphonse G. Singbo & Bruno Larue, 2014. "Scale Economies and Technical Efficiency of Quebec Dairy Farms," Cahiers de recherche CREATE 2014-7, CREATE.
    62. Bokusheva, Raushan & Kumbhakar, Subal C., 2014. "A Distance Function Model with Good and Bad Outputs," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182765, European Association of Agricultural Economists.

  84. Gary Koop & Dale J Poirer, 2001. "Bayesian Variants of Some classical Semiparametric Regression Techniques," Edinburgh School of Economics Discussion Paper Series 73, Edinburgh School of Economics, University of Edinburgh.

    Cited by:

    1. Pholo Bala, Alain, 2009. "Urban concentration and economic growth: checking for specific regional effects," LIDAM Discussion Papers CORE 2009038, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Geweke, John & Keane, Michael, 2005. "Bayesian Cross-Sectional Analysis of the Conditional Distribution of Earnings of Men in the United States, 1967-1996: Appendices," MPRA Paper 54286, University Library of Munich, Germany.
    3. Abidoye, Babatunde Oluwakayode, 2010. "Bayesian inference in modeling recreation demand," ISU General Staff Papers 201001010800002496, Iowa State University, Department of Economics.
    4. Chen, Mei-ping & Lee, Chien-Chiang & Hsu, Yi-Chung, 2011. "The impact of American depositary receipts on the Japanese index: Do industry effect and size effect matter?," Economic Modelling, Elsevier, vol. 28(1), pages 526-539.
    5. Dorfman, Jeffrey H. & Patridge, Mark D. & Galloway, Hamilton, 2008. "Are High-Tech Employment and Natural Amenities Linked?: Answers from a Smoothed Bayesian Spatial Model," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6459, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    6. Gianni Amisano & Maria Letizia Giorgetti, 2005. "Entry in Pharmaceutical submarkets: A Bayesian Panel Probit Approach," Working Papers ubs0511, University of Brescia, Department of Economics.
    7. Junrong Liu & Robin C. Sickles & E. G. Tsionas, 2017. "Bayesian Treatments for Panel Data Stochastic Frontier Models with Time Varying Heterogeneity," Econometrics, MDPI, vol. 5(3), pages 1-21, July.
    8. Griffin, J. E. & Steel, M. F. J., 2004. "Semiparametric Bayesian inference for stochastic frontier models," Journal of Econometrics, Elsevier, vol. 123(1), pages 121-152, November.
    9. Scott E. Atkinson & Jeffrey H. Dorfman, 2009. "Feasible estimation of firm-specific allocative inefficiency through Bayesian numerical methods," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(4), pages 675-697.
    10. Li, Mingliang, 2009. "Is there "white flight" into private schools? New evidence from High School and Beyond," Economics of Education Review, Elsevier, vol. 28(3), pages 382-392, June.
    11. Huang, Ho-Chuan (River) & Lin, Shu-Chin, 2008. "Smooth-time-varying Okun's coefficients," Economic Modelling, Elsevier, vol. 25(2), pages 363-375, March.
    12. Myeong Jun Kim & Stanley I. M. Ko & Sung Y. Park, 2021. "On time and frequency-varying Okun’s coefficient: a new approach based on ensemble empirical mode decomposition," Empirical Economics, Springer, vol. 61(3), pages 1151-1188, September.
    13. Maria Letizia GIORGETTI & Maria Luisa MANCUSI, 2016. "Entry and Patenting in the Pharmaceutical Industry," Departmental Working Papers 2016-02, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    14. George Halkos & Mike G. Tsionas, 2019. "Accounting for Heterogeneity in Environmental Performance Using Data Envelopment Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 54(3), pages 1005-1025, October.
    15. Bacolod, Marigee P. & Tobias, Justin L., 2006. "Schools, school quality and achievement growth: Evidence from the Philippines," Economics of Education Review, Elsevier, vol. 25(6), pages 619-632, December.
    16. Koop, Gary M & Poirier, Dale J & Tobias, Justin, 2005. "Semiparametric Bayesian Inference in Multiple Equation Models," Staff General Research Papers Archive 12009, Iowa State University, Department of Economics.
    17. Tim Salimans, 2011. "Variable Selection and Functional Form Uncertainty in Cross-Country Growth Regressions," Tinbergen Institute Discussion Papers 11-012/4, Tinbergen Institute.
    18. Emmanuel Mamatzakis & Mike G. Tsionas, 2021. "Testing for persistence in US mutual funds’ performance: a Bayesian dynamic panel model," Annals of Operations Research, Springer, vol. 299(1), pages 1203-1233, April.
    19. Koop, Gary M & Tobias, Justin, 2006. "Semiparametric Bayesian Inference in Smooth Coefficient Models," Staff General Research Papers Archive 12202, Iowa State University, Department of Economics.
    20. Krisztin, Tamás, 2018. "Semi-parametric spatial autoregressive models in freight generation modeling," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 121-143.
    21. Brendan Kline & Justin L. Tobias, 2008. "The wages of BMI: Bayesian analysis of a skewed treatment-response model with nonparametric endogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(6), pages 767-793.
    22. Gary Koop & Simon Potter, 2010. "A flexible approach to parametric inference in nonlinear and time varying time series models," Post-Print hal-00732535, HAL.
    23. Emmanuel Mamatzakis & Mike Tsionas, 2018. "A Bayesian dynamic model to test persistence in funds' performance," Working Paper series 18-23, Rimini Centre for Economic Analysis.
    24. Agee, Mark D. & Atkinson, Scott E. & Crocker, Thomas D. & Williams, Jonathan W., 2014. "Non-separable pollution control: Implications for a CO2 emissions cap and trade system," Resource and Energy Economics, Elsevier, vol. 36(1), pages 64-82.
    25. Priya Ranjan & Justin L. Tobias, 2007. "Bayesian inference for the gravity model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(4), pages 817-838.
    26. Joshua C.C. Chan & Angelia L. Grant, 2014. "Fast Computation of the Deviance Information Criterion for Latent Variable Models," CAMA Working Papers 2014-09, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    27. Preciado Arreola, José Luis & Johnson, Andrew L. & Chen, Xun C. & Morita, Hiroshi, 2020. "Estimating stochastic production frontiers: A one-stage multivariate semiparametric Bayesian concave regression method," European Journal of Operational Research, Elsevier, vol. 287(2), pages 699-711.
    28. Murat K. Munkin, 2022. "Count Roy model with finite mixtures," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1160-1181, September.
    29. Brownlees Christian T. & Vannucci Marina, 2013. "A Bayesian approach for capturing daily heterogeneity in intra-daily durations time series," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(1), pages 21-46, February.
    30. Gianni Amisano & Maria Letizia Giorgetti, 2013. "Entry Into Pharmaceutical Submarkets: A Bayesian Panel Probit Analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(4), pages 667-701, June.
    31. Brownstone, David, 2001. "Discrete Choice Modeling for Transportation," University of California Transportation Center, Working Papers qt29v7d1pk, University of California Transportation Center.
    32. Bacolod, Marigee & Tobias, Justin, 2005. "Schools, School Quality and Academic Achievement: Evidence from the Philippines," Staff General Research Papers Archive 12249, Iowa State University, Department of Economics.
    33. Panayotis Michaelides & Mike Tsionas & Panos Xidonas, 2020. "A Bayesian Signals Approach for the Detection of Crises," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(3), pages 551-585, September.
    34. Geweke, John & Keane, Michael, 2005. "Bayesian Cross-Sectional Analysis of the Conditional Distribution of Earnings of Men in the United States, 1967-1996," MPRA Paper 54281, University Library of Munich, Germany.
    35. Zheng, Xiaoyong, 2008. "Semiparametric Bayesian estimation of mixed count regression models," Economics Letters, Elsevier, vol. 100(3), pages 435-438, September.
    36. Panagiotelis, Anastasios & Smith, Michael, 2008. "Bayesian identification, selection and estimation of semiparametric functions in high-dimensional additive models," Journal of Econometrics, Elsevier, vol. 143(2), pages 291-316, April.
    37. Huang, Ho-Chuan (River) & Lin, Shu-Chin, 2007. "Semiparametric Bayesian inference of the Kuznets hypothesis," Journal of Development Economics, Elsevier, vol. 83(2), pages 491-505, July.

  85. Gary Koop, 2001. "Modeling the Evolution of Distributions: An Application to Major League Baseball," Edinburgh School of Economics Discussion Paper Series 71, Edinburgh School of Economics, University of Edinburgh.

    Cited by:

    1. Jeroen Schokkaert & Johan Swinnen, 2016. "Uncertainty of Outcome Is Higher in the Champions League Than in the European Cup," Journal of Sports Economics, , vol. 17(2), pages 115-147, February.
    2. Richard Evans, 2014. "A review of measures of competitive balance in the ‘analysis of competitive balance’ literature," Birkbeck Sports Business Centre Working Papers 9, Birkbeck College, Department of Management.
    3. Hamrick Jeff & Rasp John, 2011. "Using Local Correlation to Explain Success in Baseball," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 7(4), pages 1-29, October.
    4. Martin Schmidt, 2006. "On the evolution of competition: an application of nonlinear tests," Applied Economics, Taylor & Francis Journals, vol. 38(1), pages 1-12.

  86. Gary Koop, 2001. "Comparing the Performance of Baseball Players: A Multiple Output Approach," Edinburgh School of Economics Discussion Paper Series 72, Edinburgh School of Economics, University of Edinburgh.

    Cited by:

    1. Amar Oukil & Srikrishna Madhumohan Govindaluri, 2017. "A systematic approach for ranking football players within an integrated DEA‐OWA framework," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 38(8), pages 1125-1136, December.
    2. Carlos Pestana Barros & Nicolas Peypoch & Scott Tainsky, 2014. "Cost efficiency of French soccer league teams," Applied Economics, Taylor & Francis Journals, vol. 46(8), pages 781-789, March.
    3. Carlos Pestana Barros & Peter Wanke & Otávio Figueiredo, 2015. "The Brazilian Soccer Championship: an efficiency analysis," Applied Economics, Taylor & Francis Journals, vol. 47(9), pages 906-915, February.
    4. Chih-Tung Hsiao & Hui-Ling Peng & Hui-Hua Huang, 2012. "The impact of sports ethics of professional baseball player to the development of sports industry in Taiwan," Quality & Quantity: International Journal of Methodology, Springer, vol. 46(6), pages 1753-1767, October.
    5. Guohua Feng & Todd Jewell, 2021. "Productivity and efficiency at english football clubs: a random coefficient approach," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(5), pages 571-604, November.
    6. Luis R. Murillo‐Zamorano, 2004. "Economic Efficiency and Frontier Techniques," Journal of Economic Surveys, Wiley Blackwell, vol. 18(1), pages 33-77, February.

  87. Gary Koop & Simon M. Potter, 2000. "Bayesian Analysis of Endogenous Delay Threshold Models," Edinburgh School of Economics Discussion Paper Series 11, Edinburgh School of Economics, University of Edinburgh.

    Cited by:

    1. Tomas Konecny & Oxana Babecka-Kucharcukova, 2016. "Credit Spreads and the Links between the Financial and Real Sectors in a Small Open Economy: The Case of the Czech Republic," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(4), pages 302-321, August.
    2. Gary Koop & Simon M. Potter, 2009. "Prior Elicitation In Multiple Change-Point Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 50(3), pages 751-772, August.
    3. Franta, Michal, 2021. "The Likelihood Of Effective Lower Bound Events," Macroeconomic Dynamics, Cambridge University Press, vol. 25(8), pages 2058-2079, December.
    4. Gordon, S. & Belanger, G., 1995. "Echantillonnage de Gibbs et autres application econometriques des chaines merkoviennes," Papers 9509, Laval - Recherche en Politique Economique.
    5. Rodney W. Strachan & Herman K. Van Dijk, 2013. "Evidence On Features Of A Dsge Business Cycle Model From Bayesian Model Averaging," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 54(1), pages 385-402, February.
    6. Anthony Garratt & Gary Koop & Shaun P. Vahey, 2008. "Forecasting Substantial Data Revisions in the Presence of Model Uncertainty," Economic Journal, Royal Economic Society, vol. 118(530), pages 1128-1144, July.
    7. Michael ARTIS & Ana Beatriz C. GALVÃO & Massimiliano MARCELLINO, 2003. "The transmission mechanism in a changing world," Economics Working Papers ECO2003/18, European University Institute.
    8. Polemis, Michael & Stengos, Thanasis, 2017. "Does Competition Prevent Industrial Pollution? Evidence from a Panel Threshold Model," MPRA Paper 85177, University Library of Munich, Germany.
    9. Jaehee Kim & Chulwoo Jeong, 2016. "A Bayesian multiple structural change regression model with autocorrelated errors," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(9), pages 1690-1705, July.
    10. Minxian Yang, 2014. "Normality of Posterior Distribution Under Misspecification and Nonsmoothness, and Bayes Factor for Davies' Problem," Econometric Reviews, Taylor & Francis Journals, vol. 33(1-4), pages 305-336, June.
    11. Michal Franta, 2015. "Rare Shocks vs. Non-linearities: What Drives Extreme Events in the Economy? Some Empirical Evidence," Working Papers 2015/04, Czech National Bank.
    12. Michal Franta, 2013. "The Effect of Non-Linearity Between Credit Conditions and Economic Activity on Density Forecasts," Working Papers 2013/09, Czech National Bank.
    13. Knight John & Satchell Stephen, 2011. "Some New Results for Threshold AR(1) Models," Journal of Time Series Econometrics, De Gruyter, vol. 3(2), pages 1-42, April.
    14. Jean-Marc Le Caillec, 2021. "Threshold autoregressive model blind identification based on array clustering," Post-Print hal-03210735, HAL.
    15. Yuzhi Cai & Guodong Li, 2018. "A novel approach to modelling the distribution of financial returns," Working Papers 2018-22, Swansea University, School of Management.
    16. Giannikis, D. & Vrontos, I.D. & Dellaportas, P., 2008. "Modelling nonlinearities and heavy tails via threshold normal mixture GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1549-1571, January.

  88. Gary Koop & Simon Potter, 2000. "The Vector Floor and Ceiling Model," Discussion Papers in Economics 04/15, Division of Economics, School of Business, University of Leicester.

    Cited by:

    1. Koop, Gary & Korobilis, Dimitris, 2010. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(4), pages 267-358, July.
    2. Gefang Deborah & Strachan Rodney, 2009. "Nonlinear Impacts of International Business Cycles on the U.K. -- A Bayesian Smooth Transition VAR Approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(1), pages 1-33, December.
    3. Meriam BouAli & Adnen Ben Nasr & Abdelwahed Trabelsi, 2016. "A Nonlinear Approach for Modeling and Forecasting US Business Cycles," International Economic Journal, Taylor & Francis Journals, vol. 30(1), pages 39-74, March.

  89. Carmen Fernandez & Gary Koop & Mark F J Steel, 1999. "A Bayesian analysis of multiple-output production frontier," Edinburgh School of Economics Discussion Paper Series 21, Edinburgh School of Economics, University of Edinburgh.

    Cited by:

    1. Gstach, Dieter, 2005. "Estimating output targets to evaluate output-specific efficiencies: A statistical framework," European Journal of Operational Research, Elsevier, vol. 161(2), pages 564-578, March.
    2. C.J. O’Donnell & K. Nguyen, 2011. "An Econometric Approach To Estimating Support Prices And Measures Of Productivity Change In Public Hospitals," CEPA Working Papers Series WP032011, School of Economics, University of Queensland, Australia.
    3. Lise Tole & Gary Koop, 2011. "Estimating the Impact on Efficiency of the Adoption of a Voluntary Environmental Standard: An Empirical Study of the Global Copper Mining Industry," Working Papers 11-36, University of Strathclyde Business School, Department of Economics.
    4. Arne Henningsen & Matěj Bělín & Géraldine Henningsen, 2017. "New insights into the stochastic ray production frontier," IFRO Working Paper 2017/01, University of Copenhagen, Department of Food and Resource Economics.
    5. Walheer, Barnabé & Zhang, Linjia, 2018. "Profit Luenberger and Malmquist-Luenberger indexes for multi-activity decision making units: the case of the star-rated hotel industry in China," RIEI Working Papers 2018-06, Xi'an Jiaotong-Liverpool University, Research Institute for Economic Integration.
    6. Patricia Tecles & Benjamin M. Tabak, 2010. "Determinants of Bank Efficiency: the Case of Brazil," Working Papers Series 210, Central Bank of Brazil, Research Department.
    7. Malikov, Emir, 2016. "Estimating Multi-Product Production Functions and Productivity using Control Functions," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235108, Agricultural and Applied Economics Association.
    8. Robertson R. B. Khataza & Atakelty Hailu & Marit E. Kragt & Graeme J. Doole, 2017. "Estimating shadow price for symbiotic nitrogen and technical efficiency for legume-based conservation agriculture in Malawi," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 61(3), pages 462-480, July.
    9. Areal, Francisco J. & Jones, Philip J. & Mortimer, Simon R. & Wilson, Paul, 2018. "Measuring sustainable intensification: Combining composite indicators and efficiency analysis to account for positive externalities in cereal production," Land Use Policy, Elsevier, vol. 75(C), pages 314-326.
    10. Tsionas, Efthymios & Assaf, A. George & Gillen, David & Mattila, Anna S., 2017. "Modeling technical and service efficiency," Transportation Research Part B: Methodological, Elsevier, vol. 96(C), pages 113-125.
    11. Ferreira, Jose T.A.S. & Steel, Mark F.J., 2007. "Model comparison of coordinate-free multivariate skewed distributions with an application to stochastic frontiers," Journal of Econometrics, Elsevier, vol. 137(2), pages 641-673, April.
    12. Marconi, G. & Ritzen, J., 2014. "Money counts for a Times Higher Education top-rank," Research Memorandum 015, Maastricht University, Graduate School of Business and Economics (GSBE).
    13. Francisco José Areal & Kelvin Balcombe & Richard Tiffin, 2012. "Integrating spatial dependence into Stochastic Frontier Analysis," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 56(4), pages 521-541, October.
    14. Koop G., 2002. "Comparing the Performance of Baseball Players: A Multiple-Output Approach," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 710-720, September.
    15. Jesús Peiró-Palomino & Anabel Forte Deltell, 2013. "Does social capital matter for European regional growth?," Working Papers 2013/02, Economics Department, Universitat Jaume I, Castellón (Spain).
    16. Khataza, Robertson R.B. & Hailu, Atakelty & Kragt, Marit E. & Doole, Graeme, 2017. "The opportunity costs of enhancing legume‐based sustainable agricultural intensification practices in Malawi," 2017 Conference (61st), February 7-10, 2017, Brisbane, Australia 258672, Australian Agricultural and Resource Economics Society.
    17. Efthymios G. Tsionas, 2006. "Inference in dynamic stochastic frontier models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 669-676, July.
    18. C.J. O’Donnell, 2011. "Econometric Estimation of Distance Functions and Associated Measures of Productivity and Efficiency Change," CEPA Working Papers Series WP012011, School of Economics, University of Queensland, Australia.
    19. Jianxu Liu & Mengjiao Wang & Ji Ma & Sanzidur Rahman & Songsak Sriboonchitta, 2020. "A Simultaneous Stochastic Frontier Model with Dependent Error Components and Dependent Composite Errors: An Application to Chinese Banking Industry," Mathematics, MDPI, vol. 8(2), pages 1-23, February.
    20. Mamardashvili, Phatima & Bokusheva, Raushan & Schmid, Dierk, 2014. "Heterogeneous Farm Output and Technical Efficiency Estimates," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 63(01), pages 1-15, March.
    21. Areal, Francisco J & Tiffin, Richard & Balcombe, Kelvin, 2010. "Provision of an environmental output within a multi-output distance function approach," MPRA Paper 25051, University Library of Munich, Germany.
    22. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
    23. Goto, Mika & Makhija, Anil K., 2007. "The Impact of Competition and Corporate Structure on Productive Efficiency: The Case of the U.S. Electric Utility Industry, 1990-2004," Working Paper Series 2007-10, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    24. Carmen Fernandez & Gary Koop & Mark F J Steel, 2003. "Alternative efficiency measures for multiple-output production," Edinburgh School of Economics Discussion Paper Series 65, Edinburgh School of Economics, University of Edinburgh.
    25. Mike Tsionas & Christopher F. Parmeter & Valentin Zelenyuk, 2021. "Bridging the Divide? Bayesian Artificial Neural Networks for Frontier Efficiency Analysis," CEPA Working Papers Series WP082021, School of Economics, University of Queensland, Australia.
    26. Gary Koop & Lise Tole, 2008. "What is the environmental performance of firms overseas? An empirical investigation of the global gold mining industry," Journal of Productivity Analysis, Springer, vol. 30(2), pages 129-143, October.
    27. Areal, Francisco Jose & Balcombe, Kelvin & Tiffin, Richard, 2012. "Integrated spatial dependence into Stochastic Frontier Analysis," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 56(4), pages 1-21, December.
    28. Emir Malikov & Gudbrand Lien, 2021. "Proxy Variable Estimation of Multiproduct Production Functions," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(5), pages 1878-1902, October.
    29. Carta, Alessandro & Steel, Mark F.J., 2012. "Modelling multi-output stochastic frontiers using copulas," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3757-3773.
    30. Kumbhakar, Subal C. & Tsionas, Efthymios G., 2005. "Measuring technical and allocative inefficiency in the translog cost system: a Bayesian approach," Journal of Econometrics, Elsevier, vol. 126(2), pages 355-384, June.
    31. Lota D. Tamini & Bruno Larue & Gale West, 2012. "Technical and environmental efficiencies and best management practices in agriculture," Applied Economics, Taylor & Francis Journals, vol. 44(13), pages 1659-1672, May.
    32. Luis R. Murillo‐Zamorano, 2004. "Economic Efficiency and Frontier Techniques," Journal of Economic Surveys, Wiley Blackwell, vol. 18(1), pages 33-77, February.
    33. de Mendonça, Mário Jorge Cardoso & Pereira, Amaro Olimpio & Bellido, Marlon Max H. & Medrano, Luis Alberto & Pessanha, José Francisco Moreira, 2023. "Service quality performance indicators for electricity distribution in Brazil," Utilities Policy, Elsevier, vol. 80(C).
    34. Lota D. Tamini & Bruno Larue & Gale E. West & Moise K.Ndegue Fongue, 2016. "Agricultural production and pollutant runoffs in QuŽbecÕs Chaudi re river watershed: what are the potential environmental gains?," Cahiers de recherche CREATE 2016-2, CREATE.

  90. Gary Koop & Simon M. Potter, 1999. "Are apparent findings of nonlinearity due to structural instability in economic time series?," Staff Reports 59, Federal Reserve Bank of New York.

    Cited by:

    1. Thomas Barnay & Olivier Damette, 2012. "What drives Health Care Expenditure in France since 1950?," Working Papers hal-00717435, HAL.
    2. Geweke, John & Jiang, Yu, 2011. "Inference and prediction in a multiple-structural-break model," Journal of Econometrics, Elsevier, vol. 163(2), pages 172-185, August.
    3. Markus Jochmann, 2015. "Modeling U.S. Inflation Dynamics: A Bayesian Nonparametric Approach," Econometric Reviews, Taylor & Francis Journals, vol. 34(5), pages 537-558, May.
    4. Carrasco, Marine, 2002. "Misspecified Structural Change, Threshold, and Markov-switching models," Journal of Econometrics, Elsevier, vol. 109(2), pages 239-273, August.
    5. Gary Koop & Simon M. Potter, 2009. "Prior Elicitation In Multiple Change-Point Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 50(3), pages 751-772, August.
    6. Maslyuk, Svetlana & Smyth, Russell, 2009. "Non-linear unit root properties of crude oil production," Energy Economics, Elsevier, vol. 31(1), pages 109-118, January.
    7. John M. Maheu & Stephen Gordon, 2004. "Learning, Forecasting and Structural Breaks," Cahiers de recherche 0422, CIRPEE.
    8. Dilip Kumar, 2020. "Value-at-Risk in the Presence of Structural Breaks Using Unbiased Extreme Value Volatility Estimator," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(3), pages 587-610, September.
    9. Anthony Garratt & Gary Koop & Shaun P. Vahey, 2008. "Forecasting Substantial Data Revisions in the Presence of Model Uncertainty," Economic Journal, Royal Economic Society, vol. 118(530), pages 1128-1144, July.
    10. Couharde, Cécile & Coulibaly, Issiaka & Damette, Olivier, 2013. "Anchor currency and real exchange rate dynamics in the CFA Franc zone," Economic Modelling, Elsevier, vol. 33(C), pages 722-732.
    11. Jochmann, Markus & Koop, Gary & Strachan, Rodney W., 2010. "Bayesian forecasting using stochastic search variable selection in a VAR subject to breaks," International Journal of Forecasting, Elsevier, vol. 26(2), pages 326-347, April.
    12. Gary Koop & Simon M. Potter, 2004. "Forecasting and estimating multiple change-point models with an unknown number of change points," Staff Reports 196, Federal Reserve Bank of New York.
    13. Herrerias, M.J. & Ordóñez, J., 2014. "If the United States sneezes, does the world need “pain-killers”?," International Review of Economics & Finance, Elsevier, vol. 31(C), pages 159-170.
    14. Polemis, Michael & Stengos, Thanasis, 2017. "Does Competition Prevent Industrial Pollution? Evidence from a Panel Threshold Model," MPRA Paper 85177, University Library of Munich, Germany.
    15. Francesco Battaglia & Mattheos K. Protopapas, 2010. "Multi-regime models for nonlinear nonstationary time series," Working Papers 026, COMISEF.
    16. Haug Alfred A & Beyer Andreas & Dewald William, 2011. "Structural Breaks and the Fisher Effect," The B.E. Journal of Macroeconomics, De Gruyter, vol. 11(1), pages 1-31, May.
    17. Toshitaka Sekine, 2006. "Time-varying exchange rate pass-through: experiences of some industrial countries," BIS Working Papers 202, Bank for International Settlements.
    18. Smallwood Aaron D, 2005. "Joint Tests for Non-linearity and Long Memory: The Case of Purchasing Power Parity," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(2), pages 1-30, June.
    19. Marian Vavra, 2013. "Testing for non-linearity in multivariate stochastic processes," Working and Discussion Papers WP 2/2013, Research Department, National Bank of Slovakia.
    20. Jacek Kwiatkowski, 2008. "Bayesian Analysis of Polish Inflation Rates Using RCA and GLL Models," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 8, pages 129-138.
    21. Thomas Barnay & Olivier Damette, 2012. "What drives Health Care Expenditure in France since 1950? A time-series study with structural breaks and nonlinearity approaches," Working Papers halshs-00856117, HAL.
    22. Francesco Battaglia & Mattheos Protopapas, 2012. "Multi–regime models for nonlinear nonstationary time series," Computational Statistics, Springer, vol. 27(2), pages 319-341, June.
    23. Beyer, Andreas & Dewald, William G. & Haug, Alfred A., 2009. "Structural breaks, cointegration and the Fisher effect," Working Paper Series 1013, European Central Bank.
    24. Luis A. Gil-Alana & Guglielmo M. Caporale, 2008. "Modelling the US, the UK and Japanese unemployment rates. Fractional integrationand structural breaks," Faculty Working Papers 11/08, School of Economics and Business Administration, University of Navarra.
    25. Dalu Zhang & Peter Moffatt, 2013. "Time series non-linearity in the real growth / recession-term spread relationship," University of East Anglia Applied and Financial Economics Working Paper Series 047, School of Economics, University of East Anglia, Norwich, UK..
    26. Pesaran, M.H. & Pettenuzzo, D. & Timmermann, A., 2004. "‘Forecasting Time Series Subject to Multiple Structural Breaks’," Cambridge Working Papers in Economics 0433, Faculty of Economics, University of Cambridge.
    27. Likai Chen & Ekaterina Smetanina & Wei Biao Wu, 2022. "Estimation of nonstationary nonparametric regression model with multiplicative structure [Income and wealth distribution in macroeconomics: A continuous-time approach]," The Econometrics Journal, Royal Economic Society, vol. 25(1), pages 176-214.
    28. Arghyrou, Michael G & Gregoriou, Andros & Kontonikas, Alexandros, 2007. "Do real interest rates converge? Evidence from the European Union," Cardiff Economics Working Papers E2007/26, Cardiff University, Cardiff Business School, Economics Section.
    29. Baharumshah, Ahmad Zubaidi & Soon, Siew-Voon & Boršič, Darja, 2013. "Real interest parity in Central and Eastern European countries: Evidence on integration into EU and the US markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 25(C), pages 163-180.
    30. Donayre, Luiggi & Panovska, Irina, 2016. "Nonlinearities in the U.S. wage Phillips curve," Journal of Macroeconomics, Elsevier, vol. 48(C), pages 19-43.
    31. Aaron Smallwood, 2004. "Joint Tests for Long Memory and Non-linearity: The Case of Purchasing Power Parity," Computing in Economics and Finance 2004 23, Society for Computational Economics.
    32. Zhou, Jian, 2016. "A high-frequency analysis of the interactions between REIT return and volatility," Economic Modelling, Elsevier, vol. 56(C), pages 102-108.
    33. Haug Alfred A & Siklos Pierre L, 2006. "The Behavior of Short-Term Interest Rates: International Evidence of Non-Linear Adjustment," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(4), pages 1-34, December.
    34. Alfred A. Haug & Pierre L. Siklos, 2002. "The Term Spread International Evidence of Non-Linear Adjustment," Working Papers 2002_08, York University, Department of Economics, revised Jul 2004.
    35. Khurshid M. Kiani & Prasad V. Bidarkota, 2004. "On Business Cycle Asymmetries in G7 Countries," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(3), pages 333-351, July.
    36. Maki Daiki, 2010. "Detection of Stationarity in Nonlinear Processes: A Comparison between Structural Breaks and Three-Regime TAR Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(4), pages 1-43, September.
    37. Gary Koop & Simon Potter, 2010. "A flexible approach to parametric inference in nonlinear and time varying time series models," Post-Print hal-00732535, HAL.
    38. Timo Teräsvirta, 2017. "Nonlinear models in macroeconometrics," CREATES Research Papers 2017-32, Department of Economics and Business Economics, Aarhus University.
    39. Daud Ali Aser & Esin Firuzan, 2022. "Improving Forecast Accuracy Using Combined Forecasts with Regard to Structural Breaks and ARCH Innovations," EKOIST Journal of Econometrics and Statistics, Istanbul University, Faculty of Economics, vol. 0(37), pages 1-25, December.
    40. KIANI, Khurshid M., 2007. "Business Cycle Asymmetries In Stock Returns: Robust Evidence," International Journal of Applied Econometrics and Quantitative Studies, Euro-American Association of Economic Development, vol. 4(2), pages 99-120.
    41. Lazzarini, S. G. & Madalozzo, R. C & Artes, R. & Siqueira, J. O., 2004. "Measuring trust: An experiment in Brazil," Insper Working Papers wpe_42, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    42. Steven M. Fazzari & James Morley & Irina B. Panovska, 2017. "When Do Discretionary Changes in Government Spending or Taxes Have Larger Effects?," Discussion Papers 2017-04, School of Economics, The University of New South Wales.
    43. Donayre, Luiggi & Panovska, Irina, 2018. "U.S. wage growth and nonlinearities: The roles of inflation and unemployment," Economic Modelling, Elsevier, vol. 68(C), pages 273-292.
    44. Khurshid M. Kiani, 2009. "Asymmetries in Macroeconomic Time Series in Eleven Asian Economies," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 8(1), pages 37-54, April.
    45. Ahmad Yamin & Donayre Luiggi, 2016. "Outliers and persistence in threshold autoregressive processes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(1), pages 37-56, February.
    46. Ana Beatriz C. Galvão, 2006. "Structural break threshold VARs for predicting US recessions using the spread," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(4), pages 463-487, May.
    47. Gary Koop & Simon M. Potter, 2007. "A flexible approach to parametric inference in nonlinear time series models," Staff Reports 285, Federal Reserve Bank of New York.
    48. Martin Boďa & Mariana Považanová, 2023. "How credible are Okun coefficients? The gap version of Okun’s law for G7 economies," Economic Change and Restructuring, Springer, vol. 56(3), pages 1467-1514, June.
    49. Jacek Kwiatkowski, 2010. "Unobserved Component Model for Forecasting Polish Inflation," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 10, pages 121-129.

  91. Gary Koop & Mark F J Steel, 1999. "Bayesian Analysis of Stochastic Frontier Models," Edinburgh School of Economics Discussion Paper Series 19, Edinburgh School of Economics, University of Edinburgh.

    Cited by:

    1. Feng, Guohua & Serletis, Apostolos, 2010. "Efficiency, technical change, and returns to scale in large US banks: Panel data evidence from an output distance function satisfying theoretical regularity," Journal of Banking & Finance, Elsevier, vol. 34(1), pages 127-138, January.
    2. Supawat Rungsuriyawiboon & Chris O'Donnell, 2004. "Curvature-Constrained Estimates of Technical Efficiency and Returns to Scale for U.S. Electric Utilities," CEPA Working Papers Series WP072004, School of Economics, University of Queensland, Australia.
    3. William Griffiths & Xiaohui Zhang & Xueyan Zhao, 2010. "A Stochastic Frontier Model for Discrete Ordinal Outcomes: A Health Production Function," Monash Econometrics and Business Statistics Working Papers 3/10, Monash University, Department of Econometrics and Business Statistics.
    4. Erniel B. Barrios & Rouselle F. Lavado, 2010. "Spatial Stochastic Frontier Models," Microeconomics Working Papers 23091, East Asian Bureau of Economic Research.
    5. Myungsup Kim & Yangseon Kim & Peter Schmidt, 2007. "On the Accuracy of Bootstrap Confidence Intervals for Efficiency Levels in Stochastic Frontier Models with Panel Data," Working Papers 0704, University of Crete, Department of Economics.
    6. C. Charles Okeahalam, 2006. "Production Efficiency in the South African Banking Sector: A Stochastic Analysis," International Review of Applied Economics, Taylor & Francis Journals, vol. 20(1), pages 103-123.
    7. O'Donnell, Christopher J. & Coelli, Timothy J., 2005. "A Bayesian approach to imposing curvature on distance functions," Journal of Econometrics, Elsevier, vol. 126(2), pages 493-523, June.
    8. William Greene, 2010. "A stochastic frontier model with correction for sample selection," Journal of Productivity Analysis, Springer, vol. 34(1), pages 15-24, August.
    9. William Griffiths, 2002. "A Gibbs’ Sampler for the Parameters of a Truncated Multivariate Normal Distribution," Department of Economics - Working Papers Series 856, The University of Melbourne.
    10. Kelvin_Balcombe & Dirk_Bezemer & Junior_Davis & Iain_Fraser, 2005. "Livelihoods and Farm Efficiency in Rural Georgia," Development and Comp Systems 0502005, University Library of Munich, Germany.

  92. Gary Koop, 1999. "Bayesian inference in models based on equilibrium search theory," Edinburgh School of Economics Discussion Paper Series 12, Edinburgh School of Economics, University of Edinburgh.

    Cited by:

    1. John W. Schindler, 2001. "Testing optimality in job search models," International Finance Discussion Papers 710, Board of Governors of the Federal Reserve System (U.S.).
    2. Mohsen Mehrara & Samaneh Seijani & Abbas Rezazadeh Karsalari, 2017. "Determinants of high-tech export in developing countries based on Bayesian model averaging," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 35(1), pages 199-215.
    3. Richard J. Boys & Peter J. Dolton & Neil R. Walker, 2007. "Adapting the optimal job search model for active labour market policy," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(3), pages 759-779, July.

  93. Koop, G. & van Dijk, H.K., 1999. "Testing for integration using evolving trend and seasonal models: A Bayesian approach," Econometric Institute Research Papers EI 9934/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Richard Kleijn & Herman K. van Dijk, 2006. "Bayes model averaging of cyclical decompositions in economic time series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(2), pages 191-212, March.
    2. Michiel D. de Pooter & René Segers & Herman K. van Dijk, 2006. "On the Practice of Bayesian Inference in Basic Economic Time Series Models using Gibbs Sampling," Tinbergen Institute Discussion Papers 06-076/4, Tinbergen Institute.
    3. Svend Hylleberg, 2006. "Seasonal Adjustment," Economics Working Papers 2006-04, Department of Economics and Business Economics, Aarhus University.
    4. Stefano Grassi & Tommaso Proietti, 2011. "Stochastic trends and seasonality in economic time series: new evidence from Bayesian stochastic model specification search," CREATES Research Papers 2011-30, Department of Economics and Business Economics, Aarhus University.
    5. Bauwens, L. & Bos, C.S. & van Dijk, H.K. & van Oest, R.D., 2003. "Adaptive radial-based direction sampling; Some flexible and robust Monte Carlo integration methods," Econometric Institute Research Papers EI 2003-22, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. Richard Kleijn & Herman K. van Dijk, 2001. "A Bayesian Analysis of the PPP Puzzle using an Unobserved Components Model," Tinbergen Institute Discussion Papers 01-105/4, Tinbergen Institute.
    7. Stefano Grassi & Tommaso Proietti, 2010. "Characterizing economic trends by Bayesian stochastic model specification search," EERI Research Paper Series EERI_RP_2010_25, Economics and Econometrics Research Institute (EERI), Brussels.
    8. Jacek Kwiatkowski, 2008. "Bayesian Analysis of Polish Inflation Rates Using RCA and GLL Models," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 8, pages 129-138.
    9. Philippe J. Deschamps, 2003. "Time-varying intercepts and equilibrium analysis: an extension of the dynamic almost ideal demand model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(2), pages 209-236.
    10. BAUWENS, Luc & BOS, Charles S. & VAN DIJK, Herman K., 1999. "Adaptive polar sampling with an application to a Bayes measure of value-at-risk," LIDAM Discussion Papers CORE 1999057, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    11. Charles S. Bos & Ronald J. Mahieu & Herman K. van Dijk, 2000. "Daily Exchange Rate Behaviour and Hedging of Currency Risk," Econometric Society World Congress 2000 Contributed Papers 0504, Econometric Society.
    12. Rodrigo Barbone Gonzalez & Joaquim Lima & Leonardo Marinho, 2015. "Countercyclical Capital Buffers: bayesian estimates and alternatives focusing on credit growth," Working Papers Series 384, Central Bank of Brazil, Research Department.
    13. Harvey, Andrew C. & Trimbur, Thomas M. & Van Dijk, Herman K., 2007. "Trends and cycles in economic time series: A Bayesian approach," Journal of Econometrics, Elsevier, vol. 140(2), pages 618-649, October.
    14. Thomas M. Trimbur, 2006. "Detrending economic time series: a Bayesian generalization of the Hodrick-Prescott filter," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(4), pages 247-273.
    15. D.S. Prasada Rao & Alicia Rambaldi & Howard Doran, 2008. "A Method to Construct World Tables of Purchasing Power Parities and Real Incomes Based on Multiple Benchmarks and Auxiliary Information: Analytical and Empirical Results," CEPA Working Papers Series WP052008, School of Economics, University of Queensland, Australia.
    16. Alicia N. Rambaldi & D.S. Prasada Rao & K. Renuka Ganegodage, 2009. "Spatial Autocorrelation and Extrapolation of Purchasing Power Parities. Modelling and Sensitivity Analysis," CEPA Working Papers Series WP012009, School of Economics, University of Queensland, Australia.
    17. Koop, Gary M & Tobias, Justin, 2006. "Semiparametric Bayesian Inference in Smooth Coefficient Models," Staff General Research Papers Archive 12202, Iowa State University, Department of Economics.
    18. de Pooter, M.D. & Ravazzolo, F. & Segers, R. & van Dijk, H.K., 2008. "Bayesian near-boundary analysis in basic macroeconomic time series models," Econometric Institute Research Papers EI 2008-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    19. de Pooter, M.D. & Segers, R. & van Dijk, H.K., 2006. "Gibbs sampling in econometric practice," Econometric Institute Research Papers EI 2006-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    20. Tommaso, Proietti & Stefano, Grassi, 2010. "Bayesian stochastic model specification search for seasonal and calendar effects," MPRA Paper 27305, University Library of Munich, Germany.
    21. Rodrigo Barbone Gonzalez & Joaquim Lima & Leonardo Marinho, 2015. "Business and Financial Cycles: an estimation of cycles’ length focusing on Macroprudential Policy," Working Papers Series 385, Central Bank of Brazil, Research Department.
    22. Harvey, A.C. & Trimbur, T.M. & van Dijk, H.K., 2004. "Bayes estimates of the cyclical component in twentieth centruy US gross domestic product," Econometric Institute Research Papers EI 2004-45, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  94. Gary Koop & Kai Li, 1998. "The valuation of IPO, SEO and Post-Chapter 11 firms: A Stochastic Frontier Approach," Edinburgh School of Economics Discussion Paper Series 13, Edinburgh School of Economics, University of Edinburgh.

    Cited by:

    1. Koop, Gary & Li, Kai, 2001. "The valuation of IPO and SEO firms," Journal of Empirical Finance, Elsevier, vol. 8(4), pages 375-401, September.

  95. Gary Koop & Simon M. Potter, 1998. "Dynamic asymmetries in US unemployment," Edinburgh School of Economics Discussion Paper Series 15, Edinburgh School of Economics, University of Edinburgh.

    Cited by:

    1. So, Beong Soo & Shin, Dong Wan, 2001. "An invariant sign test for random walks based on recursive median adjustment," Journal of Econometrics, Elsevier, vol. 102(2), pages 197-229, June.
    2. Li, Dong & Ling, Shiqing & Zakoïan, Jean-Michel, 2015. "Asymptotic inference in multiple-threshold double autoregressive models," Journal of Econometrics, Elsevier, vol. 189(2), pages 415-427.
    3. Philippe J. Deschamps, 2008. "Comparing smooth transition and Markov switching autoregressive models of US unemployment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(4), pages 435-462.
    4. Aaron D. Smallwood & Paul M. Beaumont, 2002. "An Asymptotic MLE Approach to Modelling Multiple Frequency GARMA Models," Computing in Economics and Finance 2002 285, Society for Computational Economics.
    5. Sibel Cengiz & Afsin Sahin, 2014. "Modelling nonlinear behavior of labor force participation rate by STAR: An application for Turkey," International Journal of Business and Economic Sciences Applied Research (IJBESAR), International Hellenic University (IHU), Kavala Campus, Greece (formerly Eastern Macedonia and Thrace Institute of Technology - EMaTTech), vol. 7(1), pages 113-127, April.
    6. Jean-Yves Pitarakis, 2004. "Model Selection Uncertainty and Detection of Threshold Effecs," Econometrics 0409013, University Library of Munich, Germany.
    7. van Dijk, D.J.C. & Terasvirta, T. & Franses, Ph.H.B.F., 2000. "Smooth transition autoregressive models - A survey of recent developments," Econometric Institute Research Papers EI 2000-23/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    8. Popp, Aaron & Zhang, Fang, 2016. "The macroeconomic effects of uncertainty shocks: The role of the financial channel," Journal of Economic Dynamics and Control, Elsevier, vol. 69(C), pages 319-349.
    9. Gunnar Bårdsen & Stan Hurn & Zoë McHugh, 2010. "Asymmetric unemployment rate dynamics in Australia," CREATES Research Papers 2010-02, Department of Economics and Business Economics, Aarhus University.
    10. Donayre Luiggi & Eo Yunjong & Morley James, 2018. "Improving likelihood-ratio-based confidence intervals for threshold parameters in finite samples," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(1), pages 1-11, February.
    11. Norman J. Morin & John M. Roberts, 1999. "Is hysteresis important for U.S. unemployment?," Finance and Economics Discussion Series 1999-56, Board of Governors of the Federal Reserve System (U.S.).
    12. Henry, O.T. & Summers, P.M., 2000. "Australian Economic Growth: Non-Linearities and Internaitonal Influences," Department of Economics - Working Papers Series 738, The University of Melbourne.
    13. Gonzalo, Jesus & Pitarakis, Jean-Yves, 2002. "Estimation and model selection based inference in single and multiple threshold models," Journal of Econometrics, Elsevier, vol. 110(2), pages 319-352, October.
    14. Kurmaş Akdoğan, 2017. "Unemployment hysteresis and structural change in Europe," Empirical Economics, Springer, vol. 53(4), pages 1415-1440, December.
    15. van Dijk, Dick & Franses, Philip Hans & Paap, Richard, 2002. "A nonlinear long memory model, with an application to US unemployment," Journal of Econometrics, Elsevier, vol. 110(2), pages 135-165, October.
    16. Wan Shin, Dong & Lee, Oesook, 2003. "An instrumental variable approach for tests of unit roots and seasonal unit roots in asymmetric time series models," Journal of Econometrics, Elsevier, vol. 115(1), pages 29-52, July.
    17. Mariam Camarero & Josep Lluís Carrion-i-Silvestre & Cecilio Tamarit, 2004. "Testing for hysteresis in unemployment in OECD countries. New evidence using stationarity panel tests with breaks†," Economic Working Papers at Centro de Estudios Andaluces 2004/40, Centro de Estudios Andaluces.
    18. Park, Soo Jung & Wan Shin, Dong & Uk Park, Byeong & Chul Kim, Woo & Oh, Man-Suk, 2005. "Bayesian test for asymmetry and nonstationarity in MTAR model with possibly incomplete data," Computational Statistics & Data Analysis, Elsevier, vol. 49(4), pages 1192-1204, June.
    19. Michele Campolieti & Deborah Gefang & Gary Koop, 2011. "Time Variation in the Dynamics of Worker Flows: Evidence from the US and Canada," Working Papers 1138, University of Strathclyde Business School, Department of Economics.
    20. Anthony Garratt & Gary Koop & Shaun P. Vahey, 2008. "Forecasting Substantial Data Revisions in the Presence of Model Uncertainty," Economic Journal, Royal Economic Society, vol. 118(530), pages 1128-1144, July.
    21. Pérez-Alonso Alicia & Di Sanzo Silvestro, 2010. "Unemployment and Hysteresis: A Nonlinear Unobserved Components Approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(1), pages 1-29, December.
    22. Li, Dong & Ling, Shiqing, 2012. "On the least squares estimation of multiple-regime threshold autoregressive models," Journal of Econometrics, Elsevier, vol. 167(1), pages 240-253.
    23. Gary Koop & Herman K. van Dijk & Henk Hoek, 1997. "Testing for Integration using Evolving Trend and Seasonals Models: A Bayesian Approach," Tinbergen Institute Discussion Papers 97-078/4, Tinbergen Institute.
    24. Francesco Angelini & Massimiliano Castellani & Simone Giannerini & Greta Goracci, 2023. "Testing for Threshold Effects in Presence of Heteroskedasticity and Measurement Error with an application to Italian Strikes," Papers 2308.00444, arXiv.org.
    25. Panagiotidis, Theodore & Pelloni, Gianluigi, 2007. "Nonlinearity In The Canadian And U.S. Labor Markets: Univariate And Multivariate Evidence From A Battery Of Tests," Macroeconomic Dynamics, Cambridge University Press, vol. 11(5), pages 613-637, November.
    26. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    27. Dong, A.X.D. & Chan, J.S.K., 2013. "Bayesian analysis of loss reserving using dynamic models with generalized beta distribution," Insurance: Mathematics and Economics, Elsevier, vol. 53(2), pages 355-365.
    28. Lee, Oesook & Shin, Dong Wan, 2001. "A note on stationarity of the MTAR process on the boundary of the stationarity region," Economics Letters, Elsevier, vol. 73(3), pages 263-268, December.
    29. Theodore Panagiotidis, 2002. "Testing the assumption of Linearity," Economics Bulletin, AccessEcon, vol. 3(29), pages 1-9.
    30. Park, Soo Jung & Shin, Dong Wan, 2006. "A sign test for unit roots in a momentum threshold autoregressive process," Statistics & Probability Letters, Elsevier, vol. 76(10), pages 986-990, May.
    31. Terence D.Agbeyegbe & Elena Goldman, 2005. "Estimation of threshold time series models using efficient jump MCMC," Economics Working Paper Archive at Hunter College 406, Hunter College Department of Economics, revised 2005.
    32. Ulrich Woitek, 2004. "Real Wages and Business Cycle Asymmetries," CESifo Working Paper Series 1206, CESifo.
    33. Caporale, Guglielmo Maria & Gil-Alana, Luis A., 2004. "Non-linearities and fractional integration in the US unemployment rate," HWWA Discussion Papers 259, Hamburg Institute of International Economics (HWWA).
    34. Galbraith, John W. & van Norden, Simon, 2019. "Asymmetry in unemployment rate forecast errors," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1613-1626.
    35. Chavas, Jean-Paul & Mehta, Aashish, 2002. "Price Dynamics in a Vertical Sector: The Case of Butter," Staff Paper Series 452, University of Wisconsin, Agricultural and Applied Economics.
    36. Matthews, Kent & Minford, Patrick & Naraidoo, Ruthira, 2006. "Vicious and Virtuous Circles - The Political Economy of Unemployment in Interwar UK and USA," Cardiff Economics Working Papers E2006/25, Cardiff University, Cardiff Business School, Economics Section, revised Nov 2006.
    37. Singh, Tarlok, 2014. "On the regime-switching and asymmetric dynamics of economic growth in the OECD countries," Research in Economics, Elsevier, vol. 68(2), pages 169-192.
    38. Siliverstovs, B. & van Dijk, D.J.C., 2003. "Forecasting industrial production with linear, nonlinear, and structural change models," Econometric Institute Research Papers EI 2003-16, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    39. Michael Dueker & Martin Sola & Fabio Spagnolo, 2006. "Contemporaneous Threshold Autoregressive Models: Estimation, Testing and Forecasting," Department of Economics Working Papers 2006-04, Universidad Torcuato Di Tella.
    40. Baum, Anja & Koester, Gerrit B., 2011. "The impact of fiscal policy on economic activity over the business cycle - evidence from a threshold VAR analysis," Discussion Paper Series 1: Economic Studies 2011,03, Deutsche Bundesbank.
    41. Proietti, Tommaso, 2003. "Forecasting the US unemployment rate," Computational Statistics & Data Analysis, Elsevier, vol. 42(3), pages 451-476, March.
    42. Dong Li & Shiqing Ling & Jean-Michel Zakoian, 2013. "Asymptotic Inference in Multiple-Threshold Nonlinear Time Series Models," Working Papers 2013-51, Center for Research in Economics and Statistics.
    43. Strikholm, Birgit & Teräsvirta, Timo, 2005. "Determining the Number of Regimes in a Threshold Autoregressive Model Using Smooth Transition Autoregressions," SSE/EFI Working Paper Series in Economics and Finance 578, Stockholm School of Economics, revised 11 Feb 2005.
    44. D'Amuri, Francesco/FD & Marcucci, Juri/JM, 2009. ""Google it!" Forecasting the US unemployment rate with a Google job search index," MPRA Paper 18248, University Library of Munich, Germany.
    45. Ilias Georgakopoulos, 2019. "Income and wealth inequality in Malta: evidence from micro data," CBM Working Papers WP/03/2019, Central Bank of Malta.
    46. Gary Koop & Simon M. Potter, 2000. "Bayesian Analysis of Endogenous Delay Threshold Models," Edinburgh School of Economics Discussion Paper Series 11, Edinburgh School of Economics, University of Edinburgh.
    47. Penelope Smith, 2006. "Bayesian Inference for a Threshold Autoregression with a Unit Root," Melbourne Institute Working Paper Series wp2006n20, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    48. Neugart, Michael, 2004. "Complicated dynamics in a flow model of the labor market," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 57292, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    49. Yoon Young Jung & Dong Wan Shin & Man-Suk Oh, 2005. "Bayesian analysis of panel data using an MTAR model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 32(8), pages 841-854.
    50. McKay, Alisdair, 2006. "The Brevity and Violence of Contractions and Expansions," CEPR Discussion Papers 5756, C.E.P.R. Discussion Papers.
    51. Kenneth R. Szulczyk & Changyong Zhang, 2020. "Switching-regime regression for modeling and predicting a stock market return," Empirical Economics, Springer, vol. 59(5), pages 2385-2403, November.
    52. Cevik, Emrah Ismail & Dibooglu, Sel, 2013. "Persistence and non-linearity in US unemployment: A regime-switching approach," Economic Systems, Elsevier, vol. 37(1), pages 61-68.
    53. Ahmed Ali & Granberg Mark & Uddin Gazi Salah & Troster Victor, 2022. "Asymmetric dynamics between uncertainty and unemployment flows in the United States," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 26(1), pages 155-172, February.
    54. De Luigi, Clara & Huber, Florian, 2018. "Debt regimes and the effectiveness of monetary policy," Journal of Economic Dynamics and Control, Elsevier, vol. 93(C), pages 218-238.
    55. Barnichon, Regis & Matthes, Christian, 2016. "Gaussian Mixture Approximations of Impulse Responses and The Non-Linear Effects of Monetary Shocks," CEPR Discussion Papers 11374, C.E.P.R. Discussion Papers.
    56. Christian Matthes & Regis Barnichon, 2015. "Measuring the Non-Linear Effects of Monetary Policy," 2015 Meeting Papers 49, Society for Economic Dynamics.
    57. Jesús Gonzalo & Jean-Yves Pitarakis, 2013. "Estimation and inference in threshold type regime switching models," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 8, pages 189-205, Edward Elgar Publishing.
    58. Dick van Dijk & Philip Hans Franses & Michael P. Clements & Jeremy Smith, 2003. "On SETAR non-linearity and forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(5), pages 359-375.
    59. Donayre, Luiggi & Panovska, Irina, 2016. "Nonlinearities in the U.S. wage Phillips curve," Journal of Macroeconomics, Elsevier, vol. 48(C), pages 19-43.
    60. Wan Shin, Dong & Jhee, Won-Chul, 2006. "Tests for asymmetry in possibly nonstationary dynamic panel models," Economics Letters, Elsevier, vol. 91(1), pages 15-20, April.
    61. Caggiano, Giovanni & Castelnuovo, Efrem & Groshenny, Nicolas, 2014. "Uncertainty shocks and unemployment dynamics in U.S. recessions," Journal of Monetary Economics, Elsevier, vol. 67(C), pages 78-92.
    62. Mariola Piłatowska & Dorota Witkowska, 2022. "Gender Segregation at Work over Business Cycle—Evidence from Selected EU Countries," Sustainability, MDPI, vol. 14(16), pages 1-19, August.
    63. Floros, Ch., 2005. "Forecasting the UK Unemployment Rate: Model Comparisons," International Journal of Applied Econometrics and Quantitative Studies, Euro-American Association of Economic Development, vol. 2(4), pages 57-72.
    64. Zhu, Yanli & Han, Xiaoyi & Chen, Ying, 2020. "Bayesian estimation and model selection of threshold spatial Durbin model," Economics Letters, Elsevier, vol. 188(C).
    65. Skalin, Joakim & Teräsvirta, Timo, 1998. "Modelling asymmetries and moving equilibria in unemployment rates," SSE/EFI Working Paper Series in Economics and Finance 262, Stockholm School of Economics, revised Jul 1999.
    66. Thomas B. King, 2005. "Labor productivity and job-market flows: trends, cycles, and correlations," Supervisory Policy Analysis Working Papers 2005-04, Federal Reserve Bank of St. Louis.
    67. Olmedo, Elena, 2011. "Is there chaos in the Spanish labour market?," Chaos, Solitons & Fractals, Elsevier, vol. 44(12), pages 1045-1053.
    68. Francesco D'Amuri & Juri Marcucci, 2012. "The predictive power of Google searches in forecasting unemployment," Temi di discussione (Economic working papers) 891, Bank of Italy, Economic Research and International Relations Area.
    69. Gary Koop & Simon Potter, 2010. "A flexible approach to parametric inference in nonlinear and time varying time series models," Post-Print hal-00732535, HAL.
    70. Elena Olmedo, 2014. "Forecasting Spanish Unemployment Using Near Neighbour and Neural Net Techniques," Computational Economics, Springer;Society for Computational Economics, vol. 43(2), pages 183-197, February.
    71. Man-Suk Oh & Dong Wan Shin, 2002. "Bayesian model selection and parameter estimation for possibly asymmetric and non-stationary time series using a reversible jump Markov chain Monte Carlo approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 29(5), pages 771-789.
    72. Kurmaş Akdoğan, 2015. "Unemployment Hysteresis and Structural Change in Europe," EY International Congress on Economics II (EYC2015), November 5-6, 2015, Ankara, Turkey 266, Ekonomik Yaklasim Association.
    73. Laura Brown & Saeed Moshiri, 2004. "Unemployment variation over the business cycles: a comparison of forecasting models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(7), pages 497-511.
    74. Koray Yıldırım & Neşe Algan & Harun Bal, 2024. "Investment Hysteresis: An Empirical Essay Turkish Case," Evaluation Review, , vol. 48(1), pages 143-176, February.
    75. Gao, Jiti & Gijbels, Irene & Van Bellegem, Sebastien, 2008. "Nonparametric simultaneous testing for structural breaks," Journal of Econometrics, Elsevier, vol. 143(1), pages 123-142, March.
    76. Giordani, Paolo & Kohn, Robert & van Dijk, Dick, 2007. "A unified approach to nonlinearity, structural change, and outliers," Journal of Econometrics, Elsevier, vol. 137(1), pages 112-133, March.
    77. Kevin Larcher & Jaebeom Kim & Youngju Kim, 2019. "Uncertainty shocks and asymmetric dynamics in Korea: a non-linear approach," Applied Economics, Taylor & Francis Journals, vol. 51(6), pages 594-610, February.
    78. Galyna Grynkiv & Lars Stentoft, 2018. "Stationary Threshold Vector Autoregressive Models," JRFM, MDPI, vol. 11(3), pages 1-23, August.
    79. Deborah Gefang, 2012. "Money‐output Causality Revisited – A Bayesian Logistic Smooth Transition VECM Perspective," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(1), pages 131-151, February.
    80. Ioannis Papageorgiou & Ioannis Kontoyiannis, 2023. "The Bayesian Context Trees State Space Model for time series modelling and forecasting," Papers 2308.00913, arXiv.org, revised Oct 2023.
    81. Petros Dellaportas & David G. T. Denison & Chris Holmes, 2007. "Flexible Threshold Models for Modelling Interest Rate Volatility," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 419-437.
    82. Dilem Yildirim & Ralf Becker & Denise R Osborn, 2009. "Bootstrap Unit Root Tests for Nonlinear Threshold Models," Economics Discussion Paper Series 0915, Economics, The University of Manchester.
    83. Hwang, Inwook & Kim, Jaebeom, 2021. "Oil price shocks and the US stock market: A nonlinear approach," Journal of Empirical Finance, Elsevier, vol. 64(C), pages 23-36.
    84. Ginger M. Davis & Katherine B. Ensor, 2007. "Multivariate Time‐Series Analysis With Categorical and Continuous Variables in an Lstr Model," Journal of Time Series Analysis, Wiley Blackwell, vol. 28(6), pages 867-885, November.
    85. Dimitris K. Christopoulos & Miguel A. León‐Ledesma, 2010. "Revisiting The Real Wages–Unemployment Relationship. New Results From Non‐Linear Models," Bulletin of Economic Research, Wiley Blackwell, vol. 62(1), pages 79-96, January.
    86. Adriana AnaMaria Davidescu & Simona-Andreea Apostu & Liviu Adrian Stoica, 2021. "Socioeconomic Effects of COVID-19 Pandemic: Exploring Uncertainty in the Forecast of the Romanian Unemployment Rate for the Period 2020–2023," Sustainability, MDPI, vol. 13(13), pages 1-22, June.
    87. Gary Koop & Simon M. Potter, 2007. "A flexible approach to parametric inference in nonlinear time series models," Staff Reports 285, Federal Reserve Bank of New York.
    88. Reuben Ellul, 2018. "Forecasting unemployment rates in Malta: A labour market flows approach," CBM Working Papers WP/03/2018, Central Bank of Malta.
    89. Ahmed, M. Iqbal & Farah, Quazi Fidia & Kishan, Ruby P., 2023. "Oil price uncertainty and unemployment dynamics: Nonlinearities matter," Energy Economics, Elsevier, vol. 125(C).
    90. Giannikis, D. & Vrontos, I.D. & Dellaportas, P., 2008. "Modelling nonlinearities and heavy tails via threshold normal mixture GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1549-1571, January.
    91. Klein, Tony, 2022. "Agree to disagree? Predictions of U.S. nonfarm payroll changes between 2008 and 2020 and the impact of the COVID19 labor shock," Journal of Economic Behavior & Organization, Elsevier, vol. 194(C), pages 264-286.

  96. Osiewalski, J. & Koop, G. & Steel, M.F.J., 1997. "A Stochastic Frontier Analysis of Output Level and Growth in Poland and Western Economies," Discussion Paper 1997-85, Tilburg University, Center for Economic Research.

    Cited by:

    1. Maria Baquero Forero & Takanori Ida & Toshifumi Kuroda, 2015. "Institutions and Cultural Heterogeneity as Determinants of National Income: A Random-coefficients Stochastic Frontier Model," Review of Development Economics, Wiley Blackwell, vol. 19(3), pages 710-724, August.
    2. Camilla Mastromarco, 2008. "Foreign Capital And Efficiency In Developing Countries," Bulletin of Economic Research, Wiley Blackwell, vol. 60(4), pages 351-374, October.
    3. Francisco J. Ruge-Murcia, 2000. "Uncovering financial markets' beliefs about inflation targets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 483-512.
    4. Lambarraa, Fatima & Serra, Teresa & Gil Roig, Jose Maria, 2006. "Technical efficiency analysis and decomposition of productivity growth of Spanish olive farms," 98th Seminar, June 29-July 2, 2006, Chania, Crete, Greece 10071, European Association of Agricultural Economists.
    5. Malinka Koparanova, 2007. "Structural Changes in the Manufacturing Industry of Transition Economies," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 3, pages 3-42.
    6. António AFONSO & Miguel ST. AUBYN, 2010. "Public and Private Inputs in Aggregate Production and Growth: A Cross-country Efficiency Approach," EcoMod2010 259600004, EcoMod.
    7. Astrid Cullmann & Christian von Hirschhausen, 2007. "From Transition to Competition: Dynamic Efficiency Analysis of Polish Electricity Distribution Companies," Discussion Papers of DIW Berlin 716, DIW Berlin, German Institute for Economic Research.
    8. Jerzy Marzec & Andrzej Pisulewski & Artur Prędki, 2019. "Efektywność techniczna i produktywność polskich gospodarstw rolnych specjalizujących się w uprawach polowych," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 2, pages 95-125.
    9. Weill, Laurent, 2006. "On the consistency of aggregate production frontiers," European Journal of Operational Research, Elsevier, vol. 172(1), pages 326-333, July.
    10. Efthymios G. Tsionas, 2006. "Inference in dynamic stochastic frontier models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 669-676, July.
    11. Mastromarco, Camilla & Ghosh, Sucharita, 2009. "Foreign Capital, Human Capital, and Efficiency: A Stochastic Frontier Analysis for Developing Countries," World Development, Elsevier, vol. 37(2), pages 489-502, February.
    12. Laurent Weill, 2008. "On the inefficiency of European socialist economies," Journal of Productivity Analysis, Springer, vol. 29(2), pages 79-89, April.
    13. Jaume Puig, 2000. "Technical inefficiency and public capital in US States: A stochastic frontier approach," Economics Working Papers 451, Department of Economics and Business, Universitat Pompeu Fabra.
    14. Kamil Makieła, 2017. "Bayesian Inference and Gibbs Sampling in Generalized True Random-Effects Models," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 9(1), pages 69-95, March.
    15. Mr. Andrew J Tiffin, 2006. "Ukraine: The Cost of Weak Institutions," IMF Working Papers 2006/167, International Monetary Fund.
    16. Heru Margono & Subhash Sharma & Kevin Sylwester & Usama Al-Qalawi, 2009. "Technical efficiency and productivity analysis in Indonesian provincial economies," Applied Economics, Taylor & Francis Journals, vol. 43(6), pages 663-672.
    17. Marco FIORAMANTI, 2010. "Estimation And Decomposition Of Total Factor Productivity Growth In The Eu Manufacturing Sector: A Long Run Perspective," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 5(3(13)/Fal), pages 217-230.
    18. Danish Ahmed SIDDIQUI & Qazi Masood AHMED, 2019. "Exploring the role of institutions in cross country Malmquist productivity analysis: A two-stage double bootstrap DEA approach," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(4(621), W), pages 241-264, Winter.
    19. Cardoso de Mendonça, Mário Jorge & Pereira, Amaro Olimpio & Medrano, Luis Alberto & Pessanha, José Francisco M., 2021. "Analysis of electric distribution utilities efficiency levels by stochastic frontier in Brazilian power sector," Socio-Economic Planning Sciences, Elsevier, vol. 76(C).
    20. Subal Kumbhakar & Raquel Ortega-Argilés & Lesley Potters & Marco Vivarelli & Peter Voigt, 2012. "Corporate R&D and firm efficiency: evidence from Europe’s top R&D investors," Journal of Productivity Analysis, Springer, vol. 37(2), pages 125-140, April.
    21. Kamil Makieła, 2009. "Economic Growth Decomposition. An Empirical Analysis Using Bayesian Frontier Approach," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 1(4), pages 333-369, December.
    22. Marco Fioramanti, 2009. "Estimation and Decomposition of Total Factor Productivity Growth in the EU Manufacturing Sector: a Stochastic Frontier Approach," ISAE Working Papers 114, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    23. Jerzy Marzec & Andrzej Pisulewski, 2017. "The Effect of CAP Subsidies on the Technical Efficiency of Polish Dairy Farms," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 9(3), pages 243-273, September.

  97. KOOP , Gary & LEY , Eduardo & OSIEWALSKI , Jacek & STEEL , Mark, 1995. "Bayesian Analysis of Long Memory and Persistence using ARFIMA Models," LIDAM Discussion Papers CORE 1995035, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. S. Bordignon & D. Raggi, 2010. "Long memory and nonlinearities in realized volatility: a Markov switching approach," Working Papers 694, Dipartimento Scienze Economiche, Universita' di Bologna.
    2. Roberto Leon-Gonzalez & Fuyu Yang, 2010. "Bayesian Estimation and Model Selection in the Generalised Stochastic Unit Root Model," SFB 649 Discussion Papers SFB649DP2010-006, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Jacek Osiewalski & Justyna Wróblewska & Kamil Makieła, 2020. "Bayesian comparison of production function-based and time-series GDP models," Empirical Economics, Springer, vol. 58(3), pages 1355-1380, March.
    4. N. H. Chan & A. E. Brockwell, 2006. "Long-memory dynamic Tobit models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(5), pages 351-367.
    5. Kunal Saha & Vinodh Madhavan & Chandrashekhar G. R. & David McMillan, 2020. "Pitfalls in long memory research," Cogent Economics & Finance, Taylor & Francis Journals, vol. 8(1), pages 1733280-173, January.
    6. Fuyu Yang, 2007. "Bayesian Analysis of Deterministic Time Trend and Changes in Persistence Using a Generalised Stochastic Unit Root Model," Discussion Papers in Economics 07/11, Division of Economics, School of Business, University of Leicester.
    7. Laura Mayoral, 2005. "The persistence of inflation in OECD countries: A fractionally integrated approach," Economics Working Papers 958, Department of Economics and Business, Universitat Pompeu Fabra, revised Oct 2005.
    8. Goldman Elena & Nam Jouahn & Tsurumi Hiroki & Wang Jun, 2013. "Regimes and long memory in realized volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(5), pages 521-549, December.
    9. M. Dolores Gadea & Laura Mayoral, 2009. "Aggregation is not the solution: the PPP puzzle strikes back," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(6), pages 875-894.
    10. Ossama Mikhail & Curtis J. Eberwein & Jagdish Handa, 2003. "Testing and Estimating Persistence in Canadian Unemployment," Econometrics 0311004, University Library of Munich, Germany.
    11. Gael Martin, 2001. "Bayesian Analysis Of A Fractional Cointegration Model," Econometric Reviews, Taylor & Francis Journals, vol. 20(2), pages 217-234.
    12. Epaminondas Panas & Vassilia Ninni, 2010. "The Distribution of London Metal Exchange Prices: A Test of the Fractal Market Hypothesis," European Research Studies Journal, European Research Studies Journal, vol. 0(2), pages 192-210.
    13. Kai Yang & Qingqing Zhang & Xinyang Yu & Xiaogang Dong, 2023. "Bayesian inference for a mixture double autoregressive model," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 77(2), pages 188-207, May.
    14. Manveer Kaur Mangat & Erhard Reschenhofer, 2019. "Testing for Long-Range Dependence in Financial Time Series," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 11(2), pages 93-106, June.
    15. Mark F. J. Steel, 2020. "Model Averaging and Its Use in Economics," Journal of Economic Literature, American Economic Association, vol. 58(3), pages 644-719, September.
    16. Martin, V.L. & Wilkins, N.P., 1997. "Indirect Estimation of Arfima and Varfima Models," Department of Economics - Working Papers Series 547, The University of Melbourne.
    17. Andersson, Fredrik N. G. & Li, Yushu, 2014. "Are Central Bankers Inflation Nutters? - A Bayesian MCMC Estimator of the Long Memory Parameter in a State Space Model," Discussion Papers 2014/38, Norwegian School of Economics, Department of Business and Management Science.
    18. Andersson, Fredrik N.G. & Li, Yushu, 2013. "How Flexible are the Inflation Targets? A Bayesian MCMC Estimator of the Long Memory Parameter in a State Space Model," Working Papers 2013:38, Lund University, Department of Economics.
    19. Panas, E., 2001. "Long memory and chaotic models of prices on the London Metal Exchange," Resources Policy, Elsevier, vol. 27(4), pages 235-246, December.
    20. Micha³ Majsterek, 2018. "Stock and Flows in the Countegration Context," Lodz Economics Working Papers 3/2018, University of Lodz, Faculty of Economics and Sociology.
    21. Iglesias, Pilar & Jorquera, Hector & Palma, Wilfredo, 2006. "Data analysis using regression models with missing observations and long-memory: an application study," Computational Statistics & Data Analysis, Elsevier, vol. 50(8), pages 2028-2043, April.
    22. Moral-Benito, Enrique, 2010. "Model averaging in economics," MPRA Paper 26047, University Library of Munich, Germany.
    23. Ross Doppelt & Keith O'Hara, 2018. "Bayesian Estimation of Fractionally Integrated Vector Autoregressions and an Application to Identified Technology Shocks," 2018 Meeting Papers 1212, Society for Economic Dynamics.
    24. Gonçalves Mazzeu, Joao Henrique & Ruiz Ortega, Esther & Veiga, Helena, 2015. "Model uncertainty and the forecast accuracy of ARMA models: A survey," DES - Working Papers. Statistics and Econometrics. WS ws1508, Universidad Carlos III de Madrid. Departamento de Estadística.
    25. O. Mikhail & C. J. Eberwein & J. Handa, 2006. "Estimating persistence in Canadian unemployment: evidence from a Bayesian ARFIMA," Applied Economics, Taylor & Francis Journals, vol. 38(15), pages 1809-1819.
    26. Mohsen Mehrara & Nafiseh Behradmehr & Mitra Saboonchi, 2013. "Investigating the Long time Memory in the Future Market of Gold," International Journal of Financial Economics, Research Academy of Social Sciences, vol. 1(1), pages 28-32.
    27. Enrique Moral-Benito, 2015. "Model Averaging In Economics: An Overview," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 46-75, February.

  98. KOOP, Gary & OSIEWALSKI, Jacek & STEEL, Mark, 1995. "The Components of Output Growth : A Cross-Country Analysis," LIDAM Discussion Papers CORE 1995003, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Fernández, C. & Osiewalski, J. & Steel, M.F.J., 1996. "On the Use of Panel Data in Bayesian Stochastic Frontier Models," Discussion Paper 1996-17, Tilburg University, Center for Economic Research.
    2. Gordon, S. & Belanger, G., 1995. "Echantillonnage de Gibbs et autres application econometriques des chaines merkoviennes," Papers 9509, Laval - Recherche en Politique Economique.
    3. Jacek Osiewalski & Mark Steel, 1998. "Numerical Tools for the Bayesian Analysis of Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 10(1), pages 103-117, July.
    4. Temple, J., 1995. "Testing the Augmented Solow Models," Economics Papers 106, Economics Group, Nuffield College, University of Oxford.
    5. Gary Koop, 1998. "Carbon dioxide emissions and economic growth: A structural approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 25(4), pages 489-515.
    6. Boyle, Gerry & McQuinn, Kieran, 2004. "Why do some countries produce so much more output per worker than others? - A note," Research Technical Papers 9/RT/04, Central Bank of Ireland.
    7. Yasmina Reem Limam & Stephen M. Miller, 2004. "Explaining Economic Growth: Factor Accumulation, Total Factor Productivity Growth, and Production Efficiency Improvement," Working papers 2004-20, University of Connecticut, Department of Economics.
    8. Fernandez, Carmen & Osiewalski, Jacek & Steel, Mark F. J., 1997. "On the use of panel data in stochastic frontier models with improper priors," Journal of Econometrics, Elsevier, vol. 79(1), pages 169-193, July.

  99. KOOP , Gary & OSIEWALSKI, Jacek & STEEL , Mark, 1995. "Measuring the Sources of Output Growth in a Panel of Countries," LIDAM Discussion Papers CORE 1995042, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Jonathan Temple, 1997. "St Adam and the Dragons: Neo-classical economics and the East Asian miracle," Oxford Development Studies, Taylor & Francis Journals, vol. 25(3), pages 279-300.
    2. Jacek Osiewalski & Mark Steel, 1998. "Numerical Tools for the Bayesian Analysis of Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 10(1), pages 103-117, July.
    3. Binlei Gong & Robin C. Sickles, 2021. "Resource allocation in multi-divisional multi-product firms," Journal of Productivity Analysis, Springer, vol. 55(2), pages 47-70, April.
    4. Gary Koop, 1998. "Carbon dioxide emissions and economic growth: A structural approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 25(4), pages 489-515.
    5. Jonathan Temple, 1999. "The New Growth Evidence," Journal of Economic Literature, American Economic Association, vol. 37(1), pages 112-156, March.
    6. Jaume Puig, 2000. "Technical inefficiency and public capital in US States: A stochastic frontier approach," Economics Working Papers 451, Department of Economics and Business, Universitat Pompeu Fabra.
    7. Boyle, Gerry & McQuinn, Kieran, 2004. "Why do some countries produce so much more output per worker than others? - A note," Research Technical Papers 9/RT/04, Central Bank of Ireland.
    8. Cardoso de Mendonça, Mário Jorge & Pereira, Amaro Olimpio & Medrano, Luis Alberto & Pessanha, José Francisco M., 2021. "Analysis of electric distribution utilities efficiency levels by stochastic frontier in Brazilian power sector," Socio-Economic Planning Sciences, Elsevier, vol. 76(C).

  100. KOOP , Gary & OSIEWALSKI , Jacek & STEEL , Mark, 1995. "Bayesian Efficiency Analysis through Individual Effects : Hospital Cost Frontiers," LIDAM Discussion Papers CORE 1995036, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Assaf, A. George & Barros, Carlos Pestana & Managi, Shunsuke, 2011. "Cost efficiency of Japanese steam power generation companies: A Bayesian comparison of random and fixed frontier models," Applied Energy, Elsevier, vol. 88(4), pages 1441-1446, April.
    2. Gstach, Dieter, 2005. "Estimating output targets to evaluate output-specific efficiencies: A statistical framework," European Journal of Operational Research, Elsevier, vol. 161(2), pages 564-578, March.
    3. Supawat Rungsuriyawiboon & Chris O'Donnell, 2004. "Curvature-Constrained Estimates of Technical Efficiency and Returns to Scale for U.S. Electric Utilities," CEPA Working Papers Series WP072004, School of Economics, University of Queensland, Australia.
    4. Koop, Gary & Li, Kai, 2001. "The valuation of IPO and SEO firms," Journal of Empirical Finance, Elsevier, vol. 8(4), pages 375-401, September.
    5. Barnett, William A. & Serletis, Apostolos, 2008. "Consumer preferences and demand systems," MPRA Paper 8413, University Library of Munich, Germany.
    6. Lise Tole & Gary Koop, 2011. "Estimating the Impact on Efficiency of the Adoption of a Voluntary Environmental Standard: An Empirical Study of the Global Copper Mining Industry," Working Papers 11-36, University of Strathclyde Business School, Department of Economics.
    7. Oum, Tae H. & Yan, Jia & Yu, Chunyan, 2008. "Ownership forms matter for airport efficiency: A stochastic frontier investigation of worldwide airports," Journal of Urban Economics, Elsevier, vol. 64(2), pages 422-435, September.
    8. Economou, Polychronis & Malefaki, Sonia & Kounetas, Konstantinos, 2019. "Productive Performance and Technology Gaps using a Bayesian Metafrontier Production Function: A cross-country comparison," MPRA Paper 94462, University Library of Munich, Germany.
    9. Carmen Fernandez & Gary Koop & Mark F J Steel, 1999. "A Bayesian analysis of multiple-output production frontier," Edinburgh School of Economics Discussion Paper Series 21, Edinburgh School of Economics, University of Edinburgh.
    10. Yangseon Kim & Peter Schmidt, 2007. "Marginal Comparisons with the Best ant the Efficiency Measurment Problem," Working Papers 0703, University of Crete, Department of Economics, revised 01 Dec 2006.
    11. Shabbir Ahmad & Sriram Shankar & John Steen & Martie-Louise Verreynne & Abid Aman Burki, 2018. "What Drives Smallholders' Productivity in Pakistan's Horticultural Sector?," Discussion Papers Series 597, School of Economics, University of Queensland, Australia.
    12. Kalyan Chakraborty & Basudeb Biswas & W. Cris Lewis, 2001. "Measurement of Technical Efficiency in Public Education: A Stochastic and Nonstochastic Production Function Approach," Southern Economic Journal, John Wiley & Sons, vol. 67(4), pages 889-905, April.
    13. Xingyuan Zhang, 2000. "A Monte Carlo Study on the Finite Sample Properties of the Gibbs Sampling Method for a Stochastic Frontier Model," Journal of Productivity Analysis, Springer, vol. 14(1), pages 71-83, July.
    14. William C. Horrace & Kurt E. Schnier, 2008. "Fixed-Effect Estimation of Highly-Mobile Production Technologies," Center for Policy Research Working Papers 87, Center for Policy Research, Maxwell School, Syracuse University.
    15. Kamil Makieła & Błażej Mazur, 2022. "Model uncertainty and efficiency measurement in stochastic frontier analysis with generalized errors," Journal of Productivity Analysis, Springer, vol. 58(1), pages 35-54, August.
    16. Efthymios G. Tsionas, 2002. "Stochastic frontier models with random coefficients," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(2), pages 127-147.
    17. Lachaud, Michée A. & Bravo-Ureta, Boris E., 2022. "A Bayesian statistical analysis of return to agricultural R&D investment in Latin America: Implications for food security," Technology in Society, Elsevier, vol. 70(C).
    18. Daniel Bilodeau & Pierre‐Yves Crémieux & Pierre Ouellette, 2002. "Hospital Technology in a Nonmarket Health Care System," Southern Economic Journal, John Wiley & Sons, vol. 68(3), pages 511-529, January.
    19. Caroline Khan & Mike G. Tsionas, 2021. "Constraints in models of production and cost via slack-based measures," Empirical Economics, Springer, vol. 61(6), pages 3347-3374, December.
    20. J. E. Griffin & M. Kolossiatis & M. F. J. Steel, 2013. "Comparing distributions by using dependent normalized random-measure mixtures," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(3), pages 499-529, June.
    21. Patricia Tecles & Benjamin M. Tabak, 2010. "Determinants of Bank Efficiency: the Case of Brazil," Working Papers Series 210, Central Bank of Brazil, Research Department.
    22. Alfonso Flores-Lagunes & William C. Horrace & Kurt E. Schnier, 2007. "Identifying technically efficient fishing vessels: a non-empty, minimal subset approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(4), pages 729-745.
    23. William Horrace & Seth Richards-Shubik, 2013. "Expected Efficiency Ranks From Parametric Stochastic Fronteir Models," Center for Policy Research Working Papers 153, Center for Policy Research, Maxwell School, Syracuse University.
    24. Sukhmani Sidhu & Kanchan Jain & Suresh Kumar Sharma, 2018. "Bayesian estimation of generalized gamma shared frailty model," Computational Statistics, Springer, vol. 33(1), pages 277-297, March.
    25. Ho-chuan Huang, 2004. "Estimation of Technical Inefficiencies with Heterogeneous Technologies," Journal of Productivity Analysis, Springer, vol. 21(3), pages 277-296, May.
    26. William Griffiths & Xiaohui Zhang & Xueyan Zhao, 2010. "A Stochastic Frontier Model for Discrete Ordinal Outcomes: A Health Production Function," Monash Econometrics and Business Statistics Working Papers 3/10, Monash University, Department of Econometrics and Business Statistics.
    27. Yan, Jia & Sun, Xinyu & Liu, John J., 2009. "Assessing container operator efficiency with heterogeneous and time-varying production frontiers," Transportation Research Part B: Methodological, Elsevier, vol. 43(1), pages 172-185, January.
    28. Areal, Francisco J. & Jones, Philip J. & Mortimer, Simon R. & Wilson, Paul, 2018. "Measuring sustainable intensification: Combining composite indicators and efficiency analysis to account for positive externalities in cereal production," Land Use Policy, Elsevier, vol. 75(C), pages 314-326.
    29. Gholamreza Hajargasht & William E. Griffiths, 2016. "Estimation and Testing of Stochastic Frontier Models using Variational Bayes," Department of Economics - Working Papers Series 2024, The University of Melbourne.
    30. Jerzy Marzec & Andrzej Pisulewski, 2015. "Analysis of the Economic Activity of Dairy Farms in Poland: Results obtained from the Short-run Cost Function," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 39, pages 167-182.
    31. Roberto Colombi & Gianmaria Martini & Giorgio Vittadini, 2017. "Determinants of transient and persistent hospital efficiency: The case of Italy," Health Economics, John Wiley & Sons, Ltd., vol. 26(S2), pages 5-22, September.
    32. Junrong Liu & Robin C. Sickles & E. G. Tsionas, 2017. "Bayesian Treatments for Panel Data Stochastic Frontier Models with Time Varying Heterogeneity," Econometrics, MDPI, vol. 5(3), pages 1-21, July.
    33. Bo Hsiao & Li‐Hsueh Chen & Huei‐Ting Wu, 2019. "Assessing performance of Taiwan hospitals using data envelopment analysis: In view of ownership," International Journal of Health Planning and Management, Wiley Blackwell, vol. 34(1), pages 602-616, January.
    34. Wolff, Hendrik & Heckelei, Thomas & Mittelhammer, Ronald C., 2004. "Imposing Monotonicity And Curvature On Flexible Functional Forms," 2004 Annual meeting, August 1-4, Denver, CO 20256, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    35. Assaf, A. George & Barros, Carlos & Sellers-Rubio, Ricardo, 2011. "Efficiency determinants in retail stores: a Bayesian framework," Omega, Elsevier, vol. 39(3), pages 283-292, June.
    36. Apostolos Serletis & Guohua Feng, "undated". "Imposing Theoretical Regularity on Flexible Functional Forms," Working Papers 2013-11, Department of Economics, University of Calgary.
    37. Griffin, J. E. & Steel, M. F. J., 2004. "Semiparametric Bayesian inference for stochastic frontier models," Journal of Econometrics, Elsevier, vol. 123(1), pages 121-152, November.
    38. Caetano Luiz Beber & Sebastian Lakner & Ioannis Skevas, 2021. "Organizational forms and technical efficiency of the dairy processing industry in Southern Brazil," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 9(1), pages 1-22, December.
    39. Lampe, Hannes W. & Hilgers, Dennis, 2015. "Trajectories of efficiency measurement: A bibliometric analysis of DEA and SFA," European Journal of Operational Research, Elsevier, vol. 240(1), pages 1-21.
    40. Philippe K. Widmer & Peter Zweifel & Mehdi Farsi, 2011. "Accounting for heterogeneity in the measurement of hospital performance," ECON - Working Papers 052, Department of Economics - University of Zurich.
    41. Joseph Palardy & Todd M. Nesbit & Kerry A. Adzima, 2015. "Charter versus traditional public schools: a panel study of the technical efficiency in Ohio," Education Economics, Taylor & Francis Journals, vol. 23(3), pages 278-295, June.
    42. Koop, Gary & Osiewalski, Jacek & Steel, Mark F J, 2000. "A Stochastic Frontier Analysis of Output Level and Growth in Poland and Western Economies," Economic Change and Restructuring, Springer, vol. 33(3), pages 185-202.
    43. Horrace, William C., 2005. "On ranking and selection from independent truncated normal distributions," Journal of Econometrics, Elsevier, vol. 126(2), pages 335-354, June.
    44. I. Fraser & W. Horrace, 2003. "Technical Efficiency of Australian Wool Production: Point and Confidence Interval Estimates," Journal of Productivity Analysis, Springer, vol. 20(2), pages 169-190, September.
    45. Atakelty Hailu & Robert Chambers, 2012. "A Luenberger soil-quality indicator," Journal of Productivity Analysis, Springer, vol. 38(2), pages 145-154, October.
    46. Jordi Moreno-Gené & Laura Sánchez-Pulido & Eduard Cristobal-Fransi & Natalia Daries, 2018. "The Economic Sustainability of Snow Tourism: The Case of Ski Resorts in Austria, France, and Italy," Sustainability, MDPI, vol. 10(9), pages 1-20, August.
    47. Makieła, Kamil, 2016. "Bayesian inference in generalized true random-effects model and Gibbs sampling," MPRA Paper 69389, University Library of Munich, Germany.
    48. Kwaku Addai & Rahmi Deniz Ozbay & Rui Alexandre Castanho & Sema Yilmaz Genc & Gualter Couto & Dervis Kirikkaleli, 2022. "Energy Productivity and Environmental Degradation in Germany: Evidence from Novel Fourier Approaches," Sustainability, MDPI, vol. 14(24), pages 1-18, December.
    49. J. Griffin, 2011. "Bayesian clustering of distributions in stochastic frontier analysis," Journal of Productivity Analysis, Springer, vol. 36(3), pages 275-283, December.
    50. Jacek Osiewalski & Mark Steel, 1998. "Numerical Tools for the Bayesian Analysis of Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 10(1), pages 103-117, July.
    51. Ahmad, Shabbir & Shankar, Sriram & Steen, John & Verreynne, Martie-Louise & Burki, Abid Aman, 2021. "Using measures of efficiency for regionally-targeted smallholder policy intervention: The case of Pakistan’s horticulture sector," Land Use Policy, Elsevier, vol. 101(C).
    52. José Luis Gallizo & Jordi Moreno & Manuel Salvador, 2015. "European banking integration: is foreign ownership affecting banking efficiency?," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 16(2), pages 340-368, April.
    53. Kamil Makieła & Błażej Mazur, 2020. "Bayesian Model Averaging and Prior Sensitivity in Stochastic Frontier Analysis," Econometrics, MDPI, vol. 8(2), pages 1-22, April.
    54. Franc J.G.M. Klaasen & Jan R. Magnus, 2006. "Are Economic Agents Successful Optimizers? An Analysis through Service Strategy in Tennis," Tinbergen Institute Discussion Papers 06-048/2, Tinbergen Institute.
    55. Karen Eggleston & Richard Zeckhauser, 2002. "Government Contracting for Health Care," Discussion Papers Series, Department of Economics, Tufts University 0202, Department of Economics, Tufts University.
    56. Jerzy Marzec & Andrzej Pisulewski & Artur Prędki, 2019. "Efektywność techniczna i produktywność polskich gospodarstw rolnych specjalizujących się w uprawach polowych," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 2, pages 95-125.
    57. Koop G., 2002. "Comparing the Performance of Baseball Players: A Multiple-Output Approach," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 710-720, September.
    58. Jim Griffin & Mark Steel, 2005. "Bayesian Stochastic Frontier Analysis Using WinBUGS," Econometrics 0509004, University Library of Munich, Germany.
    59. Marta Arbelo-Pérez & Pilar Pérez-Gómez & Antonio Arbelo, 2023. "Profit efficiency and its determinants in the agricultural sector: A Bayesian approach," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 69(11), pages 436-445.
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    61. Klaassen, F.J.G.M. & Magnus, J.R., 2006. "Are Economic Agents Successful Optimizers? An Analysis Through Strategy in Tennis," Other publications TiSEM 73e12d86-8fe4-4a87-9181-7, Tilburg University, School of Economics and Management.
    62. Chen, Zhongfei & Barros, Carlos Pestana & Borges, Maria Rosa, 2015. "A Bayesian stochastic frontier analysis of Chinese fossil-fuel electricity generation companies," Energy Economics, Elsevier, vol. 48(C), pages 136-144.
    63. Tsionas, Efthymios G. & Papadakis, Emmanuel N., 2010. "A Bayesian approach to statistical inference in stochastic DEA," Omega, Elsevier, vol. 38(5), pages 309-314, October.
    64. Jee-Seon Kim & Edward Frees, 2007. "Multilevel Modeling with Correlated Effects," Psychometrika, Springer;The Psychometric Society, vol. 72(4), pages 505-533, December.
    65. Gary Koop, 1998. "Carbon dioxide emissions and economic growth: A structural approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 25(4), pages 489-515.
    66. George Assaf, A. & Barros, Carlos P. & Matousek, Roman, 2011. "Productivity and efficiency analysis of Shinkin banks: Evidence from bootstrap and Bayesian approaches," Journal of Banking & Finance, Elsevier, vol. 35(2), pages 331-342, February.
    67. Yangseon Kim & Peter Schmidt, 2000. "A Review and Empirical Comparison of Bayesian and Classical Approaches to Inference on Efficiency Levels in Stochastic Frontier Models with Panel Data," Journal of Productivity Analysis, Springer, vol. 14(2), pages 91-118, September.
    68. Efthymios G. Tsionas, 2006. "Inference in dynamic stochastic frontier models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 669-676, July.
    69. Makiela, Kamil, 2010. "State Level Efficiency Measures for Healthcare Systems," MPRA Paper 62172, University Library of Munich, Germany.
    70. Kamil Makieła & Błażej Mazur & Jakub Głowacki, 2022. "The Impact of Renewable Energy Supply on Economic Growth and Productivity," Energies, MDPI, vol. 15(13), pages 1-13, June.
    71. Kejia Chu & Ning Zhang & Zhongfei Chen, 2015. "The Efficiency and Its Determinants for China’s Medical Care System: Some Policy Implications for Northeast Asia," Sustainability, MDPI, vol. 7(10), pages 1-20, October.
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    73. Guohua Feng & Todd Jewell, 2021. "Productivity and efficiency at english football clubs: a random coefficient approach," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(5), pages 571-604, November.
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    75. Areal, Francisco J & Tiffin, Richard & Balcombe, Kelvin, 2010. "Provision of an environmental output within a multi-output distance function approach," MPRA Paper 25051, University Library of Munich, Germany.
    76. William Griffiths & Xiaohui Zhang & Xueyan Zhao, 2014. "Estimation and efficiency measurement in stochastic production frontiers with ordinal outcomes," Journal of Productivity Analysis, Springer, vol. 42(1), pages 67-84, August.
    77. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
    78. Goto, Mika & Makhija, Anil K., 2007. "The Impact of Competition and Corporate Structure on Productive Efficiency: The Case of the U.S. Electric Utility Industry, 1990-2004," Working Paper Series 2007-10, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    79. Peter Schmidt & Chirok Han & Luis Orea, 2004. "Estimation of a Panel Data Model with Parametric Temporal Variation in Individual Effects," Econometric Society 2004 Far Eastern Meetings 519, Econometric Society.
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    81. A. George Assaf & Carlos Pestana Barros, 2013. "A Global Benchmarking of the Hotel Industry," Tourism Economics, , vol. 19(4), pages 811-821, August.
    82. Ioannis Skevas, 2023. "A novel modeling framework for quantifying spatial spillovers on total factor productivity growth and its components," American Journal of Agricultural Economics, John Wiley & Sons, vol. 105(4), pages 1221-1247, August.
    83. Assaf, A. George & Josiassen, Alexander, 2012. "European vs. U.S. airlines: Performance comparison in a dynamic market," Tourism Management, Elsevier, vol. 33(2), pages 317-326.
    84. Klaassen, Franc J.G.M. & Magnus, Jan R., 2009. "The efficiency of top agents: An analysis through service strategy in tennis," Journal of Econometrics, Elsevier, vol. 148(1), pages 72-85, January.
    85. Carmen Fernandez & Gary Koop & Mark F J Steel, 2003. "Alternative efficiency measures for multiple-output production," Edinburgh School of Economics Discussion Paper Series 65, Edinburgh School of Economics, University of Edinburgh.
    86. Dempsey-Brench, Zara & Volta, Nicola, 2018. "A cost-efficiency analysis of European air navigation service providers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 111(C), pages 11-23.
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    90. Philippe K. Widmer, 2011. "Does prospective payment increase hospital (in)efficiency? Evidence from the Swiss hospital sector," ECON - Working Papers 053, Department of Economics - University of Zurich.
    91. Levent Kutlu & Shasha Liu & Robin C. Sickles, 2022. "Cost, Revenue, and Profit Function Estimates," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 16, pages 641-679, Springer.
    92. O'Donnell, Christopher J. & Coelli, Timothy J., 2005. "A Bayesian approach to imposing curvature on distance functions," Journal of Econometrics, Elsevier, vol. 126(2), pages 493-523, June.
    93. J. Griffin & M. Steel, 2008. "Flexible mixture modelling of stochastic frontiers," Journal of Productivity Analysis, Springer, vol. 29(1), pages 33-50, February.
    94. Gary Koop & Lise Tole, 2008. "What is the environmental performance of firms overseas? An empirical investigation of the global gold mining industry," Journal of Productivity Analysis, Springer, vol. 30(2), pages 129-143, October.
    95. Klein, Nadja & Herwartz, Helmut & Kneib, Thomas, 2020. "Modelling regional patterns of inefficiency: A Bayesian approach to geoadditive panel stochastic frontier analysis with an application to cereal production in England and Wales," Journal of Econometrics, Elsevier, vol. 214(2), pages 513-539.
    96. Carta, Alessandro & Steel, Mark F.J., 2012. "Modelling multi-output stochastic frontiers using copulas," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3757-3773.
    97. Hendrik Wolff & Thomas Heckelei & Ron C. Mittelhammer, 2004. "Imposing Curvature and Monotonicity on Flexible Functional Forms: An Efficient Regional Approach," Econometric Society 2004 North American Summer Meetings 450, Econometric Society.
    98. Dorfman, Jeffrey H. & Atkinson, Scott E., 2002. "Multiple Comparisons With The Best: Bayesian Precision Measures Of Efficiency Rankings," 2002 Annual meeting, July 28-31, Long Beach, CA 19800, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    99. Jorge Galán & Helena Veiga & Michael Wiper, 2014. "Bayesian estimation of inefficiency heterogeneity in stochastic frontier models," Journal of Productivity Analysis, Springer, vol. 42(1), pages 85-101, August.
    100. Fraser, Iain & Davis, Junior & Balcombe, Kelvin & Bezemer, Dirk, 2005. "Is Rural Income Diversity Pro-Growth? Is It Pro-Poor? Evidence from Georgia," Proceedings of the German Development Economics Conference, Kiel 2005 4, Verein für Socialpolitik, Research Committee Development Economics.
    101. Arabinda Das, 2015. "Copula-based Stochastic Frontier Model with Autocorrelated Inefficiency," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 7(2), pages 111-126, June.
    102. Kumbhakar, Subal C. & Tsionas, Efthymios G., 2005. "Measuring technical and allocative inefficiency in the translog cost system: a Bayesian approach," Journal of Econometrics, Elsevier, vol. 126(2), pages 355-384, June.
    103. Qu Feng & William C. Horrace, 2010. "Alternative Technical Efficiency Measures: Skew, Bias, and Scale," Center for Policy Research Working Papers 121, Center for Policy Research, Maxwell School, Syracuse University.
    104. Koop, Gary M & Tobias, Justin, 2006. "Semiparametric Bayesian Inference in Smooth Coefficient Models," Staff General Research Papers Archive 12202, Iowa State University, Department of Economics.
    105. A. Assaf, 2011. "Accounting for technological differences in modelling the performance of airports: a Bayesian approach," Applied Economics, Taylor & Francis Journals, vol. 43(18), pages 2267-2275.
    106. Christoph Pross & Christoph Strumann & Alexander Geissler & Helmut Herwartz & Nadja Klein, 2018. "Quality and resource efficiency in hospital service provision: A geoadditive stochastic frontier analysis of stroke quality of care in Germany," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-30, September.
    107. Anup Malani & Tomas Philipson & Guy David, 2003. "Theories of Firm Behavior in the Nonprofit Sector. A Synthesis and Empirical Evaluation," NBER Chapters, in: The Governance of Not-for-Profit Organizations, pages 181-216, National Bureau of Economic Research, Inc.
    108. Seog-Chan Oh & Jaemin Shin, 2021. "The Assessment of Car Making Plants with an Integrated Stochastic Frontier Analysis Model," Mathematics, MDPI, vol. 9(11), pages 1-21, June.
    109. Jerzy Marzec & Andrzej Pisulewski, 2020. "Pomiar efektywności zróżnicowanych technologicznie gospodarstw rolnych w Unii Europejskiej," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 3, pages 111-137.
    110. Adnan Kasman & Evrim Turgutlu, 2011. "Performance of European insurance firms in the single insurance market," International Review of Applied Economics, Taylor & Francis Journals, vol. 25(3), pages 363-378.
    111. Guohua Feng & Chuan Wang & Xibin Zhang, 2019. "Estimation of inefficiency in stochastic frontier models: a Bayesian kernel approach," Journal of Productivity Analysis, Springer, vol. 51(1), pages 1-19, February.
    112. Georges Assaf, A. & Gillen, David, 2012. "Measuring the joint impact of governance form and economic regulation on airport efficiency," European Journal of Operational Research, Elsevier, vol. 220(1), pages 187-198.
    113. Jorge E. Galán & Yong Tan, 2024. "Green light for green credit? Evidence from its impact on bank efficiency," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(1), pages 531-550, January.
    114. Mike Tsionas & Marwan Izzeldin & Arne Henningsen & Evaggelos Paravalos, 2022. "Addressing endogeneity when estimating stochastic ray production frontiers: a Bayesian approach," Empirical Economics, Springer, vol. 62(3), pages 1345-1363, March.
    115. Luis R. Murillo‐Zamorano, 2004. "Economic Efficiency and Frontier Techniques," Journal of Economic Surveys, Wiley Blackwell, vol. 18(1), pages 33-77, February.
    116. Jerzy Marzec & Andrzej Pisulewski, 2021. "Measurement of technical efficiency in the case of heterogeneity of technologies used between firms - Based on evidence from Polish crop farms," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 67(4), pages 152-161.
    117. Kelvin_Balcombe & Dirk_Bezemer & Junior_Davis & Iain_Fraser, 2005. "Livelihoods and Farm Efficiency in Rural Georgia," Development and Comp Systems 0502005, University Library of Munich, Germany.
    118. Vincenzo Atella & Federico Belotti & Silvio Daidone & Giuseppe Ilardi & Giorgia Marini, 2012. "Cost-containment policies and hospital efficiency: evidence from a panel of Italian hospitals," CEIS Research Paper 228, Tor Vergata University, CEIS, revised 13 Apr 2012.
    119. Idaira Cabrera‐Suárez & Jorge V. Pérez‐Rodríguez, 2021. "Bank branch performance and cost efficiency: A stochastic frontier panel data approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5850-5863, October.
    120. Kamil Makie{l}a & B{l}a.zej Mazur, 2020. "Stochastic Frontier Analysis with Generalized Errors: inference, model comparison and averaging," Papers 2003.07150, arXiv.org, revised Oct 2020.
    121. Tiemann, Oliver & Schreyögg, Jonas & Busse, Reinhard, 2012. "Hospital ownership and efficiency: A review of studies with particular focus on Germany," Health Policy, Elsevier, vol. 104(2), pages 163-171.
    122. Luis Alberiko Gil-Alana & Carlos Barros & Dercio Mandlaze, 2017. "A performance assessment of Mozambique banks: a Bayesian stochastic frontier," Applied Economics, Taylor & Francis Journals, vol. 49(45), pages 4579-4587, September.
    123. Fernandez, Carmen & Osiewalski, Jacek & Steel, Mark F. J., 1997. "On the use of panel data in stochastic frontier models with improper priors," Journal of Econometrics, Elsevier, vol. 79(1), pages 169-193, July.
    124. Bao Hoang Nguyen & Robin C. Sickles & Valentin Zelenyuk, 2021. "What do we know from the vast literature on efficiency and productivity in healthcare? A Systematic Review and Bibliometric Analysis," CEPA Working Papers Series WP092021, School of Economics, University of Queensland, Australia.
    125. Haider, Salman & Mishra, Prajna Paramita, 2021. "Does innovative capability enhance the energy efficiency of Indian Iron and Steel firms? A Bayesian stochastic frontier analysis," Energy Economics, Elsevier, vol. 95(C).
    126. Barros, Carlos Pestana & Assaf, A.George & de Araujo, Ari Francisco, 2011. "Cost performance of Brazilian soccer clubs: A Bayesian varying efficiency distribution model," Economic Modelling, Elsevier, vol. 28(6), pages 2730-2735.
    127. Ramsey, Austin F. & Wang, Huaiyu, 2018. "Non-Farm Income and Technical Efficiency in the Uplands of Yunnan, China: A Bayesian Non-Crossing Quantile Regression Approach," 2018 Annual Meeting, August 5-7, Washington, D.C. 274375, Agricultural and Applied Economics Association.
    128. William C. Horrace & Peter Schmidt, 2000. "Multiple comparisons with the best, with economic applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(1), pages 1-26.
    129. Antonio Arbelo & Marta Arbelo-Pérez & Pilar Pérez-Gómez, 2022. "Are SMEs less efficient? A Bayesian approach to addressing heterogeneity across firms," Small Business Economics, Springer, vol. 58(4), pages 1915-1929, April.
    130. K. M. Matawie & A. Assaf, 2010. "Bayesian and DEA efficiency modelling: an application to hospital foodservice operations," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(6), pages 945-953.
    131. Skevas, Ioannis & Emvalomatis, Grigorios & Brümmer, Bernhard, 2018. "Productivity growth measurement and decomposition under a dynamic inefficiency specification: The case of German dairy farms," European Journal of Operational Research, Elsevier, vol. 271(1), pages 250-261.
    132. Xiaohui Zhang & Katharina Hauck & Xueyan Zhao, 2013. "Patient Safety In Hospitals – A Bayesian Analysis Of Unobservable Hospital And Specialty Level Risk Factors," Health Economics, John Wiley & Sons, Ltd., vol. 22(9), pages 1158-1174, September.
    133. Kumbhakar, Subal C. & Parmeter, Christopher F. & Tsionas, Efthymios G., 2012. "Bayesian estimation approaches to first-price auctions," Journal of Econometrics, Elsevier, vol. 168(1), pages 47-59.
    134. Jerzy Marzec & Andrzej Pisulewski, 2017. "The Effect of CAP Subsidies on the Technical Efficiency of Polish Dairy Farms," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 9(3), pages 243-273, September.

  101. Koop, G. & Osiewalski, J. & Steel, M.F.J., 1994. "Bayesian efficiency analysis with a flexible form : The aim cost function," Discussion Paper 1994-13, Tilburg University, Center for Economic Research.

    Cited by:

    1. Eduardo Ley & Mark F.J. Steel, 1995. "On the Estimation of Demand Systems Through Consumption Efficiency," Econometrics 9503001, University Library of Munich, Germany, revised 22 Feb 1996.
    2. Carmen Fernandez & Gary Koop & Mark F J Steel, 1999. "A Bayesian analysis of multiple-output production frontier," Edinburgh School of Economics Discussion Paper Series 21, Edinburgh School of Economics, University of Edinburgh.
    3. Fernández, C. & Osiewalski, J. & Steel, M.F.J., 1996. "On the Use of Panel Data in Bayesian Stochastic Frontier Models," Discussion Paper 1996-17, Tilburg University, Center for Economic Research.
    4. William Barnett & Milka Kirova & Meenakshi Pasupathy, 2012. "Technology Modeling: Curvature is not Sufficient for Regularity," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201214, University of Kansas, Department of Economics, revised Sep 2012.
    5. Vaneet Bhatia & Sankarshan Basu & Subrata Kumar Mitra & Pradyumna Dash, 2018. "A review of bank efficiency and productivity," OPSEARCH, Springer;Operational Research Society of India, vol. 55(3), pages 557-600, November.
    6. Ho-chuan Huang, 2004. "Estimation of Technical Inefficiencies with Heterogeneous Technologies," Journal of Productivity Analysis, Springer, vol. 21(3), pages 277-296, May.
    7. Gordon, S. & Belanger, G., 1995. "Echantillonnage de Gibbs et autres application econometriques des chaines merkoviennes," Papers 9509, Laval - Recherche en Politique Economique.
    8. Wolff, Hendrik & Heckelei, Thomas & Mittelhammer, Ronald C., 2004. "Imposing Monotonicity And Curvature On Flexible Functional Forms," 2004 Annual meeting, August 1-4, Denver, CO 20256, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    9. Elvira Haezendonck & Julien van den Broeck & Tim Jans, 2011. "Analysing the lobby-effect of port competitiveness’ determinants: a stochastic frontier approach," Journal of Productivity Analysis, Springer, vol. 36(2), pages 113-123, October.
    10. Jacek Osiewalski & Mark Steel, 1998. "Numerical Tools for the Bayesian Analysis of Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 10(1), pages 103-117, July.
    11. Koop, Gary & Osiewalski, Jacek & Steel, Mark F. J., 1997. "Bayesian efficiency analysis through individual effects: Hospital cost frontiers," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 77-105.
    12. Koop, G. & Osiewalski, J. & Steel, M.F.J., 1994. "Hospital efficiency analysis through individual effects : A Bayesian approach," Other publications TiSEM dd6fed13-3fda-461f-9393-e, Tilburg University, School of Economics and Management.
    13. Siddhartha Chib & Edward Greenberg, 1994. "Markov Chain Monte Carlo Simulation Methods in Econometrics," Econometrics 9408001, University Library of Munich, Germany, revised 23 Feb 1995.
    14. Tsionas, Efthymios G. & Papadakis, Emmanuel N., 2010. "A Bayesian approach to statistical inference in stochastic DEA," Omega, Elsevier, vol. 38(5), pages 309-314, October.
    15. William Barnett & Meenakshi Pasupathy, 2012. "Regularity Of The Generalized Quadratic Production Model: A Counterexample," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201235, University of Kansas, Department of Economics, revised Sep 2012.
    16. Goto, Mika & Makhija, Anil K., 2007. "The Impact of Competition and Corporate Structure on Productive Efficiency: The Case of the U.S. Electric Utility Industry, 1990-2004," Working Paper Series 2007-10, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    17. Deschamps, Philippe J., 2000. "Exact small-sample inference in stationary, fully regular, dynamic demand models," Journal of Econometrics, Elsevier, vol. 97(1), pages 51-91, July.
    18. Carmen Fernandez & Gary Koop & Mark F J Steel, 2003. "Alternative efficiency measures for multiple-output production," Edinburgh School of Economics Discussion Paper Series 65, Edinburgh School of Economics, University of Edinburgh.
    19. Hendrik Wolff & Thomas Heckelei & Ron C. Mittelhammer, 2004. "Imposing Curvature and Monotonicity on Flexible Functional Forms: An Efficient Regional Approach," Econometric Society 2004 North American Summer Meetings 450, Econometric Society.
    20. McCausland, William J., 2008. "On Bayesian analysis and computation for functions with monotonicity and curvature restrictions," Journal of Econometrics, Elsevier, vol. 142(1), pages 484-507, January.
    21. Arabinda Das, 2015. "Copula-based Stochastic Frontier Model with Autocorrelated Inefficiency," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 7(2), pages 111-126, June.
    22. Mike Tsionas & Marwan Izzeldin & Arne Henningsen & Evaggelos Paravalos, 2022. "Addressing endogeneity when estimating stochastic ray production frontiers: a Bayesian approach," Empirical Economics, Springer, vol. 62(3), pages 1345-1363, March.
    23. Luis R. Murillo‐Zamorano, 2004. "Economic Efficiency and Frontier Techniques," Journal of Economic Surveys, Wiley Blackwell, vol. 18(1), pages 33-77, February.
    24. Matteo Manera & Bruno Sitzia, 2005. "Empirical factor demands and flexible functional forms: a bayesian approach," Economic Systems Research, Taylor & Francis Journals, vol. 17(1), pages 57-75.
    25. Dashti, Imad, 2003. "Inference from concave stochastic frontiers and the covariance of firm efficiency measures across firms," Energy Economics, Elsevier, vol. 25(6), pages 585-601, November.
    26. Fernandez, Carmen & Osiewalski, Jacek & Steel, Mark F. J., 1997. "On the use of panel data in stochastic frontier models with improper priors," Journal of Econometrics, Elsevier, vol. 79(1), pages 169-193, July.
    27. Lambarraa, Fatima, 2011. "Dynamic Efficiency Analysis of Spanish Outdoor and Greenhouse Horticulture Sector," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114408, European Association of Agricultural Economists.
    28. Lewis, Danielle & Webb, James R., 2007. "Potential cost synergies from banks acquiring real estate brokerage services," Journal of Banking & Finance, Elsevier, vol. 31(8), pages 2347-2363, August.
    29. Hilmer, Christiana E. & Holt, Matthew T., 2000. "A Comparison Of Resampling Techniques When Parameters Are On A Boundary: The Bootstrap, Subsample Bootstrap, And Subsample Jackknife," 2000 Annual meeting, July 30-August 2, Tampa, FL 21810, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    30. Lambarraa, Fatima, 2012. "The Spanish Horticulture Sector: A dynamic efficiency analysis of Outdoor and Greenhouse farms," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 126797, International Association of Agricultural Economists.

  102. Koop, G. & Osiewalski, J. & Steel, M.F.J., 1994. "Hospital efficiency analysis through individual effects : A Bayesian approach," Discussion Paper 1994-47, Tilburg University, Center for Economic Research.

    Cited by:

    1. Gary Koop, 1998. "Carbon dioxide emissions and economic growth: A structural approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 25(4), pages 489-515.
    2. Kamil Makieła & Błażej Mazur & Jakub Głowacki, 2022. "The Impact of Renewable Energy Supply on Economic Growth and Productivity," Energies, MDPI, vol. 15(13), pages 1-13, June.
    3. Jerzy Marzec & Andrzej Pisulewski, 2017. "The Effect of CAP Subsidies on the Technical Efficiency of Polish Dairy Farms," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 9(3), pages 243-273, September.

  103. KOOP, Gary & STEEL, Mark F. & OSIEWALSKI, Jacek, 1994. "Posterior Analysis of Stochastic Frontier Models using Gibbs Sampling," LIDAM Discussion Papers CORE 1994061, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Eduardo Ley & Mark F.J. Steel, 1995. "On the Estimation of Demand Systems Through Consumption Efficiency," Econometrics 9503001, University Library of Munich, Germany, revised 22 Feb 1996.
    2. Supawat Rungsuriyawiboon & Chris O'Donnell, 2004. "Curvature-Constrained Estimates of Technical Efficiency and Returns to Scale for U.S. Electric Utilities," CEPA Working Papers Series WP072004, School of Economics, University of Queensland, Australia.
    3. Danielle Lewis & Randy Anderson, 1999. "Residential Real Estate Brokerage Efficiency and the Implications of Franchising: A Bayesian Approach," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 27(3), pages 543-560, September.
    4. Koop G., 2002. "Comparing the Performance of Baseball Players: A Multiple-Output Approach," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 710-720, September.
    5. Jim Griffin & Mark Steel, 2005. "Bayesian Stochastic Frontier Analysis Using WinBUGS," Econometrics 0509004, University Library of Munich, Germany.
    6. Koop, G. & Osiewalski, J. & Steel, M.F.J., 1994. "Hospital efficiency analysis through individual effects : A Bayesian approach," Other publications TiSEM dd6fed13-3fda-461f-9393-e, Tilburg University, School of Economics and Management.
    7. Seongho Song & David Yi, 2011. "The fundraising efficiency in U.S. non-profit art organizations: an application of a Bayesian estimation approach using the stochastic frontier production model," Journal of Productivity Analysis, Springer, vol. 35(2), pages 171-180, April.
    8. Areal, Francisco J & Tiffin, Richard & Balcombe, Kelvin, 2010. "Provision of an environmental output within a multi-output distance function approach," MPRA Paper 25051, University Library of Munich, Germany.
    9. Goto, Mika & Makhija, Anil K., 2007. "The Impact of Competition and Corporate Structure on Productive Efficiency: The Case of the U.S. Electric Utility Industry, 1990-2004," Working Paper Series 2007-10, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    10. O'Donnell, Christopher J. & Coelli, Timothy J., 2005. "A Bayesian approach to imposing curvature on distance functions," Journal of Econometrics, Elsevier, vol. 126(2), pages 493-523, June.
    11. Griffiths, William E. & O'Donnell, Christopher J., 2005. "Estimating variable returns to scale production frontiers with alternative stochastic assumptions," Journal of Econometrics, Elsevier, vol. 126(2), pages 385-409, June.
    12. C. J. O'Donnell & W. E. Griffiths, 2006. "Estimating State-Contingent Production Frontiers," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 88(1), pages 249-266.
    13. Philip M. Bodman, 1999. "Labour Market Inefficiency and Frictional Unemployment in Australia and its States: A Stochastic Frontier Approach," The Economic Record, The Economic Society of Australia, vol. 75(2), pages 138-148, June.
    14. Lambarraa, Fatima, 2011. "Dynamic Efficiency Analysis of Spanish Outdoor and Greenhouse Horticulture Sector," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114408, European Association of Agricultural Economists.
    15. Kamil Makieła, 2009. "Economic Growth Decomposition. An Empirical Analysis Using Bayesian Frontier Approach," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 1(4), pages 333-369, December.

  104. Koop, Gary & Steel, Mark F.J., 1993. "A decision theoretic analysis of the unit root hypothesis using mixtures of elliptical models," DES - Working Papers. Statistics and Econometrics. WS 3706, Universidad Carlos III de Madrid. Departamento de Estadística.

    Cited by:

    1. Koop, Gary & Osiewalski, Jacek & Steel, Mark F.J., 1992. "Bayesian long-run prediction in time series models," UC3M Working papers. Economics 2822, Universidad Carlos III de Madrid. Departamento de Economía.
    2. Vosseler, Alexander, 2016. "Bayesian model selection for unit root testing with multiple structural breaks," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 616-630.
    3. Kim, Jae & Choi, In, 2015. "Unit Roots in Economic and Financial Time Series: A Re-Evaluation based on Enlightened Judgement," MPRA Paper 68411, University Library of Munich, Germany.
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    125. Mike Tsionas & Marwan Izzeldin & Arne Henningsen & Evaggelos Paravalos, 2022. "Addressing endogeneity when estimating stochastic ray production frontiers: a Bayesian approach," Empirical Economics, Springer, vol. 62(3), pages 1345-1363, March.
    126. Luis R. Murillo‐Zamorano, 2004. "Economic Efficiency and Frontier Techniques," Journal of Economic Surveys, Wiley Blackwell, vol. 18(1), pages 33-77, February.
    127. de Mendonça, Mário Jorge Cardoso & Pereira, Amaro Olimpio & Bellido, Marlon Max H. & Medrano, Luis Alberto & Pessanha, José Francisco Moreira, 2023. "Service quality performance indicators for electricity distribution in Brazil," Utilities Policy, Elsevier, vol. 80(C).
    128. Lovell, Knox, 2001. "Future Research Opportunities in Efficiency and Productivity Analysis," Efficiency Series Papers 2001/01, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    129. Preciado Arreola, José Luis & Johnson, Andrew L. & Chen, Xun C. & Morita, Hiroshi, 2020. "Estimating stochastic production frontiers: A one-stage multivariate semiparametric Bayesian concave regression method," European Journal of Operational Research, Elsevier, vol. 287(2), pages 699-711.
    130. Voltes-Dorta, Augusto & Pagliari, Romano, 2012. "The impact of recession on airports' cost efficiency," Transport Policy, Elsevier, vol. 24(C), pages 211-222.
    131. Jerzy Marzec & Andrzej Pisulewski, 2021. "Measurement of technical efficiency in the case of heterogeneity of technologies used between firms - Based on evidence from Polish crop farms," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 67(4), pages 152-161.
    132. Deng, Na-Qian & Liu, Li-Qiu & Deng, Ying-Zhi, 2018. "Estimating the effects of restructuring on the technical and service-quality efficiency of electricity companies in China," Utilities Policy, Elsevier, vol. 50(C), pages 91-100.
    133. Barry Arnold & Robert Beaver & A. Azzalini & N. Balakrishnan & A. Bhaumik & D. Dey & C. Cuadras & J. Sarabia & Barry Arnold & Robert Beaver, 2002. "Skewed multivariate models related to hidden truncation and/or selective reporting," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 11(1), pages 7-54, June.
    134. Delis, Manthos & Iosifidi, Maria & Tsionas, Mike G, 2017. "Endogenous bank risk and efficiency," European Journal of Operational Research, Elsevier, vol. 260(1), pages 376-387.
    135. Galán, Jorge E. & Veiga, Helena & Wiper, Michael P., 2015. "Dynamic effects in inefficiency: Evidence from the Colombian banking sector," European Journal of Operational Research, Elsevier, vol. 240(2), pages 562-571.
    136. Feder, Christophe, 2018. "The effects of disruptive innovations on productivity," Technological Forecasting and Social Change, Elsevier, vol. 126(C), pages 186-193.
    137. Ha Thu Vu & Sean Turnell, 2010. "Cost Efficiency of the Banking Sector in Vietnam: A Bayesian Stochastic Frontier Approach with Regularity Constraints," Asian Economic Journal, East Asian Economic Association, vol. 24(2), pages 115-139, June.
    138. Kamil Makie{l}a & B{l}a.zej Mazur, 2020. "Stochastic Frontier Analysis with Generalized Errors: inference, model comparison and averaging," Papers 2003.07150, arXiv.org, revised Oct 2020.
    139. Dashti, Imad, 2003. "Inference from concave stochastic frontiers and the covariance of firm efficiency measures across firms," Energy Economics, Elsevier, vol. 25(6), pages 585-601, November.
    140. Luis Alberiko Gil-Alana & Carlos Barros & Dercio Mandlaze, 2017. "A performance assessment of Mozambique banks: a Bayesian stochastic frontier," Applied Economics, Taylor & Francis Journals, vol. 49(45), pages 4579-4587, September.
    141. Rien Wagenvoort & Paul Schure, 2005. "A Recursive Thick Frontier Approach To Estimating Production Efficiency," Econometrics Working Papers 0503, Department of Economics, University of Victoria.
    142. Fernandez, Carmen & Osiewalski, Jacek & Steel, Mark F. J., 1997. "On the use of panel data in stochastic frontier models with improper priors," Journal of Econometrics, Elsevier, vol. 79(1), pages 169-193, July.
    143. Marzec, Jerzy & Pisulewski, Andrzej, 2019. "The Measurement of Time Varying Technical Efficiency and Productivity Change in Polish Crop Farms," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 68(1), March.
    144. Barros, Carlos Pestana & Assaf, A.George & de Araujo, Ari Francisco, 2011. "Cost performance of Brazilian soccer clubs: A Bayesian varying efficiency distribution model," Economic Modelling, Elsevier, vol. 28(6), pages 2730-2735.
    145. Ramsey, Austin F. & Wang, Huaiyu, 2018. "Non-Farm Income and Technical Efficiency in the Uplands of Yunnan, China: A Bayesian Non-Crossing Quantile Regression Approach," 2018 Annual Meeting, August 5-7, Washington, D.C. 274375, Agricultural and Applied Economics Association.
    146. Philip M. Bodman, 1999. "Labour Market Inefficiency and Frictional Unemployment in Australia and its States: A Stochastic Frontier Approach," The Economic Record, The Economic Society of Australia, vol. 75(2), pages 138-148, June.
    147. Lambarraa, Fatima, 2011. "Dynamic Efficiency Analysis of Spanish Outdoor and Greenhouse Horticulture Sector," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114408, European Association of Agricultural Economists.
    148. Tonini, Axel & Matus, Silvia Saravia & Gomez y Paloma, Sergio, 2011. "A Bayesian Total Factor Productivity Analysis of Tropical Agricultural Systems in Central-Western Africa And South-East Asia," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 116088, European Association of Agricultural Economists.
    149. Antonio Arbelo & Marta Arbelo-Pérez & Pilar Pérez-Gómez, 2022. "Are SMEs less efficient? A Bayesian approach to addressing heterogeneity across firms," Small Business Economics, Springer, vol. 58(4), pages 1915-1929, April.
    150. Lambarraa, Fatima, 2012. "The Spanish Horticulture Sector: A dynamic efficiency analysis of Outdoor and Greenhouse farms," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 126797, International Association of Agricultural Economists.
    151. Kamil Makieła, 2014. "Bayesian Stochastic Frontier Analysis of Economic Growth and Productivity Change in the EU, USA, Japan and Switzerland," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 6(3), pages 193-216, September.
    152. Galán, Jorge & Ramos, Sofía B. & Veiga, Helena, 2015. "An analysis of the dynamics of efficiency of mutual funds," DES - Working Papers. Statistics and Econometrics. WS ws1517, Universidad Carlos III de Madrid. Departamento de Estadística.
    153. Efthymios G. Tsionas, 2001. "Posterior Analysis of Stochastic Frontier Models with Truncated Normal Errors," Computational Statistics, Springer, vol. 16(4), pages 559-575, December.
    154. Skevas, Ioannis & Emvalomatis, Grigorios & Brümmer, Bernhard, 2018. "Productivity growth measurement and decomposition under a dynamic inefficiency specification: The case of German dairy farms," European Journal of Operational Research, Elsevier, vol. 271(1), pages 250-261.
    155. Clifford B. Sowell & Wm. Stewart Mounts Jr., 2005. "Ability, Age, and Performance," Journal of Sports Economics, , vol. 6(1), pages 78-97, February.
    156. Mrinal Kumar Dasgupta & Deepankar Sinha, 2016. "Impact of Privatization of Ports on Relative Efficiency of Major Ports of India," Foreign Trade Review, , vol. 51(3), pages 225-247, August.
    157. Kumbhakar, Subal C. & Parmeter, Christopher F. & Tsionas, Efthymios G., 2012. "Bayesian estimation approaches to first-price auctions," Journal of Econometrics, Elsevier, vol. 168(1), pages 47-59.
    158. Jerzy Marzec & Andrzej Pisulewski, 2017. "The Effect of CAP Subsidies on the Technical Efficiency of Polish Dairy Farms," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 9(3), pages 243-273, September.
    159. Troutt, Marvin D. & Hu, Michael Y. & Shanker, Murali S., 2005. "A distribution-free approach to estimating best response values with application to mutual fund performance modeling," European Journal of Operational Research, Elsevier, vol. 166(2), pages 520-527, October.
    160. Russ Kashian & Nicholas Lovett & Yuhan Xue, 2020. "Has the affordable care act affected health care efficiency?," Journal of Regulatory Economics, Springer, vol. 58(2), pages 193-233, December.
    161. Tsionas, Efthymios G., 2003. "Combining DEA and stochastic frontier models: An empirical Bayes approach," European Journal of Operational Research, Elsevier, vol. 147(3), pages 499-510, June.
    162. Annaert, Jan & van den Broeck, Julien & Vander Vennet, Rudi, 2003. "Determinants of mutual fund underperformance: A Bayesian stochastic frontier approach," European Journal of Operational Research, Elsevier, vol. 151(3), pages 617-632, December.

  106. Koop, Gary & Osiewalski, Jacek & Steel, Mark F.J., 1992. "Bayesian long-run prediction in time series models," UC3M Working papers. Economics 2822, Universidad Carlos III de Madrid. Departamento de Economía.

    Cited by:

    1. Koop, G. & Steel, M.F.J., 1991. "A decision theoretic analysis of the unit root hypothesis using mixtures of elliptical models," Discussion Paper 1991-50, Tilburg University, Center for Economic Research.
    2. Vaneet Bhatia & Sankarshan Basu & Subrata Kumar Mitra & Pradyumna Dash, 2018. "A review of bank efficiency and productivity," OPSEARCH, Springer;Operational Research Society of India, vol. 55(3), pages 557-600, November.
    3. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2011. "Combination Schemes for Turning Point Predictions," Tinbergen Institute Discussion Papers 11-123/4, Tinbergen Institute.
    4. Alexander Vosseler & Enzo Weber, 2018. "Forecasting seasonal time series data: a Bayesian model averaging approach," Computational Statistics, Springer, vol. 33(4), pages 1733-1765, December.
    5. Sylvia Kaufmann & Johann Scharler, 2013. "Bank-Lending Standards, Loan Growth and the Business Cycle in the Euro Area," Working Papers 2013-34, Faculty of Economics and Statistics, Universität Innsbruck.
    6. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    7. Lubrano, Michel, 1995. "Testing for unit roots in a Bayesian framework," Journal of Econometrics, Elsevier, vol. 69(1), pages 81-109, September.
    8. K. M. Matawie & A. Assaf, 2010. "Bayesian and DEA efficiency modelling: an application to hospital foodservice operations," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(6), pages 945-953.

  107. Deborah Gefang & Gary Koop & Aubrey Poon, "undated". "Computationally Efficient Inference in Large Bayesian Mixed Frequency VARs," Discussion Papers in Economics 20/02, Division of Economics, School of Business, University of Leicester.

    Cited by:

    1. Andrea Carriero & Todd E. Clark & Marcellino Massimiliano, 2020. "Nowcasting Tail Risks to Economic Activity with Many Indicators," Working Papers 20-13R2, Federal Reserve Bank of Cleveland, revised 22 Sep 2020.
    2. Robert Lehmann & Ida Wikman, 2022. "Quarterly GDP Estimates for the German States," ifo Working Paper Series 370, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    3. Gary Koop & Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon & Ping Wu, 2023. "Incorporating Short Data into Large Mixed-Frequency VARs for Regional Nowcasting," Working Papers 23-09, Federal Reserve Bank of Cleveland.
    4. Martin Feldkircher & Florian Huber & Michael Pfarrhofer, 2020. "Measuring the Effectiveness of US Monetary Policy during the COVID-19 Recession," Papers 2007.15419, arXiv.org.
    5. Deborah Gefang & Stephen G. Hall & George S. Tavlas, 2022. "Fast Two-Stage Variational Bayesian Approach to Estimating Panel Spatial Autoregressive Models with Unrestricted Spatial Weights Matrices," Papers 2205.15420, arXiv.org, revised Aug 2023.
    6. Luca Barbaglia & Lorenzo Frattarolo & Niko Hauzenberger & Dominik Hirschbuehl & Florian Huber & Luca Onorante & Michael Pfarrhofer & Luca Tiozzo Pezzoli, 2024. "Nowcasting economic activity in European regions using a mixed-frequency dynamic factor model," Papers 2401.10054, arXiv.org.
    7. Blagov, Boris & Müller, Henrik & Jentsch, Carsten & Schmidt, Torsten, 2021. "The investment narrative: Improving private investment forecasts with media data," Ruhr Economic Papers 921, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    8. Alain Hecq & Marie Ternes & Ines Wilms, 2021. "Hierarchical Regularizers for Mixed-Frequency Vector Autoregressions," Papers 2102.11780, arXiv.org, revised Mar 2022.
    9. Deborah Gefang & Stephen G. Hall & George S. Tavlas, 2023. "Identifying spatial interdependence in panel data with large N and small T," Papers 2309.03740, arXiv.org.
    10. Robert Lehmann, 2023. "READ-GER: Introducing German Real-Time Regional Accounts Data for Revision Analysis and Nowcasting," CESifo Working Paper Series 10315, CESifo.

Articles

  1. Gefang, Deborah & Koop, Gary & Poon, Aubrey, 2023. "Forecasting using variational Bayesian inference in large vector autoregressions with hierarchical shrinkage," International Journal of Forecasting, Elsevier, vol. 39(1), pages 346-363.

    Cited by:

    1. Marcellino, Massimiliano & Clark, Todd & Huber, Florian & Koop, Gary & Pfarrhofer, Michael, 2022. "Tail Forecasting with Multivariate Bayesian Additive Regression Trees," CEPR Discussion Papers 17461, C.E.P.R. Discussion Papers.
    2. Renata Tavanielli & Márcio Laurini, 2023. "Yield Curve Models with Regime Changes: An Analysis for the Brazilian Interest Rate Market," Mathematics, MDPI, vol. 11(11), pages 1-28, June.
    3. Joshua Chan, 2023. "BVARs and Stochastic Volatility," Papers 2310.14438, arXiv.org.
    4. Florian Huber & Massimiliano Marcellino, 2023. "Coarsened Bayesian VARs -- Correcting BVARs for Incorrect Specification," Papers 2304.07856, arXiv.org, revised May 2023.

  2. Huber, Florian & Koop, Gary & Onorante, Luca & Pfarrhofer, Michael & Schreiner, Josef, 2023. "Nowcasting in a pandemic using non-parametric mixed frequency VARs," Journal of Econometrics, Elsevier, vol. 232(1), pages 52-69.
    See citations under working paper version above.
  3. Martin Feldkircher & Florian Huber & Gary Koop & Michael Pfarrhofer, 2022. "APPROXIMATE BAYESIAN INFERENCE AND FORECASTING IN HUGE‐DIMENSIONAL MULTICOUNTRY VARs," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(4), pages 1625-1658, November.
    See citations under working paper version above.
  4. Niko Hauzenberger & Florian Huber & Gary Koop & Luca Onorante, 2022. "Fast and Flexible Bayesian Inference in Time-varying Parameter Regression Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(4), pages 1904-1918, October.
    See citations under working paper version above.
  5. Florian Huber & Gary Koop & Luca Onorante, 2021. "Inducing Sparsity and Shrinkage in Time-Varying Parameter Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(3), pages 669-683, July.
    See citations under working paper version above.
  6. Koop, Gary & McIntyre, Stuart & Mitchell, James & Poon, Aubrey, 2021. "Nowcasting ‘True’ Monthly U.S. Gdp During The Pandemic," National Institute Economic Review, National Institute of Economic and Social Research, vol. 256, pages 44-70, April.
    See citations under working paper version above.
  7. Koop, Gary & McIntyre, Stuart & Mitchell, James & Poon, Aubrey, 2020. "Reconciled Estimates And Nowcasts Of Regional Output In The Uk," National Institute Economic Review, National Institute of Economic and Social Research, vol. 253, pages 44-59, August.

    Cited by:

    1. Robert Lehmann & Ida Wikman, 2022. "Quarterly GDP Estimates for the German States," ifo Working Paper Series 370, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    2. Bhattacharjee, Arnab & Lisauskaite, Elena & Pabst, Adrian, 2021. "UK regional outlook," National Institute UK Economic Outlook, National Institute of Economic and Social Research, issue 2, pages 42-57.
    3. Niesr, 2021. "Overview," National Institute UK Economic Outlook, National Institute of Economic and Social Research, issue 2, pages 1-4.
    4. Kucuk, Hande & Lenoel, Cyrille & MacQueen, Rory, 2021. "Brisk but not better growth," National Institute UK Economic Outlook, National Institute of Economic and Social Research, issue 2, pages 5-32.
    5. Kucuk, Hande & Lenoel, Cyrille & MacQueen, Rory, 2021. "UK sectoral output," National Institute UK Economic Outlook, National Institute of Economic and Social Research, issue 2, pages 33-41.
    6. Mehmet Balcilar & David Gabauer & Rangan Gupta & Christian Pierdzioch, 2022. "Uncertainty and forecastability of regional output growth in the UK: Evidence from machine learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1049-1064, September.
    7. Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna & Mark E. Wohar, 2021. "Uncertainty and Predictability of Real Housing Returns in the United Kingdom: A Regional Analysis," Working Papers 202102, University of Pretoria, Department of Economics.
    8. Chadha, Jagjit S., 2021. "Foreward," National Institute UK Economic Outlook, National Institute of Economic and Social Research, issue 2, pages 1-3.
    9. Niesr, 2021. "Appendix," National Institute UK Economic Outlook, National Institute of Economic and Social Research, issue 2, pages 58-66.

  8. Gary Koop & Stuart McIntyre & James Mitchell, 2020. "UK regional nowcasting using a mixed frequency vector auto‐regressive model with entropic tilting," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(1), pages 91-119, January.

    Cited by:

    1. Robert Lehmann & Ida Wikman, 2022. "Quarterly GDP Estimates for the German States," ifo Working Paper Series 370, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    2. Martin Feldkircher & Florian Huber & Michael Pfarrhofer, 2020. "Measuring the Effectiveness of US Monetary Policy during the COVID-19 Recession," Papers 2007.15419, arXiv.org.
    3. Michael Beenstock & Daniel Felsenstein, 2021. "A Solution for Absent Spatial Data: The Common Correlated Effects Estimator," International Regional Science Review, , vol. 44(3-4), pages 466-484, May.
    4. Knotek, Edward S. & Zaman, Saeed, 2023. "Real-time density nowcasts of US inflation: A model combination approach," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1736-1760.
    5. Mehmet Balcilar & David Gabauer & Rangan Gupta & Christian Pierdzioch, 2021. "Uncertainty and Forecastability of Regional Output Growth in the United Kingdom: Evidence from Machine Learning," Working Papers 202111, University of Pretoria, Department of Economics.
    6. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2020. "Regional output growth in the United Kingdom: More timely and higher frequency estimates from 1970," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(2), pages 176-197, March.
    7. Mehmet Balcilar & David Gabauer & Rangan Gupta & Christian Pierdzioch, 2022. "Uncertainty and forecastability of regional output growth in the UK: Evidence from machine learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1049-1064, September.
    8. Robert Lehmann & Sascha Möhrle, 2022. "Forecasting Regional Industrial Production with High-Frequency Electricity Consumption Data," CESifo Working Paper Series 9917, CESifo.
    9. Joshua Chan, 2023. "BVARs and Stochastic Volatility," Papers 2310.14438, arXiv.org.
    10. Li Zhe & Serhat Yüksel & Hasan Dinçer & Shahriyar Mukhtarov & Mayis Azizov, 2021. "The Positive Influences of Renewable Energy Consumption on Financial Development and Economic Growth," SAGE Open, , vol. 11(3), pages 21582440211, August.

  9. Joscha Beckmann & Gary Koop & Dimitris Korobilis & Rainer Alexander Schüssler, 2020. "Exchange rate predictability and dynamic Bayesian learning," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(4), pages 410-421, June.
    See citations under working paper version above.
  10. Benati, Luca & Chan, Joshua & Eisenstat, Eric & Koop, Gary, 2020. "Identifying noise shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    See citations under working paper version above.
  11. Joshua C. C. Chan & Eric Eisenstat & Chenghan Hou & Gary Koop, 2020. "Composite likelihood methods for large Bayesian VARs with stochastic volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(6), pages 692-711, September.
    See citations under working paper version above.
  12. Gefang, Deborah & Koop, Gary & Poon, Aubrey, 2020. "Computationally efficient inference in large Bayesian mixed frequency VARs," Economics Letters, Elsevier, vol. 191(C).
    See citations under working paper version above.
  13. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2020. "Regional output growth in the United Kingdom: More timely and higher frequency estimates from 1970," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(2), pages 176-197, March.

    Cited by:

    1. Robert Lehmann & Ida Wikman, 2022. "Quarterly GDP Estimates for the German States," ifo Working Paper Series 370, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    2. Robert Lehmann, 2020. "The Forecasting Power of the ifo Business Survey," CESifo Working Paper Series 8291, CESifo.
    3. Friederike Fourné & Robert Lehmann, 2023. "From Shopping to Statistics: Tracking and Nowcasting Private Consumption Expenditures in Real-Time," CESifo Working Paper Series 10764, CESifo.
    4. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2022. "Reconciled Estimates of Monthly GDP in the US," Working Papers 22-01, Federal Reserve Bank of Cleveland.
    5. Joshua C. C. Chan, 2022. "Comparing Stochastic Volatility Specifications for Large Bayesian VARs," Papers 2208.13255, arXiv.org.
    6. Florian, Huber & Koop, Gary & Onorante, Luca & Pfarrhofer, Michael & Schreiner, Josef, 2021. "Nowcasting in a Pandemic using Non-Parametric Mixed Frequency VARs," Working Papers 2021-01, Joint Research Centre, European Commission.
    7. Martin Feldkircher & Florian Huber & Michael Pfarrhofer, 2020. "Measuring the Effectiveness of US Monetary Policy during the COVID-19 Recession," Papers 2007.15419, arXiv.org.
    8. Haoqi Qian & Zhengyu Shi & Libo Wu, 2021. "Inferring Economic Condition Uncertainty from Electricity Big Data," Papers 2107.11593, arXiv.org, revised May 2023.
    9. Marcellino, Massimiliano & Bai, Yu & Carriero, Andrea & Clark, Todd, 2022. "Macroeconomic Forecasting in a Multi-country Context," CEPR Discussion Papers 16994, C.E.P.R. Discussion Papers.
    10. Bhattacharjee, Arnab & Lisauskaite, Elena & Pabst, Adrian, 2021. "UK regional outlook," National Institute UK Economic Outlook, National Institute of Economic and Social Research, issue 2, pages 42-57.
    11. Deborah Gefang & Gary Koop & Aubrey Poon, 2020. "Computationally Efficient Inference in Large Bayesian Mixed Frequency VARs," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2020-07, Economic Statistics Centre of Excellence (ESCoE).
    12. Niesr, 2021. "Overview," National Institute UK Economic Outlook, National Institute of Economic and Social Research, issue 2, pages 1-4.
    13. Kucuk, Hande & Lenoel, Cyrille & MacQueen, Rory, 2021. "Brisk but not better growth," National Institute UK Economic Outlook, National Institute of Economic and Social Research, issue 2, pages 5-32.
    14. Mehmet Balcilar & David Gabauer & Rangan Gupta & Christian Pierdzioch, 2021. "Uncertainty and Forecastability of Regional Output Growth in the United Kingdom: Evidence from Machine Learning," Working Papers 202111, University of Pretoria, Department of Economics.
    15. Proietti, Tommaso & Giovannelli, Alessandro & Ricchi, Ottavio & Citton, Ambra & Tegami, Christían & Tinti, Cristina, 2021. "Nowcasting GDP and its components in a data-rich environment: The merits of the indirect approach," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1376-1398.
    16. Kucuk, Hande & Lenoel, Cyrille & MacQueen, Rory, 2021. "UK sectoral output," National Institute UK Economic Outlook, National Institute of Economic and Social Research, issue 2, pages 33-41.
    17. Luca Barbaglia & Lorenzo Frattarolo & Niko Hauzenberger & Dominik Hirschbuehl & Florian Huber & Luca Onorante & Michael Pfarrhofer & Luca Tiozzo Pezzoli, 2024. "Nowcasting economic activity in European regions using a mixed-frequency dynamic factor model," Papers 2401.10054, arXiv.org.
    18. Iacopini, Matteo & Poon, Aubrey & Rossini, Luca & Zhu, Dan, 2023. "Bayesian mixed-frequency quantile vector autoregression: Eliciting tail risks of monthly US GDP," Journal of Economic Dynamics and Control, Elsevier, vol. 157(C).
    19. Blagov, Boris & Müller, Henrik & Jentsch, Carsten & Schmidt, Torsten, 2021. "The investment narrative: Improving private investment forecasts with media data," Ruhr Economic Papers 921, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    20. Mehmet Balcilar & David Gabauer & Rangan Gupta & Christian Pierdzioch, 2022. "Uncertainty and forecastability of regional output growth in the UK: Evidence from machine learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1049-1064, September.
    21. Robert Lehmann & Sascha Möhrle, 2022. "Forecasting Regional Industrial Production with High-Frequency Electricity Consumption Data," CESifo Working Paper Series 9917, CESifo.
    22. Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2022. "Bayesian Forecasting in Economics and Finance: A Modern Review," Papers 2212.03471, arXiv.org, revised Jul 2023.
    23. Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
    24. Joshua Chan, 2023. "BVARs and Stochastic Volatility," Papers 2310.14438, arXiv.org.
    25. Chan, Joshua C.C. & Poon, Aubrey & Zhu, Dan, 2023. "High-dimensional conditionally Gaussian state space models with missing data," Journal of Econometrics, Elsevier, vol. 236(1).
    26. Josh Martin & Rebecca Riley, 2023. "Productivity measurement - Reassessing the production function from micro to macro," Working Papers 033, The Productivity Institute.
    27. Robert Lehmann, 2023. "READ-GER: Introducing German Real-Time Regional Accounts Data for Revision Analysis and Nowcasting," CESifo Working Paper Series 10315, CESifo.
    28. Chadha, Jagjit S., 2021. "Foreward," National Institute UK Economic Outlook, National Institute of Economic and Social Research, issue 2, pages 1-3.
    29. Niesr, 2021. "Appendix," National Institute UK Economic Outlook, National Institute of Economic and Social Research, issue 2, pages 58-66.

  14. Koop, Gary & Korobilis, Dimitris & Pettenuzzo, Davide, 2019. "Bayesian compressed vector autoregressions," Journal of Econometrics, Elsevier, vol. 210(1), pages 135-154.
    See citations under working paper version above.
  15. Gary Koop & Dimitris Korobilis, 2019. "Forecasting with High‐Dimensional Panel VARs," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(5), pages 937-959, October.
    See citations under working paper version above.
  16. Grant Allan & Gary Koop & Stuart McIntyre & Paul Smith, 2019. "Nowcasting Using Mixed Frequency Methods: An Application to the Scottish Economy," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(1), pages 12-45, September.

    Cited by:

    1. Arnab Bhattacharjee & Tapabrata Maiti, 2019. "P. C. Mahalanobis in the Context of Current Econometrics Research," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(1), pages 1-11, September.

  17. Desbordes, Rodolphe & Koop, Gary & Vicard, Vincent, 2018. "One size does not fit all… panel data: Bayesian model averaging and data poolability," Economic Modelling, Elsevier, vol. 75(C), pages 364-376.

    Cited by:

    1. Nibbering, D. & Paap, R., 2019. "Panel Forecasting with Asymmetric Grouping," Econometric Institute Research Papers EI-2019-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Simona Bigerna & Maria Chiara D’Errico & Paolo Polinori, 2022. "Sustainable Power Generation in Europe: A Panel Data Analysis of the Effects of Market and Environmental Regulations," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 83(2), pages 445-479, October.
    3. Mariam Camarero & Laura Montolio & Cecilio Tamarit, 2022. "Explaining German outward FDI in the EU: a reassessment using Bayesian model averaging and GLM estimators," Empirical Economics, Springer, vol. 62(2), pages 487-511, February.
    4. Mariam Camarero & Laura Montolio & Cecilio Tamarit, 2019. "Determinants of German outward FDI: variable selection using Bayesian statistical," Working Papers 1906, Department of Applied Economics II, Universidad de Valencia.
    5. Claire Giordano, 2019. "How frequent a BEER? Assessing the impact of data frequency on real exchange rate misalignment estimation," Questioni di Economia e Finanza (Occasional Papers) 522, Bank of Italy, Economic Research and International Relations Area.
    6. Mariam Camarero & Sergi Moliner & Cecilio Tamarit, 2020. "Is there a euro effect in the drivers of US FDI? New evidence using Bayesian Model Averaging techniques," Working Papers 2020/25, Economics Department, Universitat Jaume I, Castellón (Spain).
    7. Mark F. J. Steel, 2020. "Model Averaging and Its Use in Economics," Journal of Economic Literature, American Economic Association, vol. 58(3), pages 644-719, September.
    8. Boonman, Tjeerd M., 2023. "Portfolio capital flows before and after the Global Financial Crisis," Economic Modelling, Elsevier, vol. 127(C).
    9. Florian Morvillier, 2018. "On the impact of the launch of the euro on EMU macroeconomic vulnerability," EconomiX Working Papers 2018-51, University of Paris Nanterre, EconomiX.
    10. Florian Morvillier, 2018. "On the impact of the launch of the euro on EMU macroeconomic vulnerability," Working Papers hal-04141675, HAL.
    11. Raouf Boucekkine & Rodolphe Desbordes & Paolo Melindi-Ghidi, 2019. "Social Divisiveness and Conflicts: Grievances Matter!," Working Papers halshs-02044350, HAL.
    12. Valerio Della Corte & Claire Giordano, 2021. "Methodological issues in the estimation of current account imbalances," Questioni di Economia e Finanza (Occasional Papers) 617, Bank of Italy, Economic Research and International Relations Area.
    13. Mariam Camarero & Sergi Moliner & Cecilio Tamarit, 2019. "Searching The Us Fdi Determinants In The Eu: Is There A Euro Effect?," Working Papers 1916, Department of Applied Economics II, Universidad de Valencia.
    14. Mariam Camarero & Sergi Moliner & Cecilio Tamarit, 2020. "Japan's FDI drivers in a time of financial uncertainty. New evidence based on Bayesian Model," Working Papers 2007, Department of Applied Economics II, Universidad de Valencia.
    15. Coutinho, Leonor & Turrini, Alessandro & Zeugner, Stefan, 2022. "Assessing the euro area current account," Journal of International Money and Finance, Elsevier, vol. 121(C).
    16. Camarero, Mariam & Montolio, Laura & Tamarit, Cecilio, 2019. "What drives German foreign direct investment? New evidence using Bayesian statistical techniques," Economic Modelling, Elsevier, vol. 83(C), pages 326-345.
    17. Boonman, Tjeerd, 2023. "Have drivers of portfolio capital flows changed since the Global Financial Crisis?," MPRA Paper 116507, University Library of Munich, Germany.
    18. Camarero, Mariam & Moliner, Sergi & Tamarit, Cecilio, 2021. "Japan's FDI drivers in a time of financial uncertainty. New evidence based on Bayesian Model Averaging," Japan and the World Economy, Elsevier, vol. 57(C).

  18. Joshua C.C. Chan & Todd E. Clark & Gary Koop, 2018. "A New Model of Inflation, Trend Inflation, and Long‐Run Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(1), pages 5-53, February.
    See citations under working paper version above.
  19. Gary Koop, 2017. "Bayesian Methods for Empirical Macroeconomics," Review of Economic Analysis, Digital Initiatives at the University of Waterloo Library, vol. 9(1), pages 33-56, June.

    Cited by:

    1. Anastasios Evgenidis & Apostolos Fasianos, 2019. "Monetary Policy and Wealth Inequalities in Great Britain: Assessing the role of unconventional policies for a decade of household data," Papers 1912.09702, arXiv.org.
    2. Gianluca Cubadda & Alain Hecq, 2022. "Dimension Reduction for High Dimensional Vector Autoregressive Models," CEIS Research Paper 534, Tor Vergata University, CEIS, revised 24 Mar 2022.
    3. Amaze Lusompa, 2021. "Local Projections, Autocorrelation, and Efficiency," Research Working Paper RWP 21-01, Federal Reserve Bank of Kansas City.
    4. Lenza, Michele & Cimadomo, Jacopo & Giannone, Domenico & Monti, Francesca & Sokol, Andrej, 2021. "Nowcasting with Large Bayesian Vector Autoregressions," CEPR Discussion Papers 15854, C.E.P.R. Discussion Papers.
    5. Fasianos, Apostolos & Evgenidis, Anastasios, 2020. "Unconventional Monetary Policy and Wealth Inequalities in Great Britain," CEPR Discussion Papers 14656, C.E.P.R. Discussion Papers.
    6. Drachal, Krzysztof, 2019. "Forecasting prices of selected metals with Bayesian data-rich models," Resources Policy, Elsevier, vol. 64(C).
    7. Mark F. J. Steel, 2020. "Model Averaging and Its Use in Economics," Journal of Economic Literature, American Economic Association, vol. 58(3), pages 644-719, September.
    8. Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2018. "Macroeconomic Nowcasting and Forecasting with Big Data," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 615-643, August.
    9. Krzysztof Drachal, 2022. "Forecasting the Crude Oil Spot Price with Bayesian Symbolic Regression," Energies, MDPI, vol. 16(1), pages 1-29, December.
    10. Evgenidis, Anastasios & Salachas, Evangelos, 2019. "Unconventional monetary policy and the credit channel in the euro area," Economics Letters, Elsevier, vol. 185(C).
    11. Lake, A., 2020. "Optimal Feasible Expectations in Economics and Finance," Cambridge Working Papers in Economics 20105, Faculty of Economics, University of Cambridge.
    12. Drachal, Krzysztof, 2021. "Forecasting selected energy commodities prices with Bayesian dynamic finite mixtures," Energy Economics, Elsevier, vol. 99(C).
    13. Dimitrios P. Louzis, 2019. "Steady‐state modeling and macroeconomic forecasting quality," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(2), pages 285-314, March.
    14. Karol Szafranek & Marek Kwas & Grzegorz Szafrański & Zuzanna Wośko, 2020. "Common Determinants of Credit Default Swap Premia in the North American Oil and Gas Industry. A Panel BMA Approach," Energies, MDPI, vol. 13(23), pages 1-23, November.
    15. Krzysztof Drachal, 2018. "Some Novel Bayesian Model Combination Schemes: An Application to Commodities Prices," Sustainability, MDPI, vol. 10(8), pages 1-27, August.

  20. Desbordes, Rodolphe & Koop, Gary, 2016. "Should we care about the uncertainty around measures of political-economic development?," Journal of Comparative Economics, Elsevier, vol. 44(3), pages 752-763.

    Cited by:

    1. Stijn Ronsse & Samuel Standaert, 2017. "Combining growth and level data: An estimation of the population of Belgian municipalities between 1880 and 1970," Historical Methods: A Journal of Quantitative and Interdisciplinary History, Taylor & Francis Journals, vol. 50(4), pages 218-226, October.
    2. Simplice A. Asongu & Joseph Nnanna & Vanessa S. Tchamyou, 2020. "Finance, Institutions and Private Investment in Africa," Working Papers of the African Governance and Development Institute. 20/080, African Governance and Development Institute..
    3. Raouf Boucekkine & Rodolphe Desbordes & Paolo Melindi-Ghidi, 2019. "Social Divisiveness and Conflicts: Grievances Matter!," Working Papers halshs-02044350, HAL.
    4. Claudio Detotto & Sauveur Giannoni & Claire Goavec, 2017. "Does good governance attract tourists?," Working Papers 002, Laboratoire Lieux, Identités, eSpaces et Activités (LISA).

  21. Chan, Joshua C.C. & Eisenstat, Eric & Koop, Gary, 2016. "Large Bayesian VARMAs," Journal of Econometrics, Elsevier, vol. 192(2), pages 374-390.
    See citations under working paper version above.
  22. Joshua C. C. Chan & Gary Koop & Simon M. Potter, 2016. "A Bounded Model of Time Variation in Trend Inflation, Nairu and the Phillips Curve," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(3), pages 551-565, April.
    See citations under working paper version above.
  23. Koop, Gary & Korobilis, Dimitris, 2016. "Model uncertainty in Panel Vector Autoregressive models," European Economic Review, Elsevier, vol. 81(C), pages 115-131.
    See citations under working paper version above.
  24. Alex Dickson & Colin Jennings & Gary Koop, 2016. "Domestic Violence and Football in Glasgow: Are Reference Points Relevant?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(1), pages 1-21, February.
    See citations under working paper version above.
  25. Jochmann Markus & Koop Gary, 2015. "Regime-switching cointegration," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(1), pages 35-48, February.
    See citations under working paper version above.
  26. Luc Bauwens & Gary Koop & Dimitris Korobilis & Jeroen V.K. Rombouts, 2015. "The Contribution of Structural Break Models to Forecasting Macroeconomic Series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(4), pages 596-620, June.
    See citations under working paper version above.
  27. Campolieti, Michele & Gefang, Deborah & Koop, Gary, 2014. "A new look at variation in employment growth in Canada: The role of industry, provincial, national and external factors," Journal of Economic Dynamics and Control, Elsevier, vol. 41(C), pages 257-275.

    Cited by:

    1. Tomomi Miyazaki & Haruo Kondoh, 2022. "Effects of Monetary and Fiscal Policy Interactions on Regional Employment: Evidence from Japan," Discussion Papers 2206, Graduate School of Economics, Kobe University.
    2. Alexander Chudik & Janet Koech & Mark Wynne, 2021. "The Heterogeneous Effects of Global and National Business Cycles on Employment in US States and Metropolitan Areas," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(2), pages 495-517, April.
    3. Nidya Listiyono & Adi Wijaya & Irsan Tricahyadinata, 2021. "The effect of investment, education level, and government spending on economic growth and labor absorption in East Kalimantan Province, Indonesia," Technium Social Sciences Journal, Technium Science, vol. 20(1), pages 465-485, June.

  28. Koop, Gary & Korobilis, Dimitris, 2014. "A new index of financial conditions," European Economic Review, Elsevier, vol. 71(C), pages 101-116.
    See citations under working paper version above.
  29. Koop, Gary, 2014. "Forecasting with dimension switching VARs," International Journal of Forecasting, Elsevier, vol. 30(2), pages 280-290.

    Cited by:

    1. Gary Koop & Dimitris Korobilis, 2018. "Forecasting with High-Dimensional Panel VARs," Working Paper series 18-20, Rimini Centre for Economic Analysis.
    2. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
    3. Joshua C C Chan & Eric Eisenstat & Gary Koop, 2014. "Large Bayesian VARMAs," Working Papers 1409, University of Strathclyde Business School, Department of Economics.
    4. Hwang, Youngjin, 2019. "Forecasting recessions with time-varying models," Journal of Macroeconomics, Elsevier, vol. 62(C).
    5. Pierre Guérin & Danilo Leiva-Leon, 2015. "Model Averaging in Markov-Switching Models: Predicting National Recessions with Regional Data," Staff Working Papers 15-24, Bank of Canada.
    6. María Dolores Gadea-Rivas & Ana Gómez-Loscos & Danilo Leiva-Leon, 2017. "The evolution of regional economic interlinkages in Europe," Working Papers 1705, Banco de España.
    7. Drachal, Krzysztof, 2021. "Forecasting crude oil real prices with averaging time-varying VAR models," Resources Policy, Elsevier, vol. 74(C).
    8. Gadea-Rivas, María Dolores & Gómez-Loscos, Ana & Leiva-Leon, Danilo, 2019. "Increasing linkages among European regions. The role of sectoral composition," Economic Modelling, Elsevier, vol. 80(C), pages 222-243.
    9. Davidson, Sharada Nia, 2020. "Interdependence or contagion: A model switching approach with a focus on Latin America," Economic Modelling, Elsevier, vol. 85(C), pages 166-197.

  30. Chan, Joshua C.C. & Koop, Gary, 2014. "Modelling breaks and clusters in the steady states of macroeconomic variables," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 186-193.
    See citations under working paper version above.
  31. Miguel A.G. Belmonte & Gary Koop & Dimitris Korobilis, 2014. "Hierarchical Shrinkage in Time‐Varying Parameter Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(1), pages 80-94, January.
    See citations under working paper version above.
  32. Michele Campolieti & Deborah Gefang & Gary Koop, 2014. "Time Variation In The Dynamics Of Worker Flows: Evidence From North America And Europe," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(2), pages 265-290, March.

    Cited by:

    1. Valadkhani, Abbas & O’Mahony, Barry, 2015. "Dynamics of Australia’s tourism in a multimarket context," Annals of Tourism Research, Elsevier, vol. 55(C), pages 173-177.
    2. Panovska, Irina & Ramamurthy, Srikanth, 2022. "Decomposing the output gap with inflation learning," Journal of Economic Dynamics and Control, Elsevier, vol. 136(C).
    3. Steven M. Fazzari & James Morley & Irina B. Panovska, 2017. "When Do Discretionary Changes in Government Spending or Taxes Have Larger Effects?," Discussion Papers 2017-04, School of Economics, The University of New South Wales.
    4. Donayre, Luiggi & Panovska, Irina, 2016. "State-dependent exchange rate pass-through behavior," Journal of International Money and Finance, Elsevier, vol. 64(C), pages 170-195.
    5. Campolieti, Michele & Gefang, Deborah & Koop, Gary, 2014. "A new look at variation in employment growth in Canada: The role of industry, provincial, national and external factors," Journal of Economic Dynamics and Control, Elsevier, vol. 41(C), pages 257-275.
    6. Elroukh, Ahmed W. & Nikolsko-Rzhevskyy, Alex & Panovska, Irina, 2020. "A look at jobless recoveries in G7 countries," Journal of Macroeconomics, Elsevier, vol. 64(C).

  33. Joshua C. C. Chan & Gary Koop & Simon M. Potter, 2013. "A New Model of Trend Inflation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(1), pages 94-106, January.
    See citations under working paper version above.
  34. Gary Koop & Lise Tole, 2013. "Forecasting the European carbon market," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(3), pages 723-741, June.
    See citations under working paper version above.
  35. Koop, Gary & Korobilis, Dimitris, 2013. "Large time-varying parameter VARs," Journal of Econometrics, Elsevier, vol. 177(2), pages 185-198.
    See citations under working paper version above.
  36. Koop, Gary & Tole, Lise, 2013. "Modeling the relationship between European carbon permits and certified emission reductions," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 166-181.

    Cited by:

    1. Marc Gronwald & Beat Hintermann, 2016. "Explaining the EUA-CER Spread," CESifo Working Paper Series 5795, CESifo.
    2. Xing Yang & Yi-ting Ye & Jia-wen Li & Jun-long Mi, 2023. "Asymmetric time-varying dependence and variable structure dependence measurement and analysis of EUA and CER," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 18, pages 609-621.
    3. Gazi Salah Uddin & Jose Areola Hernandez & Syed Jawad Hussain Shahzad & Axel Hedström, 2018. "Multivariate dependence and spillover effects across energy commodities and diversification potentials of carbon assets," Post-Print hal-01996386, HAL.
    4. Kapoor, Nimisha & Ghosh, Sajal, 2014. "Long-term association between European and Indian markets on carbon credit price," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 656-662.
    5. Khurshid Ahmad & JingGuang Han & Elaine Hutson & Colm Kearney & Sha Liu, 2016. "Media-expressed negative tone and firm-level stock returns," Open Access publications 10197/8208, Research Repository, University College Dublin.
    6. Beat Hintermann & Marc Gronwald, 2019. "Linking with Uncertainty: The Relationship Between EU ETS Pollution Permits and Kyoto Offsets," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 74(2), pages 761-784, October.
    7. Elena Villar-Rubio & María-Dolores Huete-Morales & Federico Galán-Valdivieso, 2023. "Using EGARCH models to predict volatility in unconsolidated financial markets: the case of European carbon allowances," Journal of Environmental Studies and Sciences, Springer;Association of Environmental Studies and Sciences, vol. 13(3), pages 500-509, September.
    8. Mandaloufas, Melissa & Lamas, Wendell de Queiroz & Brown, Scott & Irizarry Quintero, Anamari, 2015. "Energy balance analysis of the Brazilian alcohol for flex fuel production," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 403-414.
    9. Kanamura, Takashi, 2016. "Role of carbon swap trading and energy prices in price correlations and volatilities between carbon markets," Energy Economics, Elsevier, vol. 54(C), pages 204-212.

  37. Markus Jochmann & Gary Koop & Roberto Leon‐Gonzalez & Rodney W. Strachan, 2013. "Stochastic search variable selection in vector error correction models with an application to a model of the UK macroeconomy," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(1), pages 62-81, January.
    See citations under working paper version above.
  38. Gary M. Koop, 2013. "Forecasting with Medium and Large Bayesian VARS," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(2), pages 177-203, March.
    See citations under working paper version above.
  39. Lise Tole & Gary Koop, 2013. "Estimating the impact on efficiency of the adoption of a voluntary environmental standard: an empirical study of the global copper mining industry," Journal of Productivity Analysis, Springer, vol. 39(1), pages 35-45, February.
    See citations under working paper version above.
  40. Gary Koop & M. Hashem Pesaran & Ron P. Smith, 2013. "On Identification of Bayesian DSGE Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(3), pages 300-314, July.
    See citations under working paper version above.
  41. Koop, Gary & Leon-Gonzalez, Roberto & Strachan, Rodney, 2012. "Bayesian model averaging in the instrumental variable regression model," Journal of Econometrics, Elsevier, vol. 171(2), pages 237-250.
    See citations under working paper version above.
  42. Joshua C.C. Chan & Gary Koop & Roberto Leon-Gonzalez & Rodney W. Strachan, 2012. "Time Varying Dimension Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(3), pages 358-367, January.
    See citations under working paper version above.
  43. Gary Koop & Dimitris Korobilis, 2012. "Forecasting Inflation Using Dynamic Model Averaging," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(3), pages 867-886, August.
    See citations under working paper version above.
  44. Gefang, Deborah & Koop, Gary & Potter, Simon M., 2012. "The dynamics of UK and US inflation expectations," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3120-3133.
    See citations under working paper version above.
  45. Gary Koop, 2012. "Using VARs and TVP-VARs with Many Macroeconomic Variables," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 4(3), pages 143-167, September.
    See citations under working paper version above.
  46. Koop, Gary & Potter, Simon M., 2011. "Time varying VARs with inequality restrictions," Journal of Economic Dynamics and Control, Elsevier, vol. 35(7), pages 1126-1138, July.

    Cited by:

    1. Liudas Giraitis & George Kapetanios & Tony Yates, 2015. "Inference on Multivariate Heteroscedastic Time Varying Random Coefficient Models," Working Papers 767, Queen Mary University of London, School of Economics and Finance.
    2. Delle Monache, Davide & Petrella, Ivan, 2017. "Adaptive models and heavy tails with an application to inflation forecasting," International Journal of Forecasting, Elsevier, vol. 33(2), pages 482-501.
    3. Markku Lanne & Jani Luoto, 2017. "A New Time‐Varying Parameter Autoregressive Model for U.S. Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 969-995, August.
    4. Dimitris Korobilis, 2009. "Assessing the Transmission of Monetary Policy Shocks Using Dynamic Factor Models," Working Paper series 35_09, Rimini Centre for Economic Analysis.
    5. Eric Eisenstat & Joshua C.C. Chan & Rodney W. Strachan, 2014. "Stochastic Model Specification Search for Time-Varying Parameter VARs," CAMA Working Papers 2014-23, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    6. Giacomo Rella, 2021. "The Fed, housing and household debt over time," Department of Economics University of Siena 850, Department of Economics, University of Siena.
    7. Joshua C.C. Chan & Garry Koop & Roberto Leon Gonzales & Rodney W. Strachan, 2010. "Time Varying Dimension Models," ANU Working Papers in Economics and Econometrics 2010-523, Australian National University, College of Business and Economics, School of Economics.
    8. Tao Zeng & Yong Li & Jun Yu, 2014. "Deviance Information Criterion for Comparing VAR Models," Advances in Econometrics, in: Essays in Honor of Peter C. B. Phillips, volume 33, pages 615-637, Emerald Group Publishing Limited.
    9. Pami Dua & Deepika Goel, 2021. "Inflation Persistence in India," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(3), pages 525-553, September.
    10. Adam, Marc C. & Jansson, Walter, 2019. "Credit constraints and the propagation of the Great Depression in Germany," Discussion Papers 2019/12, Free University Berlin, School of Business & Economics.
    11. Koop, Gary & Korobilis, Dimitris, 2010. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(4), pages 267-358, July.
    12. Danilo Leiva-Leon & Luis Uzeda, 2023. "Endogenous Time Variation in Vector Autoregressions," The Review of Economics and Statistics, MIT Press, vol. 105(1), pages 125-142, January.
    13. Davide Delle Monache & Ivan Petrella, 2014. "Adaptive Models and Heavy Tails," Working Papers 720, Queen Mary University of London, School of Economics and Finance.
    14. Benjamin Wong, 2013. "Inflation Dynamics and The Role of Oil Shocks: How Different Were the 1970s?," CAMA Working Papers 2013-59, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    15. Chan, Joshua & Koop, Gary & Potter, Simon, 2012. "A new model of trend inflation," MPRA Paper 39496, University Library of Munich, Germany.
    16. KOROBILIS, Dimitris, 2011. "VAR forecasting using Bayesian variable selection," LIDAM Discussion Papers CORE 2011022, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    17. Arnoud Stevens & Joris Wauters, 2021. "Is euro area lowflation here to stay? Insights from a time‐varying parameter model with survey data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 566-586, August.
    18. Gert Peersman & Sebastian K. Rüth & Wouter Van der Veken, 2019. "The Interplay between Oil and Food Commodity Prices: Has It Changed over Time?," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 19/978, Ghent University, Faculty of Economics and Business Administration.
    19. James M. Nason & Gregor W. Smith, 2021. "UK inflation forecasts since the thirteenth century," CAMA Working Papers 2021-32, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    20. Meradj Mortezapouraghdam, 2016. "Three Essays on the Role of Frictions in the Economy," Sciences Po publications info:hdl:2441/293qice3lj8, Sciences Po.
    21. Jeremy B. Rudd, 2022. "The Anatomy of Single-Digit Inflation in the 1960s," Finance and Economics Discussion Series 2022-029, Board of Governors of the Federal Reserve System (U.S.).
    22. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano & Mertens, Elmar, 2023. "Shadow-rate VARs," Discussion Papers 14/2023, Deutsche Bundesbank.
    23. Guglielminetti, Elisa & Pouraghdam, Meradj, 2018. "Time-varying job creation and macroeconomic shocks," Labour Economics, Elsevier, vol. 50(C), pages 156-179.
    24. Ekaterina V. Peneva & Jeremy B. Rudd, 2015. "The Passthrough of Labor Costs to Price Inflation," Finance and Economics Discussion Series 2015-42, Board of Governors of the Federal Reserve System (U.S.).
    25. Reusens Peter & Croux Christophe, 2017. "Detecting time variation in the price puzzle: a less informative prior choice for time varying parameter VAR models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(4), pages 1-18, September.
    26. Ekaterina V. Peneva & Jeremy B. Rudd, 2017. "The Passthrough of Labor Costs to Price Inflation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(8), pages 1777-1802, December.
    27. Meradj Morteza Pouraghdam, 2016. "Three essays on the role of frictions in the economy [Trois essais sur le rôle du désaccord en économie]," SciencePo Working papers Main tel-03498781, HAL.
    28. Ganics, Gergely & Odendahl, Florens, 2021. "Bayesian VAR forecasts, survey information, and structural change in the euro area," International Journal of Forecasting, Elsevier, vol. 37(2), pages 971-999.
    29. Benjamin Wong, 2013. "The Evolution of the U.S. Output-Inflation Tradeoff," CAMA Working Papers 2013-70, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    30. Qian, Hang, 2015. "Inequality Constrained State Space Models," MPRA Paper 66447, University Library of Munich, Germany.
    31. Todd E. Clark & Taeyoung Doh, 2011. "A Bayesian evaluation of alternative models of trend inflation," Working Papers (Old Series) 1134, Federal Reserve Bank of Cleveland.
    32. Bala Dahiru Abdullahi, 2016. "Time-Varying VAR with Stochastic Volatility and Monetary Policy Dynamics in Nigeria," Economics Bulletin, AccessEcon, vol. 36(4), pages 2237-2249.
    33. Fabio Canova & Fernando J. Pérez Forero, 2012. "Estimating Overidentified, Nonrecursive Time-Varying Coefficients Structural VARs," Working Papers 637, Barcelona School of Economics.
    34. Christou, Christina & Gupta, Rangan & Nyakabawo, Wendy, 2019. "Time-varying impact of uncertainty shocks on the US housing market," Economics Letters, Elsevier, vol. 180(C), pages 15-20.
    35. Chunyeung Kwok, 2022. "Estimating Structural Shocks with the GVAR-DSGE Model: Pre- and Post-Pandemic," Mathematics, MDPI, vol. 10(10), pages 1-32, May.
    36. Angelia L. Grant, 2017. "The Early Millennium Slowdown: Replicating the Peersman (2005) Results," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 224-232, January.
    37. Giraitis, Liudas & Kapetanios, George & Theodoridis, Konstantinos & Yates, Tony, 2014. "Estimating time-varying DSGE models using minimum distance methods," Bank of England working papers 507, Bank of England.
    38. Marco Del Negro & Giorgio E. Primiceri, 2013. "Time-Varying Structural Vector Autoregressions and Monetary Policy: a Corrigendum," Staff Reports 619, Federal Reserve Bank of New York.
    39. Clark, Todd E. & Doh, Taeyoung, 2014. "Evaluating alternative models of trend inflation," International Journal of Forecasting, Elsevier, vol. 30(3), pages 426-448.
    40. Camba-Méndez, Gonzalo, 2020. "On the inflation risks embedded in sovereign bond yields," Working Paper Series 2423, European Central Bank.
    41. Huachen Li, 2023. "The Time‐Varying Response of Hours Worked to a Productivity Shock," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 55(7), pages 1907-1935, October.

  47. Koop, Gary & Leon-Gonzalez, Roberto & Strachan, Rodney W., 2011. "Bayesian inference in a time varying cointegration model," Journal of Econometrics, Elsevier, vol. 165(2), pages 210-220.
    See citations under working paper version above.
  48. Lise Tole & Gary Koop, 2011. "Do environmental regulations affect the location decisions of multinational gold mining firms?," Journal of Economic Geography, Oxford University Press, vol. 11(1), pages 151-177, January.

    Cited by:

    1. Liu, Shaohui & Liu, Chuanjiang & Yang, Mian, 2022. "Greening of Chinese industrial sector: Stakeholders' responsiveness to non-governmental environmental monitoring," China Economic Review, Elsevier, vol. 72(C).
    2. Anja Tolonen, 2019. "Endogenous Gender Roles: Evidence from Africa’s Gold Mining Industry," OxCarre Working Papers 209, Oxford Centre for the Analysis of Resource Rich Economies, University of Oxford.
    3. Yıldız, Taşkın Deniz, 2020. "The impacts of EIA procedure on the mining sector in the permit process of mining operating activities & Turkey analysis," Resources Policy, Elsevier, vol. 67(C).
    4. Yu-Hong Ai & Di-Yun Peng & Huan-Huan Xiong, 2021. "Impact of Environmental Regulation Intensity on Green Technology Innovation: From the Perspective of Political and Business Connections," Sustainability, MDPI, vol. 13(9), pages 1-23, April.
    5. Yang, Ruicheng & Xing, Weize & Hou, Shuxia, 2020. "Evaluating the risk factors influencing foreign direct investment in Mongolia's mining sector: A complex network approach," Emerging Markets Review, Elsevier, vol. 43(C).
    6. Cui, Jingbo & Moschini, GianCarlo, 2020. "Firm internal network, environmental regulation, and plant death," Journal of Environmental Economics and Management, Elsevier, vol. 101(C).
    7. Lutao Ning & Fan Wang, 2018. "Does FDI Bring Environmental Knowledge Spillovers to Developing Countries? The Role of the Local Industrial Structure," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 71(2), pages 381-405, October.
    8. Zhonghua Cheng & Lianshui Li & Jun Liu, 2018. "The spatial correlation and interaction between environmental regulation and foreign direct investment," Journal of Regulatory Economics, Springer, vol. 54(2), pages 124-146, October.
    9. ROCHELANDET, Fabrice & TAI, Silvio H.T., 2012. "Do privacy laws affect the location decisions of internet firms? evidence for privacy havens," MPRA Paper 37354, University Library of Munich, Germany.
    10. Yunyi Hu & Haitao Yin & Jon J. Moon, 2022. "Environmental regulation and foreign investment: Evidence from China," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 31(4), pages 862-883, November.
    11. Duanmu, Jing-Lin, 2014. "A race to lower standards? Labor standards and location choice of outward FDI from the BRIC countries," International Business Review, Elsevier, vol. 23(3), pages 620-634.
    12. Assad Ullah & Xinshun Zhao & Muhammad Abdul Kamal & Jiajia Zheng, 2022. "Environmental regulations and inward FDI in China: Fresh evidence from the asymmetric autoregressive distributed lag approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 1340-1356, January.
    13. Söderholm, Kristina & Söderholm, Patrik & Helenius, Heidi & Pettersson, Maria & Viklund, Roine & Masloboev, Vladimir & Mingaleva, Tatiana & Petrov, Viktor, 2015. "Environmental regulation and competitiveness in the mining industry: Permitting processes with special focus on Finland, Sweden and Russia," Resources Policy, Elsevier, vol. 43(C), pages 130-142.
    14. Timothy Laing, 2015. "Rights to the forest, REDD+ and elections: Mining in Guyana," GRI Working Papers 181, Grantham Research Institute on Climate Change and the Environment.
    15. Slade, Margaret E., 2015. "The rise and fall of an industry: Entry in U.S. copper mining, 1835–1986," Resource and Energy Economics, Elsevier, vol. 42(C), pages 141-169.
    16. Daniela Maggioni & Grazia D. Santangelo & Seda Koymen-Ozer, 2019. "MNEs’ location strategies and labor standards: The role of operating and reputational considerations across industries," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 50(6), pages 948-972, August.
    17. Liu, Chelsea, 2018. "Are women greener? Corporate gender diversity and environmental violations," Journal of Corporate Finance, Elsevier, vol. 52(C), pages 118-142.
    18. Mei Ren & Caihong Huang & Xiaomin Wang & Wei Hu & Wenxin Zhang, 2019. "Research on the Distribution of Pollution-Intensive Industries and Their Spatial Effects in China," Sustainability, MDPI, vol. 11(19), pages 1-20, September.
    19. Söderholm, Patrik, 2023. "How environmental permitting uncertainty in large-scale mining could influence subcontractors: The underlying chicken-and-egg problem," Resources Policy, Elsevier, vol. 82(C).

  49. Koop, Gary & Korobilis, Dimitris, 2011. "UK macroeconomic forecasting with many predictors: Which models forecast best and when do they do so?," Economic Modelling, Elsevier, vol. 28(5), pages 2307-2318, September.
    See citations under working paper version above.
  50. Gefang, Deborah & Koop, Gary & Potter, Simon M., 2011. "Understanding liquidity and credit risks in the financial crisis," Journal of Empirical Finance, Elsevier, vol. 18(5), pages 903-914.
    See citations under working paper version above.
  51. Koop, Gary & Potter, Simon, 2010. "A flexible approach to parametric inference in nonlinear and time varying time series models," Journal of Econometrics, Elsevier, vol. 159(1), pages 134-150, November.
    See citations under working paper version above.
  52. Jochmann, Markus & Koop, Gary & Strachan, Rodney W., 2010. "Bayesian forecasting using stochastic search variable selection in a VAR subject to breaks," International Journal of Forecasting, Elsevier, vol. 26(2), pages 326-347, April.
    See citations under working paper version above.
  53. Koop, Gary & Korobilis, Dimitris, 2010. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(4), pages 267-358, July.
    See citations under working paper version above.
  54. Koop, Gary & Leon-Gonzalez, Roberto & Strachan, Rodney W., 2010. "Dynamic Probabilities of Restrictions in State Space Models: An Application to the Phillips Curve," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(3), pages 370-379.
    See citations under working paper version above.
  55. Jochmann, Markus & Koop, Gary & Potter, Simon M., 2010. "Modeling the dynamics of inflation compensation," Journal of Empirical Finance, Elsevier, vol. 17(1), pages 157-167, January.
    See citations under working paper version above.
  56. Gary Koop & Roberto León-González & Rodney W. Strachan, 2010. "Efficient Posterior Simulation for Cointegrated Models with Priors on the Cointegration Space," Econometric Reviews, Taylor & Francis Journals, vol. 29(2), pages 224-242, April.
    See citations under working paper version above.
  57. Gary Koop & Simon M. Potter, 2009. "Prior Elicitation In Multiple Change-Point Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 50(3), pages 751-772, August.
    See citations under working paper version above.
  58. Koop, Gary & Leon-Gonzalez, Roberto & Strachan, Rodney W., 2009. "On the evolution of the monetary policy transmission mechanism," Journal of Economic Dynamics and Control, Elsevier, vol. 33(4), pages 997-1017, April.

    Cited by:

    1. Cross, Jamie & Nguyen, Bao H., 2017. "The relationship between global oil price shocks and China's output: A time-varying analysis," Energy Economics, Elsevier, vol. 62(C), pages 79-91.
    2. Florian Huber & Josef Schreiner, 2023. "Are Phillips curves in CESEE still alive and well behaved?," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue Q3/23, pages 7-27.
    3. Dimitris Korobilis, 2009. "Assessing the Transmission of Monetary Policy Shocks Using Dynamic Factor Models," Working Paper series 35_09, Rimini Centre for Economic Analysis.
    4. Jakub Matějů, 2019. "What Drives the Strength of Monetary Policy Transmission?," International Journal of Central Banking, International Journal of Central Banking, vol. 15(3), pages 59-87, September.
    5. Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2023. "Bayesian Modeling of Time-Varying Parameters Using Regression Trees," Working Papers 23-05, Federal Reserve Bank of Cleveland.
    6. Florian Huber & Manfred M. Fischer, 2018. "A Markov Switching Factor‐Augmented VAR Model for Analyzing US Business Cycles and Monetary Policy," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 80(3), pages 575-604, June.
    7. Florian Huber & Gregor Kastner & Martin Feldkircher, 2016. "Should I stay or should I go? A latent threshold approach to large-scale mixture innovation models," Papers 1607.04532, arXiv.org, revised Jul 2018.
    8. Miguel A.G. Belmonte & Gary Koop & Dimitris Korobilis, 2014. "Hierarchical Shrinkage in Time‐Varying Parameter Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(1), pages 80-94, January.
    9. Vasilios Plakandaras & Rangan Gupta & Constantinos Katrakilidis & Mark E. Wohar, 2017. "Time-Varying Role of Macroeconomic Shocks on House Prices in the US and UK: Evidence from Over 150 Years of Data," Working Papers 201765, University of Pretoria, Department of Economics.
    10. Gary Koop & Dimitris Korobilis, 2012. "Forecasting Inflation Using Dynamic Model Averaging," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(3), pages 867-886, August.
    11. Tsionas, Mike G. & Izzeldin, Marwan & Trapani, Lorenzo, 2022. "Estimation of large dimensional time varying VARs using copulas," European Economic Review, Elsevier, vol. 141(C).
    12. Hodula Martin & Vahalík Bohdan, 2017. "Effects of oil shocks on EMU exports: technological level differences," Review of Economic Perspectives, Sciendo, vol. 17(4), pages 399-423, December.
    13. Joshua C.C. Chan & Rodney Strachan, 2014. "The Zero Lower Bound: Implications for Modelling the Interest Rate," Working Paper series 42_14, Rimini Centre for Economic Analysis.
    14. IWATA, Yasuharu & IIBOSHI, Hirokuni, 2023. "The Nexus between Public Debt and the Government Spending Multiplier: Fiscal Adjustments Matter," MPRA Paper 116355, University Library of Munich, Germany.
    15. Florian Huber & Maria Teresa Punzi, 2016. "International Housing Markets, Unconventional Monetary Policy and the Zero Lower Bound," Department of Economics Working Papers wuwp216, Vienna University of Economics and Business, Department of Economics.
    16. Valcarcel, Victor J., 2013. "Exchange rate volatility and the time-varying effects of aggregate shocks," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 822-843.
    17. KANAZAWA, Nobuyuki & 金澤, 伸幸, 2018. "Radial Basis Functions Neural Networks for Nonlinear Time Series Analysis and Time-Varying Effects of Supply Shocks," Discussion paper series HIAS-E-64, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    18. Karlsson, Sune & Österholm, Pär, 2018. "Is the US Phillips Curve Stable? Evidence from Bayesian VARs," Working Papers 2018:5, Örebro University, School of Business.
    19. Jaromír Baxa & Roman Horváth & Borek Vasícek, 2010. "How Does Monetary Policy Change? Evidence on Inflation Targeting Countries," Working Papers wpdea1007, Department of Applied Economics at Universitat Autonoma of Barcelona.
    20. Gary Koop & Dimitris Korobilis, 2012. "Large Time-Varying Parameter VARs," Working Paper series 11_12, Rimini Centre for Economic Analysis.
    21. Chan, Joshua C.C. & Eisenstat, Eric & Strachan, Rodney W., 2020. "Reducing the state space dimension in a large TVP-VAR," Journal of Econometrics, Elsevier, vol. 218(1), pages 105-118.
    22. Erdenebat Bataa & Marwan Izzeldin & Denise Osborn, 2015. "Changes in the global oil market," Working Papers 75761696, Lancaster University Management School, Economics Department.
    23. Eric Eisenstat & Joshua C.C. Chan & Rodney W. Strachan, 2014. "Stochastic Model Specification Search for Time-Varying Parameter VARs," CAMA Working Papers 2014-23, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    24. Crespo Cuaresma, Jesus & Doppelhofer, Gernot & Feldkircher, Martin & Huber, Florian, 2018. "Spillovers from US monetary policy: Evidence from a time-varying parameter GVAR model," Working Papers in Economics 2018-6, University of Salzburg.
    25. Joshua C.C. Chan & Garry Koop & Roberto Leon Gonzales & Rodney W. Strachan, 2010. "Time Varying Dimension Models," ANU Working Papers in Economics and Econometrics 2010-523, Australian National University, College of Business and Economics, School of Economics.
    26. Joshua C.C. Chan & Eric Eisenstat & Chenghan Hou & Gary Koop, 2018. "Composite likelihood methods for large Bayesian VARs with stochastic volatility," CAMA Working Papers 2018-26, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    27. Dumitriu, Ramona & Stefanescu, Razvan, 2013. "Provocările politicii monetare [Monetary policy challenges]," MPRA Paper 50261, University Library of Munich, Germany, revised 28 Sep 2013.
    28. Josef Hollmayr & Christian Matthes, 2013. "Learning about fiscal policy and the effects of policy uncertainty," Working Paper 13-15, Federal Reserve Bank of Richmond.
    29. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    30. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
    31. Michele Campolieti & Deborah Gefang & Gary Koop, 2011. "Time Variation in the Dynamics of Worker Flows: Evidence from the US and Canada," Working Papers 1138, University of Strathclyde Business School, Department of Economics.
    32. Prüser, Jan, 2021. "The horseshoe prior for time-varying parameter VARs and Monetary Policy," Journal of Economic Dynamics and Control, Elsevier, vol. 129(C).
    33. Hou, Chenghan, 2017. "Infinite hidden markov switching VARs with application to macroeconomic forecast," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1025-1043.
    34. Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2020. "Bayesian Modelling of TVP-VARs Using Regression Trees," Working Papers 2308, University of Strathclyde Business School, Department of Economics, revised Aug 2023.
    35. Behera, Harendra Kumar & Patra, Michael Debabrata, 2022. "Measuring trend inflation in India," Journal of Asian Economics, Elsevier, vol. 80(C).
    36. Koop, Gary & Korobilis, Dimitris, 2010. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(4), pages 267-358, July.
    37. Andrew Filardo & Jouchi Nakajima, 2018. "Effectiveness of unconventional monetary policies in a low interest rate environment," BIS Working Papers 691, Bank for International Settlements.
    38. Jamshaid ur Rehman & Khalil Ahmad & Jawaria Arif, 2022. "Transmission Mechanism of Monetary Policy in BRICS Countries: A Comparative Response with the USA," Journal of Policy Research (JPR), Research Foundation for Humanity (RFH), vol. 8(4), pages 23-34, December.
    39. Clara De Luigi & Florian Huber & Josef Schreiner, 2019. "The impact of labor cost growth on inflation in selected CESEE countries," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue Q4/19, pages 56-78.
    40. Chance Mwabutwa & Manoel Bittencourt & Nicola Viegi, 2013. "Evolution of Monetary Policy Transmission Mechanism in Malawi: A TVP-VAR Approach," Working Papers 201327, University of Pretoria, Department of Economics.
    41. Michal Franta & Roman Horvath & Marek Rusnak, 2011. "Evaluating Changes in the Monetary Transmission Mechanism in the Czech Republic," Working Papers 2011/13, Czech National Bank.
    42. Kabundi, Alain & De Simone, Francisco Nadal, 2020. "Monetary policy and systemic risk-taking in the euro area banking sector," Economic Modelling, Elsevier, vol. 91(C), pages 736-758.
    43. Sune Karlsson & Pär Österholm, 2020. "A note on the stability of the Swedish Phillips curve," Empirical Economics, Springer, vol. 59(6), pages 2573-2612, December.
    44. Michael T. Belongia & Peter N. Ireland, 2016. "The Evolution of U.S. Monetary Policy: 2000 - 2007," NBER Working Papers 22693, National Bureau of Economic Research, Inc.
    45. Marcellino, Massimiliano & Bai, Yu & Carriero, Andrea & Clark, Todd, 2022. "Macroeconomic Forecasting in a Multi-country Context," CEPR Discussion Papers 16994, C.E.P.R. Discussion Papers.
    46. Chauvet, Marcelle & Potter, Simon, 2013. "Forecasting Output," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 141-194, Elsevier.
    47. Jesús Crespo Cuaresma & Gernot Doppelhofer & Martin Feldkircher & Florian Huber, 2019. "Spillovers from US monetary policy: evidence from a time varying parameter global vector auto‐regressive model," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 182(3), pages 831-861, June.
    48. Guidolin, Massimo & Hansen, Erwin & Pedio, Manuela, 2019. "Cross-asset contagion in the financial crisis: A Bayesian time-varying parameter approach," Journal of Financial Markets, Elsevier, vol. 45(C), pages 83-114.
    49. Abdurrahman Nazif Çatik & Mehmet Karaçuka & A. Özlem Önder, 2022. "The Time-Varying Impact of External Shocks on the Consumer Price Components: Evidence from an Emerging Market," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(4), pages 781-807, December.
    50. Berg, Tim Oliver, 2014. "Time Varying Fiscal Multipliers in Germany," MPRA Paper 57223, University Library of Munich, Germany.
    51. Stefano Grassi & Nima Nonejad & Paolo Santucci de Magistris, 2014. "Forecasting with the Standardized Self-Perturbed Kalman Filter," CREATES Research Papers 2014-12, Department of Economics and Business Economics, Aarhus University.
    52. Yin, Hong & Chang, Long & Wang, Shu, 2023. "The impact of China's economic uncertainty on commodity and financial markets," Resources Policy, Elsevier, vol. 84(C).
    53. Rajendra Narayan Paramanik & Bandi Kamaiah, 2014. "A Structural Vector Autoregression Model for Monetary Policy Analysis in India," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 8(4), pages 401-429, November.
    54. Nikita Moiseev & Alexey Mikhaylov & Hasan Dinçer & Serhat Yüksel, 2023. "Market capitalization shock effects on open innovation models in e-commerce: golden cut q-rung orthopair fuzzy multicriteria decision-making analysis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-25, December.
    55. Jerome Creel & Paul Hubert, 2008. "Has the Adoption of Inflation Targeting Represented a Regime Switch? Empirical evidence from Canada, Sweden and the UK," Documents de Travail de l'OFCE 2008-25, Observatoire Francais des Conjonctures Economiques (OFCE).
    56. KOROBILIS, Dimitris, 2011. "VAR forecasting using Bayesian variable selection," LIDAM Discussion Papers CORE 2011022, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    57. Ewing, Bradley T. & Kang, Wensheng & Ratti, Ronald A., 2018. "The dynamic effects of oil supply shocks on the US stock market returns of upstream oil and gas companies," Energy Economics, Elsevier, vol. 72(C), pages 505-516.
    58. Eric Eisenstat & Joshua C.C. Chan & Rodney W. Strachan, 2018. "Reducing Dimensions in a Large TVP-VAR," Working Paper Series 43, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
    59. Madison Terrell & Qazi Haque & Jamie L. Cross & Firmin Doko Tchatoka, 2023. "Monetary policy shocks and exchange rate dynamics in small open economies," School of Economics and Public Policy Working Papers 2023-04 Classification-C3, University of Adelaide, School of Economics and Public Policy.
    60. Daniele Bianchi & Kenichiro McAlinn, 2018. "Large-Scale Dynamic Predictive Regressions," Papers 1803.06738, arXiv.org.
    61. Florian Huber & Maria Teresa Punzi, 2017. "The shortage of safe assets in the US investment portfolio: Some international evidence," Department of Economics Working Papers wuwp243, Vienna University of Economics and Business, Department of Economics.
    62. Smith, Michael Stanley, 2015. "Copula modelling of dependence in multivariate time series," International Journal of Forecasting, Elsevier, vol. 31(3), pages 815-833.
    63. Haakon Kavli & Nicola Viegi, 2017. "Are Determinants of Portfolio Flows Always the Same? - South African Results from a Time Varying Parameter Var Model," South African Journal of Economics, Economic Society of South Africa, vol. 85(1), pages 3-27, March.
    64. Michael Ellington, 2022. "The Empirical Relevance of the Shadow Rate and the Zero Lower Bound," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(6), pages 1605-1635, September.
    65. Ding, Qian & Huang, Jianbai & Zhang, Hongwei, 2021. "The time-varying effects of financial and geopolitical uncertainties on commodity market dynamics: A TVP-SVAR-SV analysis," Resources Policy, Elsevier, vol. 72(C).
    66. Koop, Gary & Tole, Lise, 2013. "Modeling the relationship between European carbon permits and certified emission reductions," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 166-181.
    67. Miguel, Belmonte & Gary, Koop, 2013. "Model Switching and Model Averaging in Time- Varying Parameter Regression Models," SIRE Discussion Papers 2013-34, Scottish Institute for Research in Economics (SIRE).
    68. Stefano Grassi & Paolo Santucci de Magistris, 2013. "It’s all about volatility (of volatility): evidence from a two-factor stochastic volatility model," CREATES Research Papers 2013-03, Department of Economics and Business Economics, Aarhus University.
    69. Amine Ben Amar, 2022. "On the role of Islamic banks in the monetary policy transmission in Saudi Arabia," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(1), pages 55-94, March.
    70. Pacifico, Antonio, 2020. "Structural Panel Bayesian VAR with Multivariate Time-varying Volatility to jointly deal with Structural Changes, Policy Regime Shifts, and Endogeneity Issues," MPRA Paper 104292, University Library of Munich, Germany.
    71. Gregor Kastner & Florian Huber, 2020. "Sparse Bayesian vector autoregressions in huge dimensions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1142-1165, November.
    72. Koop, Gary & Potter, Simon M., 2011. "Time varying VARs with inequality restrictions," Journal of Economic Dynamics and Control, Elsevier, vol. 35(7), pages 1126-1138, July.
    73. Karlsson, Sune & Österholm, Pär, 2019. "Volatilities, drifts and the relation between treasury yields and the corporate bond yield spread in australia," Finance Research Letters, Elsevier, vol. 30(C), pages 378-384.
    74. Maria Sole Pagliari, 2021. "Does one (unconventional) size fit all? Effects of the ECB's unconventional monetary policies on the euro area economies," Working papers 829, Banque de France.
    75. Liu, Yuelin & Morley, James, 2014. "Structural evolution of the postwar U.S. economy," Journal of Economic Dynamics and Control, Elsevier, vol. 42(C), pages 50-68.
    76. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    77. Jiménez-Rodríguez, Rebeca, 2022. "Oil shocks and global economy," Energy Economics, Elsevier, vol. 115(C).
    78. Pan, Zhiyuan & Wang, Qing & Wang, Yudong & Yang, Li, 2018. "Forecasting U.S. real GDP using oil prices: A time-varying parameter MIDAS model," Energy Economics, Elsevier, vol. 72(C), pages 177-187.
    79. Joshua C.C. Chan, 2015. "Specification tests for time-varying parameter models with stochastic volatility," CAMA Working Papers 2015-42, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    80. Jouchi Nakajima & Mike West, 2013. "Bayesian Analysis of Latent Threshold Dynamic Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(2), pages 151-164, April.
    81. Fischer, Manfred M. & Hauzenberger, Niko & Huber, Florian & Pfarrhofer, Michael, 2022. "General Bayesian time-varying parameter VARs for modeling government bond yields," Working Papers in Regional Science 2021/01, WU Vienna University of Economics and Business.
    82. Domenico Lombardi & Pierre L. Siklos & Xiangyou Xie, 2018. "Monetary policy transmission in systemically important economies and China’s impact," CAMA Working Papers 2018-50, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    83. Irfan Akbar Kazi & Hakimzadi Wagan & Farhan Akbar, 2012. "The changing international transmission of US monetary policy shocks: is there evidence of contagion effect on OECD countries," EconomiX Working Papers 2012-27, University of Paris Nanterre, EconomiX.
    84. Christiane Baumeister & Luca Benati, 2012. "Unconventional Monetary Policy and the Great Recession: Estimating the Macroeconomic Effects of a Spread Compression at the Zero Lower Bound," Staff Working Papers 12-21, Bank of Canada.
    85. De Luigi, Clara & Huber, Florian, 2018. "Debt regimes and the effectiveness of monetary policy," Journal of Economic Dynamics and Control, Elsevier, vol. 93(C), pages 218-238.
    86. Joshua C. C. Chan & Eric Eisenstat, 2018. "Bayesian model comparison for time‐varying parameter VARs with stochastic volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(4), pages 509-532, June.
    87. Lubos Hanus & Lukas Vacha, 2018. "Time-Frequency Response Analysis of Monetary Policy Transmission," Working Papers IES 2018/30, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Oct 2018.
    88. Jebabli, Ikram & Arouri, Mohamed & Teulon, Frédéric, 2014. "On the effects of world stock market and oil price shocks on food prices: An empirical investigation based on TVP-VAR models with stochastic volatility," Energy Economics, Elsevier, vol. 45(C), pages 66-98.
    89. Nikolay Hristov & Oliver Hülsewig & Thomas Siemsen & Timo Wollmershäuser, 2019. "Restoring euro area monetary transmission: Which role for government bond rates?," Empirical Economics, Springer, vol. 57(3), pages 991-1021, September.
    90. Coşkun Akdeniz & Abdurrahman Nazif Çatık & Esra Ballı, 2022. "Inflationary effects of oil price and exchange rate shocks in South Africa: Evidence from time‐varying pass‐through coefficients," South African Journal of Economics, Economic Society of South Africa, vol. 90(3), pages 301-328, September.
    91. Mehmet Balcilar & Riza Demirer & Festus V. Bekun, 2021. "Flexible Time-Varying Betas in a Novel Mixture Innovation Factor Model with Latent Threshold," Mathematics, MDPI, vol. 9(8), pages 1-20, April.
    92. Kenichiro McAlinn, 2021. "Mixed‐frequency Bayesian predictive synthesis for economic nowcasting," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(5), pages 1143-1163, November.
    93. Robert A. Hill & Paulo M. M. Rodrigues, 2022. "Forgetting approaches to improve forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1356-1371, November.
    94. Wensheng Kang & Ronald A. Ratti & Kyung Hwan Yoon, 2015. "Time-varying effect of oil market shocks on the stock market," CAMA Working Papers 2015-35, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    95. Emanuela Ciapanna & Marco Taboga, 2019. "Bayesian Analysis of Coefficient Instability in Dynamic Regressions," Econometrics, MDPI, vol. 7(3), pages 1-32, June.
    96. Baillie, Richard T. & Cho, Dooyeon, 2014. "Time variation in the standard forward premium regression: Some new models and tests," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 52-63.
    97. Jhonatan Portilla & Gabriel Rodríguez & Paul Castillo B., 2022. "Evolution of Monetary Policy in Peru: An Empirical Application Using a Mixture Innovation TVP-VAR-SV Model [Metas de Inflación en Una Economía Dolarizada: La Experencia Del Perú]," CESifo Economic Studies, CESifo Group, vol. 68(1), pages 98-126.
    98. Jakub Mateju, 2014. "Explaining the Strength and Efficiency of Monetary Policy Transmission: A Panel of Impulse Responses from a Time-Varying Parameter Model," Working Papers 2014/04, Czech National Bank.
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    87. He, Zhongfang & Maheu, John M., 2010. "Real time detection of structural breaks in GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2628-2640, November.
    88. Kim, Jaeho, 2015. "Bayesian Inference in a Non-linear/Non-Gaussian Switching State Space Model: Regime-dependent Leverage Effect in the U.S. Stock Market," MPRA Paper 67153, University Library of Munich, Germany.
    89. Jaeho Kim & Sora Chon, 2022. "Bayesian estimation of the long-run trend of the US economy," Empirical Economics, Springer, vol. 62(2), pages 461-485, February.
    90. Smith, Simon C., 2022. "Time-variation, multiple testing, and the factor zoo," International Review of Financial Analysis, Elsevier, vol. 84(C).
    91. Sylvia Kaufmann, 2011. "K-state switching models with endogenous transition distributions," Working Papers 2011-13, Swiss National Bank.
    92. Gary Koop & Simon Potter, 2010. "A flexible approach to parametric inference in nonlinear and time varying time series models," Post-Print hal-00732535, HAL.
    93. Chiara Perricone, 2013. "Clustering Macroeconomic Variables," CEIS Research Paper 283, Tor Vergata University, CEIS, revised 11 Jun 2013.
    94. DESCHAMPS, Philippe J., 2016. "Bayesian Semiparametric Forecasts of Real Interest Rate Data," LIDAM Discussion Papers CORE 2016050, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    95. Zhongjun Qu & Pierre Perron, 2008. "A Stochastic Volatility Model with Random Level Shifts: Theory and Applications to S&P 500 and NASDAQ Return Indices," Boston University - Department of Economics - Working Papers Series wp2008-007, Boston University - Department of Economics.
    96. Paul De Grauwe & Zhaoyong Zhang & Kin-Yip Ho & Yanlin Shi & Zhaoyong Zhang, 2016. "It takes two to tango: A regime-switching analysis of the correlation dynamics between the mainland Chinese and Hong Kong stock markets," Scottish Journal of Political Economy, Scottish Economic Society, vol. 63(1), pages 41-65, February.
    97. Kirsten Thompson & Reneé van Eyden & Rangan Gupta, 2015. "Testing the Out-of-Sample Forecasting Ability of a Financial Conditions Index for South Africa," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 51(3), pages 486-501, May.
    98. Jiawen Xu & Pierre Perron, 2017. "Forecasting in the presence of in and out of sample breaks," Boston University - Department of Economics - Working Papers Series WP2018-014, Boston University - Department of Economics, revised Nov 2018.
    99. Arnaud Dufays & Zhuo Li & Jeroen V.K. Rombouts & Yong Song, 2021. "Sparse change‐point VAR models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(6), pages 703-727, September.
    100. Mehmet Balcilar & Zeynel Abidin Ozdemir, 2017. "A re-examination of growth and growth uncertainty relationship in a stochastic volatility in mean model with time-varying parameters," Working Papers 15-32, Eastern Mediterranean University, Department of Economics.
    101. Jordi Maas, 2014. "Forecasting inflation using time-varying Bayesian model averaging," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 68(3), pages 149-182, August.
    102. Canepa, Alessandra, 2022. "Ination Dynamics and Time-Varying Persistence: The Importance of the Uncertainty Channel," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202211, University of Turin.
    103. Pesaran, M.H. & Pick, A. & Pranovich, M., 2011. "Optimal Forecasts in the Presence of Structural Breaks (Updated 14 November 2011)," Cambridge Working Papers in Economics 1163, Faculty of Economics, University of Cambridge.
    104. Hirano, Keisuke & Wright, Jonathan H., 2022. "Analyzing cross-validation for forecasting with structural instability," Journal of Econometrics, Elsevier, vol. 226(1), pages 139-154.
    105. Patricia Chelley‐Steeley & Neophytos Lambertides & Christos S. Savva, 2019. "Sentiment, order imbalance, and co‐movement: An examination of shocks to retail and institutional trading activity," European Financial Management, European Financial Management Association, vol. 25(1), pages 116-159, January.
    106. Angelia L. Grant, 2017. "The Early Millennium Slowdown: Replicating the Peersman (2005) Results," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 224-232, January.
    107. Joshua C.C. Chan & Eric Eisenstat, 2013. "Gibbs Samplers for VARMA and Its Extensions," ANU Working Papers in Economics and Econometrics 2013-604, Australian National University, College of Business and Economics, School of Economics.
    108. Balcilar, Mehmet & Ozdemir, Zeynel Abidin, 2019. "The nexus between the oil price and its volatility risk in a stochastic volatility in the mean model with time-varying parameters," Resources Policy, Elsevier, vol. 61(C), pages 572-584.
    109. Liew, Freddy, 2012. "Forecasting inflation in Asian economies," MPRA Paper 36781, University Library of Munich, Germany.
    110. Simon C. Smith, 2020. "Equity premium prediction and structural breaks," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 25(3), pages 412-429, July.
    111. Adam Check & Jeremy Piger, 2021. "Structural Breaks in U.S. Macroeconomic Time Series: A Bayesian Model Averaging Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 53(8), pages 1999-2036, December.
    112. Bowen Fu, 2019. "Bubbles and crises: Replicating the Anundsen et al. (2016) results," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(5), pages 822-826, August.
    113. Pretnar, Nick & Olivola, Christopher Y. & Montgomery, Alan, 2021. "Two-stage Budgeting with Bounded Rationality," MPRA Paper 105356, University Library of Munich, Germany.
    114. Jonathan H. Wright, 2023. "Breaks in the Phillips Curve: Evidence from Panel Data," Finance and Economics Discussion Series 2023-015, Board of Governors of the Federal Reserve System (U.S.).
    115. Gary Koop & Simon M. Potter, 2007. "A flexible approach to parametric inference in nonlinear time series models," Staff Reports 285, Federal Reserve Bank of New York.
    116. Sylvia Kaufmann, 2016. "Hidden Markov models in time series, with applications in economics," Working Papers 16.06, Swiss National Bank, Study Center Gerzensee.
    117. Balcilar, Mehmet & Ozdemir, Zeynel Abidin, 2019. "The volatility effect on precious metals price returns in a stochastic volatility in mean model with time-varying parameters," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    118. Ko, Stanley I. M. & Chong, Terence T. L. & Ghosh, Pulak, 2014. "Dirichlet Process Hidden Markov Multiple Change-point Model," MPRA Paper 57871, University Library of Munich, Germany.
    119. Robert Barro & Tao Jin, 2020. "Online Appendix to "Rare Events and Long-Run Risks"," Online Appendices 18-485, Review of Economic Dynamics.
    120. Chelley-Steeley, Patricia & Lambertides, Neophytos & Savva, Christos S., 2015. "The effect of security and market order flow shocks on co-movement," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 39(C), pages 136-155.

  64. Koop, Gary & Tobias, Justin L., 2006. "Semiparametric Bayesian inference in smooth coefficient models," Journal of Econometrics, Elsevier, vol. 134(1), pages 283-315, September.
    See citations under working paper version above.
  65. Dorfman, Jeffrey H. & Koop, Gary, 2005. "Current developments in productivity and efficiency measurement," Journal of Econometrics, Elsevier, vol. 126(2), pages 233-240, June.

    Cited by:

    1. Sturla Furunes Kvamsdal, 2019. "Indexing of Technical Change in Aggregated Data," Computational Economics, Springer;Society for Computational Economics, vol. 53(3), pages 901-920, March.
    2. Nehring, Richard F. & Gillespie, Jeffrey M. & Hallahan, Charles B. & Sauer, Johannes, 2012. "Economic Efficiency of U.S. Organic Versus Conventional Dairy Farms: Evidence from 2005 and 2010," 2012 Annual Meeting, February 4-7, 2012, Birmingham, Alabama 119769, Southern Agricultural Economics Association.
    3. Mehdi Farsi & Aurelio Fetz & Massimo Filippini, 2007. "Benchmarking and Regulation in the Electricity Distribution Sector," CEPE Working paper series 07-54, CEPE Center for Energy Policy and Economics, ETH Zurich.
    4. Nehring, Richard & Gillespie, Jeffrey & Harris, J. Michael Harris, 2018. "The Economics and Productivity of Organic versus Non-organic U.S. Dairy Farms," 2018 Annual Meeting, August 5-7, Washington, D.C. 273123, Agricultural and Applied Economics Association.
    5. Nehring, Richard & hallahan, Charlie, 2015. "The Impacts of Off-Farm Income on Farm Efficiency, Scale, and Profitability Rice Farms," 2015 Annual Meeting, January 31-February 3, 2015, Atlanta, Georgia 196841, Southern Agricultural Economics Association.
    6. Nehring, Richard & Katchova, Ani L. & Gillespie, Jeffrey & Hallahan, Charlie & Harris, Michael & Erickson, Ken, 2014. "A Frontier Analysis of U.S. Poultry Farms: Developing Performance Measures," 2014 Annual Meeting, February 1-4, 2014, Dallas, Texas 162434, Southern Agricultural Economics Association.
    7. Alvarez, Antonio & del Corral, Julio, 2006. "Modeling Regional Heterogeneity with Panel Data: Application to Spanish Provinces," Efficiency Series Papers 2006/06, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    8. Jim Griffin & Mark Steel, 2005. "Bayesian Stochastic Frontier Analysis Using WinBUGS," Econometrics 0509004, University Library of Munich, Germany.
    9. Nehring, Richard F. & Gillespie, Jeffrey M. & Harris, Michael & Erickson, Kenneth W., 2018. "Economic Efficiency of U.S. Organic Versus Conventional Dairy Farms: Evidence from," 2018 Annual Meeting, August 5-7, Washington, D.C. 273793, Agricultural and Applied Economics Association.
    10. Areal, Francisco J & Tiffin, Richard & Balcombe, Kelvin, 2010. "Provision of an environmental output within a multi-output distance function approach," MPRA Paper 25051, University Library of Munich, Germany.
    11. Nehring, Richard & Hallahan, Charlie, 2016. "The Impacts of Off-Farm Income on Farm Efficiency, Scale, and Profitability Cotton Farms," 2016 Annual Meeting, February 6-9, 2016, San Antonio, Texas 230413, Southern Agricultural Economics Association.
    12. Huang, Tai-Hsin & Chung, Ming-Tai, 2017. "Do undesirables matter on the examination of banking efficiency using stochastic directional distance functions," The Quarterly Review of Economics and Finance, Elsevier, vol. 65(C), pages 194-211.

  66. Fernandez, Carmen & Koop, Gary & Steel, Mark F.J., 2005. "Alternative efficiency measures for multiple-output production," Journal of Econometrics, Elsevier, vol. 126(2), pages 411-444, June.
    See citations under working paper version above.
  67. Dale J. Poirier & Gary Koop & Justin Tobias, 2005. "Semiparametric Bayesian inference in multiple equation models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(6), pages 723-747.
    See citations under working paper version above.
  68. Gary Koop & Simon Potter, 2004. "Forecasting in dynamic factor models using Bayesian model averaging," Econometrics Journal, Royal Economic Society, vol. 7(2), pages 550-565, December.

    Cited by:

    1. Adam J. Check & Anna K Nolan & Tyler C. Schipper, 2019. "Forecasting GDP Growth using Disaggregated GDP Revisions," Economics Bulletin, AccessEcon, vol. 39(4), pages 2580-2588.
    2. Randall, Alan & Chen, Ding-Rong, 2011. "A Better Approach to Resolving Variable Selection Uncertainty in Meta Analysis for Benefits Transfer," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114788, European Association of Agricultural Economists.
    3. Goodness C. Aye & Stephen M. Miller & Rangan Gupta & Mehmet Balcilar, 2013. "Forecasting the US Real Private Residential Fixed Investment Using Large Number of Predictors," Working Papers 201348, University of Pretoria, Department of Economics.
    4. Gary Koop, 2011. "Forecasting with Medium and Large Bayesian VARs," Working Papers 1117, University of Strathclyde Business School, Department of Economics.
    5. T. Ando & R. S. Tsay, 2009. "‘Model selection for generalized linear models with factor‐augmented predictors’," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 25(3), pages 243-246, May.
    6. Annalisa Cadonna & Sylvia Fruhwirth-Schnatter & Peter Knaus, 2019. "Triple the gamma -- A unifying shrinkage prior for variance and variable selection in sparse state space and TVP models," Papers 1912.03100, arXiv.org.
    7. Dimitris Korobilis, 2008. "Forecasting in vector autoregressions with many predictors," Advances in Econometrics, in: Bayesian Econometrics, pages 403-431, Emerald Group Publishing Limited.
    8. Hilde C. Bjørnland & Karsten Gerdrup & Anne Sofie Jore & Christie Smith & Leif Anders Thorsrud, 2012. "Does Forecast Combination Improve Norges Bank Inflation Forecasts?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(2), pages 163-179, April.
    9. Gary Koop & Dimitris Korobilis, 2012. "Forecasting Inflation Using Dynamic Model Averaging," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(3), pages 867-886, August.
    10. Abe, Ryosuke & Kato, Hironori, 2017. "What led to the establishment of a rail-oriented city? Determinants of urban rail supply in Tokyo, Japan, 1950–2010," Transport Policy, Elsevier, vol. 58(C), pages 72-79.
    11. Michael K. Andersson & Sune Karlsson, 2008. "Bayesian forecast combination for VAR models," Advances in Econometrics, in: Bayesian Econometrics, pages 501-524, Emerald Group Publishing Limited.
    12. Poghosyan, K. & Magnus, J.R., 2011. "WALS estimation and forecasting in factor-based dynamic models with an application to Armenia," Other publications TiSEM 419d588e-7827-4cdd-b989-4, Tilburg University, School of Economics and Management.
    13. Kim, Hyun Hak & Swanson, Norman R., 2018. "Mining big data using parsimonious factor, machine learning, variable selection and shrinkage methods," International Journal of Forecasting, Elsevier, vol. 34(2), pages 339-354.
    14. Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2016. "Bayesian Compressed Vector Autoregressions," Working Papers 103, Brandeis University, Department of Economics and International Business School.
    15. Jana Eklund & Sune Karlsson, 2007. "Forecast Combination and Model Averaging Using Predictive Measures," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 329-363.
    16. A. Girardi & R. Golinelli & C. Pappalardo, 2014. "The Role of Indicator Selection in Nowcasting Euro Area GDP in Pseudo Real Time," Working Papers wp919, Dipartimento Scienze Economiche, Universita' di Bologna.
    17. Todd E. Clark & Michael W. McCracken, 2010. "Averaging forecasts from VARs with uncertain instabilities," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 5-29.
    18. Siliverstovs Boriss & Kholodilin Konstantin A., 2012. "Assessing the Real-Time Informational Content of Macroeconomic Data Releases for Now-/Forecasting GDP: Evidence for Switzerland," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 232(4), pages 429-444, August.
    19. Lasha Kavtaradze & Manouchehr Mokhtari, 2018. "Factor Models And Time†Varying Parameter Framework For Forecasting Exchange Rates And Inflation: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 302-334, April.
    20. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
    21. Koop, Gary & Korobilis, Dimitris, 2010. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(4), pages 267-358, July.
    22. Cristina Fuentes-Albero & Leonardo Melosi, 2011. "Methods for Computing Marginal Data Densities from the Gibbs Output," Departmental Working Papers 201131, Rutgers University, Department of Economics.
    23. Ouysse, Rachida, 2016. "Bayesian model averaging and principal component regression forecasts in a data rich environment," International Journal of Forecasting, Elsevier, vol. 32(3), pages 763-787.
    24. Todd E. Clark & Michael W. McCracken, 2009. "Combining Forecasts from Nested Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(3), pages 303-329, June.
    25. Liu, Jing & Wei, Yu & Ma, Feng & Wahab, M.I.M., 2017. "Forecasting the realized range-based volatility using dynamic model averaging approach," Economic Modelling, Elsevier, vol. 61(C), pages 12-26.
    26. Gefang Deborah & Strachan Rodney, 2009. "Nonlinear Impacts of International Business Cycles on the U.K. -- A Bayesian Smooth Transition VAR Approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(1), pages 1-33, December.
    27. Kim, Hyun Hak & Swanson, Norman R., 2014. "Forecasting financial and macroeconomic variables using data reduction methods: New empirical evidence," Journal of Econometrics, Elsevier, vol. 178(P2), pages 352-367.
    28. Jochmann, Markus & Koop, Gary & Strachan, Rodney W., 2010. "Bayesian forecasting using stochastic search variable selection in a VAR subject to breaks," International Journal of Forecasting, Elsevier, vol. 26(2), pages 326-347, April.
    29. Boriss Siliverstovs & Daniel Wochner, 2020. "Recessions as Breadwinner for Forecasters State-Dependent Evaluation of Predictive Ability: Evidence from Big Macroeconomic US Data," Working Papers 2020/02, Latvijas Banka.
    30. Kelvin Balcombe & Iain Fraser & Abhijit Sharma, 2011. "Bayesian model averaging and identification of structural breaks in time series," Applied Economics, Taylor & Francis Journals, vol. 43(26), pages 3805-3818.
    31. Daniel Felix Ahelegbey & Monica Billio & Roberto Casarin, 2016. "Sparse Graphical Vector Autoregression: A Bayesian Approach," Annals of Economics and Statistics, GENES, issue 123-124, pages 333-361.
    32. KOROBILIS, Dimitris, 2011. "Hierarchical shrinkage priors for dynamic regressions with many predictors," LIDAM Discussion Papers CORE 2011021, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    33. Poghosyan, K., 2012. "Structural and reduced-form modeling and forecasting with application to Armenia," Other publications TiSEM ad1a24c3-15e6-4f04-b338-3, Tilburg University, School of Economics and Management.
    34. Knut Are Aastveit & Francesco Ravazzolo & Herman K. van Dijk, 2014. "Combined Density Nowcasting in an uncertain economic environment," Working Paper 2014/17, Norges Bank.
    35. Eidenberger, Judith & Neudorfer, Benjamin & Sigmund, Michael & Stein, Ingrid, 2014. "What predicts financial (in)stability? A Bayesian approach," Discussion Papers 36/2014, Deutsche Bundesbank.
    36. Ahlem DAHEM, 2016. "Short-Term Bayesian Inflation Forecasting For Tunisia: Some Empirical Evidence," EcoForum, "Stefan cel Mare" University of Suceava, Romania, Faculty of Economics and Public Administration - Economy, Business Administration and Tourism Department., vol. 5(1), pages 1-47, January.
    37. Hyun Hak Kim & Norman Swanson, 2013. "Mining Big Data Using Parsimonious Factor and Shrinkage Methods," Departmental Working Papers 201316, Rutgers University, Department of Economics.
    38. Nombulelo Gumata & Alain Kabundi & Eliphas Ndou, 2013. "Important channels of transmission of monetary policy shock in South Africa," Working Papers 6021, South African Reserve Bank.
    39. Konstantin Kholodilin & Boriss Siliverstovs, 2010. "Assessing the Real-Time Informational Content of Macroeconomic Data Releases for Now-/Forecasting GDP," KOF Working papers 10-251, KOF Swiss Economic Institute, ETH Zurich.
    40. Knut Aastveit & Tørres Trovik, 2012. "Nowcasting norwegian GDP: the role of asset prices in a small open economy," Empirical Economics, Springer, vol. 42(1), pages 95-119, February.
    41. Jana Eklund & Sune Karlsson, 2007. "Computational Efficiency in Bayesian Model and Variable Selection," Economics wp35, Department of Economics, Central bank of Iceland.
    42. Gary Koop & Dimitris Korompilis, 2009. "UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So?," Working Papers 0917, University of Strathclyde Business School, Department of Economics.
    43. Korobilis, Dimitris, 2013. "Bayesian forecasting with highly correlated predictors," Economics Letters, Elsevier, vol. 118(1), pages 148-150.
    44. Buncic, Daniel & Piras, Gion Donat, 2016. "Heterogeneous agents, the financial crisis and exchange rate predictability," Journal of International Money and Finance, Elsevier, vol. 60(C), pages 313-359.
    45. Weron, Rafał, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
    46. Nicholas Apergis & Ghassen El Montasser & Emmanuel Owusu-Sekyere & Ahdi N. Ajmi & Rangan Gupta, 2014. "Dutch Disease Effect of Oil Rents on Agriculture Value Added in MENA Countries," Working Papers 201408, University of Pretoria, Department of Economics.
    47. Aijun Yang & Ju Xiang & Lianjie Shu & Hongqiang Yang, 2018. "Sparse Bayesian Variable Selection with Correlation Prior for Forecasting Macroeconomic Variable using Highly Correlated Predictors," Computational Economics, Springer;Society for Computational Economics, vol. 51(2), pages 323-338, February.
    48. Reusens Peter & Croux Christophe, 2017. "Detecting time variation in the price puzzle: a less informative prior choice for time varying parameter VAR models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(4), pages 1-18, September.
    49. Risse, Marian, 2019. "Combining wavelet decomposition with machine learning to forecast gold returns," International Journal of Forecasting, Elsevier, vol. 35(2), pages 601-615.
    50. Jon D. Samuels & Rodrigo Sekkel, 2013. "Forecasting with Many Models: Model Confidence Sets and Forecast Combination," Staff Working Papers 13-11, Bank of Canada.
    51. Vanina Forget, 2012. "Doing well and doing good: a multi-dimensional puzzle," Working Papers hal-00672037, HAL.
    52. Chun Liu & John M. Maheu, 2009. "Forecasting realized volatility: a Bayesian model-averaging approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(5), pages 709-733.
    53. Mariia Artemova & Francisco Blasques & Siem Jan Koopman & Zhaokun Zhang, 2021. "Forecasting in a changing world: from the great recession to the COVID-19 pandemic," Tinbergen Institute Discussion Papers 21-006/III, Tinbergen Institute.
    54. Doojav Gan-Ochir & Luvsannyam Davaajargal, 2023. "Forecasting Inflation in Mongolia: A Dynamic Model Averaging Approach," Journal of Time Series Econometrics, De Gruyter, vol. 15(1), pages 27-48, January.
    55. Maehashi, Kohei & Shintani, Mototsugu, 2020. "Macroeconomic forecasting using factor models and machine learning: an application to Japan," Journal of the Japanese and International Economies, Elsevier, vol. 58(C).
    56. James H. Stock & Mark W. Watson, 2012. "Generalized Shrinkage Methods for Forecasting Using Many Predictors," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(4), pages 481-493, June.
    57. Boriss Siliverstovs & Daniel S. Wochner, 2021. "State‐dependent evaluation of predictive ability," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 547-574, April.
    58. Konstantin Styrin, 2019. "Forecasting Inflation in Russia Using Dynamic Model Averaging," Russian Journal of Money and Finance, Bank of Russia, vol. 78(1), pages 3-18, March.
    59. Konstantin Styrin, 2018. "Forecasting inflation in Russia by Dynamic Model Averaging," Bank of Russia Working Paper Series wps39, Bank of Russia.
    60. Gianluca Cubadda & Stefano Grassi & Barbara Guardabascio, 2024. "The Time-Varying Multivariate Autoregressive Index Model," CEIS Research Paper 571, Tor Vergata University, CEIS, revised 10 Jan 2024.
    61. Dahem, Ahlem, 2015. "Short term Bayesian inflation forecasting for Tunisia," MPRA Paper 66702, University Library of Munich, Germany.
    62. Kohei Maehashi & Mototsugu Shintani, 2020. "Macroeconomic Forecasting Using Factor Models and Machine Learning: An Application to Japan," CIRJE F-Series CIRJE-F-1146, CIRJE, Faculty of Economics, University of Tokyo.
    63. Wei-Chun Hsu & Lin Lin & Chen-Yu Li, 2014. "Forecasting automobile sales: the Peña-Box approach," Transportation Planning and Technology, Taylor & Francis Journals, vol. 37(6), pages 568-580, August.
    64. David Bolder & Yuliya Romanyuk, 2008. "Combining Canadian Interest-Rate Forecasts," Staff Working Papers 08-34, Bank of Canada.
    65. Massimiliano Serati & Andrea Venegoni, 2018. "Drivers of migration flows for companies: an integrated analysis," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 72(3), pages 53-64, July-Sept.
    66. Chul-Yong Lee & Sung-Yoon Huh, 2017. "Forecasting Long-Term Crude Oil Prices Using a Bayesian Model with Informative Priors," Sustainability, MDPI, vol. 9(2), pages 1-15, January.
    67. Jordi Maas, 2014. "Forecasting inflation using time-varying Bayesian model averaging," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 68(3), pages 149-182, August.
    68. Sandra Eickmeier & Christina Ziegler, 2008. "How successful are dynamic factor models at forecasting output and inflation? A meta-analytic approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(3), pages 237-265.
    69. Leo Krippner & Leif Anders Thorsrud, 2009. "Forecasting New Zealand's economic growth using yield curve information," Reserve Bank of New Zealand Discussion Paper Series DP2009/18, Reserve Bank of New Zealand.
    70. Jana Eklund & Sune Karlsson, 2007. "An Embarrassment of Riches: Forecasting Using Large Panels," Economics wp34, Department of Economics, Central bank of Iceland.
    71. Sakar Hasan Hamza & Qingna Li, 2023. "The Dynamics of US Gasoline Demand and Its Prediction: An Extended Dynamic Model Averaging Approach," Energies, MDPI, vol. 16(12), pages 1-13, June.
    72. Desbordes, Rodolphe & Koop, Gary & Vicard, Vincent, 2018. "One size does not fit all… panel data: Bayesian model averaging and data poolability," Economic Modelling, Elsevier, vol. 75(C), pages 364-376.
    73. Jaroslava Hlouskova & Martin Wagner, 2013. "The Determinants of Long-Run Economic Growth: A Conceptually and Computationally Simple Approach," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 149(IV), pages 445-492, December.
    74. Zhou, Xiaocong & Nakajima, Jouchi & West, Mike, 2014. "Bayesian forecasting and portfolio decisions using dynamic dependent sparse factor models," International Journal of Forecasting, Elsevier, vol. 30(4), pages 963-980.
    75. Naik, Prasad A., 2015. "Marketing Dynamics: A Primer on Estimation and Control," Foundations and Trends(R) in Marketing, now publishers, vol. 9(3), pages 175-266, December.
    76. Enrique Moral-Benito, 2015. "Model Averaging In Economics: An Overview," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 46-75, February.
    77. Tan, Xueping & Sirichand, Kavita & Vivian, Andrew & Wang, Xinyu, 2022. "Forecasting European carbon returns using dimension reduction techniques: Commodity versus financial fundamentals," International Journal of Forecasting, Elsevier, vol. 38(3), pages 944-969.
    78. Pedro Henrique Melo Albuquerque & Yaohao Peng & João Pedro Fontoura da Silva, 2022. "Making the whole greater than the sum of its parts: A literature review of ensemble methods for financial time series forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1701-1724, December.

  69. Koop, Gary & Tole, Lise, 2004. "Measuring the health effects of air pollution: to what extent can we really say that people are dying from bad air?," Journal of Environmental Economics and Management, Elsevier, vol. 47(1), pages 30-54, January.

    Cited by:

    1. X. Pautrel, 2008. "Reconsidering the Impact of the Environment on Long-run Growth when Pollution Influences Health and Agents have a Finite-lifetime," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 40(1), pages 37-52, May.
    2. Louis Anthony (Tony) Cox, 2012. "Reassessing the Human Health Benefits from Cleaner Air," Risk Analysis, John Wiley & Sons, vol. 32(5), pages 816-829, May.
    3. Chi Wang & Giovanni Parmigiani & Francesca Dominici, 2012. "Bayesian Effect Estimation Accounting for Adjustment Uncertainty," Biometrics, The International Biometric Society, vol. 68(3), pages 661-671, September.
    4. Abidoye, Babatunde Oluwakayode, 2010. "Bayesian inference in modeling recreation demand," ISU General Staff Papers 201001010800002496, Iowa State University, Department of Economics.
    5. Huigang Chen & Mr. Alin T Mirestean & Mr. Charalambos G Tsangarides, 2011. "Limited Information Bayesian Model Averaging for Dynamic Panels with An Application to a Trade Gravity Model," IMF Working Papers 2011/230, International Monetary Fund.
    6. Goenka, A. & Jafarey, S. & Pouliot, W., 2012. "Pollution, mortality and optimal environmental policy," Working Papers 12/07, Department of Economics, City University London.
    7. Negri­n, Miguel A. & Vázquez-Polo, Francisco-José, 2008. "Incorporating model uncertainty in cost-effectiveness analysis: A Bayesian model averaging approach," Journal of Health Economics, Elsevier, vol. 27(5), pages 1250-1259, September.
    8. Moeltner, K. & Kim, M.-K. & Zhu, E. & Yang, W., 2013. "Wildfire smoke and health impacts: A closer look at fire attributes and their marginal effects," Journal of Environmental Economics and Management, Elsevier, vol. 66(3), pages 476-496.
    9. Roberto Leon-Gonzalez & Daniel Montolio, 2012. "Endogeneity and Panel Data in Growth Regressions: A Bayesian Model Averaging Approach," GRIPS Discussion Papers 12-08, National Graduate Institute for Policy Studies.
    10. Roberto Leon-Gonzalez & Thanabalasingam Vinayagathasan, 2015. "Robust Determinants of Growth in Asian Developing Economies: A Bayesian Panel Data Model Averaging Approach," GRIPS Discussion Papers 15-15, National Graduate Institute for Policy Studies.
    11. Louis Anthony (Tony) Cox, 2012. "Miscommunicating Risk, Uncertainty, and Causation: Fine Particulate Air Pollution and Mortality Risk as an Example," Risk Analysis, John Wiley & Sons, vol. 32(5), pages 765-767, May.
    12. Jorge Araña & Carmelo León, 2007. "Repeated Dichotomous Choice Formats for Elicitation of Willingness to Pay: Simultaneous Estimation and Anchoring Effect," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 36(4), pages 475-497, April.
    13. David Meintrup & Chang Woon Nam, 2009. "Shadow Market Area for Air Pollutants," Environment and Planning B, , vol. 36(4), pages 664-681, August.
    14. Babatunde Abidoye & Joseph Herriges, 2012. "Model Uncertainty in Characterizing Recreation Demand," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 53(2), pages 251-277, October.
    15. Louis Anthony (Tony) Cox, 2012. "Confronting Deep Uncertainties in Risk Analysis," Risk Analysis, John Wiley & Sons, vol. 32(10), pages 1607-1629, October.
    16. Melián-González, Arturo & Moreno-Gil, Sergio & Araña, Jorge E., 2011. "Gay tourism in a sun and beach destination," Tourism Management, Elsevier, vol. 32(5), pages 1027-1037.
    17. Maddison, David, 2006. "Dose response functions and the harvesting effect," Resource and Energy Economics, Elsevier, vol. 28(4), pages 313-332, November.
    18. Judson Jaffe & Robert N. Stavins, 2007. "On the value of formal assessment of uncertainty in regulatory analysis," Regulation & Governance, John Wiley & Sons, vol. 1(2), pages 154-171, June.
    19. Mr. Alin T Mirestean & Mr. Charalambos G Tsangarides & Huigang Chen, 2009. "Limited Information Bayesian Model Averaging for Dynamic Panels with Short Time Periods," IMF Working Papers 2009/074, International Monetary Fund.
    20. Neal Fann & Amy D. Lamson & Susan C. Anenberg & Karen Wesson & David Risley & Bryan J. Hubbell, 2012. "Response to Cox Letter: “Miscommunicating Risk, Uncertainty, and Causation: Fine Particulate Air Pollution and Mortality Risk as an Example”," Risk Analysis, John Wiley & Sons, vol. 32(5), pages 768-770, May.
    21. Bangzhu Zhu & Runzhi Pang & Julien Chevallier & Yi-Ming Wei & Dinh-Tri Vo, 2019. "Including intangible costs into the cost-of-illness approach: a method refinement illustrated based on the PM2.5 economic burden in China," Working Papers 2019-010, Department of Research, Ipag Business School.

  70. Koop, Gary & Poirier, Dale J., 2004. "Bayesian variants of some classical semiparametric regression techniques," Journal of Econometrics, Elsevier, vol. 123(2), pages 259-282, December.
    See citations under working paper version above.
  71. Gary Koop, 2004. "Modelling the evolution of distributions: an application to Major League baseball," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 167(4), pages 639-655, November.
    See citations under working paper version above.
  72. Hollifield, Burton & Koop, Gary & Li, Kai, 2003. "A Bayesian analysis of a variance decomposition for stock returns," Journal of Empirical Finance, Elsevier, vol. 10(5), pages 583-601, December.

    Cited by:

    1. Andrea BASTIANIN & Matteo MANERA, 2015. "How Does Stock Market Volatility React to Oil Shocks?," Departmental Working Papers 2015-09, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    2. Zhang, Tongbin, 2021. "Stock prices and the risk-free rate: An internal rationality approach," Journal of Economic Dynamics and Control, Elsevier, vol. 127(C).
    3. Zhang, Tongbin, 2014. "Stock Price, Real Riskless Interest Rate and Learning," MPRA Paper 57090, University Library of Munich, Germany.
    4. Yi-Mien Lin & Yun-Sheng Hsu & Shieh-Liang Chen, 2009. "Cash-flow news, market liquidity and liquidity risk," Applied Economics, Taylor & Francis Journals, vol. 41(9), pages 1137-1156.
    5. Lawrenz, Jochen & Zorn, Josef, 2018. "Decomposing the predictive power of local and global financial valuation ratios," The Quarterly Review of Economics and Finance, Elsevier, vol. 70(C), pages 137-149.
    6. Maio, Paulo & Philip, Dennis, 2015. "Macro variables and the components of stock returns," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 287-308.
    7. Roy P. P. M. Hoevenaars & Roderick D. J. Molenaar & Peter C. Schotman & Tom B. M. Steenkamp, 2014. "Strategic Asset Allocation For Long‐Term Investors: Parameter Uncertainty And Prior Information," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(3), pages 353-376, April.

  73. Koop, Gary & Potter, Simon M, 2003. "Bayesian Analysis of Endogenous Delay Threshold Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 93-103, January.
    See citations under working paper version above.
  74. Nick Hanley & Robert Wright & Gary Koop, 2002. "Modelling Recreation Demand Using Choice Experiments: Climbing in Scotland," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 22(3), pages 449-466, July.

    Cited by:

    1. Kaye-Blake, William & Abell, Walter L. & Zellman, Eva, 2009. "Respondents’ ignoring of attribute information in a choice modelling survey," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 53(4), pages 1-18.
    2. Eline Poelmans & Sandra Rousseau, 2015. "Factors determining authors’ willingness to wait for editorial decisions from economic history journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(2), pages 1347-1374, February.
    3. Abid Fourati, Yosr & O'Donoghue, Cathal, 2009. "Eliciting Individual Preferences for Pension Reform," IZA Discussion Papers 4479, Institute of Labor Economics (IZA).
    4. Xuan Thi Dan Huynh & Tien Dung Khong & Adam Loch & Huynh Viet Khai, 2023. "Solid waste management program in developing countries: contingent valuation methodology versus choice experiment," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(11), pages 12395-12417, November.
    5. Mickael Bech & Trine Kjaer & Jørgen Lauridsen, 2011. "Does the number of choice sets matter? Results from a web survey applying a discrete choice experiment," Health Economics, John Wiley & Sons, Ltd., vol. 20(3), pages 273-286, March.
    6. Rambonilaza, Tina & Kerouaz, Fathallah, 2023. "Valuing harvest regulation changes in recreational fisheries with a discrete choice experiment study: What can we learn from a synthetic review?," Economic Analysis and Policy, Elsevier, vol. 79(C), pages 40-54.
    7. Stephane Hess, 2014. "Latent class structures: taste heterogeneity and beyond," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 14, pages 311-330, Edward Elgar Publishing.
    8. Yasushi Shoji & Koichi Kuriyama & Taro Mieno & Yohei Mitani, 2008. "Providing quality recreation experiences in Japan," Economics Bulletin, AccessEcon, vol. 17(7), pages 1-11.
    9. Stine Broch & Suzanne Vedel, 2012. "Using Choice Experiments to Investigate the Policy Relevance of Heterogeneity in Farmer Agri-Environmental Contract Preferences," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 51(4), pages 561-581, April.
    10. Rulleau, Bénédicte & Dachary-Bernard, Jeanne, 2012. "Preferences, rational choices and economic valuation: Some empirical tests," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 41(2), pages 198-206.
    11. Hess, Stephane & Hensher, David A. & Daly, Andrew, 2012. "Not bored yet – Revisiting respondent fatigue in stated choice experiments," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(3), pages 626-644.
    12. Mikołaj Czajkowski & Marek Giergiczny & William H. Greene, 2012. "Learning and Fatigue Effects Revisited. The Impact of Accounting for Unobservable Preference and Scale Heterogeneity on Perceived Ordering Effects in Multiple Choice Task Discrete Choice Experiments," Working Papers 2012-08, Faculty of Economic Sciences, University of Warsaw.
    13. Amedee Mollard & Christophe Boschet & Jean-Christophe Dissart & Anne Marie Lacroix & Rambonilaza Bolatiana & Dominique Vollet, 2014. "Les aménités environnementales : quelle contribution au développement des territoires ruraux ?," Post-Print hal-01818702, HAL.
    14. Mandy Ryan & Mabelle Amaya‐Amaya, 2005. "‘Threats’ to and hopes for estimating benefits," Health Economics, John Wiley & Sons, Ltd., vol. 14(6), pages 609-619, June.
    15. Jobstvogt, Niels & Watson, Verity & Kenter, Jasper O., 2014. "Looking below the surface: The cultural ecosystem service values of UK marine protected areas (MPAs)," Ecosystem Services, Elsevier, vol. 10(C), pages 97-110.
    16. Hynes, Stephen & Tinch, Dugald & Hanley, Nick, 2013. "Estimating the value of improvements to coastal waters resulting from revisions of the EU Bathing Waters Directive," Working Papers 160058, National University of Ireland, Galway, Socio-Economic Marine Research Unit.
    17. Carole Ropars-Collet & Philippe Le Goffe, 2020. "Economic evaluation of catch-and-release salmon fishing: impact on anglers’ willingness to pay," Working Papers hal-02441505, HAL.
    18. Paolo Figini & Laura Vici, 2010. "Off-Season Tourists and the Cultural Offer of a Mass-Tourism Destination: The Case of Rimini," Working Paper series 24_10, Rimini Centre for Economic Analysis.
    19. J. Shonkwiler & Nick Hanley, 2003. "A New Approach to Random Utility Modeling using the Dirichlet Multinomial Distribution," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 26(3), pages 401-416, November.
    20. Czajkowski, Mikołaj & Hanley, Nick & LaRiviere, Jacob, 2013. "The Effects of Experience on Preference Uncertainty: Theory and Empirics for Public and Quasi-Public Environmental Goods," SIRE Discussion Papers 2013-125, Scottish Institute for Research in Economics (SIRE).
    21. Benoît Chèze & Maia David & Vincent Martinet, 2020. "Understanding farmers' reluctance to reduce pesticide use: A choice experiment," Post-Print hal-02317175, HAL.
    22. Koundouri, Phoebe & Kountouris, Yannis & Stithou, Mavra, 2012. "A Choice Experiments Application in Transport Infrastructure: A Case Study on Travel Time Savings, Accidents and Pollution Reduction," MPRA Paper 38274, University Library of Munich, Germany.
    23. Hermes, Johannes & von Haaren, Christina & Schmücker, Dirk & Albert, Christian, 2021. "Nature-based recreation in Germany: Insights into volume and economic significance," Ecological Economics, Elsevier, vol. 188(C).
    24. Mariel, Petr & Ayala, Amaya de & Hoyos, David & Abdullah, Sabah, 2013. "Selecting random parameters in discrete choice experiment for environmental valuation: A simulation experiment," Journal of choice modelling, Elsevier, vol. 7(C), pages 44-57.
    25. Colombo, Sergio & Hanley, Nicholas & Louviere, Jordan, 2008. "Modelling preference heterogeneity in stated choice data: an analysis for public goods generated by agriculture," Stirling Economics Discussion Papers 2008-28, University of Stirling, Division of Economics.
    26. Czajkowski, Mikolaj & Hanley, Nicholas & LaRiviere, Jacob, 2012. "The Effects of Experience on Preference Uncertainty: Theory and Empirics for Public and Quasi-Public Goods," Stirling Economics Discussion Papers 2012-17, University of Stirling, Division of Economics.
    27. Ferrini, Silvia & Scarpa, Riccardo, 2007. "Designs with a priori information for nonmarket valuation with choice experiments: A Monte Carlo study," Journal of Environmental Economics and Management, Elsevier, vol. 53(3), pages 342-363, May.
    28. Nick Hanley & Mandy Ryan & Robert Wright, 2003. "Estimating the monetary value of health care: lessons from environmental economics," Health Economics, John Wiley & Sons, Ltd., vol. 12(1), pages 3-16, January.
    29. Ekin Birol & Phoebe Koundouri & Yiannis Kountouris, 2009. "Estimating farmers' valuation of aquifer recharge with treated wastewater: The Cypriot case study," DEOS Working Papers 0909, Athens University of Economics and Business.
    30. Ildephonse, Musafili, 2015. "An Economic Analysis Of Farmers’ Preferences For Participatory Management Of Volcanoes National Park In Rwanda," Research Theses 265680, Collaborative Masters Program in Agricultural and Applied Economics.
    31. Carole Ropars-Collet & Philippe Le Goffe & Qods Lefnatsa, 2021. "Does catch-and-release increase the recreational value of rivers? The case of salmon fishing," Post-Print hal-03342732, HAL.
    32. Jin, Jianjun & Wang, Zhishi & Ran, Shenghong, 2006. "Comparison of contingent valuation and choice experiment in solid waste management programs in Macao," Ecological Economics, Elsevier, vol. 57(3), pages 430-441, May.
    33. Marek Giergiczny & Mikołaj Czajkowski & Tomasz Żylicz & Per Angelstam, 2015. "Choice experiment assessment of public preferences for forest structural attributes," Working Papers 2015-30, Faculty of Economic Sciences, University of Warsaw.
    34. Christie, Michael & Hanley, Nick & Hynes, Stephen, 2007. "Valuing enhancements to forest recreation using choice experiment and contingent behaviour methods," Journal of Forest Economics, Elsevier, vol. 13(2-3), pages 75-102, August.
    35. Sahan T. M. Dissanayake & Andrew G. Meyer, 2021. "Incorporating Beliefs and Experiences into Choice Experiment Analysis: Implications for Policy Recommendations," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 43(2), pages 823-848, June.
    36. Yoo, James & Simonit, Silvio & Connors, John P. & Kinzig, Ann P. & Perrings, Charles, 2014. "The valuation of off-site ecosystem service flows: Deforestation, erosion and the amenity value of lakes in Prescott, Arizona," Ecological Economics, Elsevier, vol. 97(C), pages 74-83.
    37. Ropars‑Collet, Carole & Le Goffe, Philippe & Lefnatsa, Qods, 2021. "Does catch‑and‑release increase the recreational value of rivers? The case of salmon fishing," Review of Agricultural, Food and Environmental Studies, Institut National de la Recherche Agronomique (INRA), vol. 102(4), September.
    38. Mikolaj Czajkowski & Nick Hanley & Jacob LaRiviere, 2014. "The Effects of Experience on Preferences: Theory and Empirics for Environmental Public Goods," Discussion Papers in Environment and Development Economics 2014-05, University of St. Andrews, School of Geography and Sustainable Development.
    39. Carole Ropars-Collet & Philippe Goffe & Qods Lefnatsa, 2021. "Does catch-and-release increase the recreational value of rivers? The case of salmon fishing," Review of Agricultural, Food and Environmental Studies, Springer, vol. 102(4), pages 393-424, December.
    40. Mandy Ryan & Verity Watson & Vikki Entwistle, 2009. "Rationalising the ‘irrational’: a think aloud study of discrete choice experiment responses," Health Economics, John Wiley & Sons, Ltd., vol. 18(3), pages 321-336, March.
    41. Mingie, James C. & Poudyal, Neelam C. & Bowker, J.M. & Mengak, Michael T. & Siry, Jacek P., 2017. "Big game hunter preferences for hunting club attributes: A choice experiment," Forest Policy and Economics, Elsevier, vol. 78(C), pages 98-106.
    42. Jacobson, Michael & Shr, Yau-Huo & Dalemans, Floris & Magaju, Christine & Ciannella, Rodrigo, 2018. "Using a choice experiment approach to assess production tradeoffs for developing the croton value chain in Kenya," Forest Policy and Economics, Elsevier, vol. 86(C), pages 76-85.
    43. Silvia Ferrini & Riccardo Scarpa, 2005. "Experimental Designs for Environmental Valuation with Choice-Experiments: A Monte-Carlo Investigation," Working Papers in Economics 05/08, University of Waikato.
    44. Beaudet, Chloé & Tardieu, Léa & David, Maia, 2022. "Are citizens willing to accept changes in public lighting for biodiversity conservation?," Ecological Economics, Elsevier, vol. 200(C).
    45. Lee, Deborah E. & Du Preez, Mario, 2016. "Determining visitor preferences for rhinoceros conservation management at private, ecotourism game reserves in the Eastern Cape Province, South Africa: A choice modeling experiment," Ecological Economics, Elsevier, vol. 130(C), pages 106-116.
    46. Benoît Chèze & Maia M. David & Vincent Martinet, 2017. "Farmers' motivations to reduce their use of pesticides: a choice experiment analysis in France," Post-Print hal-01800261, HAL.
    47. Glenn Bush & Sergio Colombo & Nick Hanley, 2009. "Should all Choices Count? Using the Cut-Offs Approach to Edit Responses in a Choice Experiment," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 44(3), pages 397-414, November.
    48. Bénédicte Rulleau & Jeoffrey Dehez & Patrick Point, 2011. "The tourist recreational demand for coastal forests: Do forests really matter?," Review of Agricultural and Environmental Studies - Revue d'Etudes en Agriculture et Environnement, INRA Department of Economics, vol. 92(3), pages 291-310.
    49. Talpur, Musharaf & Brouwer, Roy & Koetse, Mark, 2019. "Opt-Out Forced Choice Effect in Combined Revealed and Stated Preference Discrete Choice Models: A Gender Perspective," MPRA Paper 99631, University Library of Munich, Germany.
    50. Czajkowski, Mikołaj & Hanley, Nick & LaRiviere, Jacob, 2013. "The effects of experience on preference uncertainty: theory and empirics for environmental goods," 2013 Conference (57th), February 5-8, 2013, Sydney, Australia 152155, Australian Agricultural and Resource Economics Society.
    51. Stephen Hynes & Cathal Buckley & Tom van Rensburg, 2006. "Agricultural versus Recreational Activity on Marginal Farm Land: A Discrete-Choice Model of Recreational Activity on Irish Farm Commonage," Working Papers 0603, Rural Economy and Development Programme,Teagasc.
    52. Asgary, Ali & Rezvani, Mohammad Reza & Mehregan, Nader, 2011. "Local Residents’ Preferences for Second Home Tourism Development Policies: A Choice Experiment nalysis," MPRA Paper 29703, University Library of Munich, Germany.
    53. Ekin Birol & Phoebe Koundouri & Yiannis Kountouris, 2008. "Using the Choice Experiment Method to Inform River Management in Poland: Flood Risk Reduction vs. Habitat Conservation in the Upper Silesia Region," DEOS Working Papers 0802, Athens University of Economics and Business.
    54. Rulleau, Bénédicte & Dehez, Jeoffrey & Point, Patrick, 2012. "Recreational value, user heterogeneity and site characteristics in contingent valuation," Tourism Management, Elsevier, vol. 33(1), pages 195-204.
    55. Brey, Raul & Riera, Pere & Mogas, Joan, 2007. "Estimation of forest values using choice modeling: An application to Spanish forests," Ecological Economics, Elsevier, vol. 64(2), pages 305-312, December.
    56. Peter Howley & Edel Doherty & Cathal Buckley & Stephen Hynes & Tom van Rensburg & Stuart Green, 2010. "Public access to the countryside: An exploration of the costs and benefits of farmland walking trails," Working Papers 1006, Rural Economy and Development Programme,Teagasc.
    57. Maria Salvo & Giuseppe Cucuzza & Giovanni Signorello, 2022. "Using discrete choice experiments to explore how bioecological attributes of sites drive birders’ preferences and willingness to travel," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 24(2), pages 119-146, April.
    58. Veettil, Prakashan Chellattan & Speelman, Stijn & Frija, Aymen & Buysse, Jeroen & van Huylenbroeck, Guido, 2011. "Complementarity between water pricing, water rights and local water governance: A Bayesian analysis of choice behaviour of farmers in the Krishna river basin, India," Ecological Economics, Elsevier, vol. 70(10), pages 1756-1766, August.
    59. Rambonilaza, Tina, 2005. "Land-use planning and public preferences: What can we learn from choice experiments method?," MPRA Paper 9225, University Library of Munich, Germany, revised May 2007.
    60. Carole Ropars-Collet & Mélody Leplat & Philippe Le Goffe & Marie Lesueur, 2015. "La pêche professionnelle est-elle un facteur d’attractivité récréative sur le littoral ?," Revue économique, Presses de Sciences-Po, vol. 66(4), pages 729-754.
    61. Christie, Mike & Fazey, Ioan & Cooper, Rob & Hyde, Tony & Kenter, Jasper O., 2012. "An evaluation of monetary and non-monetary techniques for assessing the importance of biodiversity and ecosystem services to people in countries with developing economies," Ecological Economics, Elsevier, vol. 83(C), pages 67-78.
    62. Doherty, Edel & Campbell, Danny & Hynes, Stephen & van Rensburg, Tom M., 2011. "The effect of using labelled alternatives in stated choice experiments: an exploration focusing on farmland walking trails in Ireland," 85th Annual Conference, April 18-20, 2011, Warwick University, Coventry, UK 108792, Agricultural Economics Society.
    63. Filyushkina, Anna & Agimass, Fitalew & Lundhede, Thomas & Strange, Niels & Jacobsen, Jette Bredahl, 2017. "Preferences for variation in forest characteristics: Does diversity between stands matter?," Ecological Economics, Elsevier, vol. 140(C), pages 22-29.
    64. Concu, Nanni & Atzeni, Gianfranco, 2012. "Conflicting preferences among tourists and residents," Tourism Management, Elsevier, vol. 33(6), pages 1293-1300.
    65. Andrew Daly & Stephane Hess & Christine Eckert, 2013. "Workshop report: working with repeated choice data," Chapters, in: Stephane Hess & Andrew Daly (ed.), Choice Modelling, chapter 4, pages 91-106, Edward Elgar Publishing.
    66. Doherty, Edel & Campbell, Danny & Hynes, Stephen & van Rensburg, Thomas, 2012. "Labelling effects in discrete choice experiments," Working Papers 148831, National University of Ireland, Galway, Socio-Economic Marine Research Unit.
    67. Abildtrup, Jens & Garcia, Serge & Olsen, Soren Boye & Stenger, Anne, 2011. "Spatial Preference Heterogeneity in Forest Recreation," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 120386, European Association of Agricultural Economists.
    68. Tonin, Stefania & Alberini, Anna & Turvani, Margherita, 2009. "The Value of Reducing Cancer Risks at Contaminated Sites: Are More Heavily Exposed People Willing to Pay More?," Sustainable Development Papers 52548, Fondazione Eni Enrico Mattei (FEEM).
    69. Rulleau, Bénédicte & Dehez, Jeoffrey & Point, Patrick, 2011. "The tourist recreational demand for coastal forests: Do forests really matter?," Review of Agricultural and Environmental Studies - Revue d'Etudes en Agriculture et Environnement (RAEStud), Institut National de la Recherche Agronomique (INRA), vol. 92(3).
    70. Raja Chakir & Maia David & Estelle Gozlan & Aminata Sangare, 2016. "Valuing the Impacts of An Invasive Biological Control Agent: A Choice Experiment on the Asian Ladybird in France," Journal of Agricultural Economics, Wiley Blackwell, vol. 67(3), pages 619-638, September.
    71. Lea Nicita & W. Douglass Shaw & Giovanni Signorello, 2018. "Valuing the Benefits of Rock Climbing and the Welfare Gains from Decreasing Injury Risk," Risk Analysis, John Wiley & Sons, vol. 38(11), pages 2258-2274, November.
    72. Glenk, Klaus & Meyerhoff, Jürgen & Akaichi, Faical & Martin-Ortega, Julia, 2019. "Revisiting cost vector effects in discrete choice experiments," Resource and Energy Economics, Elsevier, vol. 57(C), pages 135-155.
    73. Siriwardena, K.S.D. & Gunaratne, L.H.P., 2007. "Analysis of Public Choice on Environmental Health Management: The Case of Dengue Fever Control in Kandy District," Sri Lankan Journal of Agricultural Economics, Sri Lanka Agricultural Economics Association (SAEA), vol. 9, pages 1-13.
    74. Mogas, Joan & Riera, Pere & Bennett, Jeff, 2006. "A comparison of contingent valuation and choice modelling with second-order interactions," Journal of Forest Economics, Elsevier, vol. 12(1), pages 5-30, March.
    75. Yan, Jiong & Barkmann, Jan & Marggraf, Rainer, 2007. "Chinese tourist preferences for nature based destinations: a choice experiment analysis," DARE Discussion Papers 0706, Georg-August University of Göttingen, Department of Agricultural Economics and Rural Development (DARE).
    76. Mara Thiene & Marco Boeri & Caspar Chorus, 2012. "Random Regret Minimization: Exploration of a New Choice Model for Environmental and Resource Economics," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 51(3), pages 413-429, March.
    77. Stephen Hynes & Cathal Buckley & Tom van Rensburg, 2007. "Recreational Pursuits on Marginal Farm Land: A Discrete-Choice Model of Irish Farm Commonage Recreation," The Economic and Social Review, Economic and Social Studies, vol. 38(1), pages 63-84.
    78. Catalina M. Torres & Antoni Riera & Dolores García, 2009. "Are Preferences for Water Quality Different for Second-Home Residents?," Tourism Economics, , vol. 15(3), pages 629-651, September.
    79. Zander, Kerstin K. & Straton, Anna, 2010. "An economic assessment of the value of tropical river ecosystem services: Heterogeneous preferences among Aboriginal and non-Aboriginal Australians," Ecological Economics, Elsevier, vol. 69(12), pages 2417-2426, October.
    80. Catalina M. Torres Figuerola & Antoni Riera Font, 2009. "Defining environmental attributes as external costs in choice experiments: A discussion," CRE Working Papers (Documents de treball del CRE) 2009/1, Centre de Recerca Econòmica (UIB ·"Sa Nostra").
    81. Carole Ropars–Collet & Mélody Leplat & Philippe Le Goffe & Marie Lesueur, 2015. "Commercial Fishery as an Asset for Recreational Demand on the Coastline: Evidence from a Choice Experiment in France, United Kingdom and Belgium," 2015 EAFE (European Association of Fisheries Economists) Conference Papers 009, Nisea.
    82. Stefania Tonin & Anna Alberini & Margherita Turvani, 2012. "The Value of Reducing Cancer Risks at Contaminated Sites: Are More Knowledgeable People Willing to Pay More?," Risk Analysis, John Wiley & Sons, vol. 32(7), pages 1157-1182, July.
    83. Huhtala, Anni & Pouta, Eija, 2006. "Discerning welfare impacts of public provision of recreation areas," Discussion Papers 11860, MTT Agrifood Research Finland.
    84. Vecchiato, D. & Tempesta, T., 2013. "Valuing the benefits of an afforestation project in a peri-urban area with choice experiments," Forest Policy and Economics, Elsevier, vol. 26(C), pages 111-120.

  75. Koop G., 2002. "Comparing the Performance of Baseball Players: A Multiple-Output Approach," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 710-720, September.
    See citations under working paper version above.
  76. Fernandez C. & Koop G. & Steel M.F.J., 2002. "Multiple-Output Production With Undesirable Outputs: An Application to Nitrogen Surplus in Agriculture," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 432-442, June.
    See citations under working paper version above.
  77. Gary Koop & Simon M. Potter, 2001. "Are apparent findings of nonlinearity due to structural instability in economic time series?," Econometrics Journal, Royal Economic Society, vol. 4(1), pages 1-38.
    See citations under working paper version above.
  78. Gary Koop & Dale J. Poirier, 2001. "Testing for optimality in job search models," Econometrics Journal, Royal Economic Society, vol. 4(2), pages 1-6.

    Cited by:

    1. M. Daniele Paserman, 2008. "Job Search and Hyperbolic Discounting: Structural Estimation and Policy Evaluation," Economic Journal, Royal Economic Society, vol. 118(531), pages 1418-1452, August.
    2. Richard J. Boys & Peter J. Dolton & Neil R. Walker, 2007. "Adapting the optimal job search model for active labour market policy," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(3), pages 759-779, July.

  79. Nick Hanley & Gary Koop & Begoña Álvarez‐Farizo & Robert E. Wright & Ceara Nevin, 2001. "Go climb a mountain: an application of recreation demand modelling to rock climbing in Scotland," Journal of Agricultural Economics, Wiley Blackwell, vol. 52(1), pages 36-52, January.

    Cited by:

    1. Jan Hanousek & Randall K. Filer, 2001. "Consumers' Opinion of Inflation Bias Due to Quality Improvements in Transition in the Czech Republic," Development and Comp Systems 0110009, University Library of Munich, Germany.
    2. Stephen Hynes & Nick Hanley & Cathal O’Donoghue, 2006. "Using Continuous and Finite Mixture Models to Account for Preference Heterogeneity in a group of Outdoor Recreationalists," Working Papers 0602, Rural Economy and Development Programme,Teagasc.
    3. Stephen Hynes & Nick Hanley & Eoghan Garvey, 2007. "Up the Proverbial Creek without a Paddle: Accounting for Variable Participant Skill Levels in Recreational Demand Modelling," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 36(4), pages 413-426, April.
    4. Riccardo Scarpa & Mara Thiene, 2005. "Destination Choice Models for Rock Climbing in the Northeastern Alps: A Latent-Class Approach Based on Intensity of Preferences," Land Economics, University of Wisconsin Press, vol. 81(3).
    5. Nick Hanley & Robert Wright & Gary Koop, 2002. "Modelling Recreation Demand Using Choice Experiments: Climbing in Scotland," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 22(3), pages 449-466, July.
    6. J. Shonkwiler & Nick Hanley, 2003. "A New Approach to Random Utility Modeling using the Dirichlet Multinomial Distribution," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 26(3), pages 401-416, November.
    7. Mara Thiene & Riccardo Scarpa, 2008. "Hiking in the Alps: Exploring Substitution Patterns of Hiking Destinations," Tourism Economics, , vol. 14(2), pages 263-282, June.
    8. Carol Mansfield & Daniel J. Phaneuf & F. Reed Johnson & Jui-Chen Yang & Robert Beach, 2008. "Preferences for Public Lands Management under Competing Uses: The Case of Yellowstone National Park," Land Economics, University of Wisconsin Press, vol. 84(2), pages 282-305.
    9. Jan Hanousek & Randall K. Filer, 2004. "Consumers' Opinion of Inflation Bias Due to Quality Improvements," William Davidson Institute Working Papers Series 2004-681, William Davidson Institute at the University of Michigan.
    10. Deely, J. & Hynes, S. & Curtis, J., 2019. "Are objective data a suitable replacement for subjective data in site choice analysis?," Working Papers 309602, National University of Ireland, Galway, Socio-Economic Marine Research Unit.
    11. Scarpa Riccardo & Del Giudice Teresa, 2004. "Market Segmentation via Mixed Logit: Extra-Virgin Olive Oil in Urban Italy," Journal of Agricultural & Food Industrial Organization, De Gruyter, vol. 2(1), pages 1-20, August.
    12. Didi Rao & Jiaran Wang & Moucheng Liu & Nan Ma & Zhidong Li & Yunxiao Bai, 2022. "Research on Ecological Compensation of National Parks Based on Tourism Concession Mechanism," Sustainability, MDPI, vol. 14(11), pages 1-12, May.
    13. Asgary, Ali & Rezvani, Mohammad Reza & Mehregan, Nader, 2011. "Local Residents’ Preferences for Second Home Tourism Development Policies: A Choice Experiment nalysis," MPRA Paper 29703, University Library of Munich, Germany.
    14. W. Bowman Cutter & Linwood Pendleton & J. R. DeShazo, 2007. "Activities in Models of Recreational Demand," Land Economics, University of Wisconsin Press, vol. 83(3), pages 370-381.
    15. Lea Nicita & W. Douglass Shaw & Giovanni Signorello, 2018. "Valuing the Benefits of Rock Climbing and the Welfare Gains from Decreasing Injury Risk," Risk Analysis, John Wiley & Sons, vol. 38(11), pages 2258-2274, November.
    16. Riccardo Scarpa & Mara Thiene, 2004. "Destination Choice Models for Rock Climbing in the Northeast Alps: A Latent-Class Approach Based on Intensity of Participation," Working Papers 2004.131, Fondazione Eni Enrico Mattei.

  80. Koop, Gary, 2001. "Bayesian inference in models based on equilibrium search theory," Journal of Econometrics, Elsevier, vol. 102(2), pages 311-338, June.
    See citations under working paper version above.
  81. Koop, Gary & Li, Kai, 2001. "The valuation of IPO and SEO firms," Journal of Empirical Finance, Elsevier, vol. 8(4), pages 375-401, September.

    Cited by:

    1. Chen, Mei-ping & Lee, Chien-Chiang & Hsu, Yi-Chung, 2011. "The impact of American depositary receipts on the Japanese index: Do industry effect and size effect matter?," Economic Modelling, Elsevier, vol. 28(1), pages 526-539.
    2. William Dimovski & Robert Brooks, 2003. "Financial characteristics of Australian initial public offerings from 1994 to 1999," Applied Economics, Taylor & Francis Journals, vol. 35(14), pages 1599-1607.
    3. Yue-Cheong Chan & Congsheng Wu & Chuck Kwok, 2007. "Valuation of global IPOs: a stochastic frontier approach," Review of Quantitative Finance and Accounting, Springer, vol. 29(3), pages 267-284, October.
    4. Xin Chang & André F. Gygax & Elaine Oon & Hong Feng Zhang, 2008. "Audit quality, auditor compensation and initial public offering underpricing," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 48(3), pages 391-416, September.
    5. Li, Kai, 2007. "The growth in equity market size and trading activity: An international study," Journal of Empirical Finance, Elsevier, vol. 14(1), pages 59-90, January.
    6. Bill Dimovski, 2010. "The Pricing Of Infrastructure Initial Public Offerings: Evidence From Australia," ERES eres2010_028, European Real Estate Society (ERES).
    7. Reber, Beat & Vencappa, Dev, 2016. "Deliberate premarket underpricing and aftermarket mispricing: New insights on IPO pricing," International Review of Financial Analysis, Elsevier, vol. 44(C), pages 18-33.
    8. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
    9. Dimovski, William & Brooks, Robert, 2004. "Do you really want to ask an underwriter how much money you should leave on the table?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 14(3), pages 267-280, July.
    10. William Dimovski & Robert Brooks, 2006. "The Pricing of Property Trust IPOs in Australia," The Journal of Real Estate Finance and Economics, Springer, vol. 32(2), pages 185-199, March.
    11. Dimovski, William & Brooks, Robert, 2008. "The underpricing of gold mining initial public offerings," Research in International Business and Finance, Elsevier, vol. 22(1), pages 1-16, January.
    12. Reber, Beat, 2017. "Does mispricing, liquidity or third-party certification contribute to IPO downside risk?," International Review of Financial Analysis, Elsevier, vol. 51(C), pages 25-53.
    13. Kai Li, 2004. "The Growth of Global Equity Markets: A Closer Look," Econometric Society 2004 North American Winter Meetings 54, Econometric Society.
    14. Wang, Zhuqing & Wang, Xinyu & Xu, Yan & Cheng, Qiuying, 2022. "Are green IPOs priced differently? Evidence from China," Research in International Business and Finance, Elsevier, vol. 61(C).
    15. Marco Cucculelli & Manuela Geranio & Camilla Mazzoli & Sabrina Severini, 2021. "IPO Pricing and Dealers’ Interaction: A Stochastic Frontier Approach," International Business Research, Canadian Center of Science and Education, vol. 14(1), pages 1-1, January.

  82. Koop, Gary, 2001. "Cross-Sectoral Patterns of Efficiency and Technical Change in Manufacturing," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 42(1), pages 73-103, February.

    Cited by:

    1. Jaap W. B. Bos & Bertrand Candelon & Claire Economidou, 2016. "Does knowledge spill over across borders and technology regimes?," Journal of Productivity Analysis, Springer, vol. 46(1), pages 63-82, August.
    2. Djoni Hartono & Budy P. Resosudarmo, 2007. "The Economy-wide Impact of Controlling Energy Consumption in Indonesia: An Analysis Using a Social Accounting Matrix Framework," Departmental Working Papers 2007-05, The Australian National University, Arndt-Corden Department of Economics.
    3. Kyriakos Drivas & Claire Economidou & Efthymios G. Tsionas, 2018. "Production of output and ideas: efficiency and growth patterns in the United States," Regional Studies, Taylor & Francis Journals, vol. 52(1), pages 105-118, January.
    4. Li, Kai, 2007. "The growth in equity market size and trading activity: An international study," Journal of Empirical Finance, Elsevier, vol. 14(1), pages 59-90, January.
    5. Drivas, Kyriakos & Economidou, Claire & Tsionas, Efthymios G., 2014. "A Poisson Stochastic Frontier Model with Finite Mixture Structure," MPRA Paper 57485, University Library of Munich, Germany.
    6. Bos, J.W.B. & Economidou, C. & Koetter, M., 2010. "Technology clubs, R&D and growth patterns: Evidence from EU manufacturing," European Economic Review, Elsevier, vol. 54(1), pages 60-79, January.
    7. Atkinson, Scott E. & Dorfman, Jeffrey H., 2005. "Bayesian measurement of productivity and efficiency in the presence of undesirable outputs: crediting electric utilities for reducing air pollution," Journal of Econometrics, Elsevier, vol. 126(2), pages 445-468, June.
    8. Dorfman, Jeffrey H. & Atkinson, Scott E., 2002. "Multiple Comparisons With The Best: Bayesian Precision Measures Of Efficiency Rankings," 2002 Annual meeting, July 28-31, Long Beach, CA 19800, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    9. Weber, William L. & Domazlicky, Bruce R., 2006. "Capital Deepening and Manufacturing's Contribution to Regional Economic Convergence," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 36(1), pages 1-14.
    10. Subal Kumbhakar & Raquel Ortega-Argilés & Lesley Potters & Marco Vivarelli & Peter Voigt, 2012. "Corporate R&D and firm efficiency: evidence from Europe’s top R&D investors," Journal of Productivity Analysis, Springer, vol. 37(2), pages 125-140, April.
    11. Sueyoshi, Toshiyuki & Ryu, Youngbok, 2022. "Performance assessment on technology transition from small businesses to the U.S. Department of Defense," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    12. Bos, J.W.B. & Economidou, C. & Koetter, M. & Kolari, J.W., 2010. "Do all countries grow alike?," Journal of Development Economics, Elsevier, vol. 91(1), pages 113-127, January.
    13. Krishna G. Iyer & Alicia N. Rambaldi & Kam Ki Tang, 2008. "Efficiency externalities of trade and alternative forms of foreign investment in OECD countries," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(6), pages 749-766.
    14. M. Sanders & J.W.B. Bos & C. Economidou, 2007. "R&D over the Life Cycle," Working Papers 07-18, Utrecht School of Economics.

  83. Koop, Gary & Dijk, Herman K. Van, 2000. "Testing for integration using evolving trend and seasonals models: A Bayesian approach," Journal of Econometrics, Elsevier, vol. 97(2), pages 261-291, August.
    See citations under working paper version above.
  84. Koop, Gary & Osiewalski, Jacek & Steel, Mark F J, 2000. "A Stochastic Frontier Analysis of Output Level and Growth in Poland and Western Economies," Economic Change and Restructuring, Springer, vol. 33(3), pages 185-202.
    See citations under working paper version above.
  85. Koop, Gary & Osiewalski, Jacek & Steel, Mark F J, 2000. "Modeling the Sources of Output Growth in a Panel of Countries," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(3), pages 284-299, July.

    Cited by:

    1. Letizia Montinari & Michael Rochlitz, 2012. "Absorptive Capacity and Efficiency: A Comparative Stochastic Frontier Approach Using Sectoral Data," Working Papers 4/2012, IMT School for Advanced Studies Lucca, revised Jun 2012.
    2. Koop, Gary & Li, Kai, 2001. "The valuation of IPO and SEO firms," Journal of Empirical Finance, Elsevier, vol. 8(4), pages 375-401, September.
    3. Camilla Mastromarco, 2008. "Foreign Capital And Efficiency In Developing Countries," Bulletin of Economic Research, Wiley Blackwell, vol. 60(4), pages 351-374, October.
    4. Danish Ahmed SIDDIQUI & Qazi Masood AHMED, 2019. "Are institutions a crucial determinant of cross country economic efficiency? A two-stage double bootstrap data envelopment analysis," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(1(618), S), pages 89-114, Spring.
    5. Jacek Osiewalski & Justyna Wróblewska & Kamil Makieła, 2020. "Bayesian comparison of production function-based and time-series GDP models," Empirical Economics, Springer, vol. 58(3), pages 1355-1380, March.
    6. Pedro Andres Garzon Delvaux & Heinrich Hockmann & Peter Voigt & Pavel Ciaian & Sergio Gomez y Paloma, 2018. "The impact of private R&D on the performance of food-processing firms: Evidence from Europe, Japan and North America," JRC Research Reports JRC104144, Joint Research Centre.
    7. Wang Zhenhua & Zhang Guangsheng, 2016. "Industrial policy, production efficiency improvement and the Chinese county economic growth," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 34(2), pages 505-528.
    8. Camilla Mastromarco & Léopold Simar, 2015. "Effect of FDI and Time on Catching Up: New Insights from a Conditional Nonparametric Frontier Analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(5), pages 826-847, August.
    9. Lee, Jong-Wha & Hong, Kiseok, 2012. "Economic growth in Asia: Determinants and prospects," Japan and the World Economy, Elsevier, vol. 24(2), pages 101-113.
    10. Federico Inchausti-Sintes & Ubay Pérez-Granja & José Juan Morales-Mohamed, 2021. "Analysing labour productivity and its economic consequences in the two Spanish tourist archipelagos," Tourism Economics, , vol. 27(5), pages 1039-1059, August.
    11. Liao, Hailin & Wang, Bin & Li, Baibing & Weyman-Jones, Tom, 2016. "ICT as a general-purpose technology: The productivity of ICT in the United States revisited," Information Economics and Policy, Elsevier, vol. 36(C), pages 10-25.
    12. Luca Grassetti, 2011. "A note on transformed likelihood approach in linear dynamic panel models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 20(2), pages 221-240, June.
    13. Li, Kai, 2007. "The growth in equity market size and trading activity: An international study," Journal of Empirical Finance, Elsevier, vol. 14(1), pages 59-90, January.
    14. Sok-Gee Chan Mohd & Zaini Abd Karim, 2012. "Public Spending Efficiency And Political And Economic Factors: Evidence From Selected East Asian Countries," Economic Annals, Faculty of Economics and Business, University of Belgrade, vol. 57(193), pages 7-24, April- Ju.
    15. Mastromarco, Camilla & Simar, Leopold, 2018. "Globalization and productivity: A robust nonparametric world frontier analysis," LIDAM Reprints ISBA 2018008, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    16. Kamil Makieła & Błażej Mazur, 2020. "Bayesian Model Averaging and Prior Sensitivity in Stochastic Frontier Analysis," Econometrics, MDPI, vol. 8(2), pages 1-22, April.
    17. Luca Giordano & Claudia Guagliano, 2016. "The Impact of Financial Architecture on Technical Innovation," Applied Economics and Finance, Redfame publishing, vol. 3(3), pages 263-287, August.
    18. Tsionas, Efthymios G. & Papadakis, Emmanuel N., 2010. "A Bayesian approach to statistical inference in stochastic DEA," Omega, Elsevier, vol. 38(5), pages 309-314, October.
    19. Gary Koop, 1998. "Carbon dioxide emissions and economic growth: A structural approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 25(4), pages 489-515.
    20. Efthymios G. Tsionas & Panayotis G. Michaelides, 2016. "A Spatial Stochastic Frontier Model with Spillovers: Evidence for Italian Regions," Scottish Journal of Political Economy, Scottish Economic Society, vol. 63(3), pages 243-257, July.
    21. Efthymios G. Tsionas, 2006. "Inference in dynamic stochastic frontier models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 669-676, July.
    22. Makiela, Kamil, 2010. "State Level Efficiency Measures for Healthcare Systems," MPRA Paper 62172, University Library of Munich, Germany.
    23. Kamil Makieła & Błażej Mazur & Jakub Głowacki, 2022. "The Impact of Renewable Energy Supply on Economic Growth and Productivity," Energies, MDPI, vol. 15(13), pages 1-13, June.
    24. Mastromarco, Camilla & Ghosh, Sucharita, 2009. "Foreign Capital, Human Capital, and Efficiency: A Stochastic Frontier Analysis for Developing Countries," World Development, Elsevier, vol. 37(2), pages 489-502, February.
    25. Makiela, Kamil & Ouattara, Bazoumana, 2018. "Foreign direct investment and economic growth: Exploring the transmission channels," Economic Modelling, Elsevier, vol. 72(C), pages 296-305.
    26. Zwane, Talent & Biyase, Mduduzi & Binda, Thandolwethu, 2021. "Institutions and Technical Efficiency: A Stochastic Frontier Approach," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 74(4), pages 415-438.
    27. Jaume Puig, 2000. "Technical inefficiency and public capital in US States: A stochastic frontier approach," Economics Working Papers 451, Department of Economics and Business, Universitat Pompeu Fabra.
    28. Kamil Makieła, 2017. "Bayesian Inference and Gibbs Sampling in Generalized True Random-Effects Models," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 9(1), pages 69-95, March.
    29. Boyle, Gerry & McQuinn, Kieran, 2004. "Why do some countries produce so much more output per worker than others? - A note," Research Technical Papers 9/RT/04, Central Bank of Ireland.
    30. Thiago Christiano Silva & Benjamin Miranda Tabak & Marcela Tetzner Laiz, 2019. "The Finance-Growth Nexus: the role of banks," Working Papers Series 506, Central Bank of Brazil, Research Department.
    31. Mastromarco, Camilla & Simar, Leopold, 2014. "Global Dependence and Productivity: A Robust Nonparametric World Frontier Analysis," LIDAM Discussion Papers ISBA 2014049, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    32. José L. Gallizo & Jordi Moreno & Manuel Salvador, 2016. "Banking Efficiency in the Enlarged European Union: Financial Crisis and Convergence," International Finance, Wiley Blackwell, vol. 19(1), pages 66-88, April.
    33. Danish Ahmed SIDDIQUI & Qazi Masood AHMED, 2019. "Exploring the role of institutions in cross country Malmquist productivity analysis: A two-stage double bootstrap DEA approach," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(4(621), W), pages 241-264, Winter.
    34. Bos, J.W.B. & Economidou, C. & Koetter, M., 2010. "Technology clubs, R&D and growth patterns: Evidence from EU manufacturing," European Economic Review, Elsevier, vol. 54(1), pages 60-79, January.
    35. Los, Bart & Timmer, Marcel P., 2005. "The 'appropriate technology' explanation of productivity growth differentials: An empirical approach," Journal of Development Economics, Elsevier, vol. 77(2), pages 517-531, August.
    36. Tareq Sadeq, 2008. "Bayesian Analysis of DSGE models: A Panel Approach," Documents de recherche 08-03, Centre d'Études des Politiques Économiques (EPEE), Université d'Evry Val d'Essonne.
    37. Federico Inchausti-Sintes, 2020. "A tourism growth model," Tourism Economics, , vol. 26(5), pages 746-763, August.
    38. Subal Kumbhakar & Raquel Ortega-Argilés & Lesley Potters & Marco Vivarelli & Peter Voigt, 2012. "Corporate R&D and firm efficiency: evidence from Europe’s top R&D investors," Journal of Productivity Analysis, Springer, vol. 37(2), pages 125-140, April.
    39. Yasmina Rim Limam & Stephen M. Miller & Giampaolo Garzarelli, 2016. "Decomposition of Output Growth in the Presence of Input Quality: A Stochastic Frontier Approach," Working papers 2016-13, University of Connecticut, Department of Economics.
    40. Sucharita Ghosh & Camilla Mastromarco, 2013. "Cross-border Economic Activities, Human Capital and Efficiency: A Stochastic Frontier Analysis for OECD Countries," The World Economy, Wiley Blackwell, vol. 36(6), pages 761-785, June.
    41. Hockmann, Heinrich & Garzon Delvaux, Pedro Andres & Voigt, Peter & Ciaian, Pavel & Gomez y Paloma, Sergio, 2017. "Corporate R&D and the performance of foodprocessing firms: Evidence from Europe, Japan and North America," 2017 International Congress, August 28-September 1, 2017, Parma, Italy 261274, European Association of Agricultural Economists.
    42. Farrokh Nourzad, 2002. "Financial development and productive efficiency: A panel study of developed and developing countries," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 26(2), pages 138-148, June.
    43. Luis R. Murillo‐Zamorano, 2004. "Economic Efficiency and Frontier Techniques," Journal of Economic Surveys, Wiley Blackwell, vol. 18(1), pages 33-77, February.
    44. Giampaolo Garzarelli & Stephen M. Miller & Yasmina R. Limam, 2016. "Output Decomposition in the Presence of Input Quality Effects: A Stochastic Frontier Approach," Working Papers 613, Economic Research Southern Africa.
    45. Dobdinga Fonchamnyo & Molem Sama, 2016. "Determinants of public spending efficiency in education and health: evidence from selected CEMAC countries," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 40(1), pages 199-210, January.
    46. Kumbhakar, Subal C. & Tsionas, Mike G., 2021. "Dissections of input and output efficiency: A generalized stochastic frontier model," International Journal of Production Economics, Elsevier, vol. 232(C).
    47. Guanchun Liu & Shichang Ma & Chien‐Chiang Lee & Ming Xu, 2020. "Growth decomposition bias when accounting for heterogeneous regimes: Evidence from China," Review of Development Economics, Wiley Blackwell, vol. 24(2), pages 691-711, May.
    48. Yasmina Reem Limam & Stephen M. Miller, 2004. "Explaining Economic Growth: Factor Accumulation, Total Factor Productivity Growth, and Production Efficiency Improvement," Working papers 2004-20, University of Connecticut, Department of Economics.
    49. Humberto Brea-Solis & Sergio Perelman & David Saal, 2017. "Regulatory incentives to water losses reduction: the case of England and Wales," Journal of Productivity Analysis, Springer, vol. 47(3), pages 259-276, June.
    50. Guangjie Li, 2015. "A stochastic frontier model with structural breaks in efficiency and technology," Empirical Economics, Springer, vol. 49(1), pages 131-159, August.
    51. Kamil Makie{l}a & B{l}a.zej Mazur, 2020. "Stochastic Frontier Analysis with Generalized Errors: inference, model comparison and averaging," Papers 2003.07150, arXiv.org, revised Oct 2020.
    52. Kumbhakar, Subal C. & Lai, Hung-pin, 2021. "A multi-output multi-input stochastic frontier system with input- and output-specific inefficiency," Economics Letters, Elsevier, vol. 201(C).
    53. Sharma, Subhash C. & Sylwester, Kevin & Margono, Heru, 2007. "Decomposition of total factor productivity growth in U.S. states," The Quarterly Review of Economics and Finance, Elsevier, vol. 47(2), pages 215-241, May.
    54. Kai Li, 2004. "The Growth of Global Equity Markets: A Closer Look," Econometric Society 2004 North American Winter Meetings 54, Econometric Society.
    55. Bos, J.W.B. & Economidou, C. & Koetter, M. & Kolari, J.W., 2010. "Do all countries grow alike?," Journal of Development Economics, Elsevier, vol. 91(1), pages 113-127, January.
    56. Kamil Makieła, 2009. "Economic Growth Decomposition. An Empirical Analysis Using Bayesian Frontier Approach," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 1(4), pages 333-369, December.
    57. Kamil Makieła, 2014. "Bayesian Stochastic Frontier Analysis of Economic Growth and Productivity Change in the EU, USA, Japan and Switzerland," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 6(3), pages 193-216, September.

  86. Fernandez, Carmen & Koop, Gary & Steel, Mark, 2000. "A Bayesian analysis of multiple-output production frontiers," Journal of Econometrics, Elsevier, vol. 98(1), pages 47-79, September.
    See citations under working paper version above.
  87. Koop, Gary, 1999. "Bayesian Analysis, Computation and Communication Software," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(6), pages 677-689, Nov.-Dec..

    Cited by:

    1. Twaha, Koire & Rashid, Abdul, 2012. "Exploring the determinants of the productivity of microfinance institutions in India," MPRA Paper 45715, University Library of Munich, Germany.
    2. Bryant, Henry L. & Davis, George C., 2001. "Beyond The Model Specification Problem: Model And Parameter Averaging Using Bayesian Techniques," 2001 Annual meeting, August 5-8, Chicago, IL 20689, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).

  88. Gary Koop & Jacek Osiewalski & Mark F. J. Steel, 1999. "The Components of Output Growth: A Stochastic Frontier Analysis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(4), pages 455-487, November.

    Cited by:

    1. Dev Vencappa & Paul Fenn & Stephen Diacon, 2013. "Productivity Growth in the European Insurance Industry: Evidence from Life and Non-Life Companies," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 20(2), pages 281-305, July.
    2. Letizia Montinari & Michael Rochlitz, 2012. "Absorptive Capacity and Efficiency: A Comparative Stochastic Frontier Approach Using Sectoral Data," Working Papers 4/2012, IMT School for Advanced Studies Lucca, revised Jun 2012.
    3. Danish Ahmed SIDDIQUI & Qazi Masood AHMED, 2019. "Are institutions a crucial determinant of cross country economic efficiency? A two-stage double bootstrap data envelopment analysis," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(1(618), S), pages 89-114, Spring.
    4. Carmen Fernandez & Gary Koop & Mark F J Steel, 1999. "A Bayesian analysis of multiple-output production frontier," Edinburgh School of Economics Discussion Paper Series 21, Edinburgh School of Economics, University of Edinburgh.
    5. Jacek Osiewalski & Justyna Wróblewska & Kamil Makieła, 2020. "Bayesian comparison of production function-based and time-series GDP models," Empirical Economics, Springer, vol. 58(3), pages 1355-1380, March.
    6. Adetutu, Morakinyo O. & Ajayi, Victor, 2020. "The impact of domestic and foreign R&D on agricultural productivity in sub-Saharan Africa," World Development, Elsevier, vol. 125(C).
    7. A. Tonini, 2012. "A Bayesian stochastic frontier: an application to agricultural productivity growth in European countries," Economic Change and Restructuring, Springer, vol. 45(4), pages 247-269, November.
    8. Malinka Koparanova, 2007. "Structural Changes in the Manufacturing Industry of Transition Economies," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 3, pages 3-42.
    9. Camilla Mastromarco & Laura Serlenga & Yongcheol Shin, 2023. "Regional Productivity Network in the EU," CESifo Working Paper Series 10404, CESifo.
    10. Almas Heshmati & Masoomeh Rashidghalam, 2020. "Estimation of technical change and TFP growth based on observable technology shifters," Journal of Productivity Analysis, Springer, vol. 53(1), pages 21-36, February.
    11. Guarini, Giulio & Laureti, Tiziana & Garofalo, Giuseppe, 2020. "Socio-institutional determinants of educational resource efficiency according to the capability approach: An endogenous stochastic frontier analysis," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    12. Kyriakos Drivas & Claire Economidou & Efthymios G. Tsionas, 2018. "Production of output and ideas: efficiency and growth patterns in the United States," Regional Studies, Taylor & Francis Journals, vol. 52(1), pages 105-118, January.
    13. Growiec, Jakub, 2009. "On the Measurement of Technological Progress Across Countries," MPRA Paper 19321, University Library of Munich, Germany.
    14. Liao, Hailin & Wang, Bin & Li, Baibing & Weyman-Jones, Tom, 2016. "ICT as a general-purpose technology: The productivity of ICT in the United States revisited," Information Economics and Policy, Elsevier, vol. 36(C), pages 10-25.
    15. Girma, Sourafel & Görg, Holger, 2006. "Multinationals' Productivity Advantage: Scale or Technology," CEPR Discussion Papers 5841, C.E.P.R. Discussion Papers.
    16. Makieła, Kamil, 2016. "Bayesian inference in generalized true random-effects model and Gibbs sampling," MPRA Paper 69389, University Library of Munich, Germany.
    17. Li, Kai, 2007. "The growth in equity market size and trading activity: An international study," Journal of Empirical Finance, Elsevier, vol. 14(1), pages 59-90, January.
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    Cited by:

    1. Margrethe Winslow, 2005. "The environmental Kuznets curve revisited once again," Forum for Social Economics, Springer;The Association for Social Economics, vol. 35(1), pages 1-18, March.
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    47. Charles Figuières & Solenn Leplay & Estelle Midler & Sophie Thoyer, 2010. "The REDD scheme to curb deforestation: A well-designed system of incentives?," Working Papers 10-06, LAMETA, Universtiy of Montpellier, revised Jun 2010.
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    57. Asher, Sam & Garg, Teevrat & Novosad, Paul, 2018. "The Ecological Footprint of Transportation Infrastructure," 2018 Annual Meeting, August 5-7, Washington, D.C. 274246, Agricultural and Applied Economics Association.
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    60. Barbier, Edward B., 2004. "Agricultural Expansion, Resource Booms and Growth in Latin America: Implications for Long-run Economic Development," World Development, Elsevier, vol. 32(1), pages 137-157, January.
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    62. Catherine M. Chambers & Paul E. Chambers & John C. Whitehead, 2008. "Economic Growth and Threatened and Endangered Species Listings: A VAR Analysis," Working Papers 0801, University of Central Missouri, Department of Economics & Finance, revised May 2008.
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    90. Ph. Nguyen Van & Th. Azomahou, 2005. "Nonlinearties and heterogeneity in environmental quality : an empirical analysis of deforestation," THEMA Working Papers 2005-13, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    91. Ourvashi Bissoon, 2018. "A modified EKC for sustainability assessment in Sub-Saharan Africa: A panel data analysis," Economic Thought journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 2, pages 51-68,69-83.
    92. Iritié, Bi Goli Jean Jacques, 2015. "Economic growth and biodiversity: An overview. Conservation policies in Africa," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 8(2), pages 196-208.
    93. Jie He, 2007. "Is the Environmental Kuznets Curve hypothesis valid for developing countries? A survey," Cahiers de recherche 07-03, Departement d'économique de l'École de gestion à l'Université de Sherbrooke.
    94. Matthew Cole, 2005. "Re-examining the pollution-income relationship: a random coefficients approach," Economics Bulletin, AccessEcon, vol. 14(1), pages 1-7.
    95. Soytas, Ugur & Sari, Ramazan & Ewing, Bradley T., 2007. "Energy consumption, income, and carbon emissions in the United States," Ecological Economics, Elsevier, vol. 62(3-4), pages 482-489, May.
    96. Caravaggio, Nicola, 2020. "A global empirical re-assessment of the Environmental Kuznets curve for deforestation," Forest Policy and Economics, Elsevier, vol. 119(C).
    97. John Hoehn & Kwami Adanu, 2008. "Do growth, investment, and trade encourage water use or water conservation?," Letters in Spatial and Resource Sciences, Springer, vol. 1(2), pages 127-146, December.
    98. Salahodjaev, Raufhon, 2016. "Intelligence and deforestation: International data," Forest Policy and Economics, Elsevier, vol. 63(C), pages 20-27.
    99. Köthke, Margret & Leischner, Bettina & Elsasser, Peter, 2013. "Uniform global deforestation patterns — An empirical analysis," Forest Policy and Economics, Elsevier, vol. 28(C), pages 23-37.
    100. Liu, Jinlong & Liang, Ming & Li, Lingchao & Long, Hexing & De Jong, Wil, 2017. "Comparative study of the forest transition pathways of nine Asia-Pacific countries," Forest Policy and Economics, Elsevier, vol. 76(C), pages 25-34.
    101. Krah, Kwabena, 2023. "Maize price variability, land use change, and forest loss: evidence from Ghana," Land Use Policy, Elsevier, vol. 125(C).
    102. Ezzati, Majid & Singer, Burton H. & Kammen, Daniel M., 2001. "Towards an Integrated Framework for Development and Environment Policy: The Dynamics of Environmental Kuznets Curves," World Development, Elsevier, vol. 29(8), pages 1421-1434, August.
    103. Chuku, Agbai, 2011. "Economic development and environmental quality in Nigeria: is there an environmental Kuznets curve?," MPRA Paper 30195, University Library of Munich, Germany.
    104. Dinda, Soumyananda, 2004. "Environmental Kuznets Curve Hypothesis: A Survey," Ecological Economics, Elsevier, vol. 49(4), pages 431-455, August.
    105. Laetitia Duval & François-Charles Wolff, 2009. "L'effet des transferts migratoires sur la déforestation dans les pays en développement," Working Papers hal-00421222, HAL.
    106. Crespo Cuaresma, Jesús & Heger, Martin, 2019. "Deforestation and economic development: Evidence from national borders," Land Use Policy, Elsevier, vol. 84(C), pages 347-353.
    107. Novice patrick Bakehe, 2018. "Decomposition of the Environmental Kuznets curve for Deforestation in the Congo Basin," Economics Bulletin, AccessEcon, vol. 38(2), pages 1058-1068.
    108. Aldashev, Gani & Vallino, Elena, 2019. "The dilemma of NGOs and participatory conservation," World Development, Elsevier, vol. 123(C), pages 1-1.
    109. Mills Busa, Julianne H., 2013. "Dynamite in the EKC tunnel? Inconsistencies in resource stock analysis under the environmental Kuznets curve hypothesis," Ecological Economics, Elsevier, vol. 94(C), pages 116-126.
    110. Edward B. Barbier, 2001. "The Economics of Tropical Deforestation and Land Use: An Introduction to the Special Issue," Land Economics, University of Wisconsin Press, vol. 77(2), pages 155-171.
    111. Pablo-Romero, María P. & Sánchez-Braza, Antonio & Gil-Pérez, Jesús, 2023. "Is deforestation needed for growth? Testing the EKC hypothesis for Latin America," Forest Policy and Economics, Elsevier, vol. 148(C).
    112. Matias Heino & Matti Kummu & Marika Makkonen & Mark Mulligan & Peter H Verburg & Mika Jalava & Timo A Räsänen, 2015. "Forest Loss in Protected Areas and Intact Forest Landscapes: A Global Analysis," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-21, October.
    113. Lantz, V. & Feng, Q., 2006. "Assessing income, population, and technology impacts on CO2 emissions in Canada: Where's the EKC?," Ecological Economics, Elsevier, vol. 57(2), pages 229-238, May.
    114. Phu NGUYEN VAN, 2002. "Endogenous Population and Environmental Quality," Working Papers of BETA 2002-09, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    115. Danesh Miah, Md. & Farhad Hossain Masum, Md. & Koike, Masao, 2010. "Global observation of EKC hypothesis for CO2, SOx and NOx emission: A policy understanding for climate change mitigation in Bangladesh," Energy Policy, Elsevier, vol. 38(8), pages 4643-4651, August.
    116. Bhattarai, Madhusudan & Hammig, Michael, 2001. "Institutions and the Environmental Kuznets Curve for Deforestation: A Crosscountry Analysis for Latin America, Africa and Asia," World Development, Elsevier, vol. 29(6), pages 995-1010, June.
    117. Boris OK Lokonon & Ichaou Mounirou, 2019. "Does foreign direct investment impede forest area in Sub‐Saharan Africa?," Natural Resources Forum, Blackwell Publishing, vol. 43(4), pages 230-240, November.
    118. Coondoo, Dipankor & Dinda, Soumyananda, 2002. "Causality between income and emission: a country group-specific econometric analysis," Ecological Economics, Elsevier, vol. 40(3), pages 351-367, March.

  91. Koop, Gary & Potter, Simon M., 1998. "Bayes factors and nonlinearity: Evidence from economic time series1," Journal of Econometrics, Elsevier, vol. 88(2), pages 251-281, November.

    Cited by:

    1. Gianluigi Pelloni & Wolfgang Polasek, "undated". "Intersectoral Labour Reallocation and Employment Volatility: A Bayesian Analysis using a VAR-GARCH-M model," Discussion Papers 99/4, Department of Economics, University of York.
    2. Chang-Jin Kim & Jeremy Piger, 2000. "Common Stochastic Trends, Common Cycles, and Asymmetry in Economic Fluctuations," Discussion Papers in Economics at the University of Washington 0021, Department of Economics at the University of Washington.
    3. Doppelhofer, G. & Cuaresma, J.C., 2007. "Nonlinearities in Cross-Country Growth Regressions: A Bayesian Averaging of Thresholds (BAT) Approach," Cambridge Working Papers in Economics 0706, Faculty of Economics, University of Cambridge.
    4. John W. Schindler, 2001. "Testing optimality in job search models," International Finance Discussion Papers 710, Board of Governors of the Federal Reserve System (U.S.).
    5. Chang-Jin Kim & Charles R. Nelson & Jeremy M. Piger, 2003. "The less volatile U.S. economy: a Bayesian investigation of timing, breadth, and potential explanations," Working Papers 2001-016, Federal Reserve Bank of St. Louis.
    6. Marcelle Chauvet & Simon Potter, 2005. "Forecasting recessions using the yield curve," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(2), pages 77-103.
    7. Henry, O.T. & Summers, P.M., 2000. "Australian Economic Growth: Non-Linearities and Internaitonal Influences," Department of Economics - Working Papers Series 738, The University of Melbourne.
    8. Chang-Jin Kim & Charles Nelson, 1999. "A Bayesian Approach to Testing for Markov Switching in Univariate and Dynamic Factor Models," Working Papers 0035, University of Washington, Department of Economics.
    9. Simon M. Potter & Edward E. Leamer, 2004. "A Nonlinear Model of the Business Cycle," Econometric Society 2004 North American Winter Meetings 490, Econometric Society.
    10. Anthony Garratt & Gary Koop & Shaun P. Vahey, 2008. "Forecasting Substantial Data Revisions in the Presence of Model Uncertainty," Economic Journal, Royal Economic Society, vol. 118(530), pages 1128-1144, July.
    11. Huang, Yu-Fan, 2015. "Time variation in U.S. monetary policy and credit spreads," Journal of Macroeconomics, Elsevier, vol. 43(C), pages 205-215.
    12. Andrew D. Sanford & Gael Martin, 2004. "Bayesian Analysis of Continuous Time Models of the Australian Short Rate," Monash Econometrics and Business Statistics Working Papers 11/04, Monash University, Department of Econometrics and Business Statistics.
    13. Chang‐Jin Kim & Jeremy M. Piger & Richard Startz, 2007. "The Dynamic Relationship between Permanent and Transitory Components of U.S. Business Cycles," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(1), pages 187-204, February.
    14. Gianluigi Pelloni & Wolfgang Polasek, 2003. "Macroeconomic Effects of Sectoral Shocks in Germany, The U.K. and, The U.S.: A VAR-GARCH-M Approach," Computational Economics, Springer;Society for Computational Economics, vol. 21(1_2), pages 65-85, February.
    15. Marcelle Chauvet & Chinhui Juhn & Simon M. Potter, 2001. "Markov switching in disaggregate unemployment rates," Staff Reports 132, Federal Reserve Bank of New York.
    16. Marcelle Chauvet & Simon Potter, 2001. "Recent Changes in the US Business Cycle," Manchester School, University of Manchester, vol. 69(5), pages 481-508, October.
    17. Simon Potter, 1999. "Nonlinear Time Series Modelling: An Introduction," Journal of Economic Surveys, Wiley Blackwell, vol. 13(5), pages 505-528, December.
    18. Gary Koop & Simon M. Potter, 2000. "Bayesian Analysis of Endogenous Delay Threshold Models," Edinburgh School of Economics Discussion Paper Series 11, Edinburgh School of Economics, University of Edinburgh.
    19. Penelope Smith, 2006. "Bayesian Inference for a Threshold Autoregression with a Unit Root," Melbourne Institute Working Paper Series wp2006n20, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    20. Chun Liu & John M. Maheu, 2009. "Forecasting realized volatility: a Bayesian model-averaging approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(5), pages 709-733.
    21. Penelope A. Smith & Peter M. Summers, 2002. "Regime Switches in GDP Growth and Volatility: Some International Evidence and Implications for Modelling Business Cycles," Melbourne Institute Working Paper Series wp2002n21, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    22. Sugita, Katsuhiro, 2008. "Bayesian analysis of a Markov switching temporal cointegration model," Japan and the World Economy, Elsevier, vol. 20(2), pages 257-274, March.
    23. Marcelle, Chauvet & Simon, Potter, 2007. "Monitoring Business Cycles with Structural Breaks," MPRA Paper 15097, University Library of Munich, Germany, revised 31 Apr 2009.
    24. Sumru Altuğ & Melike Bildirici, 2010. "Business Cycles around the Globe: A Regime Switching Approach," Working Papers 0032, Yildiz Technical University, Department of Economics, revised Mar 2010.
    25. Chang-Jin Kim & Jeremy M. Piger & Richard Startz, 2001. "Permanent and transitory components of business cycles: their relative importance and dynamic relationship," International Finance Discussion Papers 703, Board of Governors of the Federal Reserve System (U.S.).
    26. C.S. Forbes & G.M. Martin & J. Wright, 2002. "Bayesian Estimation of a Stochastic Volatility Model Using Option and Spot Prices," Monash Econometrics and Business Statistics Working Papers 2/02, Monash University, Department of Econometrics and Business Statistics.
    27. Brock, William A., 2000. "Whither nonlinear?," Journal of Economic Dynamics and Control, Elsevier, vol. 24(5-7), pages 663-678, June.
    28. Man-Suk Oh & Dong Wan Shin, 2002. "Bayesian model selection and parameter estimation for possibly asymmetric and non-stationary time series using a reversible jump Markov chain Monte Carlo approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 29(5), pages 771-789.
    29. Petros Dellaportas & David G. T. Denison & Chris Holmes, 2007. "Flexible Threshold Models for Modelling Interest Rate Volatility," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 419-437.
    30. Hansen,B.E., 1999. "Testing for linearity," Working papers 7, Wisconsin Madison - Social Systems.
    31. Penelope A. Smith & Peter M. Summers, 2004. "Identification and normalization in Markov switching models of \"business cycles\"," Research Working Paper RWP 04-09, Federal Reserve Bank of Kansas City.

  92. Gary Koop, 1998. "Carbon dioxide emissions and economic growth: A structural approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 25(4), pages 489-515.

    Cited by:

    1. Auci, Sabrina & Vignani, Donatella, 2013. "Environmental Kuznets curve and domestic material consumption indicator: an European analysis," MPRA Paper 52882, University Library of Munich, Germany.
    2. Hua Liao & Huaishu Cao, 2012. "How does carbon dioxide emission change with the economic development? Statistical experiences from 132 countries," CEEP-BIT Working Papers 54, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    3. Wen-Ling Hsiao & Jin-Li Hu & Chan Hsiao & Ming-Chung Chang, 2018. "Energy Efficiency of the Baltic Sea Countries: An Application of Stochastic Frontier Analysis," Energies, MDPI, vol. 12(1), pages 1-11, December.
    4. Auci, Sabrina & Becchetti, Leonardo, 2006. "The instability of the adjusted and unadjusted environmental Kuznets curves," Ecological Economics, Elsevier, vol. 60(1), pages 282-298, November.
    5. Halkos, George & Tzeremes, Nickolaos, 2011. "Does the Kyoto Protocol Agreement matters? An environmental efficiency analysis," MPRA Paper 30652, University Library of Munich, Germany.
    6. Kortelainen, Mika, 2008. "Estimation of semiparametric stochastic frontiers under shape constraints with application to pollution generating technologies," MPRA Paper 9257, University Library of Munich, Germany.
    7. Oktay KIZILKAYA, 2017. "The Impact of Economic Growth and Foreign Direct Investment on CO2 Emissions: The Case of Turkey," Turkish Economic Review, KSP Journals, vol. 4(1), pages 106-118, March.
    8. Stern, David I., 2004. "The Rise and Fall of the Environmental Kuznets Curve," World Development, Elsevier, vol. 32(8), pages 1419-1439, August.
    9. Muhammad, Shahbaz & Mihai, Mutascu & Parvez, Azim, 2011. "Environmental Kuznets Curve in Romania and the Role of Energy Consumption," MPRA Paper 32254, University Library of Munich, Germany, revised 15 Jul 2011.
    10. Neophyta Empora & Theofanis Mamuneas, 2011. "The Effect of Emissions on U.S. State Total Factor Productivity Growth," Review of Economic Analysis, Digital Initiatives at the University of Waterloo Library, vol. 3(2), pages 149-172, October.
    11. Chien-Ming Chen & Magali A. Delmas, 2012. "Measuring Eco-Inefficiency: A New Frontier Approach," Operations Research, INFORMS, vol. 60(5), pages 1064-1079, October.
    12. Minzhe Du & Bing Wang & Yanrui Wu, 2014. "Sources of China’s Economic Growth: An Empirical Analysis Based on the BML Index with Green Growth Accounting," Sustainability, MDPI, vol. 6(9), pages 1-22, September.
    13. Auci, Sabrina & Castelli, Annalisa, 2011. "Pollution and economic growth: a maximum likelihood estimation of environmental Kuznets curve," MPRA Paper 53441, University Library of Munich, Germany.
    14. Carmen Fernandez & Gary Koop & Mark F J Steel, 2003. "Alternative efficiency measures for multiple-output production," Edinburgh School of Economics Discussion Paper Series 65, Edinburgh School of Economics, University of Edinburgh.
    15. Kumar, Surender, 2006. "Environmentally sensitive productivity growth: A global analysis using Malmquist-Luenberger index," Ecological Economics, Elsevier, vol. 56(2), pages 280-293, February.
    16. Gary Koop & Lise Tole, 2008. "What is the environmental performance of firms overseas? An empirical investigation of the global gold mining industry," Journal of Productivity Analysis, Springer, vol. 30(2), pages 129-143, October.
    17. Atkinson, Scott E. & Dorfman, Jeffrey H., 2005. "Bayesian measurement of productivity and efficiency in the presence of undesirable outputs: crediting electric utilities for reducing air pollution," Journal of Econometrics, Elsevier, vol. 126(2), pages 445-468, June.
    18. Dorfman, Jeffrey H. & Atkinson, Scott E., 2002. "Multiple Comparisons With The Best: Bayesian Precision Measures Of Efficiency Rankings," 2002 Annual meeting, July 28-31, Long Beach, CA 19800, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    19. Germani, Anna Rita & Morone, Piergiuseppe & Testa, Giuseppina, 2014. "Environmental justice and air pollution: A case study on Italian provinces," Ecological Economics, Elsevier, vol. 106(C), pages 69-82.
    20. Managi, Shunsuke & Kumar, Surender, 2009. "Trade-induced technological change: Analyzing economic and environmental outcomes," Economic Modelling, Elsevier, vol. 26(3), pages 721-732, May.
    21. Pantelis Kalaitzidakis & Theofanis P. Mamuneas & Thanasis Stengos, 2018. "Greenhouse Emissions and Productivity Growth," JRFM, MDPI, vol. 11(3), pages 1-14, July.
    22. Neophyta Empora, 2017. "Air pollution spillovers and U.S. state productivity growth," University of Cyprus Working Papers in Economics 06-2017, University of Cyprus Department of Economics.
    23. Yongling Yao & Xinyi Shen, 2021. "Environmental protection and economic efficiency of low-carbon pilot cities in China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(12), pages 18143-18166, December.

  93. Franses, Philip Hans & Koop, Gary, 1998. "On the sensitivity of unit root inference to nonlinear data transformations," Economics Letters, Elsevier, vol. 59(1), pages 7-15, April.

    Cited by:

    1. Kramer, Walter & Davies, Laurie, 2002. "Testing for unit roots in the context of misspecified logarithmic random walks," Economics Letters, Elsevier, vol. 74(3), pages 313-319, February.
    2. Deleersnyder, B. & Geyskens, I. & Gielens, K. & Dekimpe, M.G., 2002. "How Cannibalistic is the Internet Channel?," ERIM Report Series Research in Management ERS-2002-22-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    3. Helmut Lütkepohl & Fang Xu, 2009. "The Role of the Log Transformation in Forecasting Economic Variables," CESifo Working Paper Series 2591, CESifo.
    4. Deleersnyder, B. & Geyskens, I. & Gielens, K.J.P. & Dekimpe, M.G., 2002. "How cannibalistic is the internet channel? A study of the newspaper industry in the United Kingdom and the Netherlands," Other publications TiSEM 16dcb25c-7ea9-4c75-bdf6-5, Tilburg University, School of Economics and Management.
    5. Valentina Corradi & Norman R. Swanson, 2003. "The Effect of Data Transformation on Common Cycle, Cointegration and Unit Root Tests: Monte Carlo Results and a Simple Test," Departmental Working Papers 200322, Rutgers University, Department of Economics.
    6. Franses, Philip Hans & de Bruin, Paul, 2002. "On data transformations and evidence of nonlinearity," Computational Statistics & Data Analysis, Elsevier, vol. 40(3), pages 621-632, September.
    7. Yang, Zhenlin & Abeysinghe, Tilak, 2002. "An explicit variance formula for the Box-Cox functional form estimator," Economics Letters, Elsevier, vol. 76(2), pages 259-265, July.
    8. Krämer Walter, 2002. "Statistische Besonderheiten von Finanzzeitreihen / Statistical Properties of Financial Time Series," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 222(2), pages 210-229, April.
    9. Gijsenberg, Maarten J. & Nijs, Vincent R., 2019. "Advertising spending patterns and competitor impact," International Journal of Research in Marketing, Elsevier, vol. 36(2), pages 232-250.
    10. Kornelis, Marcel & Dekimpe, Marnik G. & Leeflang, Peter S.H., 2008. "Does competitive entry structurally change key marketing metrics?," International Journal of Research in Marketing, Elsevier, vol. 25(3), pages 173-182.
    11. Damen, Sven & Vastmans, Frank & Buyst, Erik, 2016. "The effect of mortgage interest deduction and mortgage characteristics on house prices," Journal of Housing Economics, Elsevier, vol. 34(C), pages 15-29.

  94. Koop, Gary & Tole, Lise, 1997. "Measuring differential forest outcomes: A tale of two countries," World Development, Elsevier, vol. 25(12), pages 2043-2056, December.

    Cited by:

    1. David López-Carr, 2021. "A Review of Small Farmer Land Use and Deforestation in Tropical Forest Frontiers: Implications for Conservation and Sustainable Livelihoods," Land, MDPI, vol. 10(11), pages 1-23, October.
    2. Cerian Gibbes & Allison L. Hopkins & Armando Inurreta Díaz & Juan Jimenez-Osornio, 2020. "Defining and measuring sustainability: a systematic review of studies in rural Latin America and the Caribbean," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(1), pages 447-468, January.
    3. Nora L. Álvarez-Berríos & Daniel J. Redo & T. Mitchell Aide & Matthew L. Clark & Ricardo Grau, 2013. "Land Change in the Greater Antilles between 2001 and 2010," Land, MDPI, vol. 2(2), pages 1-27, March.

  95. Koop, Gary & Poirier, Dale J., 1997. "Learning about the across-regime correlation in switching regression models," Journal of Econometrics, Elsevier, vol. 78(2), pages 217-227, June.

    Cited by:

    1. Becher, Michael & Stegmueller, Daniel, 2019. "Cognitive Ability, Union Membership, and Voter Turnout," IAST Working Papers 19-97, Institute for Advanced Study in Toulouse (IAST).
    2. James Heckman & Justin L. Tobias & Edward Vytlacil, 2001. "Four Parameters of Interest in the Evaluation of Social Programs," Southern Economic Journal, John Wiley & Sons, vol. 68(2), pages 210-223, October.
    3. Matthew Masten & Alexandre Poirier, 2017. "Inference on breakdown frontiers," CeMMAP working papers 20/17, Institute for Fiscal Studies.
    4. Li, Mingliang & Tobias, Justin L., 2011. "Bayesian inference in a correlated random coefficients model: Modeling causal effect heterogeneity with an application to heterogeneous returns to schooling," Journal of Econometrics, Elsevier, vol. 162(2), pages 345-361, June.
    5. De Groote, Olivier & Declercq, Koen, 2018. "Tracking and specialization of high schools: heterogeneous effects of school choice," TSE Working Papers 18-958, Toulouse School of Economics (TSE), revised Jun 2020.
    6. Andrés Ramírez–Hassan & Rosember Guerra–Urzola, 2021. "Bayesian treatment effects due to a subsidized health program: the case of preventive health care utilization in Medellín (Colombia)," Empirical Economics, Springer, vol. 60(3), pages 1477-1506, March.
    7. Vijay Ganesh Hariharan & Ram Bezawada & Debabrata Talukdar, 2015. "Aggregate Impact of Different Brand Development Strategies," Management Science, INFORMS, vol. 61(5), pages 1164-1182, May.
    8. Gary Koop & M. Hashem Pesaran & Ron P. Smith, 2013. "On Identification of Bayesian DSGE Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(3), pages 300-314, July.
    9. Ishdorj, Ariun & Crepinsek, Mary Kay & Jensen, Helen H., 2012. "Children’s Consumption of Fruits and Vegetables: Do School Environment and Policies Affect Choice in School Meals?," 2012 AAEA/EAAE Food Environment Symposium 123534, Agricultural and Applied Economics Association.
    10. Ariun Ishdorj & Mary Kay Crepinsek & Helen H. Jensen, 2013. "Children's Consumption of Fruits and Vegetables: Do School Environment and Policies Affect Choices at School and Away from School?," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 35(2), pages 341-359.
    11. Axel Heitmueller, 2006. "Public-private sector pay differentials in a devolved Scotland," Journal of Applied Economics, Universidad del CEMA, vol. 9, pages 295-323, November.
    12. Mingliang Li & Dale J. Poirier & Justin L. Tobias, 2004. "Do dropouts suffer from dropping out? Estimation and prediction of outcome gains in generalized selection models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(2), pages 203-225.
    13. Caio Waisman & Harikesh S. Nair & Carlos Carrion, 2019. "Online Causal Inference for Advertising in Real-Time Bidding Auctions," Papers 1908.08600, arXiv.org, revised Feb 2024.
    14. Martijn van Hasselt, 2005. "Bayesian Sampling Algorithms for the Sample Selection and Two-Part Models," Computing in Economics and Finance 2005 241, Society for Computational Economics.
    15. Kajal Lahiri & Jae G. Song, 2000. "The effect of smoking on health using a sequential self‐selection model," Health Economics, John Wiley & Sons, Ltd., vol. 9(6), pages 491-511, September.
    16. Liana Jacobi & Helga Wagner & Sylvia Frühwirth-Schnatter, 2014. "Bayesian Treatment Effects Models with Variable Selection for Panel Outcomes with an Application to Earnings Effects of Maternity Leave," NRN working papers 2014-12, The Austrian Center for Labor Economics and the Analysis of the Welfare State, Johannes Kepler University Linz, Austria.
    17. Jean-Sauveur Ay, 2015. "Information sur l’hétérogénéité de la terre et délégation de la régulation foncière," Post-Print hal-01180698, HAL.
    18. Joshua C.C. Chan & Justin L. Tobias, 2012. "Priors and Posterior Computation in Linear Endogenous Variable Models with Imperfect Instruments," ANU Working Papers in Economics and Econometrics 2012-580, Australian National University, College of Business and Economics, School of Economics.
    19. Michele Piffer, 2016. "Assessing Identifying Restrictions in SVAR Models," Discussion Papers of DIW Berlin 1563, DIW Berlin, German Institute for Economic Research.
    20. Ishdorj, Ariun & Jensen, Helen H. & Tobias, Justin, 2007. "Intra-Household Allocation and Consumption of WIC-Approved Foods: A Bayesian Approach," Staff General Research Papers Archive 12833, Iowa State University, Department of Economics.
    21. van Hasselt, Martijn, 2011. "Bayesian inference in a sample selection model," Journal of Econometrics, Elsevier, vol. 165(2), pages 221-232.
    22. Heitmueller, Axel, 2004. "Public-Private Sector Wage Differentials in Scotland: An Endogenous Switching Model," IZA Discussion Papers 992, Institute of Labor Economics (IZA).
    23. Du Juan, 2012. "Formal and Informal Care: An Empirical Bayesian Analysis Using the Two-part Model," Forum for Health Economics & Policy, De Gruyter, vol. 15(2), pages 1-42, November.
    24. Chib, Siddhartha, 2007. "Analysis of treatment response data without the joint distribution of potential outcomes," Journal of Econometrics, Elsevier, vol. 140(2), pages 401-412, October.
    25. Chib, Siddhartha & Hamilton, Barton H., 2000. "Bayesian analysis of cross-section and clustered data treatment models," Journal of Econometrics, Elsevier, vol. 97(1), pages 25-50, July.
    26. Ira N. Gang & Catherine Y. Co & Myeong-Su Yun, 1999. "Switching Models with Self-Selection: Self-Employment in Hungary," Departmental Working Papers 199912, Rutgers University, Department of Economics.
    27. Halliday, Timothy J. & Mazumder, Bhashkar & Wong, Ashley, 2019. "The Intergenerational Transmission of Health in the United States: A Latent Variables Analysis," IZA Discussion Papers 12740, Institute of Labor Economics (IZA).
    28. Munkin, Murat K. & Trivedi, Pravin K., 2003. "Bayesian analysis of a self-selection model with multiple outcomes using simulation-based estimation: an application to the demand for healthcare," Journal of Econometrics, Elsevier, vol. 114(2), pages 197-220, June.
    29. Ding, Peng, 2014. "Bayesian robust inference of sample selection using selection-t models," Journal of Multivariate Analysis, Elsevier, vol. 124(C), pages 451-464.
    30. Jacobi, Liana & Wagner, Helga & Frühwirth-Schnatter, Sylvia, 2016. "Bayesian treatment effects models with variable selection for panel outcomes with an application to earnings effects of maternity leave," Journal of Econometrics, Elsevier, vol. 193(1), pages 234-250.

  96. Koop, Gary & Ley, Eduardo & Osiewalski, Jacek & Steel, Mark F. J., 1997. "Bayesian analysis of long memory and persistence using ARFIMA models," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 149-169.
    See citations under working paper version above.
  97. Koop, Gary & Osiewalski, Jacek & Steel, Mark F. J., 1997. "Bayesian efficiency analysis through individual effects: Hospital cost frontiers," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 77-105.
    See citations under working paper version above.
  98. Koop, Gary, 1996. "Parameter uncertainty and impulse response analysis," Journal of Econometrics, Elsevier, vol. 72(1-2), pages 135-149.

    Cited by:

    1. Canova, Fabio & Pappa, Evi & Gambetti, Luca, 2006. "The Structural Dynamics of Output Growth and Inflation: Some International Evidence," CEPR Discussion Papers 5878, C.E.P.R. Discussion Papers.
    2. van Dijk, Dick & Hans Franses, Philip & Peter Boswijk, H., 2007. "Absorption of shocks in nonlinear autoregressive models," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4206-4226, May.
    3. Canova, Fabio & Gambetti, Luca, 2009. "Structural changes in the US economy: Is there a role for monetary policy?," Journal of Economic Dynamics and Control, Elsevier, vol. 33(2), pages 477-490, February.
    4. Antonio Pacifico, 2018. "Panel Bayesian VAR Modeling for Policy and Forecasting when dealing with confounding and latent effects," EERI Research Paper Series EERI RP 2018/15, Economics and Econometrics Research Institute (EERI), Brussels.
    5. Mohamed, Hazik & Masih, Mansur, 2017. "Stock market comovement among the ASEAN-5 : a causality analysis," MPRA Paper 98781, University Library of Munich, Germany.
    6. Koop, Gary & Leon-Gonzalez, Roberto & Strachan, Rodney W., 2009. "On the evolution of the monetary policy transmission mechanism," Journal of Economic Dynamics and Control, Elsevier, vol. 33(4), pages 997-1017, April.
    7. Camilo Alberto Cárdenas-Hurtado & Aaron Levi Garavito-Acosta & Jorge Hernán Toro-Córdoba, 2018. "Asymmetric Effects of Terms of Trade Shocks on Tradable and Non-tradable Investment Rates: The Colombian Case," Borradores de Economia 1043, Banco de la Republica de Colombia.
    8. Gary Koop & Roberto Leon-Gonzalez & Rodney W. Strachan, 2008. "On the Evolution of Monetary Policy," Working Paper series 24_08, Rimini Centre for Economic Analysis.
    9. Simon M. Potter, 1999. "Nonlinear impulse response functions," Staff Reports 65, Federal Reserve Bank of New York.
    10. Luca Gambetti & Evi Pappa & Fabio Canova, 2005. "The structural dynamics of US output and inflation: What explains the changes?," Economics Working Papers 921, Department of Economics and Business, Universitat Pompeu Fabra.
    11. Marina Tkalec, 2011. "The Dynamics of Deposit Euroization in European Post-transition Countries: Evidence from Threshold VAR," Working Papers 1102, The Institute of Economics, Zagreb.
    12. Kilian, Lutz, 2019. "Facts and Fiction in Oil Market Modeling," CEPR Discussion Papers 14047, C.E.P.R. Discussion Papers.
    13. Atsushi Inoue & Lutz Kilian, 2020. "Joint Bayesian Inference about Impulse Responses in VAR Models," Working Papers 2022, Federal Reserve Bank of Dallas.
    14. Canova, Fabio & Gambetti, Luca, 2006. "Structural Changes in the US Economy: Bad Luck or Bad Policy?," CEPR Discussion Papers 5457, C.E.P.R. Discussion Papers.
    15. Berg, Tim Oliver, 2014. "Time Varying Fiscal Multipliers in Germany," MPRA Paper 57223, University Library of Munich, Germany.
    16. Fabio Canova & Luca Gambetti, 2004. "On the Time Variations of US Monetary Policy: Who is right?," Money Macro and Finance (MMF) Research Group Conference 2004 96, Money Macro and Finance Research Group.
    17. Samuel F. Onipede & Nafiu A. Bashir & Jamaladeen Abubakar, 2023. "Small open economies and external shocks: an application of Bayesian global vector autoregression model," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(2), pages 1673-1699, April.
    18. Simon Potter, 1999. "Nonlinear Time Series Modelling: An Introduction," Journal of Economic Surveys, Wiley Blackwell, vol. 13(5), pages 505-528, December.
    19. Baum, Anja & Koester, Gerrit B., 2011. "The impact of fiscal policy on economic activity over the business cycle - evidence from a threshold VAR analysis," Discussion Paper Series 1: Economic Studies 2011,03, Deutsche Bundesbank.
    20. Pettenuzzo, Davide & Sabbatucci, Riccardo & Timmermann, Allan, 2023. "Dividend suspensions and cash flows during the Covid-19 pandemic: A dynamic econometric model," Journal of Econometrics, Elsevier, vol. 235(2), pages 1522-1541.
    21. Pacifico, Antonio, 2020. "Structural Panel Bayesian VAR with Multivariate Time-varying Volatility to jointly deal with Structural Changes, Policy Regime Shifts, and Endogeneity Issues," MPRA Paper 104292, University Library of Munich, Germany.
    22. Thobekile Qabhobho & Anokye M. Adam & Anthony Adu-Asare Idun & Emmanuel Asafo-Adjei & Ebenezer Boateng, 2023. "Exploring the Time-varying Connectedness and Contagion Effects among Exchange Rates of BRICS, Energy Commodities, and Volatilities," International Journal of Energy Economics and Policy, Econjournals, vol. 13(2), pages 272-283, March.
    23. Jean-Pierre Allegret & Audrey Allegret, 2018. "The role of international reserves holding in buffering external shocks," Applied Economics, Taylor & Francis Journals, vol. 50(29), pages 3128-3147, June.
    24. Calza Alessandro & Sousa João, 2006. "Output and Inflation Responses to Credit Shocks: Are There Threshold Effects in the Euro Area?," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(2), pages 1-21, May.
    25. Antonio Pacifico, 2019. "International Co-movements and Business Cycles Synchronization Across Advanced Economies: A SPBVAR Evidence," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 8(4), pages 68-84, July.
    26. Antonio Pacifico, 2021. "Structural Panel Bayesian VAR with Multivariate Time-Varying Volatility to Jointly Deal with Structural Changes, Policy Regime Shifts, and Endogeneity Issues," Econometrics, MDPI, vol. 9(2), pages 1-35, May.
    27. Rozina Shaheen, 2020. "Credit market conditions and impact of monetary policy in a developing economy context," International Economics and Economic Policy, Springer, vol. 17(2), pages 409-425, May.
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    31. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    32. Ms. Anja Baum & Mr. Marcos Poplawski Ribeiro & Miss Anke Weber, 2012. "Fiscal Multipliers and the State of the Economy," IMF Working Papers 2012/286, International Monetary Fund.
    33. Kim, Bong-Han & Chun, Sun-Eae & Min, Hong-Ghi, 2010. "Nonlinear dynamics in arbitrage of the S&P 500 index and futures: A threshold error-correction model," Economic Modelling, Elsevier, vol. 27(2), pages 566-573, March.
    34. van Dijk, D.J.C. & Franses, Ph.H.B.F. & Boswijk, H.P., 2000. "Asymmetric and common absorption of shocks in nonlinear autoregressive models," Econometric Institute Research Papers EI 2000-01/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    35. Wright, Jonathan H., 1999. "Frequency domain inference for univariate impulse responses," Economics Letters, Elsevier, vol. 63(3), pages 269-277, June.
    36. Shen, Chung-Hua & Chiang, Thomas Chi-Nan, 1999. "Retrieving the vanishing liquidity effect--a threshold vector autoregressive model," Journal of Economics and Business, Elsevier, vol. 51(3), pages 259-277, May.
    37. Antonio Pacifico, 2019. "Structural Panel Bayesian VAR Model to Deal with Model Misspecification and Unobserved Heterogeneity Problems," Econometrics, MDPI, vol. 7(1), pages 1-24, March.
    38. Xiaqing Su & Zhe Liu, 2021. "Sector Volatility Spillover and Economic Policy Uncertainty: Evidence from China’s Stock Market," Mathematics, MDPI, vol. 9(12), pages 1-22, June.
    39. Sevda Yaprakli & Fatih Kaplan, 2015. "Re-examining of the Turkish Crude Oil Import Demand with Multi-structural Breaks Analysis in the Long Run Period," International Journal of Energy Economics and Policy, Econjournals, vol. 5(2), pages 402-407.
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  99. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.

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    3. Andrey Sinyakov, 2013. "Declared and actual policy of the Russian Central Bank in 2000–2008: how large is the difference? (in Russian)," Quantile, Quantile, issue 11, pages 91-106, December.
    4. Andreas Georgantopoulos, 2012. "Electricity Consumption and Economic Growth: Analysis and Forecasts using VAR/VEC Approach for Greece with Capital Formation," International Journal of Energy Economics and Policy, Econjournals, vol. 2(4), pages 263-278.
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    6. Ioannis Chatziantoniou & David Gabauer, 2019. "EMU-Risk Synchronisation and Financial Fragility Through the Prism of Dynamic Connectedness," Working Papers in Economics & Finance 2019-07, University of Portsmouth, Portsmouth Business School, Economics and Finance Subject Group.
    7. Kamal, Javed Bin & Hassan, M. Kabir, 2022. "Asymmetric connectedness between cryptocurrency environment attention index and green assets," The Journal of Economic Asymmetries, Elsevier, vol. 25(C).
    8. Bouri, Elie & Cepni, Oguzhan & Gabauer, David & Gupta, Rangan, 2021. "Return connectedness across asset classes around the COVID-19 outbreak," International Review of Financial Analysis, Elsevier, vol. 73(C).
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    10. Hasan, Mudassar & Arif, Muhammad & Naeem, Muhammad Abubakr & Ngo, Quang-Thanh & Taghizadeh–Hesary, Farhad, 2021. "Time-frequency connectedness between Asian electricity sectors," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 208-224.
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    2137. Fasanya, Ismail O. & Oyewole, Oluwatomisin & Dauda, Mariam, 2023. "Uncertainty due to infectious diseases and bitcoin-gold nexus: Evidence from a non-parametric causality-in-quantiles approach," Resources Policy, Elsevier, vol. 82(C).
    2138. Le, Thai-Ha & Chang, Youngho, 2013. "Oil price shocks and trade imbalances," Energy Economics, Elsevier, vol. 36(C), pages 78-96.
    2139. Lee, Chien-Chiang & Chien, Mei-Se, 2010. "Dynamic modelling of energy consumption, capital stock, and real income in G-7 countries," Energy Economics, Elsevier, vol. 32(3), pages 564-581, May.
    2140. Efthymios Pavlidis & Ivan Paya & David Peel, 2010. "Further empirical evidence on the consumption-real exchange rate anomaly," Working Papers 447022, Lancaster University Management School, Economics Department.
    2141. Castrén, Olli & Dées, Stéphane & Zaher, Fadi, 2010. "Stress-testing euro area corporate default probabilities using a global macroeconomic model," Journal of Financial Stability, Elsevier, vol. 6(2), pages 64-78, June.
    2142. Kang, Sang Hoon & Uddin, Gazi Salah & Troster, Victor & Yoon, Seong-Min, 2019. "Directional spillover effects between ASEAN and world stock markets," Journal of Multinational Financial Management, Elsevier, vol. 52.
    2143. Soytas, Ugur & Sari, Ramazan, 2006. "Can China contribute more to the fight against global warming?," Journal of Policy Modeling, Elsevier, vol. 28(8), pages 837-846, November.
    2144. Wang, Yudong & Guo, Zhuangyue, 2018. "The dynamic spillover between carbon and energy markets: New evidence," Energy, Elsevier, vol. 149(C), pages 24-33.
    2145. Catherine Araujo Bonjean & Magali Aubert & Johny Egg, 2011. "Commerce du mil en Afrique de l'Ouest : les frontières abolies ?," CERDI Working papers halshs-00556667, HAL.
    2146. Ngo Thai Hung, 2020. "Market integration among foreign exchange rate movements in central and eastern European countries," Society and Economy, Akadémiai Kiadó, Hungary, vol. 42(1), pages 1-20, March.
    2147. Lance Kent & Toan Phan, 2019. "Time-Varying Skewness and Real Business Cycles," Economic Quarterly, Federal Reserve Bank of Richmond, issue 2Q, pages 59-103.
    2148. Grimme, Christian & Henzel, Steffen, 2023. "Uncertainty Shocks in Times of Low and High Uncertainty," VfS Annual Conference 2023 (Regensburg): Growth and the "sociale Frage" 277629, Verein für Socialpolitik / German Economic Association.
    2149. Giovanni Ballarin, 2023. "Impulse Response Analysis of Structural Nonlinear Time Series Models," Papers 2305.19089, arXiv.org, revised Aug 2023.
    2150. Balli, Faruk & Hasan, Mudassar & Ozer-Balli, Hatice & Gregory-Allen, Russell, 2021. "Why do U.S. uncertainties drive stock market spillovers? International evidence," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 288-301.
    2151. Kang, Sang Hoon & McIver, Ron & Yoon, Seong-Min, 2017. "Dynamic spillover effects among crude oil, precious metal, and agricultural commodity futures markets," Energy Economics, Elsevier, vol. 62(C), pages 19-32.
    2152. Liu, Ming-Lei & Ji, Qiang & Fan, Ying, 2013. "How does oil market uncertainty interact with other markets? An empirical analysis of implied volatility index," Energy, Elsevier, vol. 55(C), pages 860-868.
    2153. Apostolakis, Georgios N. & Giannellis, Nikolaos & Papadopoulos, Athanasios P., 2019. "Financial stress and asymmetric shocks transmission within the Eurozone. How fragile is the common monetary policy?," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    2154. Evrim Mandaci, Pınar & Azimli, Asil & Mandaci, Nazif, 2023. "The impact of geopolitical risks on connectedness among natural resource commodities: A quantile vector autoregressive approach," Resources Policy, Elsevier, vol. 85(PA).
    2155. Dario Caldara & Chiara Scotti & Molin Zhong, 2021. "Macroeconomic and Financial Risks: A Tale of Mean and Volatility," International Finance Discussion Papers 1326, Board of Governors of the Federal Reserve System (U.S.).
    2156. Jushuang Qin & Menglu Ma & Jiabin Shi & Shurui Ma & Baoguo Wu & Xiaohui Su, 2023. "The Time-Lag Effect of Climate Factors on the Forest Enhanced Vegetation Index for Subtropical Humid Areas in China," IJERPH, MDPI, vol. 20(1), pages 1-18, January.
    2157. Bajo-Rubio, Oscar & Berke, Burcu & McMillan, David, 2017. "The behaviour of asset return and volatility spillovers in Turkey: A tale of two crises," Research in International Business and Finance, Elsevier, vol. 41(C), pages 577-589.
    2158. José Cancelo & Estefanía Mourelle, 2005. "Modeling Cyclical Asymmetries in GDP: International Evidence," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 33(3), pages 297-309, September.
    2159. Guglielmo Maria Caporale & Nicola Spagnolo & Awon Almajali, 2022. "Fossil and Renewable Energy Stock Indices: Connectedness and the COP Meetings," CESifo Working Paper Series 9824, CESifo.
    2160. Al-Shboul, Mohammad & Assaf, Ata & Mokni, Khaled, 2022. "When bitcoin lost its position: Cryptocurrency uncertainty and the dynamic spillover among cryptocurrencies before and during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 83(C).
    2161. Lu, Helen & Jacobsen, Ben, 2016. "Cross-asset return predictability: Carry trades, stocks and commodities," Journal of International Money and Finance, Elsevier, vol. 64(C), pages 62-87.
    2162. Xiao-Li Gong & Jin-Yan Lu & Xiong Xiong & Wei Zhang, 2022. "Higher-order dynamic effects of uncertainty risk under thick-tailed stochastic volatility," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-22, December.
    2163. Zhang, Dayong & Lei, Lei & Ji, Qiang & Kutan, Ali M., 2019. "Economic policy uncertainty in the US and China and their impact on the global markets," Economic Modelling, Elsevier, vol. 79(C), pages 47-56.
    2164. Yaming Ma & Ziwei Wang & Feng He, 2022. "How do economic policy uncertainties affect stock market volatility? Evidence from G7 countries," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 2303-2325, April.
    2165. Li, Yanshuang & Zhuang, Xintian & Wang, Jian, 2021. "Analysis of the cross-region risk contagion effect in stock market based on volatility spillover networks: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    2166. Michael Fratantoni & Scott Schuh, 2000. "Monetary policy, housing investment, and heterogeneous regional markets," Working Papers 00-1, Federal Reserve Bank of Boston.
    2167. Váry, Miklós, 2021. "The long-run real effects of monetary shocks: Lessons from a hybrid post-Keynesian-DSGE-agent-based menu cost model," Economic Modelling, Elsevier, vol. 105(C).
    2168. Meryem Türel & Ayhan Orhan, 2022. "Asymmetries in Exchange Rate Pass-through in Turkey: A Threshold VAR Analysis," Prague Economic Papers, Prague University of Economics and Business, vol. 2022(3-4), pages 276-295.
    2169. Ramiro Losada & Ricardo Laborda, 2020. "La interconexión en las instituciones de inversión colectiva no alternativas y el riesgo sistémico," CNMV Documentos de Trabajo CNMV Documentos de Trabaj, CNMV- Comisión Nacional del Mercado de Valores - Departamento de Estudios y Estadísticas.
    2170. Francesco Cordoni & Nicolas Doremus & Alessio Moneta, 2023. "Identification of Vector Autoregressive Models with Nonlinear Contemporaneous Structure," LEM Papers Series 2023/07, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    2171. Francis Vitek, 2005. "On Risk Premia and Volatility Transmission Across the Stock and Bond Markets," Finance 0508014, University Library of Munich, Germany.

  100. Koop, Gary & Osiewalski, Jacek & Steel, Mark F. J., 1995. "Bayesian long-run prediction in time series models," Journal of Econometrics, Elsevier, vol. 69(1), pages 61-80, September.
    See citations under working paper version above.
  101. Gary Koop & Dale J. Poirier, 1995. "An Empirical Investigation of Wagner's Hypothesis by Using a Model Occurrence Framework," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 158(1), pages 123-141, January.

    Cited by:

    1. Samad Bashirli & Ilkin Sabiroglu, 2013. "Testing Wagner’s Law in an Oil-Exporting Economy: the Case of Azerbaijan," Transition Studies Review, Springer;Central Eastern European University Network (CEEUN), vol. 20(3), pages 295-307, November.
    2. Magazzino, Cosimo, 2010. "Wagner's law and augmented Wagner's law in EU-27. A time-series analysis on stationarity, cointegration and causality," MPRA Paper 26668, University Library of Munich, Germany.
    3. Francisca Galindo-Garre & Jeroen K. Vermunt & Wicher P. Bergsma, 2004. "Bayesian Posterior Estimation of Logit Parameters with Small Samples," Sociological Methods & Research, , vol. 33(1), pages 88-117, August.
    4. Magazzino, Cosimo, 2009. "Wagner's law in Italy: empirical evidence from 1960 to 2008," MPRA Paper 25526, University Library of Munich, Germany.
    5. Magazzino, Cosimo, 2010. "Wagner's law and Italian disaggregated public spending: some empirical evidences," MPRA Paper 26662, University Library of Munich, Germany.

  102. Koop, Gary, 1994. "An objective Bayesian analysis of common stochastic trends in international stock prices and exchange rates," Journal of Empirical Finance, Elsevier, vol. 1(3-4), pages 343-364, July.

    Cited by:

    1. Roberto Leon-Gonzalez & Fuyu Yang, 2010. "Bayesian Estimation and Model Selection in the Generalised Stochastic Unit Root Model," SFB 649 Discussion Papers SFB649DP2010-006, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Magris Martin & Iosifidis Alexandros, 2021. "Approximate Bayes factors for unit root testing," Papers 2102.10048, arXiv.org, revised Feb 2021.
    3. Koop, G. & Strachan, R.W. & van Dijk, H.K. & Villani, M., 2005. "Bayesian approaches to cointegratrion," Econometric Institute Research Papers EI 2005-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Srinivasan Palamalai & Kalaivani M. & Christopher Devakumar, 2013. "Stock Market Linkages in Emerging Asia-Pacific Markets," SAGE Open, , vol. 3(4), pages 21582440135, November.
    5. P.R. Madhusoodanan & Hareesh V. Kumar, 2008. "An Empirical Verification of Cointegration and Causality in Indian Stock Markets," South Asia Economic Journal, Institute of Policy Studies of Sri Lanka, vol. 9(1), pages 159-172, June.
    6. P., Srinivasan & M., Kalaivani, 2013. "Stock Market Linkages in Emerging Asia-Pacific Markets," MPRA Paper 45871, University Library of Munich, Germany.
    7. Pan, Ming-Shiun & Liu, Y. Angela, 1999. "Fractional cointegration, long memory, and exchange rate dynamics," International Review of Economics & Finance, Elsevier, vol. 8(3), pages 305-316, September.
    8. Yi Zheng & Heng Chen, 2011. "Who is More Important – a Leading Power or a Close Neighbor?," Chapters, in: Lilai Xu (ed.), China’s Economy in the Post-WTO Environment, chapter 1, Edward Elgar Publishing.
    9. Rodney Strachan & Herman K. van Dijk, "undated". "Bayesian Model Averaging in Vector Autoregressive Processes with an Investigation of Stability of the US Great Ratios and Risk of a Liquidity Trap in the USA, UK and Japan," MRG Discussion Paper Series 1407, School of Economics, University of Queensland, Australia.
    10. Gary Koop & Roberto León-González & Rodney W. Strachan, 2010. "Efficient Posterior Simulation for Cointegrated Models with Priors on the Cointegration Space," Econometric Reviews, Taylor & Francis Journals, vol. 29(2), pages 224-242, April.
    11. Pagan, Adrian, 1996. "The econometrics of financial markets," Journal of Empirical Finance, Elsevier, vol. 3(1), pages 15-102, May.
    12. Zheng Yi & Chen Heng & Wing-Keung Wong, 2009. "China’s Stock Market Integration with a Leading Power and a Close Neighbor," JRFM, MDPI, vol. 2(1), pages 1-37, December.

  103. Koop, G & Poirier, D J, 1994. "Rank-Ordered Logit Models: An Empirical Analysis of Ontario Voter Preferences," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 9(4), pages 369-388, Oct.-Dec..

    Cited by:

    1. Mulatu Debalke, Negash, 2011. "Determinants of farmers’ preference for adaptation strategies to climate change: evidence from north shoa zone of Amhara region Ethiopia," MPRA Paper 48753, University Library of Munich, Germany.
    2. Poirier, Dale J., 1997. "Comparing and choosing between two models with a third model in the background," Journal of Econometrics, Elsevier, vol. 78(2), pages 139-151, June.
    3. Lei Zhang & David Levinson, 2006. "Determinants of Route Choice and the Value of Traveler Information," Working Papers 200808, University of Minnesota: Nexus Research Group.
    4. McCabe, Christopher & Brazier, John & Gilks, Peter & Tsuchiya, Aki & Roberts, Jennifer & O'Hagan, Anthony & Stevens, Katherine, 2006. "Using rank data to estimate health state utility models," Journal of Health Economics, Elsevier, vol. 25(3), pages 418-431, May.
    5. Alain Carpentier & Karine Latouche & Pierre Rainelli & . Association of Environmental And Resource Economists, 2002. "Food safety in the demand for meat quality : the case of pork chops in France," Post-Print hal-01937048, HAL.
    6. Dennis Fok & Richard Paap & Bram Van Dijk, 2012. "A Rank‐Ordered Logit Model With Unobserved Heterogeneity In Ranking Capabilities," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(5), pages 831-846, August.
    7. Paudel, Krishna P. & Poudel, Biswo N. & Dunn, Michael A. & Pandit, Mahesh, 2009. "An Analysis of Rank Ordered Data," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49518, Agricultural and Applied Economics Association.
    8. Poirier, Dale J., 1996. "A Bayesian analysis of nested logit models," Journal of Econometrics, Elsevier, vol. 75(1), pages 163-181, November.
    9. McCabe, C & Brazier, J & Gilks, P & Tsuchiya, A & Roberts, J & O'Hagan, A & Stevens, K, 2004. "Estimating population cardinal health state valuation models from individual ordinal (rank) health state preference data," MPRA Paper 29759, University Library of Munich, Germany.
    10. Philip Yu, 2000. "Bayesian analysis of order-statistics models for ranking data," Psychometrika, Springer;The Psychometric Society, vol. 65(3), pages 281-299, September.
    11. Can Cui & Susheela P. Singh & Ana‐Maria Staicu & Brian J. Reich, 2021. "Bayesian variable selection for high‐dimensional rank data," Environmetrics, John Wiley & Sons, Ltd., vol. 32(7), November.
    12. Marco A. Palma, 2017. "Improving the prediction of ranking data," Empirical Economics, Springer, vol. 53(4), pages 1681-1710, December.

  104. van den Broeck, Julien & Koop, Gary & Osiewalski, Jacek & Steel, Mark F. J., 1994. "Stochastic frontier models : A Bayesian perspective," Journal of Econometrics, Elsevier, vol. 61(2), pages 273-303, April.
    See citations under working paper version above.
  105. Koop, Gary, 1994. "Bayesian Semi-nonparametric ARCH Models," The Review of Economics and Statistics, MIT Press, vol. 76(1), pages 176-181, February.

    Cited by:

    1. Font, Begoña, 1998. "Modelización de series temporales financieras. Una recopilación," DES - Documentos de Trabajo. Estadística y Econometría. DS 3664, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Xibin Zhang & Maxwell L. King, 2011. "Bayesian semiparametric GARCH models," Monash Econometrics and Business Statistics Working Papers 24/11, Monash University, Department of Econometrics and Business Statistics.
    3. Xibin Zhang & Maxwell L. King, 2013. "Gaussian kernel GARCH models," Monash Econometrics and Business Statistics Working Papers 19/13, Monash University, Department of Econometrics and Business Statistics.

  106. Koop, Gary, 1994. "Recent Progress in Applied Bayesian Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 8(1), pages 1-34, March.

    Cited by:

    1. Justin L. Tobias & Mingliang Li, 2004. "Returns to Schooling and Bayesian Model Averaging: A Union of Two Literatures," Journal of Economic Surveys, Wiley Blackwell, vol. 18(2), pages 153-180, April.
    2. Thabo M. Mokoena & Rangan Gupta & Reneé Van Eyden, 2009. "Testing For Ppp Using Sadc Real Exchange Rates," South African Journal of Economics, Economic Society of South Africa, vol. 77(3), pages 351-362, September.
    3. Koop, Gary & Osiewalski, Jacek & Steel, Mark F. J., 1997. "Bayesian efficiency analysis through individual effects: Hospital cost frontiers," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 77-105.
    4. Francis W. Ahking, 2004. "The Power of the "Objective" Bayesian Unit-Root Test," Working papers 2004-14, University of Connecticut, Department of Economics.
    5. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2014. "On the Rise of Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 14-085/III, Tinbergen Institute, revised 04 Sep 2014.
    6. Stefano Grassi & Tommaso Proietti, 2010. "Characterizing economic trends by Bayesian stochastic model specification search," EERI Research Paper Series EERI_RP_2010_25, Economics and Econometrics Research Institute (EERI), Brussels.
    7. Marta Arbelo-Pérez & Pilar Pérez-Gómez & Antonio Arbelo, 2023. "Profit efficiency and its determinants in the agricultural sector: A Bayesian approach," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 69(11), pages 436-445.
    8. Koop, G. & Osiewalski, J. & Steel, M.F.J., 1994. "Hospital efficiency analysis through individual effects : A Bayesian approach," Other publications TiSEM dd6fed13-3fda-461f-9393-e, Tilburg University, School of Economics and Management.
    9. Siddhartha Chib & Edward Greenberg, 1994. "Markov Chain Monte Carlo Simulation Methods in Econometrics," Econometrics 9408001, University Library of Munich, Germany, revised 23 Feb 1995.
    10. Gary Koop, 1998. "Carbon dioxide emissions and economic growth: A structural approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 25(4), pages 489-515.
    11. Efthymios G. Tsionas, 2006. "Inference in dynamic stochastic frontier models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 669-676, July.
    12. Justel, Ana & Peña, Daniel & Sánchez, María Jesús, 1994. "Grupos atípicos en modelos econométricos," DES - Documentos de Trabajo. Estadística y Econometría. DS 10755, Universidad Carlos III de Madrid. Departamento de Estadística.
    13. Francis W. Ahking, 2002. "Is the Bayesian Approach Necessarily Better than the Classical Approach in Unit-Root Test?," Working papers 2002-18, University of Connecticut, Department of Economics.
    14. Tanizaki, Hisashi, 1997. "Nonlinear and nonnormal filters using Monte Carlo methods," Computational Statistics & Data Analysis, Elsevier, vol. 25(4), pages 417-439, September.
    15. Tanizaki, Hisashi & Mariano, Roberto S., 1998. "Nonlinear and non-Gaussian state-space modeling with Monte Carlo simulations," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 263-290.
    16. Hanrahan, Kevin F. & Westhoff, Patrick C. & Young, Robert E., II, 2001. "Trade Allocation Modeling: Comparing The Results From Armington And Locally Regular Ai Demand System Specifications Of A Uk Beef Import Demand Allocation Model," 2001 Annual meeting, August 5-8, Chicago, IL 20510, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    17. Davis, George C., 2001. "Confirmation And Falsification Of Equilibrium Displacement Models," 2001 Annual meeting, August 5-8, Chicago, IL 20525, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    18. Luis R. Murillo‐Zamorano, 2004. "Economic Efficiency and Frontier Techniques," Journal of Economic Surveys, Wiley Blackwell, vol. 18(1), pages 33-77, February.
    19. Heckelei, Thomas & Mittelhammer, Ronald C. & Wahl, Thomas I., 1997. "Bayesian Analysis of a Japanese Meat Demand System: A Robust Likelihood Approach," Discussion Papers 18783, University of Bonn, Institute for Food and Resource Economics.
    20. Loukia Meligkotsidou & Elias Tzavalis & Ioannis D. Vrontos, 2004. "A Bayesian Analysis of Unit Roots and Structural Breaks in the Level and the Error Variance of Autoregressive Models," Working Papers 514, Queen Mary University of London, School of Economics and Finance.

  107. Koop, Gary & Osiewalski, Jacek & Steel, Mark F J, 1994. "Bayesian Efficiency Analysis with a Flexible Form: The AIM Cost Function," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 339-346, July.
    See citations under working paper version above.
  108. Koop, Gary & Steel, Mark F J, 1994. "A Decision-Theoretic Analysis of the Unit-Root Hypothesis Using Mixtures of Elliptical Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(1), pages 95-107, January.
    See citations under working paper version above.
  109. Koop, Gary & Osiewalski, Jacek & Steel, Mark F J, 1994. "Posterior Properties of Long-Run Impulse Responses," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(4), pages 489-492, October.

    Cited by:

    1. Koop, G. & Ley, E. & Osiewalski, J. & Steel, M. F. J., 1997. "Bayesian analysis of long memory and persistence using ARFIMA models," LIDAM Reprints CORE 1246, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Manveer Kaur Mangat & Erhard Reschenhofer, 2019. "Testing for Long-Range Dependence in Financial Time Series," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 11(2), pages 93-106, June.
    3. Koop, Gary, 1996. "Parameter uncertainty and impulse response analysis," Journal of Econometrics, Elsevier, vol. 72(1-2), pages 135-149.
    4. Guney, Selin, 2015. "An evaluation of price forecasts of the cattle market under structural changes," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205109, Agricultural and Applied Economics Association.

  110. Koop, Gary & Poirier, Dale J., 1993. "Bayesian analysis of logit models using natural conjugate priors," Journal of Econometrics, Elsevier, vol. 56(3), pages 323-340, April.

    Cited by:

    1. Poirier, Dale J., 1997. "Comparing and choosing between two models with a third model in the background," Journal of Econometrics, Elsevier, vol. 78(2), pages 139-151, June.
    2. Gary Koop, 2001. "Modeling the Evolution of Distributions: An Application to Major League Baseball," Edinburgh School of Economics Discussion Paper Series 71, Edinburgh School of Economics, University of Edinburgh.
    3. Mohammad Arshad Rahman & Angela Vossmeyer, 2019. "Estimation and Applications of Quantile Regression for Binary Longitudinal Data," Papers 1909.05560, arXiv.org.
    4. David Hensher & William Greene, 2003. "The Mixed Logit model: The state of practice," Transportation, Springer, vol. 30(2), pages 133-176, May.
    5. Filippeli, Thomai & Harrison, Richard & Theodoridis, Konstantinos, 2018. "DSGE-based priors for BVARs and quasi-Bayesian DSGE estimation," Bank of England working papers 716, Bank of England.
    6. Bermúdez, Ll. & Pérez, J.M. & Ayuso, M. & Gómez, E. & Vázquez, F.J., 2008. "A Bayesian dichotomous model with asymmetric link for fraud in insurance," Insurance: Mathematics and Economics, Elsevier, vol. 42(2), pages 779-786, April.
    7. Kerem Tuzcuoglu, 2019. "Composite Likelihood Estimation of an Autoregressive Panel Probit Model with Random Effects," Staff Working Papers 19-16, Bank of Canada.
    8. Poirier, Dale J., 1996. "A Bayesian analysis of nested logit models," Journal of Econometrics, Elsevier, vol. 75(1), pages 163-181, November.
    9. Kajal Lahiri & Jian Gao, 2001. "Bayesian Analysis of Nested Logit Model by Markov Chain Monte Carlo," Discussion Papers 01-14, University at Albany, SUNY, Department of Economics.
    10. Daziano, Ricardo A., 2013. "Conditional-logit Bayes estimators for consumer valuation of electric vehicle driving range," Resource and Energy Economics, Elsevier, vol. 35(3), pages 429-450.
    11. Ricardo A. Daziano & Luis Miranda-Moreno & Shahram Heydari, 2013. "Computational Bayesian Statistics in Transportation Modeling: From Road Safety Analysis to Discrete Choice," Transport Reviews, Taylor & Francis Journals, vol. 33(5), pages 570-592, September.
    12. Jihyun Park & Juhyun Lee & Suneung Ahn, 2018. "Bayesian Approach for Estimating the Probability of Cartel Penalization under the Leniency Program," Sustainability, MDPI, vol. 10(6), pages 1-15, June.
    13. John Geweke & Michael P. Keane, 1997. "Mixture of normals probit models," Staff Report 237, Federal Reserve Bank of Minneapolis.
    14. McCulloch, Robert E. & Polson, Nicholas G. & Rossi, Peter E., 2000. "A Bayesian analysis of the multinomial probit model with fully identified parameters," Journal of Econometrics, Elsevier, vol. 99(1), pages 173-193, November.
    15. Thomai Filippeli, 2011. "Theoretical Priors for BVAR Models & Quasi-Bayesian DSGE Model Estimation," 2011 Meeting Papers 396, Society for Economic Dynamics.
    16. Filippeli, Thomai & Harrison, Richard & Theodoridis, Konstantinos, 2018. "DSGE-based Priors for BVARs & Quasi-Bayesian DSGE Estimation," Cardiff Economics Working Papers E2018/5, Cardiff University, Cardiff Business School, Economics Section.
    17. Brownstone, David, 2001. "Discrete Choice Modeling for Transportation," University of California Transportation Center, Working Papers qt29v7d1pk, University of California Transportation Center.
    18. Guggisberg Michael, 2019. "Misspecified Discrete Choice Models and Huber-White Standard Errors," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-17, January.

  111. Koop, Gary & Ruhm, Christopher J., 1993. "Econometric estimation of proportional hazard models," Journal of Economics and Business, Elsevier, vol. 45(5), pages 421-430, December.

    Cited by:

    1. Garczorz, Ingo, 2001. "Anwendung der Hazard-Analyse im Marketing: Einführung und Literaturüberblick," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 548, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    2. Yang, Zhenlin & Tsui, Albert K., 2004. "Analytically calibrated Box-Cox percentile limits for duration and event-time models," Insurance: Mathematics and Economics, Elsevier, vol. 35(3), pages 649-677, December.

  112. Beaudry, Paul & Koop, Gary, 1993. "Do recessions permanently change output?," Journal of Monetary Economics, Elsevier, vol. 31(2), pages 149-163, April.

    Cited by:

    1. Kennedy, James E., 1998. "An Analysis of Time-Series Estimates of Capacity Utilization," Journal of Macroeconomics, Elsevier, vol. 20(1), pages 169-187, January.
    2. Garcia, R. & Schaller, H., 1995. "Are the Effects of Monetary Policy Asymmetric?," Cahiers de recherche 9505, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    3. Quentin LAJAUNIE, 2021. "Nonlinear Impulse Response Function for Dichotomous Models," LEO Working Papers / DR LEO 2852, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    4. Frédéric Karamé & Alexandra Olmedo, 2010. "Asymmetric Properties of Impulse Response Functions in Markov-Switching Structural Vector AutoRegressions," Documents de recherche 10-04, Centre d'Études des Politiques Économiques (EPEE), Université d'Evry Val d'Essonne.
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    1. Canova, Fabio & Ciccarelli, Matteo, 2001. "Forecasting and Turning Point Predictions in a Bayesian Panel VAR Model," CEPR Discussion Papers 2961, C.E.P.R. Discussion Papers.
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    4. Koop, Gary & Korobilis, Dimitris, 2010. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(4), pages 267-358, July.
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    8. Markku Lanne & Helmut Luetkepohl & Katarzyna Maciejowska, 2009. "Structural Vector Autoregressions with Markov Switching," Economics Working Papers ECO2009/06, European University Institute.
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  114. Koop, Gary, 1992. "'Objective' Bayesian Unit Root Tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(1), pages 65-82, Jan.-Marc.

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    1. Koedijk, Kees G. & Tims, Ben & van Dijk, Mathijs A., 2004. "Purchasing power parity and the euro area," Journal of International Money and Finance, Elsevier, vol. 23(7-8), pages 1081-1107.
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    4. Thabo M. Mokoena & Rangan Gupta & Reneé Van Eyden, 2009. "Testing For Ppp Using Sadc Real Exchange Rates," South African Journal of Economics, Economic Society of South Africa, vol. 77(3), pages 351-362, September.
    5. Francis W. Ahking, 2004. "The Power of the "Objective" Bayesian Unit-Root Test," Working papers 2004-14, University of Connecticut, Department of Economics.
    6. Stefano Grassi & Tommaso Proietti, 2010. "Characterizing economic trends by Bayesian stochastic model specification search," EERI Research Paper Series EERI_RP_2010_25, Economics and Econometrics Research Institute (EERI), Brussels.
    7. Grigorios Emvalomatis, 2017. "Is productivity diverging in the EU? Evidence from 11 Member States," Empirical Economics, Springer, vol. 53(3), pages 1171-1192, November.
    8. N. Vijayamohanan Pillai, 2010. "Electricity Demand Analysis and Forecasting- The Tradition is Questioned," Working Papers id:2966, eSocialSciences.
    9. Francis W. Ahking, 2002. "Is the Bayesian Approach Necessarily Better than the Classical Approach in Unit-Root Test?," Working papers 2002-18, University of Connecticut, Department of Economics.
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    12. N. Vijayamohanan Pillai, 2001. "Electricity demand analysis and forecasting: The tradition is questioned," Centre for Development Studies, Trivendrum Working Papers 312, Centre for Development Studies, Trivendrum, India.
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  115. Koop, Gary, 1991. "Intertemporal Properties of Real Output: A Bayesian Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(3), pages 253-265, July.

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    1. Granger, C.W.J. (Clive William John), 1992. "What are we learning about the long-run?," UC3M Working papers. Economics 2886, Universidad Carlos III de Madrid. Departamento de Economía.
    2. Koop, G. & Ley, E. & Osiewalski, J. & Steel, M. F. J., 1997. "Bayesian analysis of long memory and persistence using ARFIMA models," LIDAM Reprints CORE 1246, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Koop, G. & Steel, M.F.J., 1991. "A decision theoretic analysis of the unit root hypothesis using mixtures of elliptical models," Discussion Paper 1991-50, Tilburg University, Center for Economic Research.
    4. Gael Martin, 2001. "Bayesian Analysis Of A Fractional Cointegration Model," Econometric Reviews, Taylor & Francis Journals, vol. 20(2), pages 217-234.
    5. Grigorios Emvalomatis, 2017. "Is productivity diverging in the EU? Evidence from 11 Member States," Empirical Economics, Springer, vol. 53(3), pages 1171-1192, November.
    6. Cribari-Neto, Francisco, 1996. "On time series econometrics," The Quarterly Review of Economics and Finance, Elsevier, vol. 36(Supplemen), pages 37-60.
    7. Daniel Neuhoff, 2015. "Dynamics of Real Per Capita GDP," SFB 649 Discussion Papers SFB649DP2015-039, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    8. Charley Xia and William Griffiths, 2012. "Bayesian Unit Root Testing: The Effect Of Choice Of Prior On Test Outcomes," Department of Economics - Working Papers Series 1152, The University of Melbourne.
    9. Gil-Alana, L. A. & Robinson, P. M., 1997. "Testing of unit root and other nonstationary hypotheses in macroeconomic time series," Journal of Econometrics, Elsevier, vol. 80(2), pages 241-268, October.

  116. Koop, Gary, 1991. "Cointegration tests in present value relationships : A Bayesian look at the bivariate properties of stock prices and dividends," Journal of Econometrics, Elsevier, vol. 49(1-2), pages 105-139.

    Cited by:

    1. Caporale, Guglielmo Maria & Gil-Alana, Luis A., 2004. "Fractional cointegration and tests of present value models," Review of Financial Economics, Elsevier, vol. 13(3), pages 245-258.
    2. Magris Martin & Iosifidis Alexandros, 2021. "Approximate Bayes factors for unit root testing," Papers 2102.10048, arXiv.org, revised Feb 2021.
    3. Koop, G. & Strachan, R.W. & van Dijk, H.K. & Villani, M., 2005. "Bayesian approaches to cointegratrion," Econometric Institute Research Papers EI 2005-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Guglielmo Maria Caporale & Luis A. Gil-Alana, 2011. "Fractional Integration and Cointegration in US Financial Time Series Data," Discussion Papers of DIW Berlin 1116, DIW Berlin, German Institute for Economic Research.
    5. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2014. "On the Rise of Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 14-085/III, Tinbergen Institute, revised 04 Sep 2014.
    6. Kleibergen, F.R. & Paap, R., 1998. "Priors, posteriors and Bayes factors for a Bayesian analysis of cointegration," Econometric Institute Research Papers EI 9821, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    7. Rodney Strachan & Herman K. van Dijk, "undated". "Bayesian Model Averaging in Vector Autoregressive Processes with an Investigation of Stability of the US Great Ratios and Risk of a Liquidity Trap in the USA, UK and Japan," MRG Discussion Paper Series 1407, School of Economics, University of Queensland, Australia.
    8. Dorfman, Jeffrey H., 1995. "A numerical bayesian test for cointegration of AR processes," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 289-324.
    9. Ossama Mikhail, 2005. "What Happens After A Technology Shock? A Bayesian Perspective," Macroeconomics 0510016, University Library of Munich, Germany.

  117. Koop, Gary & Steel, Mark F J, 1991. "To Criticize the Critics: An Objective Bayesian Analysis of Stochastic Trends: A Comment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(4), pages 365-370, Oct.-Dec..

    Cited by:

    1. Yong Li & Jun Yu, 2011. "Bayesian Hypothesis Testing in Latent Variable Models," Working Papers 11-2011, Singapore Management University, School of Economics.
    2. Koop, G. & Steel, M.F.J., 1991. "A decision theoretic analysis of the unit root hypothesis using mixtures of elliptical models," Discussion Paper 1991-50, Tilburg University, Center for Economic Research.
    3. Márcio Alves Diniz & C.A.B.Pereira & J.M.Stern, 2008. "FBST for Unit Root Problems," Working Papers 08_11, Universidade de São Paulo, Faculdade de Economia, Administração e Contabilidade de Ribeirão Preto.
    4. Dedola, Luca & Neri, Stefano, 2007. "What does a technology shock do? A VAR analysis with model-based sign restrictions," Journal of Monetary Economics, Elsevier, vol. 54(2), pages 512-549, March.
    5. Marek Jarocinski & Albert Marcet, 2011. "Autoregressions in Small Samples, Priors about Observables and Initial Conditions," CEP Discussion Papers dp1061, Centre for Economic Performance, LSE.
    6. Loukia Meligkotsidou & Elias Tzavalis & Ioannis D. Vrontos, 2004. "A Bayesian Analysis of Unit Roots and Structural Breaks in the Level and the Error Variance of Autoregressive Models," Working Papers 514, Queen Mary University of London, School of Economics and Finance.

Chapters

  1. Gary Koop & Luca Onorante, 2019. "Macroeconomic Nowcasting Using Google Probabilities☆," Advances in Econometrics, in: Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part A, volume 40, pages 17-40, Emerald Group Publishing Limited.

    Cited by:

    1. Anttonen, Jetro, 2018. "Nowcasting the Unemployment Rate in the EU with Seasonal BVAR and Google Search Data," ETLA Working Papers 62, The Research Institute of the Finnish Economy.
    2. VAN DER WIELEN Wouter & BARRIOS Salvador, 2020. "Fear and Employment During the COVID Pandemic: Evidence from Search Behaviour in the EU," JRC Working Papers on Taxation & Structural Reforms 2020-08, Joint Research Centre.
    3. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
    4. Tuhkuri, Joonas, 2016. "Forecasting Unemployment with Google Searches," ETLA Working Papers 35, The Research Institute of the Finnish Economy.
    5. Levent Bulut, 2015. "Google Trends and Forecasting Performance of Exchange Rate Models," IPEK Working Papers 1505, Ipek University, Department of Economics.
    6. James Chapman & Ajit Desai, 2021. "Using Payments Data to Nowcast Macroeconomic Variables During the Onset of COVID-19," Staff Working Papers 21-2, Bank of Canada.
    7. Götz, Thomas B. & Knetsch, Thomas A., 2019. "Google data in bridge equation models for German GDP," International Journal of Forecasting, Elsevier, vol. 35(1), pages 45-66.
    8. Svatopluk Kapounek & Evžen Kocenda & Zuzana Kucerová, 2021. "Selective Attention in Exchange Rate Forecasting," CESifo Working Paper Series 8901, CESifo.
    9. Pierre Guérin & Danilo Leiva-Leon, 2015. "Model Averaging in Markov-Switching Models: Predicting National Recessions with Regional Data," Staff Working Papers 15-24, Bank of Canada.
    10. Bańbura, Marta & Belousova, Irina & Bodnár, Katalin & Tóth, Máté Barnabás, 2023. "Nowcasting employment in the euro area," Working Paper Series 2815, European Central Bank.
    11. M. Elshendy & A. Fronzetti Colladon & E. Battistoni & P. A. Gloor, 2021. "Using four different online media sources to forecast the crude oil price," Papers 2105.09154, arXiv.org.
    12. Serena Ng, 2017. "Opportunities and Challenges: Lessons from Analyzing Terabytes of Scanner Data," NBER Working Papers 23673, National Bureau of Economic Research, Inc.
    13. Luca Onorante & Adrian E. Raftery, 2014. "Dynamic Model Averaging in Large Model Spaces Using Dynamic Occam's Window," Papers 1410.7799, arXiv.org.
    14. Caperna, Giulio & Colagrossi, Marco & Geraci, Andrea & Mazzarella, Gianluca, 2020. "Googling Unemployment During the Pandemic: Inference and Nowcast Using Search Data," Working Papers 2020-04, Joint Research Centre, European Commission.
    15. Eraslan, Sercan & Schröder, Maximilian, 2019. "Nowcasting GDP with a large factor model space," Discussion Papers 41/2019, Deutsche Bundesbank.
    16. Krzysztof DRACHAL, 2020. "Forecasting the Inflation Rate in Poland and U.S. Using Dynamic Model Averaging (DMA) and Google Queries," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 18-34, July.
    17. Cristea, R. G., 2020. "Can Alternative Data Improve the Accuracy of Dynamic Factor Model Nowcasts?," Cambridge Working Papers in Economics 20108, Faculty of Economics, University of Cambridge.
    18. James Chapman & Ajit Desai, 2022. "Macroeconomic Predictions Using Payments Data and Machine Learning," Staff Working Papers 22-10, Bank of Canada.
    19. Caperna, Giulio & Colagrossi, Marco & Geraci, Andrea & Mazzarella, Gianluca, 2022. "A babel of web-searches: Googling unemployment during the pandemic," Labour Economics, Elsevier, vol. 74(C).

  2. Miguel Belmonte & Gary Koop, 2014. "Model Switching and Model Averaging in Time-Varying Parameter Regression Models," Advances in Econometrics, in: Bayesian Model Comparison, volume 34, pages 45-69, Emerald Group Publishing Limited.
    See citations under working paper version above.

Books

  1. Chan,Joshua & Koop,Gary & Poirier,Dale J. & Tobias,Justin L., 2019. "Bayesian Econometric Methods," Cambridge Books, Cambridge University Press, number 9781108423380.
    See citations under working paper version above.
  2. Geweke, John & Koop, Gary & van Dijk, Herman (ed.), 2013. "The Oxford Handbook of Bayesian Econometrics," OUP Catalogue, Oxford University Press, number 9780199681334, Decembrie.

    Cited by:

    1. Olga Korotkikh, 2020. "A Multi-Country BVAR Model for the External Sector," Russian Journal of Money and Finance, Bank of Russia, vol. 79(4), pages 98-112, December.
    2. Barbara Rossi, 2019. "Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them," Economics Working Papers 1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.

  3. Geweke, John & Koop, Gary & van Dijk, Herman (ed.), 2011. "The Oxford Handbook of Bayesian Econometrics," OUP Catalogue, Oxford University Press, number 9780199559084, Decembrie.

    Cited by:

    1. Hautsch, Nikolaus & Voigt, Stefan, 2017. "Large-scale portfolio allocation under transaction costs and model uncertainty," CFS Working Paper Series 582, Center for Financial Studies (CFS).
    2. Robert Kollmann, 2014. "Tractable Latent State Filtering for Non-Linear DSGE Models Using a Second-Order Approximation and Pruning," ULB Institutional Repository 2013/250061, ULB -- Universite Libre de Bruxelles.
    3. Dario Caldara & Cristina Fuentes-Albero & Simon Gilchrist & Egon Zakrajšek, 2016. "The Macroeconomic Impact of Financial and Uncertainty Shocks," International Finance Discussion Papers 1166, Board of Governors of the Federal Reserve System (U.S.).
    4. Leonardo Nogueira Ferreira & Silvia Miranda-Agrippino & Giovanni Ricco, 2023. "Bayesian Local Projections," Working Papers Series 581, Central Bank of Brazil, Research Department.
    5. Chang, Tsung-Sheng & Tone, Kaoru & Wu, Chen-Hui, 2021. "Nested dynamic network data envelopment analysis models with infinitely many decision making units for portfolio evaluation," European Journal of Operational Research, Elsevier, vol. 291(2), pages 766-781.
    6. Yong Li & Jun Yu, 2011. "Bayesian Hypothesis Testing in Latent Variable Models," Working Papers 11-2011, Singapore Management University, School of Economics.
    7. Paccagnini, Alessia, 2017. "Dealing with Misspecification in DSGE Models: A Survey," MPRA Paper 82914, University Library of Munich, Germany.
    8. S. Boragan Aruoba & Luigi Bocola & Frank Schorfheide, 2013. "Assessing DSGE model nonlinearities," Working Papers 13-47, Federal Reserve Bank of Philadelphia.
    9. Miranda-Agrippino, Silvia & Ricco, Giovanni, 2018. "Bayesian vector autoregressions," LSE Research Online Documents on Economics 87393, London School of Economics and Political Science, LSE Library.
    10. Frank Schorfheide & Dongho Song, 2015. "Real-Time Forecasting With a Mixed-Frequency VAR," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(3), pages 366-380, July.
    11. Stoye, Jörg, 2012. "Minimax regret treatment choice with covariates or with limited validity of experiments," Journal of Econometrics, Elsevier, vol. 166(1), pages 138-156.
    12. Li, Youwei & Waterworth, James, 2016. "Eurozone network connectedness during calm and crisis: evidence from the MTS platform for interdealer trading of European sovereign debt," MPRA Paper 71221, University Library of Munich, Germany.
    13. Mawuli Segnon & Rangan Gupta & Stelios Bekiros & Mark E. Wohar, 2018. "Forecasting US GNP growth: The role of uncertainty," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(5), pages 541-559, August.
    14. Leung, Melvern & Fung, Man Chung & O’Hare, Colin, 2018. "A comparative study of pricing approaches for longevity instruments," Insurance: Mathematics and Economics, Elsevier, vol. 82(C), pages 95-116.
    15. Cosmas Dery & Apostolos Serletis, 2021. "Disentangling the Effects of Uncertainty, Monetary Policy and Leverage Shocks on the Economy," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(5), pages 1029-1065, October.
    16. Heckelei, Thomas & Huettel, Silke & Odening, Martin & Rommel, Jens, 2021. "The replicability crisis and the p-value debate – what are the consequences for the agricultural and food economics community?," Discussion Papers 316369, University of Bonn, Institute for Food and Resource Economics.
    17. I-Chun Tsai & Che-Chun Lin, 2019. "Variations and Influences of Connectedness among US Housing Markets," International Real Estate Review, Global Social Science Institute, vol. 22(1), pages 27-58.
    18. Güneş Kamber & Chris McDonald & Gael Price, 2013. "Drying out: Investigating the economic effects of drought in New Zealand," Reserve Bank of New Zealand Analytical Notes series AN2013/02, Reserve Bank of New Zealand.
    19. Rodney W. Strachan & Herman K. Van Dijk, 2013. "Evidence On Features Of A Dsge Business Cycle Model From Bayesian Model Averaging," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 54(1), pages 385-402, February.
    20. Yong Li & Xiaobin Liu & Jun Yu & Tao Zeng, 2018. "A New Wald Test for Hypothesis Testing Based on MCMC outputs," Papers 1801.00973, arXiv.org.
    21. BAUWENS, Luc & KOROBILIS, Dimitris, 2011. "Bayesian methods," LIDAM Discussion Papers CORE 2011061, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    22. Amendola, Adalgiso & Di Serio, Mario & Fragetta, Matteo & Melina, Giovanni, 2020. "The euro-area government spending multiplier at the effective lower bound," European Economic Review, Elsevier, vol. 127(C).
    23. Canova, Fabio & Ciccarelli, Matteo, 2012. "ClubMed? Cyclical fluctuations in the Mediterranean basin," Journal of International Economics, Elsevier, vol. 88(1), pages 162-175.
    24. Rubio-Ramírez, Juan Francisco & Schorfheide, Frank & Fernández-Villaverde, Jesús, 2015. "Solution and Estimation Methods for DSGE Models," CEPR Discussion Papers 11032, C.E.P.R. Discussion Papers.
    25. Gael M. Martin & David T. Frazier & Christian P. Robert, 2022. "Computing Bayes: From Then `Til Now," Monash Econometrics and Business Statistics Working Papers 14/22, Monash University, Department of Econometrics and Business Statistics.
    26. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    27. Tomasz Woźniak, 2016. "Bayesian Vector Autoregressions," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 49(3), pages 365-380, September.
    28. Di Serio, Mario & Fragetta, Matteo & Gasteiger, Emanuel, 2020. "The government spending multiplier at the zero lower bound: Evidence from the United States," ECON WPS - Working Papers in Economic Theory and Policy 04/2020, TU Wien, Institute of Statistics and Mathematical Methods in Economics, Economics Research Unit.
    29. Ankargren Sebastian & Unosson Måns & Yang Yukai, 2020. "A Flexible Mixed-Frequency Vector Autoregression with a Steady-State Prior," Journal of Time Series Econometrics, De Gruyter, vol. 12(2), pages 1-41, July.
    30. Glen Livingston Jr & Darfiana Nur, 2020. "Bayesian estimation and model selection of a multivariate smooth transition autoregressive model," Environmetrics, John Wiley & Sons, Ltd., vol. 31(6), September.
    31. Cosmas Dery & Apostolos Serletis, 2021. "The Relative Importance of Monetary Policy, Uncertainty, and Financial Shocks," Open Economies Review, Springer, vol. 32(2), pages 311-333, April.
    32. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2014. "On the Rise of Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 14-085/III, Tinbergen Institute, revised 04 Sep 2014.
    33. Canova, Fabio & Ferroni, Filippo, 2020. "A hitchhiker guide to empirical macro models," CEPR Discussion Papers 15446, C.E.P.R. Discussion Papers.
    34. Dario Caldara & Michele Cavallo & Matteo Iacoviello, 2016. "Oil Price Elasticities and Oil Price Fluctuations," International Finance Discussion Papers 1173, Board of Governors of the Federal Reserve System (U.S.).
    35. Diebold, Francis X. & Schorfheide, Frank & Shin, Minchul, 2017. "Real-time forecast evaluation of DSGE models with stochastic volatility," CFS Working Paper Series 577, Center for Financial Studies (CFS).
    36. Mark F. J. Steel, 2020. "Model Averaging and Its Use in Economics," Journal of Economic Literature, American Economic Association, vol. 58(3), pages 644-719, September.
    37. Matthew Read, 2021. "Algorithms for Inference in SVARs Identified with Sign and Zero Restrictions," Papers 2109.10676, arXiv.org, revised Jan 2022.
    38. Didit Nugroho & Takayuki Morimoto, 2015. "Estimation of realized stochastic volatility models using Hamiltonian Monte Carlo-Based methods," Computational Statistics, Springer, vol. 30(2), pages 491-516, June.
    39. Lopresti, John, 2016. "Multiproduct firms and product scope adjustment in trade," Journal of International Economics, Elsevier, vol. 100(C), pages 160-173.
    40. Li, Yong & Liu, Xiaobin & Zeng, Tao & Yu, Jun, 2018. "A Posterior-Based Wald-Type Statistic for Hypothesis Testing," Economics and Statistics Working Papers 8-2018, Singapore Management University, School of Economics.
    41. Karun Adusumilli & Friedrich Geiecke & Claudio Schilter, 2019. "Dynamically Optimal Treatment Allocation using Reinforcement Learning," Papers 1904.01047, arXiv.org, revised May 2022.
    42. Krzysztof Drachal, 2022. "Forecasting the Crude Oil Spot Price with Bayesian Symbolic Regression," Energies, MDPI, vol. 16(1), pages 1-29, December.
    43. Herbst, Edward & Schorfheide, Frank, 2012. "Evaluating DSGE model forecasts of comovements," Journal of Econometrics, Elsevier, vol. 171(2), pages 152-166.
    44. Yasutomo Murasawa, 2014. "Measuring the natural rates, gaps, and deviation cycles," Empirical Economics, Springer, vol. 47(2), pages 495-522, September.
    45. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2013. "Historical Developments in Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 13-191/III, Tinbergen Institute.
    46. McKnight, Stephen & Mihailov, Alexander & Pompa Rangel, Antonio, 2020. "What do Latin American inflation targeters care about? A comparative Bayesian estimation of central bank preferences," Journal of Macroeconomics, Elsevier, vol. 63(C).
    47. AMENDOLA, Adalgiso & DI SERIO, Mario & FRAGETTA, Matteo, 2018. "The Government Spending Multiplier at the Zero Lower Bound: Evidence from the Euro Area," CELPE Discussion Papers 153, CELPE - CEnter for Labor and Political Economics, University of Salerno, Italy.
    48. Heather Anderson & Giovanni Caggiano & Farshid Vahid & Benjamin Wong, 2020. "Sectoral Employment Dynamics in Australia," Monash Econometrics and Business Statistics Working Papers 20/20, Monash University, Department of Econometrics and Business Statistics.
    49. Keisuke Hirano & Jack R. Porter, 2016. "Panel Asymptotics and Statistical Decision Theory," The Japanese Economic Review, Springer, vol. 67(1), pages 33-49, March.
    50. Hanck, Christoph & Prüser, Jan, 2016. "House prices and interest rates: Bayesian evidence from Germany," Ruhr Economic Papers 620, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    51. Morley, James & Wong, Benjamin, 2018. "Estimating and Accounting for the Output Gap with Large Bayesian Vector Autoregressions," Working Papers 2018-04, University of Sydney, School of Economics, revised Feb 2019.
    52. Prüser Jan & Hanck Christoph, 2021. "A Comparison of Approaches to Select the Informativeness of Priors in BVARs," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 241(4), pages 501-525, August.
    53. Li, Yong & Zeng, Tao & Yu, Jun, 2014. "A new approach to Bayesian hypothesis testing," Journal of Econometrics, Elsevier, vol. 178(P3), pages 602-612.
    54. Hamill, Philip A. & Li, Youwei & Pantelous, Athanasios A. & Vigne, Samuel A. & Waterworth, James, 2021. "Was a deterioration in ‘connectedness’ a leading indicator of the European sovereign debt crisis?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    55. Li, Yong & Yu, Jun & Zeng, Tao, 2018. "Integrated Deviance Information Criterion for Latent Variable Models," Economics and Statistics Working Papers 6-2018, Singapore Management University, School of Economics.
    56. Di Serio, Mario & Fragetta, Matteo & Melina, Giovanni, 2021. "The impact of r-g on Euro-Area government spending multipliers," Journal of International Money and Finance, Elsevier, vol. 119(C).
    57. Raffaella Giacomini & Toru Kitagawa & Matthew Read, 2020. "Robust Bayesian inference in proxy SVARs," CeMMAP working papers CWP13/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    58. Fausto Pacicco & Massimiliano Serati, 2017. "A proposal for a micro-territorial well-being index: the WIT," LIUC Papers in Economics 307, Cattaneo University (LIUC).
    59. László Békési & Lorant Kaszab & Szabolcs Szentmihályi, 2017. "The EAGLE model for Hungary - a global perspective," MNB Working Papers 2017/7, Magyar Nemzeti Bank (Central Bank of Hungary).
    60. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    61. Balcilar, Mehmet & Gupta, Rangan & Kotzé, Kevin, 2015. "Forecasting macroeconomic data for an emerging market with a nonlinear DSGE model," Economic Modelling, Elsevier, vol. 44(C), pages 215-228.
    62. Tomasz Wozniak, 2016. "Rare Events and Risk Perception: Evidence from Fukushima Accident," Department of Economics - Working Papers Series 2021, The University of Melbourne.
    63. Berg, Tim Oliver, 2015. "Multivariate Forecasting with BVARs and DSGE Models," MPRA Paper 62405, University Library of Munich, Germany.
    64. Koop, Gary, 2014. "Forecasting with dimension switching VARs," International Journal of Forecasting, Elsevier, vol. 30(2), pages 280-290.
    65. Gu, Xin & Zhu, Zixiang & Yu, Minli, 2021. "The macro effects of GPR and EPU indexes over the global oil market—Are the two types of uncertainty shock alike?," Energy Economics, Elsevier, vol. 100(C).
    66. Yong Li & Tao Zeng & Jun Yu, 2012. "Robust Deviance Information Criterion for Latent Variable Models," Working Papers 30-2012, Singapore Management University, School of Economics.
    67. Gan-Ochir Doojav & Kaliappa Kalirajan, 2020. "Financial Frictions and Shocks in an Estimated Small Open Economy DSGE Model," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(2), pages 253-291, June.
    68. Waggoner, Daniel F. & Zha, Tao, 2012. "Confronting model misspecification in macroeconomics," Journal of Econometrics, Elsevier, vol. 171(2), pages 167-184.
    69. Vasco Curdia & Andrea Ferrero & Ging Cee Ng & Andrea Tambalotti, 2014. "Has U.S. Monetary Policy Tracked the Efficient Interest Rate?," Working Paper Series 2014-12, Federal Reserve Bank of San Francisco.
    70. Roth, Markus, 2020. "Partial pooling with cross-country priors: An application to house price shocks," Discussion Papers 06/2020, Deutsche Bundesbank.
    71. Mihaela Simionescu (Bratu), 2014. "The Bayesian Modelling Of Inflation Rate In Romania," Romanian Statistical Review, Romanian Statistical Review, vol. 62(2), pages 147-160, June.
    72. Mark Bognanni, 2018. "A Class of Time-Varying Parameter Structural VARs for Inference under Exact or Set Identification," Working Papers (Old Series) 1811, Federal Reserve Bank of Cleveland.
    73. Lieb, Lenard & Smeekes, Stephan, 2017. "Inference for Impulse Responses under Model Uncertainty," Research Memorandum 022, Maastricht University, Graduate School of Business and Economics (GSBE).
    74. Jim Griffin & Maria Kalli & Mark Steel, 2018. "Discussion of “Nonparametric Bayesian Inference in Applications”: Bayesian nonparametric methods in econometrics," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(2), pages 207-218, June.
    75. Sebastian Ankargren & Måns Unosson & Yukai Yang, 2018. "A mixed-frequency Bayesian vector autoregression with a steady-state prior," CREATES Research Papers 2018-32, Department of Economics and Business Economics, Aarhus University.
    76. Gregor Bäurle & Daniel Kaufmann, 2018. "Measuring Exchange Rate, Price, and Output Dynamics at the Effective Lower Bound," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 80(6), pages 1243-1266, December.

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