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Todd Clark

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. Todd E. Clark, 1995. "Do producer prices lead consumer prices?," Economic Review, Federal Reserve Bank of Kansas City, vol. 80(Q III), pages 25-39.

    Mentioned in:

    1. From PPI to CPI
      by ? in FRED blog on 2021-04-12 13:00:00
  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

RePEc Biblio mentions

As found on the RePEc Biblio, the curated bibliography of Economics:
  1. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015. "Realtime nowcasting with a Bayesian mixed frequency model with stochastic volatility," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(4), pages 837-862, October.

    Mentioned in:

    1. > Econometrics > Forecasting > Nowcasting
    2. > Econometrics > Time Series Models > VAR Models > Time Varying Parameters and Stochastic Volatility
  2. Todd E. Clark & Fabian Krueger & Francesco Ravazzolo, 2015. "Using Entropic Tilting to Combine BVAR Forecasts with External Nowcasts," Working Papers (Old Series) 1439, Federal Reserve Bank of Cleveland.

    Mentioned in:

    1. > Econometrics > Time Series Models > VAR Models > Bayesian Vector autoregressions (BVARs)
  3. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015. "Bayesian VARs: Specification Choices and Forecast Accuracy," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(1), pages 46-73, January.

    Mentioned in:

    1. > Econometrics > Time Series Models > VAR Models > Bayesian Vector autoregressions (BVARs)
  4. Clark, Todd E., 2011. "Real-Time Density Forecasts From Bayesian Vector Autoregressions With Stochastic Volatility," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(3), pages 327-341.

    Mentioned in:

    1. > Econometrics > Time Series Models > VAR Models > Time Varying Parameters and Stochastic Volatility
  5. Todd E. Clark & Michael W. McCracken, 2011. "Reality Checks and Comparisons of Nested Predictive Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 53-66, February.

    Mentioned in:

    1. > Econometrics > Forecasting

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. 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.

    Mentioned in:

    1. Averaging forecasts from VARs with uncertain instabilities (Journal of Applied Econometrics 2010) in ReplicationWiki ()

Working papers

  1. Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2024. "Specification Choices in Quantile Regression for Empirical Macroeconomics," CEPR Discussion Papers 18901, C.E.P.R. Discussion Papers.

    Cited by:

    1. 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.

  2. Clark, Todd & Huber, Florian & Koop, Gary & Marcellino, Massimiliano & Pfarrhofer, Michael, 2022. "Tail Forecasting with Multivariate Bayesian Additive Regression Trees," CEPR Discussion Papers 17461, C.E.P.R. Discussion Papers.

    Cited by:

    1. 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.
    2. Lenza, Michele & Moutachaker, Inès & Paredes, Joan, 2023. "Forecasting euro area inflation with machine-learning models," Research Bulletin, European Central Bank, vol. 112.
    3. 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.
    4. 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.
    5. 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.
    6. Michael Pfarrhofer, 2024. "Forecasts with Bayesian vector autoregressions under real time conditions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(3), pages 771-801, April.
    7. Massimiliano MARCELLINO & Michael PFARRHOFER, 2024. "Bayesian nonparametric methods for macroeconomic forecasting," BAFFI CAREFIN Working Papers 24224, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    8. 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.
    9. Zhemkov, Michael, 2021. "Nowcasting Russian GDP using forecast combination approach," International Economics, Elsevier, vol. 168(C), pages 10-24.
    10. Philippe Goulet Coulombe & Mikael Frenette & Karin Klieber, 2023. "From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks," Papers 2311.16333, arXiv.org, revised Apr 2024.
    11. 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.
    12. Tibor Szendrei & Arnab Bhattacharjee, 2024. "Momentum Informed Inflation-at-Risk," Papers 2408.12286, arXiv.org.
    13. Joshua Chan, 2023. "BVARs and Stochastic Volatility," Papers 2310.14438, arXiv.org.

  3. Bai, Yu & Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2022. "Macroeconomic Forecasting in a Multi-country Context," CEPR Discussion Papers 16994, C.E.P.R. Discussion Papers.

    Cited by:

    1. Florian Huber & Gary Koop & Massimiliano Marcellino & Tobias Scheckel, 2024. "Bayesian modelling of VAR precision matrices using stochastic block networks," Papers 2407.16349, arXiv.org.
    2. Niko Hauzenberger & Florian Huber & Karin Klieber & Massimiliano Marcellino, 2022. "Bayesian Neural Networks for Macroeconomic Analysis," Papers 2211.04752, arXiv.org, revised Apr 2024.

  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. 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.
    2. M. Lenza & I. Moutachaker & I. Moutachaker, 2024. "Density forecasts of inflation : a quantile regression forest approach," Documents de Travail de l'Insee - INSEE Working Papers 2024-12, Institut National de la Statistique et des Etudes Economiques.
    3. 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.
    4. Martin Gachter & Elias Hasler & Florian Huber, 2023. "A tale of two tails: 130 years of growth-at-risk," Papers 2302.08920, arXiv.org.
    5. Jacobi Liana & Kwok Chun Fung & Ramírez-Hassan Andrés & Nghiem Nhung, 2024. "Posterior Manifolds over Prior Parameter Regions: Beyond Pointwise Sensitivity Assessments for Posterior Statistics from MCMC Inference," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 28(2), pages 403-434, April.
    6. 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.
    7. 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. Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2022. "Capturing Macroeconomic Tail Risks with Bayesian Vector Autoregressions," CEPR Discussion Papers 17512, C.E.P.R. Discussion Papers.

    Cited by:

    1. Szendrei, Tibor & Varga, Katalin, 2023. "Revisiting vulnerable growth in the Euro Area: Identifying the role of financial conditions in the distribution," Economics Letters, Elsevier, vol. 223(C).
    2. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022. "Nowcasting tail risk to economic activity at a weekly frequency," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 843-866, August.
    3. 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.
    4. Adrian, Tobias & Adams, Patrick & Boyarchenko, Nina & Giannone, Domenico, 2020. "Forecasting Macroeconomic Risks," CEPR Discussion Papers 14436, C.E.P.R. Discussion Papers.
    5. Hilde C. Bjørnland & Roberto Casarin & Marco Lorusso & Francesco Ravazzolo, 2023. "Fiscal Policy Regimes in Resource-Rich Economies," Working Papers No 13/2023, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    6. 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.
    7. Falconio, Andrea & Manganelli, Simone, 2020. "Financial conditions, business cycle fluctuations and growth at risk," Working Paper Series 2470, European Central Bank.
    8. Kevin Moran & Dalibor Stevanovic & Stéphane Surprenant, 2024. "Risk Scenarios and Macroeconomic Forecasts," CIRANO Working Papers 2024s-03, CIRANO.
    9. Garratt, Anthony & Henckel, Timo & Vahey, Shaun P., 2023. "Empirically-transformed linear opinion pools," International Journal of Forecasting, Elsevier, vol. 39(2), pages 736-753.
    10. Kiss, Tamás & Nguyen, Hoang & Österholm, Pär, 2022. "The Relation between the High-Yield Bond Spread and the Unemployment Rate in the Euro Area," Finance Research Letters, Elsevier, vol. 46(PA).
    11. Kiss, Tamás & Mazur, Stepan & Nguyen, Hoang & Österholm, Pär, 2021. "Modelling the Relation between the US Real Economy and the Corporate Bond-Yield Spread in Bayesian VARs with non-Gaussian Disturbances," Working Papers 2021:9, Örebro University, School of Business.
    12. Iseringhausen, Martin, 2024. "A time-varying skewness model for Growth-at-Risk," International Journal of Forecasting, Elsevier, vol. 40(1), pages 229-246.
    13. Karlsson, Sune & Mazur, Stepan & Nguyen, Hoang, 2021. "Vector autoregression models with skewness and heavy tails," Working Papers 2021:8, Örebro University, School of Business.
    14. Martin Gachter & Elias Hasler & Florian Huber, 2023. "A tale of two tails: 130 years of growth-at-risk," Papers 2302.08920, arXiv.org.
    15. Deng, Chuang & Wu, Jian, 2023. "Macroeconomic downside risk and the effect of monetary policy," Finance Research Letters, Elsevier, vol. 54(C).
    16. Mihail Yanchev, 2022. "Deep Growth-at-Risk Model: Nowcasting the 2020 Pandemic Lockdown Recession in Small Open Economies," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 7, pages 20-41.
    17. Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    18. Huang, Yu-Fan & Liao, Wenting & Luo, Sui & Ma, Jun, 2024. "Financial conditions, macroeconomic uncertainty, and macroeconomic tail risks," Journal of Economic Dynamics and Control, Elsevier, vol. 163(C).
    19. Leopoldo Catania & Alessandra Luati & Pierluigi Vallarino, 2021. "Economic vulnerability is state dependent," CREATES Research Papers 2021-09, Department of Economics and Business Economics, Aarhus University.
    20. Schick, Manuel, 2024. "Real-time Nowcasting Growth-at-Risk using the Survey of Professional Forecasters," Working Papers 0750, University of Heidelberg, Department of Economics.

  6. Marcellino, Massimiliano & Clark, Todd & Carriero, Andrea, 2021. "Nowcasting Tail Risk to Economic Activity at a Weekly Frequency," CEPR Discussion Papers 16496, C.E.P.R. Discussion Papers.

    Cited by:

    1. Eraslan, Sercan & Reif, Magnus, 2023. "A latent weekly GDP indicator for Germany," Technical Papers 08/2023, Deutsche Bundesbank.
    2. Helena Chuliá & Ignacio Garrón & Jorge M. Uribe, 2022. ""Daily Growth at Risk: financial or real drivers? The answer is not always the same"," IREA Working Papers 202208, University of Barcelona, Research Institute of Applied Economics, revised Jun 2022.
    3. 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).
    4. Antolín-Díaz, Juan & Drechsel, Thomas & Petrella, Ivan, 2024. "Advances in nowcasting economic activity: The role of heterogeneous dynamics and fat tails," Journal of Econometrics, Elsevier, vol. 238(2).
    5. Matteo Iacopini & Aubrey Poon & Luca Rossini & Dan Zhu, 2024. "A Quantile Nelson-Siegel model," Papers 2401.09874, arXiv.org.
    6. Narasingha Das & Partha Gangopadhyay, 2023. "Did weekly economic index and volatility index impact US food sales during the first year of the pandemic?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.
    7. Paul Labonne, 2022. "Asymmetric Uncertainty: Nowcasting Using Skewness in Real-time Data," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-23, Economic Statistics Centre of Excellence (ESCoE).
    8. Matteo Iacopini & Francesco Ravazzolo & Luca Rossini, 2022. "Bayesian Multivariate Quantile Regression with alternative Time-varying Volatility Specifications," Papers 2211.16121, arXiv.org, revised Aug 2024.
    9. Schick, Manuel, 2024. "Real-time Nowcasting Growth-at-Risk using the Survey of Professional Forecasters," Working Papers 0750, University of Heidelberg, Department of Economics.

  7. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2021. "Forecasting with Shadow-Rate VARs," Working Papers 21-09, Federal Reserve Bank of Cleveland.

    Cited by:

    1. Aruoba, S. Borağan & Mlikota, Marko & Schorfheide, Frank & Villalvazo, Sergio, 2022. "SVARs with occasionally-binding constraints," Journal of Econometrics, Elsevier, vol. 231(2), pages 477-499.

  8. 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. 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.
    2. Dimitris Korobilis & Maximilian Schröder, 2023. "Monitoring multicountry macroeconomic risk," Working Paper 2023/9, Norges Bank.
    3. Simon Lloyd & Ed Manuel & Konstantin Panchev, 2024. "Foreign Vulnerabilities, Domestic Risks: The Global Drivers of GDP-at-Risk," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 72(1), pages 335-392, March.
    4. Ignace De Vos & Gerdie Everaert, 2024. "GLS Estimation of Local Projections: Trading Robustness for Efficiency," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 24/1095, Ghent University, Faculty of Economics and Business Administration.
    5. Vegard Høghaug Larsen & Nicolò Maffei-Faccioli & Laura Pagenhardt, 2023. "Where do they care? The ECB in the media and inflation expectations," Working Papers No 04/2023, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    6. Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).

  9. Marcellino, Massimiliano & Clark, Todd & Carriero, Andrea & Mertens, Elmar, 2021. "Addressing COVID-19 Outliers in BVARs with Stochastic Volatility," CEPR Discussion Papers 15964, C.E.P.R. Discussion Papers.

    Cited by:

    1. Valenti, Daniele & Bastianin, Andrea & Manera, Matteo, "undated". "A weekly structural VAR model of the US crude oil market," FEEM Working Papers 324040, Fondazione Eni Enrico Mattei (FEEM).
    2. Joshua C. C. Chan, 2022. "Comparing Stochastic Volatility Specifications for Large Bayesian VARs," Papers 2208.13255, arXiv.org.
    3. Bańbura, Marta & Belousova, Irina & Bodnár, Katalin & Tóth, Máté Barnabás, 2023. "Nowcasting employment in the euro area," Working Paper Series 2815, European Central Bank.
    4. 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.
    5. Frank Schorfheide & Dongho Song, 2020. "Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic," PIER Working Paper Archive 20-039, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    6. Prüser, Jan, 2021. "The horseshoe prior for time-varying parameter VARs and Monetary Policy," Journal of Economic Dynamics and Control, Elsevier, vol. 129(C).
    7. Mertens, Elmar, 2023. "Precision-based sampling for state space models that have no measurement error," Discussion Papers 25/2023, Deutsche Bundesbank.
    8. 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.
    9. Budnik, Katarzyna & Groß, Johannes & Vagliano, Gianluca & Dimitrov, Ivan & Lampe, Max & Panos, Jiri & Velasco, Sofia & Boucherie, Louis & Jančoková, Martina, 2023. "BEAST: A model for the assessment of system-wide risks and macroprudential policies," Working Paper Series 2855, European Central Bank.
    10. Bańbura, Marta & Bobeica, Elena & Martínez Hernández, Catalina, 2023. "What drives core inflation? The role of supply shocks," Working Paper Series 2875, European Central Bank.
    11. Sun, Weihong & Liu, Ding, 2023. "Great moderation with Chinese characteristics: Uncovering the role of monetary policy," Economic Modelling, Elsevier, vol. 121(C).
    12. Hugo Morão, 2024. "An Economic Policy Uncertainty Index for Portugal," Working Papers REM 2024/0322, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    13. Andrejs Zlobins, 2021. "On the Time-varying Effects of the ECB's Asset Purchases," Working Papers 2021/02, Latvijas Banka.
    14. Bhattacharjee, Arnab & Kohns, David, 2022. "Nowcasting Growth using Google Trends Data: A Bayesian Structural Time Series Model," National Institute of Economic and Social Research (NIESR) Discussion Papers 538, National Institute of Economic and Social Research.
    15. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Papers 2202.04146, arXiv.org, revised Oct 2024.
    16. 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.
    17. Danilo Cascaldi-Garcia, 2022. "Pandemic Priors," International Finance Discussion Papers 1352, Board of Governors of the Federal Reserve System (U.S.).
    18. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2021. "Forecasting with Shadow-Rate VARs," Working Papers 21-09, Federal Reserve Bank of Cleveland.
    19. Barend Abeln & Jan P.A.M. Jacobs, 2021. "COVID-19 and seasonal adjustment," CAMA Working Papers 2021-23, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    20. Granados, Camilo & Parra-Amado, Daniel, 2024. "Estimating the output gap after COVID: How to address unprecedented macroeconomic variations," Economic Modelling, Elsevier, vol. 135(C).
    21. Cross, Jamie L. & Hou, Chenghan & Koop, Gary & Poon, Aubrey, 2023. "Large stochastic volatility in mean VARs," Journal of Econometrics, Elsevier, vol. 236(1).
    22. Knüppel, Malte & Krüger, Fabian & Pohle, Marc-Oliver, 2022. "Score-based calibration testing for multivariate forecast distributions," Discussion Papers 50/2022, Deutsche Bundesbank.
    23. Luis J. Álvarez & Florens Odendahl, 2022. "Data outliers and Bayesian VARs in the Euro Area," Working Papers 2239, Banco de España.
    24. Colunga L. Fernando & Torre Cepeda Leonardo, 2023. "Effects of Supply, Demand, and Labor Market Shocks in the Mexican Manufacturing Sector," Working Papers 2023-10, Banco de México.
    25. Budnik, Katarzyna & Ponte Marques, Aurea & Giglio, Carla & Grassi, Alberto & Durrani, Agha & Figueres, Juan Manuel & Konietschke, Paul & Le Grand, Catherine & Metzler, Julian & Población García, Franc, 2024. "Advancements in stress-testing methodologies for financial stability applications," Occasional Paper Series 348, European Central Bank.
    26. 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.
    27. Serena Ng, 2021. "Modeling Macroeconomic Variations After COVID-19," Papers 2103.02732, arXiv.org, revised Jul 2021.
    28. Kiss, Tamas & Nguyen, Hoang & Österholm, Pär, 2022. "Modelling Okun’s Law – Does non-Gaussianity Matter?," Working Papers 2022:1, Örebro University, School of Business.
    29. Liu, Ying & Wen, Long & Liu, Han & Song, Haiyan, 2024. "Predicting tourism recovery from COVID-19: A time-varying perspective," Economic Modelling, Elsevier, vol. 135(C).
    30. Morley, James & Palenzuela, Diego Rodriguez & Sun, Yiqiao & Wong, Benjamin, 2022. "Estimating the Euro Area output gap using multivariate information and addressing the COVID-19 pandemic," Working Paper Series 2716, European Central Bank.
    31. Nalban, Valeriu & Smădu, Andra, 2021. "Asymmetric effects of uncertainty shocks: Normal times and financial disruptions are different," Journal of Macroeconomics, Elsevier, vol. 69(C).
    32. Karlsson, Sune & Mazur, Stepan & Nguyen, Hoang, 2021. "Vector autoregression models with skewness and heavy tails," Working Papers 2021:8, Örebro University, School of Business.
    33. 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).
    34. Alanya-Beltran, Willy, 2022. "Unit roots in lower-bounded series with outliers," Economic Modelling, Elsevier, vol. 115(C).
    35. Antolín-Díaz, Juan & Drechsel, Thomas & Petrella, Ivan, 2024. "Advances in nowcasting economic activity: The role of heterogeneous dynamics and fat tails," Journal of Econometrics, Elsevier, vol. 238(2).
    36. Klieber, Karin, 2024. "Non-linear dimension reduction in factor-augmented vector autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 159(C).
    37. 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.
    38. Florian Huber, 2023. "Bayesian Nonlinear Regression using Sums of Simple Functions," Papers 2312.01881, arXiv.org.
    39. Barauskaitė, Kristina & Nguyen, Anh D.M. & Rousová, Linda & Cappiello, Lorenzo, 2022. "The impact of credit supply shocks in the euro area: market-based financing versus loans," Working Paper Series 2673, European Central Bank.
    40. 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.
    41. Davidson, Sharada Nia & Moccero, Diego Nicolas, 2024. "The nonlinear effects of banks’ vulnerability to capital depletion in euro area countries," Working Paper Series 2912, European Central Bank.
    42. Vito Polito & Yunyi Zhang, 2021. "Tackling Large Outliers in Macroeconomic Data with Vector Artificial Neural Network Autoregression," CESifo Working Paper Series 9395, CESifo.
    43. Evgenidis, Anastasios & Fasianos, Apostolos, 2023. "Modelling monetary policy’s impact on labour markets under Covid-19," Economics Letters, Elsevier, vol. 230(C).
    44. Saeed Zaman, 2021. "A Unified Framework to Estimate Macroeconomic Stars," Working Papers 21-23R2, Federal Reserve Bank of Cleveland, revised 31 May 2024.

  10. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2021. "Using Time-Varying Volatility for Identification in Vector Autoregressions: An Application to Endogenous Uncertainty," CEPR Discussion Papers 16346, C.E.P.R. Discussion Papers.

    Cited by:

    1. Chang, Hao-Wen & Chang, Tsangyao & Lee, Chien-Chiang, 2023. "Return and volatility connectedness among the BRICS stock and oil markets," Resources Policy, Elsevier, vol. 86(PA).
    2. Alina Bobasu & Lucia Quaglietti & Martino Ricci, 2024. "Tracking Global Economic Uncertainty: Implications for the Euro Area," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 72(2), pages 820-857, June.
    3. Ambrocio, Gene, 2020. "Inflationary household uncertainty shocks," Bank of Finland Research Discussion Papers 5/2020, Bank of Finland.
    4. Beckmann, Joscha & Czudaj, Robert L., 2024. "Uncertainty Shocks and Inflation: The Role of Credibility and Expectation Anchoring," MPRA Paper 119971, University Library of Munich, Germany.
    5. Yujia, Li & Zixiang, Zhu & Ming, Che, 2024. "Exploring the relationship between China's economic policy uncertainty and business cycles: Exogenous impulse or endogenous responses?," Emerging Markets Review, Elsevier, vol. 58(C).
    6. Emanuele Bacchiocchi & Catalin Dragomirescu-Gaina, 2022. "Uncertainty spill-overs: when policy and financial realms overlap," Working Papers wp1174, Dipartimento Scienze Economiche, Universita' di Bologna.
    7. Olli Palm'en, 2022. "Macroeconomic Effect of Uncertainty and Financial Shocks: a non-Gaussian VAR approach," Papers 2202.10834, arXiv.org.
    8. Gnangnon, Sèna Kimm, 2023. "Effect of Economic Uncertainty on Remittances Flows from Developed Countries," EconStor Preprints 279480, ZBW - Leibniz Information Centre for Economics.
    9. Dibiasi, Andreas & Sarferaz, Samad, 2023. "Measuring macroeconomic uncertainty: A cross-country analysis," European Economic Review, Elsevier, vol. 153(C).
    10. Koivisto, Tero, 2024. "Asset price shocks and inflation in the Finnish economy," BoF Economics Review 6/2024, Bank of Finland.
    11. Karlsson, Sune & Mazur, Stepan & Nguyen, Hoang, 2021. "Vector autoregression models with skewness and heavy tails," Working Papers 2021:8, Örebro University, School of Business.
    12. Che, Ming & Zhu, Zixiang & Li, Yujia, 2023. "Geopolitical risk and economic policy uncertainty: Different roles in China's financial cycle," International Review of Financial Analysis, Elsevier, vol. 90(C).
    13. Carriero, Andrea & Marcellino, Massimiliano & Tornese, Tommaso, 2023. "Macro uncertainty in the long run," Economics Letters, Elsevier, vol. 225(C).
    14. Sèna Kimm Gnangnon, 2024. "The effect of economic uncertainty on remittance flows from developed countries," Economic Affairs, Wiley Blackwell, vol. 44(2), pages 267-280, June.
    15. Andrea Carriero & Alessio Volpicella, 2022. "Generalizing the Max Share Identification to multiple shocks identification: an Application to Uncertainty," School of Economics Discussion Papers 0322, School of Economics, University of Surrey.

  11. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd & Mertens, Elmar, 2021. "Measuring Uncertainty and Its Effects in the COVID-19 Era," CEPR Discussion Papers 15965, C.E.P.R. Discussion Papers.

    Cited by:

    1. Cross, Jamie L. & Hou, Chenghan & Koop, Gary & Poon, Aubrey, 2023. "Large stochastic volatility in mean VARs," Journal of Econometrics, Elsevier, vol. 236(1).
    2. Luis J. Álvarez & Florens Odendahl, 2022. "Data outliers and Bayesian VARs in the Euro Area," Working Papers 2239, Banco de España.
    3. Klieber, Karin, 2024. "Non-linear dimension reduction in factor-augmented vector autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 159(C).

  12. 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.

    Cited by:

    1. Jack Fosten & Daniel Gutknecht & Marc-Oliver Pohle, 2023. "Testing Quantile Forecast Optimality," Papers 2302.02747, arXiv.org, revised Oct 2023.
    2. Salisu, Afees A. & Ogbonna, Ahamuefula E. & Vo, Xuan Vinh, 2023. "Oil tail risks and the realized variance of consumer prices in advanced economies," Resources Policy, Elsevier, vol. 83(C).
    3. Frank Schorfheide & Dongho Song, 2020. "Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic," PIER Working Paper Archive 20-039, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    4. Aaron J. Amburgey & Michael W. McCracken, 2023. "On the real‐time predictive content of financial condition indices for growth," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(2), pages 137-163, March.
    5. Tibor Szendrei & Arnab Bhattacharjee & Mark E. Schaffer, 2024. "MIDAS-QR with 2-Dimensional Structure," Papers 2406.15157, arXiv.org.
    6. Hager Ben Romdhane, 2021. "Nowcasting in Tunisia using large datasets and mixed frequency models," IHEID Working Papers 11-2021, Economics Section, The Graduate Institute of International Studies.
    7. Teng, Bin & Wang, Sicong & Shi, Yufeng & Sun, Yunchuan & Wang, Wei & Hu, Wentao & Shi, Chaojun, 2022. "Economic recovery forecasts under impacts of COVID-19," Economic Modelling, Elsevier, vol. 110(C).
    8. Tino Berger & James Morley & Benjamin Wong, 2020. "Nowcasting the output gap," CAMA Working Papers 2020-78, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    9. Gloria González-Rivera & Carlos Vladimir Rodríguez-Caballero & Esther Ruiz Ortega, 2021. "Expecting the unexpected: economic growth under stress," CREATES Research Papers 2021-06, Department of Economics and Business Economics, Aarhus University.
    10. Cimadomo, Jacopo & Giannone, Domenico & Lenza, Michele & Monti, Francesca & Sokol, Andrej, 2022. "Nowcasting with large Bayesian vector autoregressions," Journal of Econometrics, Elsevier, vol. 231(2), pages 500-519.
    11. Galvao, Ana Beatriz & Owyang, Michael, 2020. "Forecasting Low Frequency Macroeconomic Events with High Frequency Data," EMF Research Papers 38, Economic Modelling and Forecasting Group.
    12. Stolbov, Mikhail & Shchepeleva, Maria, 2022. "Modeling global real economic activity: Evidence from variable selection across quantiles," The Journal of Economic Asymmetries, Elsevier, vol. 25(C).
    13. Marcellino, Massimiliano & Foroni, Claudia & Stevanovic, Dalibor, 2020. "Forecasting the Covid-19 recession and recovery: Lessons from the financial crisis," CEPR Discussion Papers 15114, C.E.P.R. Discussion Papers.
    14. David Kohns & Tibor Szendrei, 2021. "Decoupling Shrinkage and Selection for the Bayesian Quantile Regression," Papers 2107.08498, arXiv.org.
    15. Ferrara, Laurent & Mogliani, Matteo & Sahuc, Jean-Guillaume, 2022. "High-frequency monitoring of growth at risk," International Journal of Forecasting, Elsevier, vol. 38(2), pages 582-595.
    16. Matteo Iacopini & Francesco Ravazzolo & Luca Rossini, 2020. "Proper scoring rules for evaluating asymmetry in density forecasting," Working Papers No 06/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    17. Iseringhausen, Martin, 2024. "A time-varying skewness model for Growth-at-Risk," International Journal of Forecasting, Elsevier, vol. 40(1), pages 229-246.
    18. Wegmüller, Philipp & Glocker, Christian & Guggia, Valentino, 2023. "Weekly economic activity: Measurement and informational content," International Journal of Forecasting, Elsevier, vol. 39(1), pages 228-243.
    19. Korobilis, Dimitris & Landau, Bettina & Musso, Alberto & Phella, Anthoulla, 2021. "The time-varying evolution of inflation risks," Working Paper Series 2600, European Central Bank.
    20. Hans Genberg & Özer Karagedikli, 2021. "Machine Learning and Central Banks: Ready for Prime Time?," Working Papers wp43, South East Asian Central Banks (SEACEN) Research and Training Centre.
    21. Yfanti, Stavroula & Karanasos, Menelaos & Zopounidis, Constantin & Christopoulos, Apostolos, 2023. "Corporate credit risk counter-cyclical interdependence: A systematic analysis of cross-border and cross-sector correlation dynamics," European Journal of Operational Research, Elsevier, vol. 304(2), pages 813-831.
    22. Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    23. Alina Stundziene & Vaida Pilinkiene & Jurgita Bruneckiene & Andrius Grybauskas & Mantas Lukauskas, 2023. "Nowcasting Economic Activity Using Electricity Market Data: The Case of Lithuania," Economies, MDPI, vol. 11(5), pages 1-21, May.
    24. Jennifer Betz & Maximilian Nagl & Daniel Rösch, 2022. "Credit line exposure at default modelling using Bayesian mixed effect quantile regression," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 2035-2072, October.

  13. Marcellino, Massimiliano & Clark, Todd & Carriero, Andrea, 2019. "Assessing International Commonality in Macroeconomic Uncertainty and Its Effects," CEPR Discussion Papers 13970, C.E.P.R. Discussion Papers.

    Cited by:

    1. Andreas Dibiasi & Samad Sarferaz, 2020. "Measuring Macroeconomic Uncertainty: The Labor Channel of Uncertainty from a Cross-Country Perspective," Papers 2006.09007, arXiv.org, revised Dec 2020.
    2. Jaromir Baxa & Tomas Sestorad, 2024. "Economic Policy Uncertainty in Europe: Spillovers and Common Shocks," Working Papers IES 2024/34, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2024.
    3. Lodge, David & Pérez, Javier J. & Albrizio, Silvia & Everett, Mary & De Bandt, Olivier & Georgiadis, Georgios & Ca' Zorzi, Michele & Lastauskas, Povilas & Carluccio, Juan & Parrága, Susana & Carvalho,, 2021. "The implications of globalisation for the ECB monetary policy strategy," Occasional Paper Series 263, European Central Bank.
    4. Jose E. Gomez-Gonzalez & Jorge Hirs-Garzon & Jorge M. Uribe, 2020. "Global effects of US uncertainty: real and financial shocks on real and financial markets," IREA Working Papers 202015, University of Barcelona, Research Institute of Applied Economics, revised Oct 2020.
    5. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2021. "Using Time-Varying Volatility for Identification in Vector Autoregressions: An Application to Endogenous Uncertainty," CEPR Discussion Papers 16346, C.E.P.R. Discussion Papers.
    6. Arigoni, Filippo & Lenarcic, Crt, 2023. "Foreign economic policy uncertainty shocks and real activity in the Euro area," Research Technical Papers 7/RT/23, Central Bank of Ireland.
    7. Carlos Giraldo & Iader Giraldo & Jose E. Gomez-Gonzalez & Jorge M. Uribe, 2023. ""US uncertainty shocks, credit, production, and prices: The case of fourteen Latin American countries"," IREA Working Papers 202302, University of Barcelona, Research Institute of Applied Economics, revised Feb 2023.
    8. Giovanni Caggiano & Efrem Castelnuovo, 2023. "Global financial uncertainty," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(3), pages 432-449, April.
    9. Alina Bobasu & Lucia Quaglietti & Martino Ricci, 2024. "Tracking Global Economic Uncertainty: Implications for the Euro Area," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 72(2), pages 820-857, June.
    10. Jamie L. Cross & Chenghan Hou & Aubrey Poon, 2018. "International Transmission of Macroeconomic Uncertainty in Small Open Economies: An Empirical Approach," Working Papers No 12/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    11. Cross, Jamie L. & Hou, Chenghan & Koop, Gary & Poon, Aubrey, 2023. "Large stochastic volatility in mean VARs," Journal of Econometrics, Elsevier, vol. 236(1).
    12. Efrem Castelnuovo, 2022. "Uncertainty Before and During COVID-19: A Survey," "Marco Fanno" Working Papers 0279, Dipartimento di Scienze Economiche "Marco Fanno".
    13. Ductor, Lorenzo & Leiva-León, Danilo, 2022. "Fluctuations in global output volatility," Journal of International Money and Finance, Elsevier, vol. 120(C).
    14. Bonciani, Dario & Ricci, Martino, 2020. "The international effects of global financial uncertainty shocks," Journal of International Money and Finance, Elsevier, vol. 109(C).
    15. Miescu, Mirela S., 2023. "Uncertainty shocks in emerging economies: A global to local approach for identification," European Economic Review, Elsevier, vol. 154(C).
    16. Helena Chuliá & Ignacio Garrón & Jorge M. Uribe, 2021. ""Vulnerable Funding in the Global Economy"," IREA Working Papers 202106, University of Barcelona, Research Institute of Applied Economics, revised Mar 2021.
    17. Nina Biljanovska & Mr. Francesco Grigoli & Martina Hengge, 2017. "Fear Thy Neighbor: Spillovers from Economic Policy Uncertainty," IMF Working Papers 2017/240, International Monetary Fund.
    18. Dibiasi, Andreas & Sarferaz, Samad, 2023. "Measuring macroeconomic uncertainty: A cross-country analysis," European Economic Review, Elsevier, vol. 153(C).
    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. 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.
    21. 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).
    22. Paul Labonne, 2020. "Asymmetric uncertainty : Nowcasting using skewness in real-time data," Papers 2012.02601, arXiv.org, revised May 2024.
    23. Ogbuabor, Jonathan E. & Ukwueze, Ezebuilo R. & Mba, Ifeoma C. & Ojonta, Obed I. & Orji, Anthony, 2023. "The asymmetric impact of economic policy uncertainty on global retail energy markets: Are the markets responding to the fear of the unknown?," Applied Energy, Elsevier, vol. 334(C).
    24. Graziano Moramarco, 2022. "Measuring Global Macroeconomic Uncertainty and Cross-Country Uncertainty Spillovers," Econometrics, MDPI, vol. 11(1), pages 1-29, December.
    25. Andrea Carriero & Alessio Volpicella, 2022. "Generalizing the Max Share Identification to multiple shocks identification: an Application to Uncertainty," School of Economics Discussion Papers 0322, School of Economics, University of Surrey.
    26. Paul Labonne, 2022. "Asymmetric Uncertainty: Nowcasting Using Skewness in Real-time Data," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-23, Economic Statistics Centre of Excellence (ESCoE).

  14. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2018. "Endogenous Uncertainty," Working Papers (Old Series) 1805, Federal Reserve Bank of Cleveland.

    Cited by:

    1. Qazi Haque & Leandro M. Magnusson & Kazuki Tomioka, 2019. "Empirical evidence on the dynamics of investment under uncertainty in the US," CAMA Working Papers 2019-87, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    2. Maria Elena Bontempi & Michele Frigeri & Roberto Golinelli & Matteo Squadrani, 2021. "EURQ: A New Web Search‐based Uncertainty Index," Economica, London School of Economics and Political Science, vol. 88(352), pages 969-1015, October.
    3. Gian Paulo Soave, 2020. "International Drivers of Policy Uncertainty in Emerging Economies," Economics Bulletin, AccessEcon, vol. 40(1), pages 716-726.
    4. Hauzenberger, Niko & Pfarrhofer, Michael & Stelzer, Anna, 2021. "On the effectiveness of the European Central Bank’s conventional and unconventional policies under uncertainty," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 822-845.

  15. Todd E Clark & Michael W McCracken & Elmar Mertens, 2017. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," BIS Working Papers 667, Bank for International Settlements.

    Cited by:

    1. Galvao, Ana Beatriz & Mitchell, James, 2020. "Real-Time Perceptions of Historical GDP Data Uncertainty," EMF Research Papers 35, Economic Modelling and Forecasting Group.
    2. Kajal Lahiri & Huaming Peng & Xuguang Simon Sheng, 2021. "Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity," Working Papers 2021-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    3. Galvao, Ana Beatriz & Garratt, Anthony & Mitchell, James, 2020. "Does Judgment Improve Macroeconomic Density Forecasts?," EMF Research Papers 33, Economic Modelling and Forecasting Group.
    4. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano & Mertens, Elmar, 2022. "Addressing COVID-19 outliers in BVARs with stochastic volatility," Discussion Papers 13/2022, Deutsche Bundesbank.
    5. Knüppel, Malte & Schultefrankenfeld, Guido, 2019. "Assessing the uncertainty in central banks’ inflation outlooks," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1748-1769.
    6. Adrian, Tobias & Adams, Patrick & Boyarchenko, Nina & Giannone, Domenico, 2020. "Forecasting Macroeconomic Risks," CEPR Discussion Papers 14436, C.E.P.R. Discussion Papers.
    7. Corradi, Valentina & Fosten, Jack & Gutknecht, Daniel, 2023. "Out-of-sample tests for conditional quantile coverage an application to Growth-at-Risk," Journal of Econometrics, Elsevier, vol. 236(2).
    8. Li, Zheng & Zeng, Jingjing & Hensher, David A., 2023. "An efficient approach to structural breaks and the case of automobile gasoline consumption in Australia," Transportation Research Part A: Policy and Practice, Elsevier, vol. 169(C).
    9. Li, Zheng & Zhou, Bo & Hensher, David A., 2022. "Forecasting automobile gasoline demand in Australia using machine learning-based regression," Energy, Elsevier, vol. 239(PD).
    10. Weiqi Zhang & Huong Ha & Hui Ting Evelyn Gay, 2020. "Analysts’ forecasts between last consensus and earning announcement date," Journal of Financial Reporting and Accounting, Emerald Group Publishing Limited, vol. 18(4), pages 779-793, November.
    11. Oliver Grothe & Fabian Kachele & Fabian Kruger, 2022. "From point forecasts to multivariate probabilistic forecasts: The Schaake shuffle for day-ahead electricity price forecasting," Papers 2204.10154, arXiv.org.
    12. Efrem Castelnuovo, 2022. "Uncertainty Before and During COVID-19: A Survey," "Marco Fanno" Working Papers 0279, Dipartimento di Scienze Economiche "Marco Fanno".
    13. Todd E. Clark & Gergely Ganics & Elmar Mertens, 2022. "What is the Predictive Value of SPF Point and Density Forecasts?," Working Papers 22-37, Federal Reserve Bank of Cleveland.
    14. Kiss, Tamás & Mazur, Stepan & Nguyen, Hoang & Österholm, Pär, 2021. "Modelling the Relation between the US Real Economy and the Corporate Bond-Yield Spread in Bayesian VARs with non-Gaussian Disturbances," Working Papers 2021:9, Örebro University, School of Business.
    15. Mirela Miescu, 2019. "Uncertainty shocks in emerging economies," Working Papers 277077821, Lancaster University Management School, Economics Department.
    16. Knüppel, Malte, 2014. "Forecast-error-based estimation of forecast uncertainty when the horizon is increased," Discussion Papers 40/2014, Deutsche Bundesbank.
    17. Dibiasi, Andreas & Sarferaz, Samad, 2023. "Measuring macroeconomic uncertainty: A cross-country analysis," European Economic Review, Elsevier, vol. 153(C).
    18. 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.
    19. Yoosoon Chang & Yong-gun Kim & Boreum Kwak & Joon Y. Park, 2024. "Using Density Forecast for Growth-at-Risk to Improve Mean Forecast of GDP Growth in Korea," CAEPR Working Papers 2024-005 Classification-C, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    20. Barbara Rossi, 2019. "Identifying and Estimating the Effects of Unconventional Monetary Policy in the Data: How to Do It and What Have We Learned?," Working Papers 1081, Barcelona School of Economics.
    21. Bas Scheer, 2022. "Addressing Unemployment Rate Forecast Errors in Relation to the Business Cycle," CPB Discussion Paper 434, CPB Netherlands Bureau for Economic Policy Analysis.
    22. Fabian Kruger & Hendrik Plett, 2022. "Prediction intervals for economic fixed-event forecasts," Papers 2210.13562, arXiv.org, revised Mar 2024.
    23. Sharpe, Steven A. & Sinha, Nitish R. & Hollrah, Christopher A., 2023. "The power of narrative sentiment in economic forecasts," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1097-1121.
    24. Reifschneider, David & Tulip, Peter, 2019. "Gauging the uncertainty of the economic outlook using historical forecasting errors: The Federal Reserve’s approach," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1564-1582.
    25. Grothe, Oliver & Kächele, Fabian & Krüger, Fabian, 2023. "From point forecasts to multivariate probabilistic forecasts: The Schaake shuffle for day-ahead electricity price forecasting," Energy Economics, Elsevier, vol. 120(C).
    26. Simón Sosvilla-Rivero & María del Carmen Ramos-Herrera, 2018. "Inflation, real economic growth and unemployment expectations: an empirical analysis based on the ECB survey of professional forecasters," Applied Economics, Taylor & Francis Journals, vol. 50(42), pages 4540-4555, September.
    27. Schick, Manuel, 2024. "Real-time Nowcasting Growth-at-Risk using the Survey of Professional Forecasters," Working Papers 0750, University of Heidelberg, Department of Economics.

  16. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2016. "Measuring Uncertainty and Its Impact on the Economy," BAFFI CAREFIN Working Papers 1639, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.

    Cited by:

    1. Yoosoon Chang & Ana Maria Herrera & Elena Pesavento, 2023. "Oil Prices Uncertainty, Endogenous Regime Switching, and Inflation Anchoring," CAEPR Working Papers 2023-002 Classification-C, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    2. Benjamin K. Johannsen & Elmar Mertens, 2016. "A Time Series Model of Interest Rates With the Effective Lower Bound," Finance and Economics Discussion Series 2016-033, Board of Governors of the Federal Reserve System (U.S.).
    3. Ambrogio Cesa-Bianchi & M. Hashem Pesaran & Alessandro Rebucci, 2018. "Uncertainty and Economic Activity: A Multi-Country Perspective," NBER Working Papers 24325, National Bureau of Economic Research, Inc.
    4. Hauzenberger, Niko & Böck, Maximilian & Pfarrhofer, Michael & Stelzer, Anna & Zens, Gregor, 2018. "Implications of Macroeconomic Volatility in the Euro Area," Department of Economics Working Paper Series 6246, WU Vienna University of Economics and Business.
    5. Gian Paulo Soave, 2023. "A panel threshold VAR with stochastic volatility-in-mean model: an application to the effects of financial and uncertainty shocks in emerging economies," Applied Economics, Taylor & Francis Journals, vol. 55(4), pages 397-431, January.
    6. Danilo Leiva-Leon & Luis Uzeda, 2021. "Endogenous time variation in vector autoregressions," Working Papers 2108, Banco de España.
    7. Brianti, Marco, 2021. "Financial Shocks, Uncertainty Shocks, and Monetary Policy Trade-Offs," Working Papers 2021-5, University of Alberta, Department of Economics.
    8. Joshua C.C. Chan & Rodney W. Strachan, 2020. "Bayesian state space models in macroeconometrics," CAMA Working Papers 2020-90, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    9. Laurent Ferrara & Stéphane Lhuissier & Fabien Tripier, 2017. "Uncertainty Fluctuations: Measures, Effects and Macroeconomic Policy Challenges," CEPII Policy Brief 2017-20, CEPII research center.
    10. Giovanni Caggiano & Efrem Castelnuovo & Juan Manuel Figueres, 2018. "Economic Policy Uncertainty Spillovers in Booms and Busts," "Marco Fanno" Working Papers 0220, Dipartimento di Scienze Economiche "Marco Fanno".
    11. Kevin Moran & Dalibor Stevanovic & Adam Kader Touré, 2022. "Macroeconomic uncertainty and the COVID‐19 pandemic: Measure and impacts on the Canadian economy," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 55(S1), pages 379-405, February.
    12. Ma, Xiaohan & Samaniego, Roberto, 2020. "The macroeconomic impact of oil earnings uncertainty: New evidence from analyst forecasts," Energy Economics, Elsevier, vol. 90(C).
    13. Johnson Worlanyo Ahiadorme, 2022. "On the aggregate effects of global uncertainty: Evidence from an emerging economy," South African Journal of Economics, Economic Society of South Africa, vol. 90(3), pages 390-407, September.
    14. Soojin Jo & Rodrigo Sekkel, 2019. "Macroeconomic Uncertainty Through the Lens of Professional Forecasters," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(3), pages 436-446, July.
    15. Gabriele Fiorentini & Enrique Sentana, 2021. "Specification tests for non‐Gaussian maximum likelihood estimators," Quantitative Economics, Econometric Society, vol. 12(3), pages 683-742, July.
    16. Saygin Sahinoz & Evren Erdogan Cosar, 2020. "Quantifying uncertainty and identifying its impacts on the Turkish economy," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 47(2), pages 365-387, May.
    17. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2021. "Using Time-Varying Volatility for Identification in Vector Autoregressions: An Application to Endogenous Uncertainty," CEPR Discussion Papers 16346, C.E.P.R. Discussion Papers.
    18. Joseph P. Byrne & Prince Asare Vitenu-Sackey, 2024. "The Macroeconomic Impact of Global and Country-Specific Climate Risk," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 87(3), pages 655-682, March.
    19. Travis J. Berge, 2020. "Time-varying Uncertainty of the Federal Reserve’s Output Gap Estimate," Finance and Economics Discussion Series 2020-012r1, Board of Governors of the Federal Reserve System (U.S.), revised 14 Apr 2021.
    20. Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2019. "How is Machine Learning Useful for Macroeconomic Forecasting?," CIRANO Working Papers 2019s-22, CIRANO.
    21. Candelon, Bertrand & Ferrara, Laurent & Joëts, Marc, 2021. "Global financial interconnectedness: a non-linear assessment of the uncertainty channel," LIDAM Reprints LFIN 2021003, Université catholique de Louvain, Louvain Finance (LFIN).
    22. Shin, Minchul & Zhang, Boyuan & Zhong, Molin & Lee, Dong Jin, 2018. "Measuring international uncertainty: The case of Korea," Economics Letters, Elsevier, vol. 162(C), pages 22-26.
    23. Joelle Miffre & Hossein Rad & Rand Kwong Yew Low & Robert Faff, 2023. "The commodity risk premium and neural networks," Post-Print hal-04322519, HAL.
    24. Fischer, Manfred M. & Huber, Florian & Pfarrhofer, Michael, 2018. "The transmission of uncertainty shocks on income inequality: State-level evidence from the United States," Working Papers in Regional Science 2018/06, WU Vienna University of Economics and Business.
    25. Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2022. "Capturing Macroeconomic Tail Risks with Bayesian Vector Autoregressions," CEPR Discussion Papers 17512, C.E.P.R. Discussion Papers.
    26. Kang, Wensheng & Ratti, Ronald A. & Vespignani, Joaquin L., 2020. "Revising the Impact of Financial and Non-Financial Global Stock Market Volatility Shocks," MPRA Paper 103019, University Library of Munich, Germany.
    27. Karanasos, M. & Yfanti, S., 2021. "On the Economic fundamentals behind the Dynamic Equicorrelations among Asset classes: Global evidence from Equities, Real estate, and Commodities," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    28. Juan M. Londono & Sai Ma & Beth Anne Wilson, 2021. "The Global Transmission of Real Economic Uncertainty," International Finance Discussion Papers 1317, Board of Governors of the Federal Reserve System (U.S.).
    29. Lin Liu, 2021. "U.S. Economic Uncertainty Shocks and China’s Economic Activities: A Time-Varying Perspective," SAGE Open, , vol. 11(3), pages 21582440211, July.
    30. Balcilar, Mehmet & Ozdemir, Zeynel Abidin & Ozdemir, Huseyin & Aygun, Gurcan & Wohar, Mark E., 2022. "The macroeconomic impact of economic uncertainty and financial shocks under low and high financial stress," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    31. Gorgi, Paolo & Koopman, Siem Jan & Li, Mengheng, 2019. "Forecasting economic time series using score-driven dynamic models with mixed-data sampling," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1735-1747.
    32. Yao, Shouyu & Liu, Zezhong & Wang, Chunfeng & Palma, Alessia & Goodell, John W., 2024. "Is macroeconomic tail risk contagious to stock idiosyncratic risk?," Finance Research Letters, Elsevier, vol. 63(C).
    33. Minchul Shin & Molin Zhong, 2020. "A New Approach to Identifying the Real Effects of Uncertainty Shocks," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 367-379, April.
    34. Bae, Siye & Jo, Soojin & Shim, Myungkyu, 2023. "United States of Mind under Uncertainty," Journal of Economic Behavior & Organization, Elsevier, vol. 213(C), pages 102-127.
    35. Xianbo Zhou & Zhuoran Chen, 2023. "The Impact of Uncertainty Shocks to Consumption under Different Confidence Regimes Based on a Stochastic Uncertainty-in-Mean TVAR Model," Sustainability, MDPI, vol. 15(4), pages 1-20, February.
    36. Danilo Cascaldi-Garcia & Ana Beatriz Galvao, 2018. "News and Uncertainty Shocks," International Finance Discussion Papers 1240, Board of Governors of the Federal Reserve System (U.S.).
    37. Michael Ryan, 2020. "A Narrative Approach to Creating Instruments with Unstructured and Voluminous Text: An Application to Policy Uncertainty," Working Papers in Economics 20/10, University of Waikato.
    38. Geert Bekaert & Eric Engstrom & Andrey Ermolov, 2017. "Macro Risks and the Term Structure of Interest Rates," Finance and Economics Discussion Series 2017-058, Board of Governors of the Federal Reserve System (U.S.).
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    94. Ganwen Zheng & Songping Zhu, 2021. "Research on the Effectiveness of China’s Macro Control Policy on Output and Technological Progress under Economic Policy Uncertainty," Sustainability, MDPI, vol. 13(12), pages 1-18, June.
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    96. Cristiana Fiorelli & Alfredo Cartone & Matteo Foglia, 2021. "Shadow rates and spillovers across the Eurozone: a spatial dynamic panel model," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 48(1), pages 223-245, February.
    97. Emmanuel Joel Aikins Abakah & Guglielmo Maria Caporale & Luis A. Gil-Alana, 2020. "Economic Policy Uncertainty: Persistence and Cross-Country Linkages," CESifo Working Paper Series 8289, CESifo.
    98. Śmiech, Sławomir & Papież, Monika & Dąbrowski, Marek A., 2019. "How important are different aspects of uncertainty in driving industrial production in the CEE countries?," Research in International Business and Finance, Elsevier, vol. 50(C), pages 252-266.
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    100. Cheng, Dong & Shi, Xunpeng & Yu, Jian & Zhang, Dayong, 2019. "How does the Chinese economy react to uncertainty in international crude oil prices?," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 147-164.
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    102. 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).
    103. 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.
    104. Klieber, Karin, 2024. "Non-linear dimension reduction in factor-augmented vector autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 159(C).
    105. Piergiorgio Alessandri & Andrea Gazzani & Alejandro Vicondoa, 2023. "Are the Effects of Uncertainty Shocks Big or Small?," Working Papers 244, Red Nacional de Investigadores en Economía (RedNIE).
    106. Gupta, Rangan & Ma, Jun & Risse, Marian & Wohar, Mark E., 2018. "Common business cycles and volatilities in US states and MSAs: The role of economic uncertainty," Journal of Macroeconomics, Elsevier, vol. 57(C), pages 317-337.
    107. Fuest, Angela & Schmidt, Torsten, 2020. "Inflation expectation uncertainty in a New Keynesian framework," Ruhr Economic Papers 867, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    108. Awijen, Haithem & Ben Zaied, Younes & Nguyen, Duc Khuong & Sensoy, Ahmet, 2020. "Endogenous Financial Uncertainty and Macroeconomic Volatility: Evidence from the United States," MPRA Paper 101276, University Library of Munich, Germany, revised Jun 2020.
    109. Philippe Goulet Coulombe & Mikael Frenette & Karin Klieber, 2023. "From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks," Papers 2311.16333, arXiv.org, revised Apr 2024.
    110. 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).
    111. Paul Labonne, 2020. "Asymmetric uncertainty : Nowcasting using skewness in real-time data," Papers 2012.02601, arXiv.org, revised May 2024.
    112. Aviral Kumar Tiwari & Micheal Kofi Boachie & Rangan Gupta, 2021. "Network Analysis of Economic and Financial Uncertainties in Advanced Economies: Evidence from Graph-Theory," Advances in Decision Sciences, Asia University, Taiwan, vol. 25(1), pages 188-215, March.
    113. Schüler, Yves S., 2020. "The impact of uncertainty and certainty shocks," Discussion Papers 14/2020, Deutsche Bundesbank.
    114. Li, Wenhui & Ockenfels, Peter & Wilde, Christian, 2021. "The effect of ambiguity on price formation and trading behavior in financial markets," SAFE Working Paper Series 326, Leibniz Institute for Financial Research SAFE.
    115. OH, Joonseok, 2019. "The propagation of uncertainty shocks : Rotemberg vs. Calvo," Economics Working Papers ECO 2019/01, European University Institute.
    116. Asad Dossani & John Elder, 2024. "Uncertainty and investment: Evidence from domestic oil rigs," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(2), pages 323-340, February.
    117. Kang, Wensheng & Ratti, Ronald A. & Vespignani, Joaquin, 2021. "Financial and nonfinancial global stock market volatility shocks," Economic Modelling, Elsevier, vol. 96(C), pages 128-134.
    118. Kim C. Raath & Katherine B. Ensor, 2023. "Wavelet-L2E Stochastic Volatility Models: an Application to the Water-Energy Nexus," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 150-176, May.
    119. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2020. "Measuring Uncertainty and Its Effects in the COVID-19 Era," Working Papers 20-32R, Federal Reserve Bank of Cleveland, revised 05 Jan 2022.
    120. Bucci, Andrea & Palomba, Giulio & Rossi, Eduardo, 2023. "The role of uncertainty in forecasting volatility comovements across stock markets," Economic Modelling, Elsevier, vol. 125(C).
    121. Zheng, Hannan & Schwenkler, Gustavo, 2020. "The network of firms implied by the news," ESRB Working Paper Series 108, European Systemic Risk Board.
    122. Myriam Gómez-Méndez & Erwin Hansen, 2021. "Economic policy uncertainty and presidential approval: Evidence from Latin America," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-17, March.
    123. Timo Wollmershäuser & Florian Eckert & Marcell Göttert & Christian Grimme & Carla Krolage & Stefan Lautenbacher & Robert Lehmann & Sebastian Link & Heiner Mikosch & Stefan Neuwirth & Wolfgang Nierhaus, 2019. "ifo Konjunkturprognose Winter 2019: Deutsche Konjunktur stabilisiert sich," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 72(24), pages 27-89, December.
    124. Karaki, Mohamad B. & Rangaraju, Sandeep Kumar, 2023. "The confidence channel of U.S. financial uncertainty: Evidence from industry-level data," Economic Modelling, Elsevier, vol. 129(C).
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  17. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2016. "Large Vector Autoregressions with Stochastic Volatility and Flexible Priors," Working Papers (Old Series) 1617, Federal Reserve Bank of Cleveland.

    Cited by:

    1. Bognanni, Mark, 2022. "Comment on “Large Bayesian vector autoregressions with stochastic volatility and non-conjugate priors”," Journal of Econometrics, Elsevier, vol. 227(2), pages 498-505.
    2. Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2016. "Bayesian Compressed Vector Autoregressions," Working Papers 2016_09, Business School - Economics, University of Glasgow.
    3. Eric Eisenstat & Joshua C.C. Chan & Rodney W. Strachan, 2018. "Reducing Dimensions in a Large TVP-VAR," Working Paper series 18-37, Rimini Centre for Economic Analysis.
    4. 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.
    5. Harry Turunen & Anastasia Zhutova & Matthieu Lemoine, 2023. "Stochastic Simulation of the FR-BDF Model and an Assessment of Uncertainty around Conditional Forecasts," Working papers 920, Banque de France.
    6. Petrova, Katerina, 2022. "Asymptotically valid Bayesian inference in the presence of distributional misspecification in VAR models," Journal of Econometrics, Elsevier, vol. 230(1), pages 154-182.
    7. 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.
    8. Kohns, David & Potjagailo, Galina, 2023. "Flexible Bayesian MIDAS: time‑variation, group‑shrinkage and sparsity," Bank of England working papers 1025, Bank of England.
    9. Lu, Yunzhi & Li, Jie & Yang, Haisheng, 2023. "Time-varying impacts of monetary policy uncertainty on China's housing market," Economic Modelling, Elsevier, vol. 118(C).
    10. Angelini, Elena & Lalik, Magdalena & Lenza, Michele & Paredes, Joan, 2019. "Mind the gap: a multi-country BVAR benchmark for the Eurosystem projections," Working Paper Series 2227, European Central Bank.
    11. Dellaportas, Petros & Titsias, Michalis K. & Petrova, Katerina & Plataniotis, Anastasios, 2023. "Scalable inference for a full multivariate stochastic volatility model," Journal of Econometrics, Elsevier, vol. 232(2), pages 501-520.
    12. 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.

  18. 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. 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.
    2. Kristin Forbes, 2019. "Has globalization changed the inflation process?," BIS Working Papers 791, Bank for International Settlements.
    3. Jaromir Baxa & Miroslav Plasil & Borek Vasicek, 2013. "Inflation and the Steeplechase Between Economic Activity Variables," Working Papers 2013/15, Czech National Bank.
    4. Bańbura, Marta & Bobeica, Elena, 2020. "Does the Phillips curve help to forecast euro area inflation?," Working Paper Series 2471, European Central Bank.
    5. Juan Angel Garcia & Aubrey Poon, 2022. "Inflation trends in Asia: implications for central banks [Are Phillips curves useful for forecasting inflation?]," Oxford Economic Papers, Oxford University Press, vol. 74(3), pages 671-700.
    6. Diegel, Max, 2022. "Time-varying credibility, anchoring and the Fed's inflation target," Discussion Papers 2022/9, Free University Berlin, School of Business & Economics.
    7. Bańbura, Marta & Leiva-Leon, Danilo & Menz, Jan-Oliver, 2021. "Do inflation expectations improve model-based inflation forecasts?," Working Paper Series 2604, European Central Bank.
    8. Kamber, Güneş & Wong, Benjamin, 2020. "Global factors and trend inflation," Journal of International Economics, Elsevier, vol. 122(C).
    9. 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.
    10. Francesca Rondina, 2018. "Estimating unobservable inflation expectations in the New Keynesian Phillips Curve," Working Papers 1804E, University of Ottawa, Department of Economics.
    11. Christina Anderl & Guglielmo Maria Caporale, 2022. "Forecasting Inflation with a Zero Lower Bound or Negative Interest Rates: Evidence from Point and Density Forecasts," CESifo Working Paper Series 9687, CESifo.
    12. 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.
    13. Florian, Huber & Kaufmann, Daniel, 2019. "Trend Fundamentals and Exchange Rate Dynamics," Working Papers in Economics 2019-4, University of Salzburg.
    14. 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.
    15. 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.
    16. Arnoud Stevens & Joris Wauters, 2018. "Is euro area lowflation here to stay ? Insights from a time-varying parameter model with survey data," Working Paper Research 355, National Bank of Belgium.
    17. Lukmanova, Elizaveta & Rabitsch, Katrin, 2018. "New VAR evidence on monetary transmission channels: temporary interest rate versus inflation target shocks," Department of Economics Working Paper Series 274, WU Vienna University of Economics and Business.
    18. Dany-Knedlik, Geraldine & Holtemöller, Oliver, 2017. "Inflation dynamics during the financial crisis in Europe: Cross-sectional identification of long-run inflation expectations," IWH Discussion Papers 10/2017, Halle Institute for Economic Research (IWH).
    19. Manuel M. F. Martins & Fabio Verona, 2021. "Inflation Dynamics and Forecast: Frequency Matters," CEF.UP Working Papers 2101, Universidade do Porto, Faculdade de Economia do Porto.
    20. 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.
    21. Österholm, Pär & Poon, Aubrey, 2022. "Trend Inflation in Sweden," Working Papers 2022:2, Örebro University, School of Business.
    22. Geraldine Dany-Knedlik & Juan Angel Garcia, 2018. "Monetary Policy and Inflation Dynamics in ASEAN Economies," IMF Working Papers 2018/147, International Monetary Fund.
    23. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Papers 2202.04146, arXiv.org, revised Oct 2024.
    24. Marco Gross & Willi Semmler, 2019. "Mind the Output Gap: The Disconnect of Growth and Inflation during Recessions and Convex Phillips Curves in the Euro Area," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(4), pages 817-848, August.
    25. McNeil, James, 2023. "Monetary policy and the term structure of inflation expectations with information frictions," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
    26. 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.
    27. Bańbura, Marta & Bobeica, Elena, 2020. "PCCI – a data-rich measure of underlying inflation in the euro area," Statistics Paper Series 38, European Central Bank.
    28. 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.
    29. 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).
    30. 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.
    31. Juan Angel Garcia & Sebastian Werner, 2018. "Inflation News and Euro Area Inflation Expectations," IMF Working Papers 2018/167, International Monetary Fund.
    32. 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.
    33. Chen, Ji & Yang, Xinglin & Liu, Xiliang, 2022. "Learning, disagreement and inflation forecasting," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    34. 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.
    35. 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.
    36. Kurozumi, Takushi & Van Zandweghe, Willem, 2022. "Macroeconomic changes with declining trend inflation: Complementarity with the superstar firm hypothesis," European Economic Review, Elsevier, vol. 141(C).
    37. Nikita D. Fokin & Ekaterina V. Malikova & Andrey V. Polbin, 2024. "Time-varying parameters error correction model for real ruble exchange rate and oil prices: What has changed due to capital control and sanctions?," Russian Journal of Economics, ARPHA Platform, vol. 10(1), pages 20-33, March.
    38. Juan Angel Garcia & Aubrey Poon, 2018. "Trend Inflation and Inflation Compensation," IMF Working Papers 2018/154, International Monetary Fund.
    39. Richard K. Crump & Stefano Eusepi & Emanuel Moench & Bruce Preston, 2021. "The Term Structure of Expectations," Staff Reports 992, Federal Reserve Bank of New York.
    40. 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.
    41. Marek Jarociński & Michele Lenza, 2018. "An Inflation‐Predicting Measure of the Output Gap in the Euro Area," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(6), pages 1189-1224, September.
    42. Marcelo Arbex & Sidney Caetano & Wilson Correa, 2018. "Macroeconomic Effects of Inflation Target Uncertainty Shocks," Working Papers 1804, University of Windsor, Department of Economics.
    43. Hauber, Philipp & Schumacher, Christian, 2021. "Precision-based sampling with missing observations: A factor model application," Discussion Papers 11/2021, Deutsche Bundesbank.
    44. 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.
    45. James Mitchell & Saeed Zaman, 2023. "The Distributional Predictive Content of Measures of Inflation Expectations," Working Papers 23-31, Federal Reserve Bank of Cleveland.
    46. 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).
    47. Andriantomanga, Zo, 2023. "The role of survey-based expectations in real-time forecasting of US inflation," MPRA Paper 119904, University Library of Munich, Germany.
    48. Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    49. 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.
    50. 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.
    51. 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.
    52. 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.
    53. Beechey, Meredith & Österholm, Pär & Poon, Aubrey, 2023. "Estimating the US trend short-term interest rate," Finance Research Letters, Elsevier, vol. 55(PA).
    54. 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.
    55. Saeed Zaman, 2021. "A Unified Framework to Estimate Macroeconomic Stars," Working Papers 21-23R2, Federal Reserve Bank of Cleveland, revised 31 May 2024.

  19. 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.

    Cited by:

    1. Christian Hotz‐Behofsits & Florian Huber & Thomas Otto Zörner, 2018. "Predicting crypto‐currencies using sparse non‐Gaussian state space models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(6), pages 627-640, September.
    2. Feldkircher, Martin & Gruber, Thomas & Huber, Florian, 2017. "Spreading the word or reducing the term spread? Assessing spillovers from euro area monetary policy," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168111, Verein für Socialpolitik / German Economic Association.
    3. Martin Feldkircher & Florian Huber, 2018. "Unconventional U.S. Monetary Policy: New Tools, Same Channels?," JRFM, MDPI, vol. 11(4), pages 1-31, October.
    4. Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2016. "Bayesian Compressed Vector Autoregressions," Working Papers 2016_09, Business School - Economics, University of Glasgow.
    5. Florian Huber & Thomas Zörner, 2017. "Threshold cointegration and adaptive shrinkage," Department of Economics Working Papers wuwp250, Vienna University of Economics and Business, Department of Economics.
    6. Feldkircher, Martin & Lukmanova, Elizaveta & Tondl, Gabriele, 2019. "Global Factors Driving Inflation and Monetary Policy: A Global VAR Assessment," Department of Economics Working Paper Series 289, WU Vienna University of Economics and Business.
    7. 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.
    8. Feldkircher, Martin & Gruber, Thomas & Huber, Florian, 2020. "International effects of a compression of euro area yield curves," Journal of Banking & Finance, Elsevier, vol. 113(C).
    9. 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.
    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. MOLTENI, Francesco, PAPPA, Evi, 2017. "The Combination of Monetary and Fiscal Policy Shocks: A TVP-FAVAR Approach," Economics Working Papers MWP 2017/13, European University Institute.
    12. 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.
    13. 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.

  20. Fabian Kr ger & Todd E. Clark & Francesco Ravazzolo, 2015. "Using Entropic Tilting to Combine BVAR Forecasts with External Nowcasts," Working Papers No 8/2015, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.

    Cited by:

    1. Knotek, Edward S. & Zaman, Saeed, 2019. "Financial nowcasts and their usefulness in macroeconomic forecasting," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1708-1724.
    2. Galvao, Ana Beatriz & Garratt, Anthony & Mitchell, James, 2020. "Does Judgment Improve Macroeconomic Density Forecasts?," EMF Research Papers 33, Economic Modelling and Forecasting Group.
    3. Bańbura, Marta & Leiva-Leon, Danilo & Menz, Jan-Oliver, 2021. "Do inflation expectations improve model-based inflation forecasts?," Working Paper Series 2604, European Central Bank.
    4. Edward S. Knotek & Saeed Zaman, 2020. "Real-Time Density Nowcasts of US Inflation: A Model-Combination Approach," Working Papers 20-31, Federal Reserve Bank of Cleveland.
    5. Davide Pettenuzzo & Konstantinos Metaxoglou & Aaron Smith, 2016. "Option-Implied Equity Premium Predictions via Entropic TiltinG," Working Papers 99R, Brandeis University, Department of Economics and International Business School, revised Aug 2016.
    6. 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.
    7. 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.
    8. Christopher McDonald & Craig Thamotheram & Shaun P. Vahey & Elizabeth C. Wakerly, 2016. "Assessing the economic value of probabilistic forecasts in the presence of an inflation target," CAMA Working Papers 2016-40, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    9. 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).
    10. Marta Baltar Moreira Areosa & Wagner Piazza Gaglianone, 2023. "Anchoring Long-term VAR Forecasts Based On Survey Data and State-space Models," Working Papers Series 574, Central Bank of Brazil, Research Department.
    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. Bańbura, Marta & Brenna, Federica & Paredes, Joan & Ravazzolo, Francesco, 2021. "Combining Bayesian VARs with survey density forecasts: does it pay off?," Working Paper Series 2543, European Central Bank.
    13. Baumeister, Christiane, 2021. "Measuring Market Expectations," CEPR Discussion Papers 16520, C.E.P.R. Discussion Papers.
    14. Bjarni G. Einarsson, 2024. "Online Monitoring of Policy Optimality," Economics wp95, Department of Economics, Central bank of Iceland.
    15. Hauber, Philipp, 2021. "How useful is external information from professional forecasters? Conditional forecasts in large factor models," EconStor Preprints 251469, ZBW - Leibniz Information Centre for Economics.
    16. Wolf, Elias & Montes-Galdón, Carlos & Paredes, Joan, 2024. "Conditional density forecasting: a tempered importance sampling approach," VfS Annual Conference 2024 (Berlin): Upcoming Labor Market Challenges 302442, Verein für Socialpolitik / German Economic Association.
    17. Zhiyuan Pan & Jun Zhang & Yudong Wang & Juan Huang, 2024. "Modeling and forecasting stock return volatility using the HARGARCH model with VIX information," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(8), pages 1383-1403, August.
    18. Todd E. Clark & Gergely Ganics & Elmar Mertens, 2022. "What is the Predictive Value of SPF Point and Density Forecasts?," Working Papers 22-37, Federal Reserve Bank of Cleveland.
    19. Todd E. Clark & Gergely Ganics & Elmar Mertens, 2024. "Constructing Fan Charts from the Ragged Edge of SPF Forecasts," Working Papers 22-36R, Federal Reserve Bank of Cleveland.
    20. Dimitris Kenourgios & Stephanos Papadamou & Dimitrios Dimitriou & Constantin Zopounidis, 2020. "Modelling the dynamics of unconventional monetary policies’ impact on professionals’ forecasts," Post-Print hal-02880071, HAL.
    21. 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.
    22. 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.
    23. 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.
    24. Fabian Krüger & Sebastian Lerch & Thordis Thorarinsdottir & Tilmann Gneiting, 2021. "Predictive Inference Based on Markov Chain Monte Carlo Output," International Statistical Review, International Statistical Institute, vol. 89(2), pages 274-301, August.
    25. Richard K. Crump & Stefano Eusepi & Domenico Giannone & Eric Qian & Argia M. Sbordone, 2021. "A Large Bayesian VAR of the United States Economy," Staff Reports 976, Federal Reserve Bank of New York.
    26. Richard Schnorrenberger & Aishameriane Schmidt & Guilherme Valle Moura, 2024. "Harnessing Machine Learning for Real-Time Inflation Nowcasting," Working Papers 806, DNB.
    27. Maryam Movahedifar & Hossein Hassani & Masoud Yarmohammadi & Mahdi Kalantari & Rangan Gupta, 2021. "A robust approach for outlier imputation: Singular Spectrum Decomposition," Working Papers 202164, University of Pretoria, Department of Economics.
    28. Markus Heinrich & Magnus Reif, 2020. "Real-Time Forecasting Using Mixed-Frequency VARS with Time-Varying Parameters," CESifo Working Paper Series 8054, CESifo.
    29. Fabian Krüger, 2017. "Survey-based forecast distributions for Euro Area growth and inflation: ensembles versus histograms," Empirical Economics, Springer, vol. 53(1), pages 235-246, August.
    30. Pablo Guerróon‐Quintana & Molin Zhong, 2023. "Macroeconomic forecasting in times of crises," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(3), pages 295-320, April.
    31. Taeyoung Doh, 2017. "Trend and Uncertainty in the Long-Term Real Interest Rate: Bayesian Exponential Tilting with Survey Data," Research Working Paper RWP 17-8, Federal Reserve Bank of Kansas City.
    32. Cem Cakmakli & Hamza Demircan, 2020. "Using Survey Information for Improving the Density Nowcasting of US GDP with a Focus on Predictive Performance during Covid-19 Pandemic," Koç University-TUSIAD Economic Research Forum Working Papers 2016, Koc University-TUSIAD Economic Research Forum.
    33. Nadiia Shapovalenko, 2021. "A BVAR Model for Forecasting Ukrainian Inflation," IHEID Working Papers 05-2021, Economics Section, The Graduate Institute of International Studies.

  21. Kristle Romero Cortes & Philip E. Strahan, 2014. "Tracing Out Capital Flows: How Financially Integrated Banks Respond to Natural Disasters," Working Papers (Old Series) 1412, Federal Reserve Bank of Cleveland.

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    1. Radoslav Raykov & Consuelo Silva-Buston, 2018. "Multibank Holding Companies and Bank Stability," Staff Working Papers 18-51, Bank of Canada.
    2. Kilian Huber, 2020. "Are bigger banks better? Firm-level evidence from Germany," CEP Discussion Papers dp1735, Centre for Economic Performance, LSE.
    3. Ruchi Avtar & Kristian S. Blickle & Rajashri Chakrabarti & Janavi Janakiraman & Maxim L. Pinkovskiy, 2023. "Understanding the Linkages between Climate Change and Inequality in the United States," Economic Policy Review, Federal Reserve Bank of New York, vol. 29(1), pages 1-39, June.
    4. Victor Aguirregabiria & Robert Clark & Hui Wang, 2024. "The geographic flow of bank funding and access to credit: Branch networks, local synergies and competition," Papers 2407.03517, arXiv.org.
    5. Shala, Iliriana & Schumacher, Benno, 2022. "The impact of natural disasters on banks' impairment flow: Evidence from Germany," Discussion Papers 36/2022, Deutsche Bundesbank.
    6. Noth, Felix & Rehbein, Oliver, 2019. "Badly hurt? Natural disasters and direct firm effects," Finance Research Letters, Elsevier, vol. 28(C), pages 254-258.
    7. Bos, Jaap & Li, Runliang & Sanders, Mark, 2018. "Hazardous Lending: The Impact of Natural Disasters on Banks'Asset Portfolio," Research Memorandum 021, Maastricht University, Graduate School of Business and Economics (GSBE).
    8. Brei, Michael & Mohan, Preeya & Strobl, Eric, 2019. "The impact of natural disasters on the banking sector: Evidence from hurricane strikes in the Caribbean," The Quarterly Review of Economics and Finance, Elsevier, vol. 72(C), pages 232-239.
    9. Galina Hale, 2024. "Climate Disasters and Exchange Rates: Are Beliefs Keeping up with Climate Change?," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 72(1), pages 253-291, March.
    10. Salih Fendo?lu & Eda Gül?en & José-Luis Peydró, 2019. "Global Liquidity and Impairment of Local Monetary Policy," Working Papers 1131, Barcelona School of Economics.
    11. Tho Pham & Oleksandr Talavera & Andriy Tsapin, 2018. "Shock propaganda, asset quality and lending behaviour," Working Papers 2018-04, Swansea University, School of Management.
    12. Barth, James R. & Hu, Qinyou & Sickles, Robin & Sun, Yanfei & Yu, Xiaoyu, 2024. "Direct and indirect impacts of natural disasters on banks: A spatial framework," Journal of Financial Stability, Elsevier, vol. 70(C).
    13. Francisco Zabala Aguayo & Beata Ślusarczyk, 2020. "Risks of Banking Services’ Digitalization: The Practice of Diversification and Sustainable Development Goals," Sustainability, MDPI, vol. 12(10), pages 1-10, May.
    14. Cuñat, Vicente & Cvijanovic, Dragana & Yuan, Kathy, 2018. "Within-bank spillovers of real estate shocks," LSE Research Online Documents on Economics 87374, London School of Economics and Political Science, LSE Library.
    15. Antonio Forte & Selay Sahan & Damiano B. Silipo, 2024. "Do Natural Disasters Reduce Loans to the More CO 2 -Emitting Sectors?," Sustainability, MDPI, vol. 16(10), pages 1-24, May.
    16. Raykov, Radoslav & Silva-Buston, Consuelo, 2020. "Holding company affiliation and bank stability: Evidence from the US banking sector," Journal of Corporate Finance, Elsevier, vol. 65(C).
    17. Xia Chen & Chun-Ping Chang, 2021. "The shocks of natural hazards on financial systems," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 105(3), pages 2327-2359, February.
    18. Giovanni Dell’Ariccia & Dalida Kadyrzhanova & Camelia Minoiu & Lev Ratnovski, 2021. "Bank Lending in the Knowledge Economy," The Review of Financial Studies, Society for Financial Studies, vol. 34(10), pages 5036-5076.
    19. Eileen van Straelen, 2021. "Desperate House Sellers: Distress Among Developers," Finance and Economics Discussion Series 2021-065, Board of Governors of the Federal Reserve System (U.S.).
    20. Wang, Teng, 2021. "Local banks and the effects of oil price shocks," Journal of Banking & Finance, Elsevier, vol. 125(C).
    21. Kristian S. Blickle & Sarah Ngo Hamerling & Donald P. Morgan, 2021. "How Bad Are Weather Disasters for Banks?," Staff Reports 990, Federal Reserve Bank of New York.
    22. Littke, Helge & Ossandon Busch, Matias, 2021. "Banks fearing the drought? Liquidity hoarding as a response to idiosyncratic interbank funding dry-ups," Discussion Papers 16/2021, Deutsche Bundesbank.
    23. Noth, Felix & Schüwer, Ulrich, 2017. "Natural disasters and bank stability: Evidence from the U.S. financial system," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168263, Verein für Socialpolitik / German Economic Association.
    24. Wan-Li Zhang & Chun-Ping Chang & Yang Xuan, 2022. "The impacts of climate change on bank performance: What’s the mediating role of natural disasters?," Economic Change and Restructuring, Springer, vol. 55(3), pages 1913-1952, August.
    25. Rubio-Andrés, Mercedes & Ramos-González, Mª del Mar & Sastre-Castillo, Miguel Ángel & Gutiérrez-Broncano, Santiago, 2023. "Stakeholder pressure and innovation capacity of SMEs in the COVID-19 pandemic: Mediating and multigroup analysis," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    26. Sebastian Doerr & Philipp Schaz, 2019. "Bank loan supply during crises: the importance of geographic diversification," BIS Working Papers 827, Bank for International Settlements.
    27. Nuno Paixao, 2019. "Propagation of House Price Shocks through the Banking System," 2019 Meeting Papers 1237, Society for Economic Dynamics.
    28. Yavuz Arslan & Ahmet Degerli & Gazi Kabas, 2019. "Unintended Consequences of Unemployment Insurance Benefits: The Role of Banks," Swiss Finance Institute Research Paper Series 19-44, Swiss Finance Institute.
    29. Rappoport, Veronica & Federico, Stefano & Hassan, Fadi, 2020. "Trade Shocks and Credit Reallocation," CEPR Discussion Papers 14792, C.E.P.R. Discussion Papers.
    30. Markus Herrmann & Martin Hibbeln, 2023. "Trading and liquidity in the catastrophe bond market," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 90(2), pages 283-328, June.
    31. João Granja & Christian Leuz & Raghuram Rajan, 2018. "Going the Extra Mile: Distant Lending and Credit Cycles," NBER Working Papers 25196, National Bureau of Economic Research, Inc.
    32. Allen, Kyle D. & Whitledge, Matthew D. & Winters, Drew B., 2022. "Community bank liquidity: Natural disasters as a natural experiment," Journal of Financial Stability, Elsevier, vol. 60(C).
    33. Teng Liu, 2024. "Save the Farms: Nonlinear Impact of Climate Change on Banks' Agricultural Lending," Papers 2409.19463, arXiv.org.
    34. Mathias Hoffmann & Toshihiro Okubo, 2012. "'By a Silken Thread': regional banking integration and credit reallocation during Japan’s Lost Decade," ECON - Working Papers 102, Department of Economics - University of Zurich, revised May 2021.
    35. Robert Clark & Hui Wang & Victor Aguirregabiria, 2017. "The Geographic Flow Of Bank Funding And Access To Credit: Branch Networks And Local-market Competition," Working Paper 1402, Economics Department, Queen's University.
    36. Schüwer, Ulrich & Gropp, Reint E. & Noth, Felix, 2016. "What drives banks' geographic expansion? The role of locally non-diversifiable risk," VfS Annual Conference 2016 (Augsburg): Demographic Change 145885, Verein für Socialpolitik / German Economic Association.
    37. Duqi, Andi & McGowan, Danny & Onali, Enrico & Torluccio, Giuseppe, 2021. "Natural disasters and economic growth: The role of banking market structure," Journal of Corporate Finance, Elsevier, vol. 71(C).
    38. Aguilar-Gomez, Sandra & Gutierrez, Emilio & Heres, David & Jaume, David & Tobal, Martin, 2024. "Thermal stress and financial distress: Extreme temperatures and firms’ loan defaults in Mexico," Journal of Development Economics, Elsevier, vol. 168(C).
    39. Petkov, Ivan, 2023. "Small business lending and the bank-branch network," Journal of Financial Stability, Elsevier, vol. 64(C).
    40. Rauf, Asad, 2023. "Bank stability and the price of loan commitments," Journal of Financial Intermediation, Elsevier, vol. 54(C).
    41. Avril Pauline & Levieuge Grégory & Turcu Camelia, 2022. "Natural Disasters and Financial Stress: Can Macroprudential Regulation Tame Green Swans?," Working papers 874, Banque de France.
    42. Abedifar, Pejman & Kashizadeh, Seyed Javad & Ongena, Steven, 2024. "Flood, farms and credit: The role of branch banking in the era of climate change," Journal of Corporate Finance, Elsevier, vol. 85(C).
    43. Smolyansky, Michael, 2019. "Policy externalities and banking integration," Journal of Financial Economics, Elsevier, vol. 132(3), pages 118-139.
    44. Agus Sugiarto & Ni Nyoman Puspani & Mustika Septiyas Trisilia, 2023. "The Shocks of Climate Change on Bank Loans," International Journal of Energy Economics and Policy, Econjournals, vol. 13(5), pages 493-514, September.
    45. Garbarino, Nicola & Guin, Benjamin, 2021. "High water, no marks? Biased lending after extreme weather," Journal of Financial Stability, Elsevier, vol. 54(C).
    46. Breckenfelder, Johannes & Maćkowiak, Bartosz & Marqués-Ibáñez, David & Olovsson, Conny & Popov, Alexander & Porcellacchia, Davide & Schepens, Glenn, 2023. "The climate and the economy," Working Paper Series 2793, European Central Bank.
    47. Kristian S. Blickle & João A. C. Santos, 2022. "Unintended Consequences of "Mandatory" Flood Insurance," Staff Reports 1012, Federal Reserve Bank of New York.
    48. M. Ali Choudhary & Anil K. Jain, 2017. "Finance and Inequality : The Distributional Impacts of Bank Credit Rationing," International Finance Discussion Papers 1211, Board of Governors of the Federal Reserve System (U.S.).
    49. Le, Anh-Tuan & Tran, Thao Phuong & Mishra, Anil V., 2023. "Climate risk and bank stability: International evidence," Journal of Multinational Financial Management, Elsevier, vol. 70.
    50. Li, Jie & An, Yahui & Wang, Lidan & Zhang, Yongjie, 2022. "Combating the COVID-19 pandemic: The role of disaster experience," Research in International Business and Finance, Elsevier, vol. 60(C).
    51. Kakuho Furukawa & Hibiki Ichiue & Noriyuki Shiraki, 2020. "How Does Climate Change Interact with the Financial System? A Survey," Bank of Japan Working Paper Series 20-E-8, Bank of Japan.
    52. Doerr, Sebastian & Schaz, Philipp, 2021. "Geographic diversification and bank lending during crises," Journal of Financial Economics, Elsevier, vol. 140(3), pages 768-788.
    53. Barbaglia, Luca & Fatica, Serena & Rho, Caterina, 2023. "Flooded credit markets: physical climate risk and small business lending," Working Papers 2023-14, Joint Research Centre, European Commission.
    54. Petkov, Ivan, 2015. "Small Business Lending and the Bank-Branch Network," MPRA Paper 85762, University Library of Munich, Germany, revised 13 Oct 2017.
    55. Hua Song & Yudong Yang & Zheng Tao, 2020. "How different types of financial service providers support small- and medium- enterprises under the impact of COVID-19 pandemic: from the perspective of expectancy theory," Frontiers of Business Research in China, Springer, vol. 14(1), pages 1-27, December.
    56. Henry He Huang & Joseph Kerstein & Chong Wang & Feng (Harry) Wu, 2022. "Firm climate risk, risk management, and bank loan financing," Strategic Management Journal, Wiley Blackwell, vol. 43(13), pages 2849-2880, December.
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    85. Sebastian Doerr & Thomas Drechsel & Donggyu Lee, 2022. "Income Inequality and Job Creation," Staff Reports 1021, Federal Reserve Bank of New York.
    86. Goetz, Martin R. & Gozzi, Juan Carlos, 2022. "Financial integration and the co-movement of economic activity: Evidence from U.S. states," Journal of International Economics, Elsevier, vol. 135(C).
    87. Feng, Zhi-Yuan & Wang, Chou-Wen & Lu, Yu-Hong, 2022. "The impact of climatic disaster on corporate investment policy," Journal of Multinational Financial Management, Elsevier, vol. 66(C).
    88. Kristian S. Blickle & Evan Perry & João A. C. Santos, 2024. "Do Mortgage Lenders Respond to Flood Risk?," Staff Reports 1101, Federal Reserve Bank of New York.
    89. Celil, Hursit S. & Oh, Seungjoon & Selvam, Srinivasan, 2022. "Natural disasters and the role of regional lenders in economic recovery," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 116-132.
    90. Temesvary, Judit & Wei, Andrew, 2024. "Domestic lending and the pandemic: How does banks’ exposure to COVID-19 abroad affect their lending in the United States?," Journal of International Money and Finance, Elsevier, vol. 143(C).
    91. Lee, Chien-Chiang & Wang, Chih-Wei & Thinh, Bui Tien & Xu, Zhi-Ting, 2022. "Climate risk and bank liquidity creation: International evidence," International Review of Financial Analysis, Elsevier, vol. 82(C).
    92. Dursun-de Neef, H. Özlem, 2023. "Bank specialization, mortgage lending and house prices," Journal of Banking & Finance, Elsevier, vol. 151(C).
    93. Ge, Shan & Weisbach, Michael S., 2021. "The role of financial conditions in portfolio choices: The case of insurers," Journal of Financial Economics, Elsevier, vol. 142(2), pages 803-830.
    94. Allen N. Berger & Filippo Curti & Nika Lazaryan & Atanas Mihov & Raluca A. Roman, 2023. "Climate Risks in the U.S. Banking Sector: Evidence from Operational Losses and Extreme Storms," Working Papers 21-31, Federal Reserve Bank of Philadelphia.
    95. Sebastian Doerr & Thomas Drechsel & Donggyu Lee, 2021. "Income inequality, financial intermediation, and small firms," BIS Working Papers 944, Bank for International Settlements.
    96. Ivan Faiella & Filippo Natoli, 2018. "Natural catastrophes and bank lending: the case of flood risk in Italy," Questioni di Economia e Finanza (Occasional Papers) 457, Bank of Italy, Economic Research and International Relations Area.
    97. Shi, Yining, 2022. "Financial liberalization and house prices: Evidence from China," Journal of Banking & Finance, Elsevier, vol. 145(C).
    98. Izadi, Mohammad & Saadi, Vahid, 2023. "Banking Market Structure and Trade Shocks," Journal of Banking & Finance, Elsevier, vol. 153(C).
    99. Berger, Allen N. & Molyneux, Phil & Wilson, John O.S., 2020. "Banks and the real economy: An assessment of the research," Journal of Corporate Finance, Elsevier, vol. 62(C).
    100. Sergio Mayordomo & Omar Rachedi, 2019. "The China syndrome affects banks: the credit supply channel of foreign import competition (Updated February 2020)," Working Papers 1908, Banco de España, revised Feb 2020.
    101. Pagnottoni, Paolo & Spelta, Alessandro & Flori, Andrea & Pammolli, Fabio, 2022. "Climate change and financial stability: Natural disaster impacts on global stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 599(C).
    102. Dou, Yiwei & Hung, Mingyi & She, Guoman & Wang, Lynn Linghuan, 2024. "Learning from peers: Evidence from disclosure of consumer complaints," Journal of Accounting and Economics, Elsevier, vol. 77(2).
    103. Bos, Jaap & Li, Runliang, 2017. "Understanding the Trembles of Nature: How Do Disaster Experiences Shape Bank Risk Taking?," Research Memorandum 033, Maastricht University, Graduate School of Business and Economics (GSBE).
    104. Noth, Felix & Rehbein, Oliver, 2017. "Badly hurt? Natural disasters and direct firm effects," IWH Discussion Papers 25/2017, Halle Institute for Economic Research (IWH).
    105. Ross Levine & Chen Lin & Wensi Xie, 2021. "Geographic Diversification and Banks’ Funding Costs," Management Science, INFORMS, vol. 67(5), pages 2657-2678, May.
    106. Braun, Alexander & Braun, Julia & Weigert, Florian, 2023. "Extreme weather risk and the cost of equity," CFR Working Papers 23-08, University of Cologne, Centre for Financial Research (CFR).
    107. Xu, Minhong & Xu, Yilan, 2023. "Do non-damaging earthquakes shake mortgage lenders' risk perception?," Journal of Environmental Economics and Management, Elsevier, vol. 117(C).
    108. James R. Brown & Matthew T. Gustafson & Ivan T. Ivanov, 2021. "Weathering Cash Flow Shocks," Journal of Finance, American Finance Association, vol. 76(4), pages 1731-1772, August.
    109. Horvath, Roman, 2021. "Natural catastrophes and financial depth: An empirical analysis," Journal of Financial Stability, Elsevier, vol. 53(C).
    110. Erel, Isil & Liebersohn, Jack, 2022. "Can FinTech reduce disparities in access to finance? Evidence from the Paycheck Protection Program," Journal of Financial Economics, Elsevier, vol. 146(1), pages 90-118.
    111. MD Gyasuddin Ansari & Rudra Sensarma, 2023. "Monetary Policy, Liquidity Shock and Bank lending: The Case of Currency Demonetization in India," Working papers 575, Indian Institute of Management Kozhikode.
    112. Mercy Berman DeMenno, 2023. "Environmental sustainability and financial stability: can macroprudential stress testing measure and mitigate climate-related systemic financial risk?," Journal of Banking Regulation, Palgrave Macmillan, vol. 24(4), pages 445-473, December.
    113. James Feigenbaum & James Lee & Filippo Mezzanotti, 2022. "Capital Destruction and Economic Growth: The Effects of Sherman's March, 1850–1920," American Economic Journal: Applied Economics, American Economic Association, vol. 14(4), pages 301-342, October.
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    116. Neville Francis & Laura E. Jackson & Michael T. Owyang, 2014. "How Has Empirical Monetary Policy Analysis Changed After the Financial Crisis?," Working Papers 2014-19, Federal Reserve Bank of St. Louis.
    117. Tho Pham & Oleksandr Talavera & Andriy Tsapin, 2021. "Shock contagion, asset quality and lending behaviour: The case of war in Eastern Ukraine," Kyklos, Wiley Blackwell, vol. 74(2), pages 243-269, May.
    118. Chabot, Miia & Bertrand, Jean-Louis, 2023. "Climate risks and financial stability: Evidence from the European financial system," Journal of Financial Stability, Elsevier, vol. 69(C).
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    121. Alogoskoufis, Spyros & Dunz, Nepomuk & Emambakhsh, Tina & Hennig, Tristan & Kaijser, Michiel & Kouratzoglou, Charalampos & Muñoz, Manuel A. & Parisi, Laura & Salleo, Carmelo, 2021. "ECB’s economy-wide climate stress test," Occasional Paper Series 281, European Central Bank.
    122. Giovanni Calice & Yong Kyu Gam, 2023. "US National Banks and Local Economic Fragility," Journal of Financial Services Research, Springer;Western Finance Association, vol. 63(3), pages 313-338, June.
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    124. Ghosh, Saibal, 2023. "Does climate legislation matter for bank lending? Evidence from MENA countries," Ecological Economics, Elsevier, vol. 212(C).
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  22. Knut Are Aastveit & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2014. "Have standard VARs remained stable since the crisis?," Working Paper 2014/13, Norges Bank.

    Cited by:

    1. Davide Delle Monache & Ivan Petrella, 2016. "Adaptive models and heavy tails with an application to inflation forecasting," BCAM Working Papers 1603, Birkbeck Centre for Applied Macroeconomics.
    2. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    3. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    4. Knotek, Edward S. & Zaman, Saeed, 2019. "Financial nowcasts and their usefulness in macroeconomic forecasting," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1708-1724.
    5. 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.
    6. Rachidi Kotchoni & Dalibor Stevanovic, 2016. "Forecasting U.S. Recessions and Economic Activity," Working Papers hal-04141569, HAL.
    7. Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2020. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(531), pages 1092-1110, July.
    8. Karlsson, Sune & Österholm, Pär, 2018. "A Note on the Stability of the Swedish Philips Curve," Working Papers 2018:6, Örebro University, School of Business.
    9. George Kapetanios & Massimiliano Marcellino & Fabrizio Venditti, 2017. "Large time-varying parameter VARs: a non-parametric approach," Temi di discussione (Economic working papers) 1122, Bank of Italy, Economic Research and International Relations Area.
    10. 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.
    11. Jarociński, Marek & Bobeica, Elena, 2017. "Missing disinflation and missing inflation: the puzzles that aren't," Working Paper Series 2000, European Central Bank.
    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. Pierre Guérin & Danilo Leiva-Leon & Massimiliano Marcellino, 2017. "Markov-Switching Three-Pass Regression Filter," Staff Working Papers 17-13, Bank of Canada.
    14. Kavanagh, Ella & Zhu, Sheng & O’Sullivan, Niall, 2022. "Monetary policy, trade-offs and the transmission of UK Monetary Policy," Journal of Policy Modeling, Elsevier, vol. 44(6), pages 1128-1147.
    15. Bjarni G. Einarsson, 2024. "Online Monitoring of Policy Optimality," Economics wp95, Department of Economics, Central bank of Iceland.
    16. Heinrich, Markus, 2020. "Does the Current State of the Business Cycle matter for Real-Time Forecasting? A Mixed-Frequency Threshold VAR approach," EconStor Preprints 219312, ZBW - Leibniz Information Centre for Economics.
    17. 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.
    18. Hacioglu Hoke, Sinem, 2019. "Macroeconomic effects of political risk shocks," Bank of England working papers 841, Bank of England.
    19. Antonio Maria Conti & Stefano Neri & Alessandro Notarpietro, 2024. "Credit strikes back: the macroeconomic impact of the 2022-23 ECB monetary tightening and the role of lending rates," Questioni di Economia e Finanza (Occasional Papers) 884, Bank of Italy, Economic Research and International Relations Area.
    20. Petrella, Ivan & Antolin-Diaz, Juan & Rubio-Ramírez, Juan Francisco, 2018. "Structural Scenario Analysis with SVARs," CEPR Discussion Papers 12579, C.E.P.R. Discussion Papers.
    21. Edvinsson, Rodney & Karlsson, Sune & Österholm, Pär, 2023. "Does Money Growth Predict Inflation? Evidence from Vector Autoregressions Using Four Centuries of Data," Working Papers 2023:3, Örebro University, School of Business.
    22. Orkideh Gharehgozli & Sunhyung Lee, 2022. "Money Supply and Inflation after COVID-19," Economies, MDPI, vol. 10(5), pages 1-14, April.
    23. 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.
    24. 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.
    25. Todd E. Clark & Michael W. McCracken, 2014. "Evaluating Conditional Forecasts from Vector Autoregressions," Working Papers (Old Series) 1413, Federal Reserve Bank of Cleveland.
    26. Markus Heinrich & Magnus Reif, 2020. "Real-Time Forecasting Using Mixed-Frequency VARS with Time-Varying Parameters," CESifo Working Paper Series 8054, CESifo.
    27. Conti, Antonio M., 2021. "Resurrecting the Phillips Curve in Low-Inflation Times," Economic Modelling, Elsevier, vol. 96(C), pages 172-195.
    28. Benjamin Garcia & Arsenios Skaperdas, 2017. "Inferring the Shadow Rate from Real Activity," Finance and Economics Discussion Series 2017-106, Board of Governors of the Federal Reserve System (U.S.).
    29. Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    30. Rachidi Kotchoni & Dalibor Stevanovic, 2020. "GDP Forecast Accuracy During Recessions," Working Papers 20-06, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    31. Aymeric Ortmans, 2020. "Evolving Monetary Policy in the Aftermath of the Great Recession," Documents de recherche 20-01, Centre d'Études des Politiques Économiques (EPEE), Université d'Evry Val d'Essonne.
    32. Neville Francis & Laura E. Jackson & Michael T. Owyang, 2014. "How Has Empirical Monetary Policy Analysis Changed After the Financial Crisis?," Working Papers 2014-19, Federal Reserve Bank of St. Louis.
    33. 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.
    34. Legrand, Romain, 2018. "Time-Varying Vector Autoregressions: Efficient Estimation, Random Inertia and Random Mean," MPRA Paper 88925, University Library of Munich, Germany.
    35. Shang, Fei, 2022. "The effect of uncertainty on the sensitivity of the yield curve to monetary policy surprises," Journal of Economic Dynamics and Control, Elsevier, vol. 137(C).
    36. 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.
    37. Conti, Antonio M. & Nobili, Andrea & Signoretti, Federico M., 2023. "Bank capital requirement shocks: A narrative perspective," European Economic Review, Elsevier, vol. 151(C).

  23. 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.

    Cited by:

    1. Florian Huber & Tamas Krisztin & Philipp Piribauer, 2014. "Forecasting Global Equity Indices using Large Bayesian VARs," Department of Economics Working Papers wuwp184, Vienna University of Economics and Business, Department of Economics.
    2. Minchul Shin & Molin Zhong, 2013. "Does realized volatility help bond yield density prediction?," PIER Working Paper Archive 13-064, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    3. Andrea Renzetti, 2023. "Theory coherent shrinkage of Time-Varying Parameters in VARs," Papers 2311.11858, arXiv.org, revised Nov 2024.
    4. 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.

  24. Todd E. Clark & Michael W. McCracken, 2014. "Evaluating Conditional Forecasts from Vector Autoregressions," Working Papers (Old Series) 1413, Federal Reserve Bank of Cleveland.

    Cited by:

    1. Craig S. Hakkio & Jun Nie, 2014. "Implications of recent U.S. energy trends for trade forecasts," Economic Review, Federal Reserve Bank of Kansas City, issue Q IV, pages 29-51.
    2. Sokol, Andrej, 2021. "Fan charts 2.0: flexible forecast distributions with expert judgement," Working Paper Series 2624, European Central Bank.
    3. Giannone, Domenico & Banbura, Marta & Lenza, Michele, 2014. "Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections," CEPR Discussion Papers 9931, C.E.P.R. Discussion Papers.
    4. Mehmet Pasaogullari, 2015. "Forecasts from Reduced-form Models under the Zero-Lower-Bound Constraint," Working Papers (Old Series) 1512, Federal Reserve Bank of Cleveland.
    5. Knut Are Aastveit & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2014. "Have standard VARs remained stable since the crisis?," Working Paper 2014/13, Norges Bank.
    6. Boneva, Lena & Fawcett, Nicholas & Masolo, Riccardo M. & Waldron, Matt, 2019. "Forecasting the UK economy: Alternative forecasting methodologies and the role of off-model information," International Journal of Forecasting, Elsevier, vol. 35(1), pages 100-120.
    7. Petrella, Ivan & Antolin-Diaz, Juan & Rubio-Ramírez, Juan Francisco, 2018. "Structural Scenario Analysis with SVARs," CEPR Discussion Papers 12579, C.E.P.R. Discussion Papers.
    8. Tim Oliver Berg, 2015. "Forecast Accuracy of a BVAR under Alternative Specifications of the Zero Lower Bound," ifo Working Paper Series 203, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    9. Angelini, Elena & Lalik, Magdalena & Lenza, Michele & Paredes, Joan, 2019. "Mind the gap: a multi-country BVAR benchmark for the Eurosystem projections," Working Paper Series 2227, European Central Bank.
    10. Travis J. Berge & Andrew C. Chang & Nitish R. Sinha, 2019. "Evaluating the Conditionality of Judgmental Forecasts," Finance and Economics Discussion Series 2019-002, Board of Governors of the Federal Reserve System (U.S.).

  25. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2013. "Real-Time Nowcasting with a Bayesian Mixed Frequency Model with Stochastic Volatility," CEPR Discussion Papers 9312, C.E.P.R. Discussion Papers.

    Cited by:

    1. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022. "Nowcasting tail risk to economic activity at a weekly frequency," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 843-866, August.
    2. Galvão, Ana Beatriz & Giraitis, Liudas & Kapetanios, George & Petrova, Katerina, 2016. "A time varying DSGE model with financial frictions," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 690-716.
    3. Berg, Tim Oliver & Henzel, Steffen, 2013. "Point and Density Forecasts for the Euro Area Using Many Predictors: Are Large BVARs Really Superior?," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79783, Verein für Socialpolitik / German Economic Association.
    4. Edward S. Knotek & Saeed Zaman, 2020. "Real-Time Density Nowcasts of US Inflation: A Model-Combination Approach," Working Papers 20-31, Federal Reserve Bank of Cleveland.
    5. Soojin Jo & Rodrigo Sekkel, 2019. "Macroeconomic Uncertainty Through the Lens of Professional Forecasters," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(3), pages 436-446, July.
    6. Giannone, Domenico & Reichlin, Lucrezia & Bańbura, Marta & Modugno, Michele, 2013. "Now-casting and the real-time data flow," Working Paper Series 1564, European Central Bank.
    7. 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.
    8. Antonello D’Agostino & Jacopo Cimadomo, 2015. "Combining time-variation and mixed-frequencies: an analysis of government spending multipliers in Italy," Working Papers 7, European Stability Mechanism.
    9. 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.
    10. Foroni, Claudia & Guérin, Pierre & Marcellino, Massimiliano, 2018. "Using low frequency information for predicting high frequency variables," International Journal of Forecasting, Elsevier, vol. 34(4), pages 774-787.
    11. 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.
    12. 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.
    13. 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.
    14. Matteo Mogliani & Anna Simoni, 2024. "Bayesian Bi-level Sparse Group Regressions for Macroeconomic Forecasting," Papers 2404.02671, arXiv.org, revised Sep 2024.
    15. Shrub, Yuliya & Rieger, Jonas & Müller, Henrik & Jentsch, Carsten, 2022. "Text data rule - don't they? A study on the (additional) information of Handelsblatt data for nowcasting German GDP in comparison to established economic indicators," Ruhr Economic Papers 964, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    16. Markus Heinrich & Magnus Reif, 2018. "Forecasting using mixed-frequency VARs with time-varying parameters," ifo Working Paper Series 273, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    17. Martin Feldkircher & Florian Huber & Michael Pfarrhofer, 2020. "Measuring the Effectiveness of US Monetary Policy during the COVID-19 Recession," Papers 2007.15419, arXiv.org.
    18. Knut Are Aastveit & Francesco Ravazzolo & Herman K. van Dijk, 2014. "Combined Density Nowcasting in an Uncertain Economic Environment," Tinbergen Institute Discussion Papers 14-152/III, Tinbergen Institute.
    19. Jos Jansen, W. & Jin, Xiaowen & Winter, Jasper M. de, 2016. "Forecasting and nowcasting real GDP: Comparing statistical models and subjective forecasts," Munich Reprints in Economics 43488, University of Munich, Department of Economics.
    20. Bhattacharjee, Arnab & Kohns, David, 2022. "Nowcasting Growth using Google Trends Data: A Bayesian Structural Time Series Model," National Institute of Economic and Social Research (NIESR) Discussion Papers 538, National Institute of Economic and Social Research.
    21. Edward S. Knotek & Saeed Zaman, 2014. "Nowcasting U.S. Headline and Core Inflation," Working Papers (Old Series) 1403, Federal Reserve Bank of Cleveland.
    22. Tim Oliver Berg & Steffen Henzel, 2014. "Point and Density Forecasts for the Euro Area Using Bayesian VARs," CESifo Working Paper Series 4711, CESifo.
    23. Cimadomo, Jacopo & Giannone, Domenico & Lenza, Michele & Monti, Francesca & Sokol, Andrej, 2022. "Nowcasting with large Bayesian vector autoregressions," Journal of Econometrics, Elsevier, vol. 231(2), pages 500-519.
    24. Heinrich, Markus, 2020. "Does the Current State of the Business Cycle matter for Real-Time Forecasting? A Mixed-Frequency Threshold VAR approach," EconStor Preprints 219312, ZBW - Leibniz Information Centre for Economics.
    25. Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2014. "Density forecasts with MIDAS models," Working Paper 2014/10, Norges Bank.
    26. Pettenuzzo, Davide & Timmermann, Allan & Valkanov, Rossen, 2016. "A MIDAS approach to modeling first and second moment dynamics," Journal of Econometrics, Elsevier, vol. 193(2), pages 315-334.
    27. Galvao, Ana Beatriz & Owyang, Michael, 2020. "Forecasting Low Frequency Macroeconomic Events with High Frequency Data," EMF Research Papers 38, Economic Modelling and Forecasting Group.
    28. Hassani, Hossein & Rua, António & Silva, Emmanuel Sirimal & Thomakos, Dimitrios, 2019. "Monthly forecasting of GDP with mixed-frequency multivariate singular spectrum analysis," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1263-1272.
    29. Marcellino, Massimiliano & Foroni, Claudia & Stevanovic, Dalibor, 2020. "Forecasting the Covid-19 recession and recovery: Lessons from the financial crisis," CEPR Discussion Papers 15114, C.E.P.R. Discussion Papers.
    30. Claudia Foroni & Francesco Ravazzolo & Luca Rossini, 2020. "Are low frequency macroeconomic variables important for high frequency electricity prices?," Papers 2007.13566, arXiv.org, revised Dec 2022.
    31. Bec, Frédérique & Mogliani, Matteo, 2015. "Nowcasting French GDP in real-time with surveys and “blocked” regressions: Combining forecasts or pooling information?," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1021-1042.
    32. Fabian Kr ger & Todd E. Clark & Francesco Ravazzolo, 2015. "Using Entropic Tilting to Combine BVAR Forecasts with External Nowcasts," Working Papers No 8/2015, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    33. Kiss, Tamás & Mazur, Stepan & Nguyen, Hoang & Österholm, Pär, 2021. "Modelling the Relation between the US Real Economy and the Corporate Bond-Yield Spread in Bayesian VARs with non-Gaussian Disturbances," Working Papers 2021:9, Örebro University, School of Business.
    34. Boriss Siliverstovs, 2021. "New York FED Staff Nowcasts and Reality: What Can We Learn about the Future, the Present, and the Past?," Econometrics, MDPI, vol. 9(1), pages 1-25, March.
    35. Marek Rusnak, 2013. "Nowcasting Czech GDP in Real Time," Working Papers 2013/06, Czech National Bank.
    36. Sebastian Ankargren & Paulina Jon'eus, 2019. "Estimating Large Mixed-Frequency Bayesian VAR Models," Papers 1912.02231, arXiv.org.
    37. Mogliani, Matteo & Darné, Olivier & Pluyaud, Bertrand, 2017. "The new MIBA model: Real-time nowcasting of French GDP using the Banque de France's monthly business survey," Economic Modelling, Elsevier, vol. 64(C), pages 26-39.
    38. Mogliani, Matteo & Simoni, Anna, 2021. "Bayesian MIDAS penalized regressions: Estimation, selection, and prediction," Journal of Econometrics, Elsevier, vol. 222(1), pages 833-860.
    39. Michael W. McCracken & Michael T. Owyang & Tatevik Sekhposyan, 2015. "Real-Time Forecasting and Scenario Analysis using a Large Mixed-Frequency Bayesian VAR," Working Papers 2015-030, Federal Reserve Bank of St. Louis, revised 10 Apr 2020.
    40. 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.
    41. Foroni, Claudia & Ravazzolo, Francesco & Rossini, Luca, 2019. "Forecasting daily electricity prices with monthly macroeconomic variables," Working Paper Series 2250, European Central Bank.
    42. Knut Are Aastveit & Tuva Marie Fastbø & Eleonora Granziera & Kenneth Sæterhagen Paulsen & Kjersti Næss Torstensen, 2020. "Nowcasting Norwegian household consumption with debit card transaction data," Working Paper 2020/17, Norges Bank.
    43. George Kapetanios & Fotis Papailias, 2018. "Big Data & Macroeconomic Nowcasting: Methodological Review," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-12, Economic Statistics Centre of Excellence (ESCoE).
    44. Kohns, David & Potjagailo, Galina, 2023. "Flexible Bayesian MIDAS: time‑variation, group‑shrinkage and sparsity," Bank of England working papers 1025, Bank of England.
    45. Luiz Renato Lima & Lucas Lúcio Godeiro & Mohammed Mohsin, 2021. "Time-Varying Dictionary and the Predictive Power of FED Minutes," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 149-181, January.
    46. Richard Schnorrenberger & Aishameriane Schmidt & Guilherme Valle Moura, 2024. "Harnessing Machine Learning for Real-Time Inflation Nowcasting," Working Papers 806, DNB.
    47. Lucas P. Harlaar & Jacques J.F. Commandeur & Jan A. van den Brakel & Siem Jan Koopman & Niels Bos & Frits D. Bijleveld, 2024. "Statistical Early Warning Models with Applications," Tinbergen Institute Discussion Papers 24-037/III, Tinbergen Institute.
    48. González-Astudillo, Manuel & Baquero, Daniel, 2019. "A nowcasting model for Ecuador: Implementing a time-varying mean output growth," Economic Modelling, Elsevier, vol. 82(C), pages 250-263.
    49. Alessandro Girardi & Roberto Golinelli & Carmine Pappalardo, 2017. "The role of indicator selection in nowcasting euro-area GDP in pseudo-real time," Empirical Economics, Springer, vol. 53(1), pages 79-99, August.
    50. George Athanasopoulos & Puwasala Gamakumara & Anastasios Panagiotelis & Rob J Hyndman & Mohamed Affan, 2019. "Hierarchical Forecasting," Monash Econometrics and Business Statistics Working Papers 2/19, Monash University, Department of Econometrics and Business Statistics.
    51. 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.
    52. Markus Heinrich & Magnus Reif, 2020. "Real-Time Forecasting Using Mixed-Frequency VARS with Time-Varying Parameters," CESifo Working Paper Series 8054, CESifo.
    53. 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.
    54. Marcellino, Massimiliano & Foroni, Claudia, 2014. "Markov-Switching Mixed-Frequency VAR Models," CEPR Discussion Papers 9815, C.E.P.R. Discussion Papers.
    55. Robert M. Kunst & Martin Wagner, 2020. "Economic forecasting: editors’ introduction," Empirical Economics, Springer, vol. 58(1), pages 1-5, January.
    56. Carriero, Andrea & Mumtaz, Haroon & Theophilopoulou, Angeliki, 2015. "Macroeconomic information, structural change, and the prediction of fiscal aggregates," International Journal of Forecasting, Elsevier, vol. 31(2), pages 325-348.
    57. 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.
    58. Soybilgen, Barış & Yazgan, Ege, 2018. "Evaluating nowcasts of bridge equations with advanced combination schemes for the Turkish unemployment rate," Economic Modelling, Elsevier, vol. 72(C), pages 99-108.
    59. Garciga, Christian & Knotek II, Edward S., 2019. "Forecasting GDP growth with NIPA aggregates: In search of core GDP," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1814-1828.
    60. 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.).
    61. Cem Cakmakli & Hamza Demircan, 2020. "Using Survey Information for Improving the Density Nowcasting of US GDP with a Focus on Predictive Performance during Covid-19 Pandemic," Koç University-TUSIAD Economic Research Forum Working Papers 2016, Koc University-TUSIAD Economic Research Forum.
    62. Boriss Siliverstovs, 2020. "Assessing nowcast accuracy of US GDP growth in real time: the role of booms and busts," Empirical Economics, Springer, vol. 58(1), pages 7-27, January.
    63. David Kohns & Arnab Bhattacharjee, 2019. "Interpreting Big Data in the Macro Economy: A Bayesian Mixed Frequency Estimator," CEERP Working Paper Series 010, Centre for Energy Economics Research and Policy, Heriot-Watt University.
    64. Boriss Siliverstovs, 2021. "Gauging the Effect of Influential Observations on Measures of Relative Forecast Accuracy in a Post-COVID-19 Era: Application to Nowcasting Euro Area GDP Growth," Working Papers 2021/01, Latvijas Banka.

  26. Todd E. Clark & Michael W. McCracken, 2013. "Evaluating the accuracy of forecasts from vector autoregressions," Working Papers 2013-010, Federal Reserve Bank of St. Louis.

    Cited by:

    1. Pincheira, Pablo & Selaive, Jorge & Nolazco, Jose Luis, 2017. "Forecasting Inflation in Latin America with Core Measures," MPRA Paper 80496, University Library of Munich, Germany.
    2. Coble, David & Pincheira, Pablo, 2017. "Nowcasting Building Permits with Google Trends," MPRA Paper 76514, University Library of Munich, Germany.
    3. Pincheira, Pablo M. & West, Kenneth D., 2016. "A comparison of some out-of-sample tests of predictability in iterated multi-step-ahead forecasts," Research in Economics, Elsevier, vol. 70(2), pages 304-319.
    4. Nicholson, William B. & Matteson, David S. & Bien, Jacob, 2017. "VARX-L: Structured regularization for large vector autoregressions with exogenous variables," International Journal of Forecasting, Elsevier, vol. 33(3), pages 627-651.
    5. Francisco Lasso-Valderrama & Héctor M. Zárate-Solano, 2019. "Forecasting the Colombian Unemployment Rate Using Labour Force Flows," Borradores de Economia 1073, Banco de la Republica de Colombia.
    6. William J. Procasky & Anwen Yin, 2022. "Forecasting high‐yield equity and CDS index returns: Does observed cross‐market informational flow have predictive power?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(8), pages 1466-1490, August.
    7. Mihaela Simionescu, 2015. "The Improvement of Unemployment Rate Predictions Accuracy," Prague Economic Papers, Prague University of Economics and Business, vol. 2015(3), pages 274-286.

  27. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2012. "Common Drifting Volatility in Large Bayesian VARs," CEPR Discussion Papers 8894, C.E.P.R. Discussion Papers.

    Cited by:

    1. Christine Garnier & Elmar Mertens & Edward Nelson, 2013. "Trend inflation in advanced economies," Finance and Economics Discussion Series 2013-74, Board of Governors of the Federal Reserve System (U.S.).
    2. Oguzhan Cepni & I. Ethem Guney & Norman R. Swanson, 2020. "Forecasting and nowcasting emerging market GDP growth rates: The role of latent global economic policy uncertainty and macroeconomic data surprise factors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(1), pages 18-36, January.
    3. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    4. Jiawen Luo & Langnan Chen, 2019. "Multivariate realized volatility forecasts of agricultural commodity futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(12), pages 1565-1586, December.
    5. 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.
    6. Joshua C. C. Chan, 2022. "Comparing Stochastic Volatility Specifications for Large Bayesian VARs," Papers 2208.13255, arXiv.org.
    7. 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.
    8. Dovern, Jonas & Feldkircher, Martin & Huber, Florian, 2015. "Does Joint Modelling of the World Economy Pay Off? Evaluating Multivariate Forecasts from a Bayesian GVAR," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112999, Verein für Socialpolitik / German Economic Association.
    9. Haroon Mumtaz & Konstantinos Theodoridis, 2014. "The Changing Transmission of Uncertainty shocks in the US: An Empirical Analysis," Working Papers 735, Queen Mary University of London, School of Economics and Finance.
    10. Francisco Serranito & Nicolas Himounet & Julien Vauday, 2023. "Uncertainty is bad for Business. Really?," EconomiX Working Papers 2023-26, University of Paris Nanterre, EconomiX.
    11. Gregor Kastner, 2016. "Sparse Bayesian time-varying covariance estimation in many dimensions," Papers 1608.08468, arXiv.org, revised Nov 2017.
    12. Berg, Tim Oliver & Henzel, Steffen, 2013. "Point and Density Forecasts for the Euro Area Using Many Predictors: Are Large BVARs Really Superior?," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79783, Verein für Socialpolitik / German Economic Association.
    13. Michele Lenza & Giorgio E. Primiceri, 2022. "How to estimate a vector autoregression after March 2020," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 688-699, June.
    14. Byrne, Joseph P. & Cao, Shuo & Korobilis, Dimitris, 2019. "Decomposing global yield curve co-movement," Journal of Banking & Finance, Elsevier, vol. 106(C), pages 500-513.
    15. Mike Tsionas & Marwan Izzeldin & Lorenzo Trapani, 2019. "Bayesian estimation of large dimensional time varying VARs using copulas," Papers 1912.12527, arXiv.org.
    16. Joshua C.C. Chan & Rodney W. Strachan, 2020. "Bayesian state space models in macroeconometrics," CAMA Working Papers 2020-90, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    17. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015. "Realtime nowcasting with a Bayesian mixed frequency model with stochastic volatility," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(4), pages 837-862, October.
    18. Irina Zviadadze, 2017. "Term Structure of Consumption Risk Premia in the Cross Section of Currency Returns," Journal of Finance, American Finance Association, vol. 72(4), pages 1529-1566, August.
    19. Jonas Dovern & Martin Feldkircher & Florian Huber, 2015. "Does Joint Modelling of the World Economy Pay Off? Evaluating Global Forecasts from a Bayesian GVAR," Working Papers 200, Oesterreichische Nationalbank (Austrian Central Bank).
    20. Mumtaz, Haroon & Theodoridis, Konstantinos, 2017. "Common and country specific economic uncertainty," Journal of International Economics, Elsevier, vol. 105(C), pages 205-216.
    21. Alessandri, Piergiorgio & Mumtaz, Haroon, 2019. "Financial regimes and uncertainty shocks," Journal of Monetary Economics, Elsevier, vol. 101(C), pages 31-46.
    22. Hadjiantoni, Stella & Kontoghiorghes, Erricos John, 2022. "An alternative numerical method for estimating large-scale time-varying parameter seemingly unrelated regressions models," Econometrics and Statistics, Elsevier, vol. 21(C), pages 1-18.
    23. Roberto Leon-Gonzalez & Blessings Majon, 2024. "Exact Likelihood for Inverse Gamma Stochastic Volatility Models," GRIPS Discussion Papers 24-03, National Graduate Institute for Policy Studies.
    24. Ellington, Michael, 2022. "Fat tails, serial dependence, and implied volatility index connections," European Journal of Operational Research, Elsevier, vol. 299(2), pages 768-779.
    25. Valentina Aprigliano & Alessandro Borin & Francesco Paolo Conteduca & Simone Emiliozzi & Marco Flaccadoro & Sabina Marchetti & Stefania Villa, 2021. "Forecasting Italian GDP growth with epidemiological data," Questioni di Economia e Finanza (Occasional Papers) 664, Bank of Italy, Economic Research and International Relations Area.
    26. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2021. "Using Time-Varying Volatility for Identification in Vector Autoregressions: An Application to Endogenous Uncertainty," CEPR Discussion Papers 16346, C.E.P.R. Discussion Papers.
    27. Huber, Florian, 2016. "Density forecasting using Bayesian global vector autoregressions with stochastic volatility," International Journal of Forecasting, Elsevier, vol. 32(3), pages 818-837.
    28. Sebastian Ankargren & Paulina Jon'eus, 2019. "Simulation smoothing for nowcasting with large mixed-frequency VARs," Papers 1907.01075, arXiv.org.
    29. 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.
    30. Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2022. "Capturing Macroeconomic Tail Risks with Bayesian Vector Autoregressions," CEPR Discussion Papers 17512, C.E.P.R. Discussion Papers.
    31. Ching-Wai Chiu & Haroon Mumtaz & Gabor Pinter, 2016. "VAR Models with Non-Gaussian Shocks," Discussion Papers 1609, Centre for Macroeconomics (CFM).
    32. Andrea Carriero & Davide Pettenuzzo & Shubhranshu Shekhar, 2024. "Macroeconomic Forecasting with Large Language Models," Papers 2407.00890, arXiv.org.
    33. MeiChi Huang, 2022. "Time‐varying impacts of expectations on housing markets across hot and cold phases," International Finance, Wiley Blackwell, vol. 25(2), pages 249-265, August.
    34. Chuliá, Helena & Guillén, Montserrat & Uribe, Jorge M., 2017. "Measuring uncertainty in the stock market," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 18-33.
    35. 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.
    36. 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.
    37. Himounet, Nicolas, 2022. "Searching the nature of uncertainty: Macroeconomic and financial risks VS geopolitical and pandemic risks," International Economics, Elsevier, vol. 170(C), pages 1-31.
    38. Joshua C.C. Chan & Xuewen Yu, 2020. "Fast and accurate variational inference for large Bayesian VARs with stochastic volatility," CAMA Working Papers 2020-108, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    39. Thore Schlaak & Malte Rieth & Maximilian Podstawski, 2018. "Monetary Policy, External Instruments and Heteroskedasticity," Discussion Papers of DIW Berlin 1749, DIW Berlin, German Institute for Economic Research.
    40. 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.
    41. Joshua C. C. Chan, 2019. "Asymmetric conjugate priors for large Bayesian VARs," CAMA Working Papers 2019-51, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    42. M. Lenza & I. Moutachaker & I. Moutachaker, 2024. "Density forecasts of inflation : a quantile regression forest approach," Documents de Travail de l'Insee - INSEE Working Papers 2024-12, Institut National de la Statistique et des Etudes Economiques.
    43. Joshua C. C. Chan & Gary Koop & Xuewen Yu, 2024. "Large Order-Invariant Bayesian VARs with Stochastic Volatility," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(2), pages 825-837, April.
    44. 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).
    45. Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2016. "Bayesian Compressed Vector Autoregressions," Working Papers 2016_09, Business School - Economics, University of Glasgow.
    46. Antonio Pacifico, 2022. "Structural Compressed Panel VAR with Stochastic Volatility: A Robust Bayesian Model Averaging Procedure," Econometrics, MDPI, vol. 10(3), pages 1-24, July.
    47. Fritsche, Jan Philipp & Klein, Mathias & Rieth, Malte, 2021. "Government spending multipliers in (un)certain times," Journal of Public Economics, Elsevier, vol. 203(C).
    48. Hardik A. Marfatia & Qiang Ji & Jiawen Luo, 2022. "Forecasting the volatility of agricultural commodity futures: The role of co‐volatility and oil volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 383-404, March.
    49. Eric Eisenstat & Joshua C.C. Chan & Rodney W. Strachan, 2018. "Reducing Dimensions in a Large TVP-VAR," Working Paper series 18-37, Rimini Centre for Economic Analysis.
    50. 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.
    51. Uribe Jorge M. & Chuliá Helena, 2023. "Expected, unexpected, good and bad aggregate uncertainty," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(2), pages 265-284, April.
    52. Florian Huber & Tamas Krisztin & Philipp Piribauer, 2014. "Forecasting Global Equity Indices using Large Bayesian VARs," Department of Economics Working Papers wuwp184, Vienna University of Economics and Business, Department of Economics.
    53. 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.
    54. 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.
    55. 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.
    56. Markus Heinrich & Magnus Reif, 2018. "Forecasting using mixed-frequency VARs with time-varying parameters," ifo Working Paper Series 273, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    57. Martin Feldkircher & Florian Huber & Michael Pfarrhofer, 2020. "Measuring the Effectiveness of US Monetary Policy during the COVID-19 Recession," Papers 2007.15419, arXiv.org.
    58. Giannone, Domenico & Banbura, Marta & Lenza, Michele, 2014. "Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections," CEPR Discussion Papers 9931, C.E.P.R. Discussion Papers.
    59. Jamie L. Cross & Chenghan Hou & Aubrey Poon, 2018. "International Transmission of Macroeconomic Uncertainty in Small Open Economies: An Empirical Approach," Working Papers No 12/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    60. Joshua C.C. Chan & Eric Eisenstat & Chenghan Hou & Gary Koop, 2018. "Composite Likelihood Methods for Large Bayesian VARs with Stochastic Volatility," Working Paper Series 44, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
    61. 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.
    62. 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.
    63. 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.
    64. Mark Bognanni & John Zito, 2019. "Sequential Bayesian Inference for Vector Autoregressions with Stochastic Volatility," Working Papers 19-29, Federal Reserve Bank of Cleveland.
    65. Zheng, Tingguo & Ye, Shiqi & Hong, Yongmiao, 2023. "Fast estimation of a large TVP-VAR model with score-driven volatilities," Journal of Economic Dynamics and Control, Elsevier, vol. 157(C).
    66. 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.
    67. 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.
    68. Danilo Cascaldi-Garcia, 2022. "Pandemic Priors," International Finance Discussion Papers 1352, Board of Governors of the Federal Reserve System (U.S.).
    69. Tim Oliver Berg & Steffen Henzel, 2014. "Point and Density Forecasts for the Euro Area Using Bayesian VARs," CESifo Working Paper Series 4711, CESifo.
    70. Cimadomo, Jacopo & Giannone, Domenico & Lenza, Michele & Monti, Francesca & Sokol, Andrej, 2022. "Nowcasting with large Bayesian vector autoregressions," Journal of Econometrics, Elsevier, vol. 231(2), pages 500-519.
    71. Heinrich, Markus, 2020. "Does the Current State of the Business Cycle matter for Real-Time Forecasting? A Mixed-Frequency Threshold VAR approach," EconStor Preprints 219312, ZBW - Leibniz Information Centre for Economics.
    72. 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.
    73. Pettenuzzo, Davide & Timmermann, Allan & Valkanov, Rossen, 2016. "A MIDAS approach to modeling first and second moment dynamics," Journal of Econometrics, Elsevier, vol. 193(2), pages 315-334.
    74. David L. Reifschneider & Peter Tulip, 2017. "Gauging the Uncertainty of the Economic Outlook Using Historical Forecasting Errors : The Federal Reserve's Approach," Finance and Economics Discussion Series 2017-020, Board of Governors of the Federal Reserve System (U.S.).
    75. 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.
    76. Haroon Mumtaz & Laura Sunder-Plassmann & Angeliki Theophilopoulou, 2016. "The State Level Impact of Uncertainty Shocks," Working Papers 793, Queen Mary University of London, School of Economics and Finance.
    77. Kyle Jurado & Sydney C. Ludvigson & Serena Ng, 2015. "Measuring Uncertainty," American Economic Review, American Economic Association, vol. 105(3), pages 1177-1216, March.
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    80. 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.
    81. Cross, Jamie L. & Hou, Chenghan & Koop, Gary & Poon, Aubrey, 2023. "Large stochastic volatility in mean VARs," Journal of Econometrics, Elsevier, vol. 236(1).
    82. Michael Pfarrhofer, 2024. "Forecasts with Bayesian vector autoregressions under real time conditions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(3), pages 771-801, April.
    83. Tsionas, Mike G. & Izzeldin, Marwan & Trapani, Lorenzo, 2022. "Estimation of large dimensional time varying VARs using copulas," European Economic Review, Elsevier, vol. 141(C).
    84. Koop, Gary & Korobilis, Dimitris, 2012. "Large Time-Varying Parameter VARs," SIRE Discussion Papers 2012-14, Scottish Institute for Research in Economics (SIRE).
    85. 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.
    86. Florian Huber & Gary Koop, 2023. "Fast and Order-invariant Inference in Bayesian VARs with Non-Parametric Shocks," Papers 2305.16827, arXiv.org.
    87. Helena Chuliá & Jorge M. Uribe, 2019. "“Expected, Unexpected, Good and Bad Uncertainty"," IREA Working Papers 201919, University of Barcelona, Research Institute of Applied Economics, revised Nov 2019.
    88. 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.
    89. Sebastian Ankargren & Paulina Jon'eus, 2019. "Estimating Large Mixed-Frequency Bayesian VAR Models," Papers 1912.02231, arXiv.org.
    90. Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2017. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," Working Papers 17-15R, Federal Reserve Bank of Cleveland.
    91. Prüser, Jan, 2023. "Data-based priors for vector error correction models," International Journal of Forecasting, Elsevier, vol. 39(1), pages 209-227.
    92. 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.
    93. Simon Beyeler, 2019. "Streamlining Time-varying VAR with a Factor Structure in the Parameters," Working Papers 19.03, Swiss National Bank, Study Center Gerzensee.
    94. 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.
    95. Valeriu Nalban & Andra Smadu, 2020. "Financial disruptions and heightened uncertainty: a case for timely policy action," Working Papers 687, DNB.
    96. Michele Lenza & Giorgio E. Primiceri, 2020. "How to Estimate a VAR after March 2020," NBER Working Papers 27771, National Bureau of Economic Research, Inc.
    97. 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.
    98. Luo, Jiawen & Marfatia, Hardik A. & Ji, Qiang & Klein, Tony, 2023. "Co-volatility and asymmetric transmission of risks between the global oil and China's futures markets," Energy Economics, Elsevier, vol. 117(C).
    99. Nalban, Valeriu & Smădu, Andra, 2021. "Asymmetric effects of uncertainty shocks: Normal times and financial disruptions are different," Journal of Macroeconomics, Elsevier, vol. 69(C).
    100. Gong, Xiao-Li & Liu, Xi-Hua & Xiong, Xiong & Zhuang, Xin-Tian, 2019. "Non-Gaussian VARMA model with stochastic volatility and applications in stock market bubbles," Chaos, Solitons & Fractals, Elsevier, vol. 121(C), pages 129-136.
    101. 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.
    102. 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).
    103. Jonas E. Arias & Juan F. Rubio-Ramirez & Minchul Shin, 2021. "Macroeconomic Forecasting and Variable Ordering in Multivariate Stochastic Volatility Models," Working Papers 21-21, Federal Reserve Bank of Philadelphia.
    104. Todd E. Clark & Francesco Ravazzolo, 2012. "The macroeconomic forecasting performance of autoregressive models with alternative specifications of time-varying volatility," Working Paper 2012/09, Norges Bank.
    105. 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).
    106. 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.
    107. 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.
    108. 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.
    109. Barbara Rossi, 2019. "Identifying and Estimating the Effects of Unconventional Monetary Policy in the Data: How to Do It and What Have We Learned?," Working Papers 1081, Barcelona School of Economics.
    110. Fu, Bowen, 2023. "Measuring the trend real interest rate in a data-rich environment," Journal of Economic Dynamics and Control, Elsevier, vol. 147(C).
    111. 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.
    112. 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.
    113. 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.
    114. Paul Labonne, 2020. "Asymmetric uncertainty : Nowcasting using skewness in real-time data," Papers 2012.02601, arXiv.org, revised May 2024.
    115. 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.
    116. Haroon Mumtaz, 2020. "A Generalised Stochastic Volatility in Mean VAR. An Updated Algorithm," Working Papers 908, Queen Mary University of London, School of Economics and Finance.
    117. Follett, Lendie & Yu, Cindy, 2019. "Achieving parsimony in Bayesian vector autoregressions with the horseshoe prior," Econometrics and Statistics, Elsevier, vol. 11(C), pages 130-144.
    118. 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.
    119. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2016. "Large Vector Autoregressions with Stochastic Volatility and Flexible Priors," Working Papers (Old Series) 1617, Federal Reserve Bank of Cleveland.
    120. Stefan Griller & Florian Huber & Michael Pfarrhofer, 2022. "Measuring Shocks to Central Bank Independence using Legal Rulings," Papers 2202.12695, arXiv.org.
    121. 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.
    122. 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.
    123. Carriero, Andrea & Mumtaz, Haroon & Theophilopoulou, Angeliki, 2015. "Macroeconomic information, structural change, and the prediction of fiscal aggregates," International Journal of Forecasting, Elsevier, vol. 31(2), pages 325-348.
    124. Hartwig, Benny, 2022. "Bayesian VARs and prior calibration in times of COVID-19," Discussion Papers 52/2022, Deutsche Bundesbank.
    125. 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.
    126. Thomas B Götz & Klemens Hauzenberger, 2021. "Large mixed-frequency VARs with a parsimonious time-varying parameter structure," The Econometrics Journal, Royal Economic Society, vol. 24(3), pages 442-461.
    127. Jamie L. Cross & Aubrey Poon, 2020. "On the contribution of international shocks in Australian business cycle fluctuations," Empirical Economics, Springer, vol. 59(6), pages 2613-2637, December.
    128. Andrea Carriero & Francesco Corsello & Massimiliano Marcellino, 2020. "The economic drivers of volatility and uncertainty," Temi di discussione (Economic working papers) 1285, Bank of Italy, Economic Research and International Relations Area.
    129. Reifschneider, David & Tulip, Peter, 2019. "Gauging the uncertainty of the economic outlook using historical forecasting errors: The Federal Reserve’s approach," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1564-1582.
    130. Paul Labonne, 2022. "Asymmetric Uncertainty: Nowcasting Using Skewness in Real-time Data," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-23, Economic Statistics Centre of Excellence (ESCoE).
    131. 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.
    132. Matteo Iacopini & Francesco Ravazzolo & Luca Rossini, 2022. "Bayesian Multivariate Quantile Regression with alternative Time-varying Volatility Specifications," Papers 2211.16121, arXiv.org, revised Aug 2024.
    133. 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.

  28. Todd E. Clark & Francesco Ravazzolo, 2012. "The macroeconomic forecasting performance of autoregressive models with alternative specifications of time-varying volatility," Working Paper 2012/09, Norges Bank.

    Cited by:

    1. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2012. "Time-varying Combinations of Predictive Densities using Nonlinear Filtering," Tinbergen Institute Discussion Papers 12-118/III, Tinbergen Institute.
    2. Benjamin K. Johannsen & Elmar Mertens, 2016. "A Time Series Model of Interest Rates With the Effective Lower Bound," Finance and Economics Discussion Series 2016-033, Board of Governors of the Federal Reserve System (U.S.).
    3. Petrella, Ivan & Delle Monache, Davide, 2016. "Adaptive models and heavy tails," Bank of England working papers 577, Bank of England.
    4. Bjørnland, Hilde C. & Ravazzolo, Francesco & Thorsrud, Leif Anders, 2017. "Forecasting GDP with global components: This time is different," International Journal of Forecasting, Elsevier, vol. 33(1), pages 153-173.
    5. Pami Dua, 2023. "Macroeconomic Modelling and Bayesian Methods," Springer Books, in: Pami Dua (ed.), Macroeconometric Methods, chapter 0, pages 19-37, Springer.
    6. 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.
    7. Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2014. "Density forecasts with MIDAS models," Working Paper 2014/10, Norges Bank.
    8. Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2013. "Parallel Sequential Monte Carlo for Efficient Density Combination: The Deco Matlab Toolbox," CREATES Research Papers 2013-09, Department of Economics and Business Economics, Aarhus University.
    9. Fabian Kr ger & Todd E. Clark & Francesco Ravazzolo, 2015. "Using Entropic Tilting to Combine BVAR Forecasts with External Nowcasts," Working Papers No 8/2015, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    10. José Antonio Gibanel Salazar, 2014. "Economic models: comparative analysis of their adjustment and prediction capacities," Contribuciones a la Economía, Servicios Académicos Intercontinentales SL, issue 2014-05, November.
    11. Roberto Casarin & Marco Tronzano & Domenico Sartore, 2013. "Bayesian Markov Switching Stochastic Correlation Models," Working Papers 2013:11, Department of Economics, University of Venice "Ca' Foscari".
    12. Mihaela Bratu, 2012. "A Strategy to Improve the Survey of Professional Forecasters (SPF) Predictions Using Bias-Corrected-Accelerated (BCA) Bootstrap Forecast Intervals," International Journal of Synergy and Research, ToKnowPress, vol. 1(2), pages 45-59.
    13. Awijen, Haithem & Ben Zaied, Younes & Nguyen, Duc Khuong & Sensoy, Ahmet, 2020. "Endogenous Financial Uncertainty and Macroeconomic Volatility: Evidence from the United States," MPRA Paper 101276, University Library of Munich, Germany, revised Jun 2020.

  29. Todd E. Clark & Michael W. McCracken, 2011. "Tests of equal forecast accuracy for overlapping models," Working Papers (Old Series) 1121, Federal Reserve Bank of Cleveland.

    Cited by:

    1. Corradi, Valentina & Fosten, Jack & Gutknecht, Daniel, 2024. "Predictive ability tests with possibly overlapping models," Journal of Econometrics, Elsevier, vol. 241(1).
    2. Corradi, Valentina & Fosten, Jack & Gutknecht, Daniel, 2023. "Out-of-sample tests for conditional quantile coverage an application to Growth-at-Risk," Journal of Econometrics, Elsevier, vol. 236(2).
    3. Atsushi Inoue & Barbara Rossi, 2011. "Out-of-sample forecast tests robust to the choice of window size," Working Papers 11-31, Federal Reserve Bank of Philadelphia.
    4. Firmin Doko Tchatoka & Qazi Haque, 2020. "On bootstrapping tests of equal forecast accuracy for nested models," School of Economics and Public Policy Working Papers 2020-03, University of Adelaide, School of Economics and Public Policy.
    5. T. S. McElroy, 2016. "Nonnested model comparisons for time series," Biometrika, Biometrika Trust, vol. 103(4), pages 905-914.
    6. Mayer, Walter J. & Liu, Feng & Dang, Xin, 2017. "Improving the power of the Diebold–Mariano–West test for least squares predictions," International Journal of Forecasting, Elsevier, vol. 33(3), pages 618-626.
    7. Isao Ishida & Virmantas Kvedaras, 2015. "Modeling Autoregressive Processes with Moving-Quantiles-Implied Nonlinearity," Econometrics, MDPI, vol. 3(1), pages 1-53, January.
    8. Brent Meyer & Saeed Zaman, 2013. "It’s not just for inflation: The usefulness of the median CPI in BVAR forecasting," Working Papers (Old Series) 1303, Federal Reserve Bank of Cleveland.

  30. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2011. "Bayesian VARs: Specification Choices and Forecast Accuracy," CEPR Discussion Papers 8273, C.E.P.R. Discussion Papers.

    Cited by:

    1. Milas, Costas & Panagiotidis, Theodore & Papapanagiotou, Georgios, 2024. "UK Foreign Direct Investment in uncertain economic times," Journal of International Money and Finance, Elsevier, vol. 147(C).
    2. Joshua C.C. Chan & Eric Eisenstat & Gary Koop, 2014. "Large Bayesian VARMAs," Working Paper series 40_14, Rimini Centre for Economic Analysis.
    3. Cascaldi-Garcia, Danilo, 2017. "News Shocks and the Slope of the Term Structure of Interest Rates : Comment," EMF Research Papers 15, Economic Modelling and Forecasting Group.
    4. Ashwin Madhou & Tayushma Sewak & Imad Moosa & Vikash Ramiah, 2017. "GDP nowcasting: application and constraints in a small open developing economy," Applied Economics, Taylor & Francis Journals, vol. 49(38), pages 3880-3890, August.
    5. Carriero, Andrea & Galvão, Ana Beatriz & Kapetanios, George, 2019. "A comprehensive evaluation of macroeconomic forecasting methods," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1226-1239.
    6. Joshua C. C. Chan, 2022. "Comparing Stochastic Volatility Specifications for Large Bayesian VARs," Papers 2208.13255, arXiv.org.
    7. Koop, Gary & Korobilis, Dimitris, 2016. "Model uncertainty in Panel Vector Autoregressive models," European Economic Review, Elsevier, vol. 81(C), pages 115-131.
    8. Mokinski, Frieder, 2017. "A severity function approach to scenario selection," Discussion Papers 34/2017, Deutsche Bundesbank.
    9. Knotek, Edward S. & Zaman, Saeed, 2019. "Financial nowcasts and their usefulness in macroeconomic forecasting," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1708-1724.
    10. Hashmat Khan & Santosh Upadhayaya, 2017. "Does Business Confidence Matter for Investment?," Carleton Economic Papers 17-13, Carleton University, Department of Economics, revised 20 Mar 2019.
    11. James Morley & Benjamin Wong, 2020. "Estimating and accounting for the output gap with large Bayesian vector autoregressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 1-18, January.
    12. Berg, Tim Oliver & Henzel, Steffen, 2013. "Point and Density Forecasts for the Euro Area Using Many Predictors: Are Large BVARs Really Superior?," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79783, Verein für Socialpolitik / German Economic Association.
    13. Mike Tsionas & Marwan Izzeldin & Lorenzo Trapani, 2019. "Bayesian estimation of large dimensional time varying VARs using copulas," Papers 1912.12527, arXiv.org.
    14. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015. "Realtime nowcasting with a Bayesian mixed frequency model with stochastic volatility," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(4), pages 837-862, October.
    15. Moramarco, Graziano, 2024. "Financial-cycle ratios and medium-term predictions of GDP: Evidence from the United States," International Journal of Forecasting, Elsevier, vol. 40(2), pages 777-795.
    16. Joohun Han & John N. Ng’ombe, 2023. "The relation between wheat, soybean, and hemp acreage: a Bayesian time series analysis," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 11(1), pages 1-12, December.
    17. Gary Koop, 2013. "Using VARs and TVP-VARs with Many Macroeconomic Variables," Working Papers 1303, University of Strathclyde Business School, Department of Economics.
    18. Florian Huber & Gary Koop, 2021. "Subspace Shrinkage in Conjugate Bayesian Vector Autoregressions," Papers 2107.07804, arXiv.org.
    19. Baumeister, Christiane & Korobilis, Dimitris & Lee, Thomas K., 2020. "Energy Markets and Global Economic Conditions," CEPR Discussion Papers 14580, C.E.P.R. Discussion Papers.
    20. 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.
    21. Marcus P. A. Cobb, 2020. "Aggregate density forecasting from disaggregate components using Bayesian VARs," Empirical Economics, Springer, vol. 58(1), pages 287-312, January.
    22. Barnett, Alina & Mumtaz, Haroon & Theodoridis, Konstantinos, 2014. "Forecasting UK GDP growth and inflation under structural change. A comparison of models with time-varying parameters," International Journal of Forecasting, Elsevier, vol. 30(1), pages 129-143.
    23. 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.
    24. Ralf Brüggemann & Christian Kascha, 2017. "Directed Graphs and Variable Selection in Large Vector Autoregressive Models," Working Paper Series of the Department of Economics, University of Konstanz 2017-06, Department of Economics, University of Konstanz.
    25. Kenneth Beauchemin & Saeed Zaman, 2011. "A medium scale forecasting model for monetary policy," Working Papers (Old Series) 1128, Federal Reserve Bank of Cleveland.
    26. Andrea Carriero & Davide Pettenuzzo & Shubhranshu Shekhar, 2024. "Macroeconomic Forecasting with Large Language Models," Papers 2407.00890, arXiv.org.
    27. 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.
    28. 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.
    29. Joshua C.C. Chan & Xuewen Yu, 2020. "Fast and accurate variational inference for large Bayesian VARs with stochastic volatility," CAMA Working Papers 2020-108, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    30. Monica Billio & Roberto Casarin & Luca Rossini, 2016. "Bayesian nonparametric sparse VAR models," Papers 1608.02740, arXiv.org, revised Oct 2018.
    31. Демешев Борис Борисович & Малаховская Оксана Анатольевна, 2016. "Макроэкономическое Прогнозирование С Помощью Bvar Литтермана," Higher School of Economics Economic Journal Экономический журнал Высшей школы экономики, CyberLeninka;Федеральное государственное автономное образовательное учреждение высшего образования «Национальный исследовательский университет «Высшая школа экономики», vol. 20(4), pages 691-710.
    32. Joshua C. C. Chan, 2019. "Asymmetric conjugate priors for large Bayesian VARs," CAMA Working Papers 2019-51, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    33. Kascha, Christian & Trenkler, Carsten, 2015. "Forecasting VARs, model selection, and shrinkage," Working Papers 15-07, University of Mannheim, Department of Economics.
    34. Simone Emiliozzi & Elisa Guglielminetti & Michele Loberto, 2018. "Forecasting house prices in Italy," Questioni di Economia e Finanza (Occasional Papers) 463, Bank of Italy, Economic Research and International Relations Area.
    35. Antonio Pacifico, 2022. "Structural Compressed Panel VAR with Stochastic Volatility: A Robust Bayesian Model Averaging Procedure," Econometrics, MDPI, vol. 10(3), pages 1-24, July.
    36. Jean Boivin & Marc P. Giannoni & Dalibor Stevanovic, 2013. "Dynamic Effects of Credit Shocks in a Data-Rich Environment," CIRANO Working Papers 2013s-11, CIRANO.
    37. Carriero, Andrea & Kapetanios, George & Marcellino, Massimiliano, 2012. "Forecasting government bond yields with large Bayesian vector autoregressions," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 2026-2047.
    38. Rachidi Kotchoni & Maxime Leroux & Dalibor Stevanovic, 2019. "Macroeconomic Forecast Accuracy in data-rich environment," Post-Print hal-02435757, HAL.
    39. Demeshev, Boris & Malakhovskaya, Oxana, 2016. "BVAR mapping," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 43, pages 118-141.
    40. Danilo Cascaldi-Garcia & Ana Beatriz Galvao, 2018. "News and Uncertainty Shocks," International Finance Discussion Papers 1240, Board of Governors of the Federal Reserve System (U.S.).
    41. 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.
    42. Salzmann, Leonard, 2020. "The Impact of Uncertainty and Financial Shocks in Recessions and Booms," VfS Annual Conference 2020 (Virtual Conference): Gender Economics 224588, Verein für Socialpolitik / German Economic Association.
    43. Anna Staszewska-Bystrova & Peter Winker, 2014. "Measuring Forecast Uncertainty of Corporate Bond Spreads by Bonferroni-Type Prediction Bands," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 6(2), pages 89-104, June.
    44. Anna Sznajderska & Alfred A. Haug, 2023. "Bayesian VARs of the U.S. economy before and during the pandemic," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 13(2), pages 211-236, June.
    45. Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2017. "Macroeconomic nowcasting and forecasting with big data," Staff Reports 830, Federal Reserve Bank of New York.
    46. 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.
    47. Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio, 2012. "Prior Selection for Vector Autoregressions," CEPR Discussion Papers 8755, C.E.P.R. Discussion Papers.
    48. Dellaportas, Petros & Tsionas, Mike G., 2019. "Importance sampling from posterior distributions using copula-like approximations," Journal of Econometrics, Elsevier, vol. 210(1), pages 45-57.
    49. Bacchiocchi, Emanuele & Bastianin, Andrea & Missale, Alessandro & Rossi, Eduardo, 2020. "Structural analysis with mixed-frequency data: A model of US capital flows," Economic Modelling, Elsevier, vol. 89(C), pages 427-443.
    50. Higgins, Patrick & Zha, Tao & Zhong, Wenna, 2016. "Forecasting China's economic growth and inflation," China Economic Review, Elsevier, vol. 41(C), pages 46-61.
    51. Paul Ho, 2020. "Global Robust Bayesian Analysis in Large Models," Working Paper 20-07, Federal Reserve Bank of Richmond.
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    1. Michael Dotsey & Shigeru Fujita & Tom Stark, 2018. "Do Phillips Curves Conditionally Help to Forecast Inflation?," International Journal of Central Banking, International Journal of Central Banking, vol. 14(4), pages 43-92, September.
    2. Brent Meyer & Guhan Venkatu, 2012. "Trimmed-mean inflation statistics: just hit the one in the middle," Working Papers (Old Series) 1217, Federal Reserve Bank of Cleveland.
    3. Krüger, Fabian & Nolte, Ingmar, 2016. "Disagreement versus uncertainty: Evidence from distribution forecasts," Journal of Banking & Finance, Elsevier, vol. 72(S), pages 172-186.
    4. Jiahan Li & Ilias Tsiakas & Wei Wang, 2015. "Predicting Exchange Rates Out of Sample: Can Economic Fundamentals Beat the Random Walk?," Journal of Financial Econometrics, Oxford University Press, vol. 13(2), pages 293-341.
    5. Carriero, Andrea & Galvão, Ana Beatriz & Kapetanios, George, 2019. "A comprehensive evaluation of macroeconomic forecasting methods," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1226-1239.
    6. Altug, Sumru & Çakmaklı, Cem, 2016. "Forecasting inflation using survey expectations and target inflation: Evidence for Brazil and Turkey," International Journal of Forecasting, Elsevier, vol. 32(1), pages 138-153.
    7. Yin, Anwen, 2015. "Forecasting and model averaging with structural breaks," ISU General Staff Papers 201501010800005727, Iowa State University, Department of Economics.
    8. Mathijs Cosemans & Rik Frehen & Peter C. Schotman & Rob Bauer, 2016. "Estimating Security Betas Using Prior Information Based on Firm Fundamentals," The Review of Financial Studies, Society for Financial Studies, vol. 29(4), pages 1072-1112.
    9. Galvão, Ana Beatriz, 2013. "Changes in predictive ability with mixed frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 395-410.
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    11. Anwen Yin, 2022. "Does the kitchen‐sink model work forecasting the equity premium?," International Review of Finance, International Review of Finance Ltd., vol. 22(1), pages 223-247, March.
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    23. Lafond, François & Bailey, Aimee Gotway & Bakker, Jan David & Rebois, Dylan & Zadourian, Rubina & McSharry, Patrick & Farmer, J. Doyne, 2018. "How well do experience curves predict technological progress? A method for making distributional forecasts," Technological Forecasting and Social Change, Elsevier, vol. 128(C), pages 104-117.
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    26. Ayse Kabukcuoglu & Enrique Martínez-García, 2016. "What Helps Forecast U.S. Inflation?—Mind the Gap!," Koç University-TUSIAD Economic Research Forum Working Papers 1615, Koc University-TUSIAD Economic Research Forum.
    27. Carlos Medel, 2015. "Inflation Dynamics and the Hybrid Neo Keynesian Phillips Curve: The Case of Chile," Working Papers Central Bank of Chile 769, Central Bank of Chile.
    28. Fabio Busetti & Juri Marcucci & Giovanni Veronese, 2009. "Comparing forecast accuracy: A Monte Carlo investigation," Temi di discussione (Economic working papers) 723, Bank of Italy, Economic Research and International Relations Area.
    29. Ahmed, Shamim & Liu, Xiaoquan & Valente, Giorgio, 2016. "Can currency-based risk factors help forecast exchange rates?," International Journal of Forecasting, Elsevier, vol. 32(1), pages 75-97.
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    31. Engelke, Carola & Heinisch, Katja & Schult, Christoph, 2019. "How forecast accuracy depends on conditioning assumptions," IWH Discussion Papers 18/2019, Halle Institute for Economic Research (IWH).
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    33. Meyler, Aidan & Grothe, Magdalena, 2015. "Inflation forecasts: Are market-based and survey-based measures informative?," Working Paper Series 1865, European Central Bank.
    34. Kiss, Tamás & Nguyen, Hoang & Österholm, Pär, 2020. "Modelling Returns in US Housing Prices – You’re the One for Me, Fat Tails," Working Papers 2020:13, Örebro University, School of Business.
    35. Pablo Pincheira Brown & Nicolás Hardy, 2024. "Correlation‐based tests of predictability," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 1835-1858, September.
    36. Helena Chuliá & Ignacio Garrón & Jorge M. Uribe, 2022. ""Daily Growth at Risk: financial or real drivers? The answer is not always the same"," IREA Working Papers 202208, University of Barcelona, Research Institute of Applied Economics, revised Jun 2022.
    37. Ahmed, Shamim & Tsvetanov, Daniel, 2016. "The predictive performance of commodity futures risk factors," Journal of Banking & Finance, Elsevier, vol. 71(C), pages 20-36.
    38. Atsushi Inoue & Barbara Rossi, 2011. "Out-of-sample forecast tests robust to the choice of window size," Working Papers 11-31, Federal Reserve Bank of Philadelphia.
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    41. Groen, Jan J.J. & Kapetanios, George, 2016. "Revisiting useful approaches to data-rich macroeconomic forecasting," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 221-239.
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    44. Jonathan H. Wright, 2015. "Comment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(1), pages 12-13, January.
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    46. Boot, Tom & Pick, Andreas, 2020. "Does modeling a structural break improve forecast accuracy?," Journal of Econometrics, Elsevier, vol. 215(1), pages 35-59.
    47. Rodrigo Sekkel, 2014. "Balance Sheets of Financial Intermediaries: Do They Forecast Economic Activity?," Staff Working Papers 14-40, Bank of Canada.
    48. Nima Nonejad, 2022. "New Findings Regarding the Out-of-Sample Predictive Impact of the Price of Crude Oil on the United States Industrial Production," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 18(1), pages 1-35, March.
    49. Gagnon, Marie-Hélène & Power, Gabriel J. & Toupin, Dominique, 2023. "The sum of all fears: Forecasting international returns using option-implied risk measures," Journal of Banking & Finance, Elsevier, vol. 146(C).
    50. Nicolas S. Magner & Nicolás Hardy & Tiago Ferreira & Jaime F. Lavin, 2023. "“Agree to Disagree”: Forecasting Stock Market Implied Volatility Using Financial Report Tone Disagreement Analysis," Mathematics, MDPI, vol. 11(7), pages 1-16, March.
    51. Francesco Ravazzolo & Philip Rothman, 2011. "Oil and US GDP: A Real-Time out-of Sample Examination," Working Papers No 2/2011, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    52. Fabian Kr ger & Todd E. Clark & Francesco Ravazzolo, 2015. "Using Entropic Tilting to Combine BVAR Forecasts with External Nowcasts," Working Papers No 8/2015, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
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    54. 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.
    55. Tunaru, Diana, 2017. "Gaussian estimation and forecasting of the U.K. yield curve with multi-factor continuous-time models," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 119-129.
    56. Papantonis, Ioannis & Rompolis, Leonidas & Tzavalis, Elias, 2023. "Improving variance forecasts: The role of Realized Variance features," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1221-1237.
    57. Michael P Clements & Ana Beatriz Galvao, 2017. "Data Revisions and Real-time Probabilistic Forecasting of Macroeconomic Variables," ICMA Centre Discussion Papers in Finance icma-dp2017-01, Henley Business School, University of Reading.
    58. Mayer, Walter J. & Liu, Feng & Dang, Xin, 2017. "Improving the power of the Diebold–Mariano–West test for least squares predictions," International Journal of Forecasting, Elsevier, vol. 33(3), pages 618-626.
    59. Håvard Hungnes, 2020. "Predicting the exchange rate path. The importance of using up-to-date observations in the forecasts," Discussion Papers 934, Statistics Norway, Research Department.
    60. Catherine L. Kling & Raymond W. Arritt & Gray Calhoun & David A. Keiser, 2017. "Integrated Assessment Models of the Food, Energy, and Water Nexus: A Review and an Outline of Research Needs," Annual Review of Resource Economics, Annual Reviews, vol. 9(1), pages 143-163, October.
    61. Boneva, Lena & Fawcett, Nicholas & Masolo, Riccardo M. & Waldron, Matt, 2019. "Forecasting the UK economy: Alternative forecasting methodologies and the role of off-model information," International Journal of Forecasting, Elsevier, vol. 35(1), pages 100-120.
    62. Stephen McKnight & Alexander Mihailov & Fabio Rumler, 2018. "NKPC-Based Inflation Forecasts with a Time-Varying Trend," Serie documentos de trabajo del Centro de Estudios Económicos 2018-05, El Colegio de México, Centro de Estudios Económicos.
    63. Nima Nonejad, 2020. "A detailed look at crude oil price volatility prediction using macroeconomic variables," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1119-1141, November.
    64. Costantini, Mauro & Kunst, Robert M., 2021. "On using predictive-ability tests in the selection of time-series prediction models: A Monte Carlo evaluation," International Journal of Forecasting, Elsevier, vol. 37(2), pages 445-460.
    65. Kurmaş Akdoğan, 2019. "Size and sign asymmetries in house price adjustments," Applied Economics, Taylor & Francis Journals, vol. 51(48), pages 5268-5281, October.
    66. Wada, Tatsuma, 2022. "Out-of-sample forecasting of foreign exchange rates: The band spectral regression and LASSO," Journal of International Money and Finance, Elsevier, vol. 128(C).
    67. Dichtl, Hubert & Drobetz, Wolfgang & Neuhierl, Andreas & Wendt, Viktoria-Sophie, 2021. "Data snooping in equity premium prediction," International Journal of Forecasting, Elsevier, vol. 37(1), pages 72-94.
    68. Dimitrios P. Louzis, 2017. "Macroeconomic and credit forecasts during the Greek crisis using Bayesian VARs," Empirical Economics, Springer, vol. 53(2), pages 569-598, September.
    69. Clark, Todd E. & Doh, Taeyoung, 2014. "Evaluating alternative models of trend inflation," International Journal of Forecasting, Elsevier, vol. 30(3), pages 426-448.
    70. Todd E. Clark & Taeyoung Doh, 2011. "A Bayesian evaluation of alternative models of trend inflation," Research Working Paper RWP 11-16, Federal Reserve Bank of Kansas City.
    71. Fabian Krüger & Sebastian Lerch & Thordis Thorarinsdottir & Tilmann Gneiting, 2021. "Predictive Inference Based on Markov Chain Monte Carlo Output," International Statistical Review, International Statistical Institute, vol. 89(2), pages 274-301, August.
    72. Petri Kuosmanen & Juuso Vataja, 2017. "The return of financial variables in forecasting GDP growth in the G-7," Economic Change and Restructuring, Springer, vol. 50(3), pages 259-277, August.
    73. Guizzardi, Andrea & Pons, Flavio Maria Emanuele & Angelini, Giovanni & Ranieri, Ercolino, 2021. "Big data from dynamic pricing: A smart approach to tourism demand forecasting," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1049-1060.
    74. Daniel Borup & Jonas N. Eriksen & Mads M. Kjær & Martin Thyrsgaard, 2024. "Predicting Bond Return Predictability," Management Science, INFORMS, vol. 70(2), pages 931-951, February.
    75. Guizzardi, Andrea & Stacchini, Annalisa, 2015. "Real-time forecasting regional tourism with business sentiment surveys," Tourism Management, Elsevier, vol. 47(C), pages 213-223.
    76. McGurk, Zachary, 2020. "US real estate inflation prediction: Exchange rates and net foreign assets," The Quarterly Review of Economics and Finance, Elsevier, vol. 75(C), pages 53-66.
    77. Duffee, Gregory, 2013. "Forecasting Interest Rates," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 385-426, Elsevier.
    78. David I. Harvey & Stephen J. Leybourne & Emily J. Whitehouse, 2017. "Forecast evaluation tests and negative long-run variance estimates in small samples," Discussion Papers 17/03, University of Nottingham, Granger Centre for Time Series Econometrics.
    79. Antolín-Díaz, Juan & Drechsel, Thomas & Petrella, Ivan, 2024. "Advances in nowcasting economic activity: The role of heterogeneous dynamics and fat tails," Journal of Econometrics, Elsevier, vol. 238(2).
    80. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2021. "Time-Varying Comovement of Foreign Exchange Markets: A GLS-Based Time-Varying Model Approach," Mathematics, MDPI, vol. 9(8), pages 1-13, April.
    81. Anwen Yin, 2021. "Forecasting the Market Equity Premium: Does Nonlinearity Matter?," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 13(5), pages 1-9, May.
    82. Francis X. Diebold, 2012. "Comparing Predictive Accuracy, Twenty Years Later: A Personal Perspective on the Use and Abuse of Diebold-Mariano Tests," NBER Working Papers 18391, National Bureau of Economic Research, Inc.
    83. Chalmovianský, Jakub & Porqueddu, Mario & Sokol, Andrej, 2020. "Weigh(t)ing the basket: aggregate and component-based inflation forecasts for the euro area," Working Paper Series 2501, European Central Bank.
    84. Brent Meyer & Saeed Zaman, 2016. "The Usefulness of the Median CPI in Bayesian VARs Used for Macroeconomic Forecasting and Policy," FRB Atlanta Working Paper 2016-13, Federal Reserve Bank of Atlanta.
    85. Federico D'Amario & Milos Ciganovic, 2022. "Forecasting Cryptocurrencies Log-Returns: a LASSO-VAR and Sentiment Approach," Papers 2210.00883, arXiv.org.
    86. Petrella, Ivan & Antolin-Diaz, Juan & Drechsel, Thomas, 2021. "Advances in Nowcasting Economic Activity: Secular Trends, Large Shocks and New Data," CEPR Discussion Papers 15926, C.E.P.R. Discussion Papers.
    87. Ziegel, Johanna F. & Krueger, Fabian & Jordan, Alexander & Fasciati, Fernando, 2017. "Murphy Diagrams: Forecast Evaluation of Expected Shortfall," Working Papers 0632, University of Heidelberg, Department of Economics.
    88. Zhu, Yinchu & Timmermann, Allan, 2022. "Conditional rotation between forecasting models," Journal of Econometrics, Elsevier, vol. 231(2), pages 329-347.
    89. Johanna F. Ziegel & Fabian Kruger & Alexander Jordan & Fernando Fasciati, 2017. "Murphy Diagrams: Forecast Evaluation of Expected Shortfall," Papers 1705.04537, arXiv.org.
    90. Valentina Corradi & Sainan Jin & Norman R. Swanson, 2023. "Robust forecast superiority testing with an application to assessing pools of expert forecasters," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 596-622, June.
    91. Carriero, Andrea & Mumtaz, Haroon & Theophilopoulou, Angeliki, 2015. "Macroeconomic information, structural change, and the prediction of fiscal aggregates," International Journal of Forecasting, Elsevier, vol. 31(2), pages 325-348.
    92. Yin, Anwen, 2019. "Out-of-sample equity premium prediction in the presence of structural breaks," International Review of Financial Analysis, Elsevier, vol. 65(C).
    93. Mauersberger, Felix, 2019. "Thompson Sampling: Endogenously Random Behavior in Games and Markets," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203600, Verein für Socialpolitik / German Economic Association.
    94. Laura Coroneo & Fabrizio Iacone & Alessia Paccagnini & Paulo Santos Monteiro, 2020. "Testing the predictive accuracy of COVID-19 forecasts," Discussion Papers 20/10, Department of Economics, University of York.
    95. Jean-Yves Pitarakis, 2020. "A Novel Approach to Predictive Accuracy Testing in Nested Environments," Papers 2008.08387, arXiv.org, revised Oct 2023.
    96. Jamali, Ibrahim & Yamani, Ehab, 2019. "Out-of-sample exchange rate predictability in emerging markets: Fundamentals versus technical analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 241-263.
    97. Jin, Sainan & Corradi, Valentina & Swanson, Norman R., 2017. "Robust Forecast Comparison," Econometric Theory, Cambridge University Press, vol. 33(6), pages 1306-1351, December.
    98. Pablo Pincheira & Nicolás Hardy & Felipe Muñoz, 2021. "“Go Wild for a While!”: A New Test for Forecast Evaluation in Nested Models," Mathematics, MDPI, vol. 9(18), pages 1-28, September.
    99. Laura Coroneo & Fabrizio Iacone, 2020. "Comparing predictive accuracy in small samples using fixed‐smoothing asymptotics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(4), pages 391-409, June.
    100. Håvard Hungnes, 2020. "Equal predictability test for multi-step-ahead system forecasts invariant to linear transformations," Discussion Papers 931, Statistics Norway, Research Department.
    101. Timmermann, Allan & Zhu, Yinchu, 2021. "Conditional Rotation Between Forecasting Models," CEPR Discussion Papers 15917, C.E.P.R. Discussion Papers.
    102. Arai, Natsuki, 2014. "Using forecast evaluation to improve the accuracy of the Greenbook forecast," International Journal of Forecasting, Elsevier, vol. 30(1), pages 12-19.
    103. Hinterlang, Natascha, 2019. "Predicting Monetary Policy Using Artificial Neural Networks," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203503, Verein für Socialpolitik / German Economic Association.
    104. Laura Coroneo & Fabrizio Iacone, 2015. "Comparing predictive accuracy in small samples," Discussion Papers 15/15, Department of Economics, University of York.

  32. 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.

    Cited by:

    1. Christine Garnier & Elmar Mertens & Edward Nelson, 2013. "Trend inflation in advanced economies," Finance and Economics Discussion Series 2013-74, Board of Governors of the Federal Reserve System (U.S.).
    2. Petrella, Ivan & Delle Monache, Davide, 2016. "Adaptive models and heavy tails," Bank of England working papers 577, Bank of England.
    3. Emmanuel O. Akande & Elijah O. Akanni & Oyedamola F. Taiwo & Jeremiah D. Joshua & Abel Anthony, 2023. "Predicting inflation component drivers in Nigeria: a stacked ensemble approach," SN Business & Economics, Springer, vol. 3(1), pages 1-32, January.
    4. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
    5. Joshua C C Chan & Gary Koop & Simon M Potter, 2012. "A New Model of Trend Inflation," CAMA Working Papers 2012-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    6. Sohei Kaihatsu & Jouchi Nakajima, 2015. "Has Trend Inflation Shifted?: An Empirical Analysis with a Regime-Switching Model," Bank of Japan Working Paper Series 15-E-3, Bank of Japan.
    7. Deborah Gefang & Gary Koop & Simon M. Potter, 2009. "The Dynamics of UK and US Inflation Expectations," Working Paper series 14_09, Rimini Centre for Economic Analysis.
    8. Henzel, Steffen R., 2013. "Fitting survey expectations and uncertainty about trend inflation," Journal of Macroeconomics, Elsevier, vol. 35(C), pages 172-185.
    9. Taeyoung Doh, 2011. "Is unemployment helpful in understanding inflation?," Economic Review, Federal Reserve Bank of Kansas City, vol. 96(Q IV), pages 5-26.
    10. 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.
    11. 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.
    12. 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.

  33. Todd E. Clark & Michael W. McCracken, 2010. "Reality checks and nested forecast model comparisons," Working Papers 2010-032, Federal Reserve Bank of St. Louis.

    Cited by:

    1. Kirstin Hubrich & Kenneth D. West, 2008. "Forecast Evaluation of Small Nested Model Sets," NBER Working Papers 14601, National Bureau of Economic Research, Inc.
    2. Atsushi Inoue & Barbara Rossi, 2011. "Out-of-sample forecast tests robust to the choice of window size," Working Papers 11-31, Federal Reserve Bank of Philadelphia.

  34. Todd E. Clark & Michael W. McCracken, 2010. "Testing for unconditional predictive ability," Working Papers 2010-031, Federal Reserve Bank of St. Louis.

    Cited by:

    1. Santiago Cajiao Raigosa & Luis Fernando Melo Velandia & Daniel Parra Amado, 2014. "Pronósticos para una economía menos volátil: El caso colombiano," Borradores de Economia 821, Banco de la Republica de Colombia.
    2. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
    3. Andrea CARRIERO & Todd E. CLARK & Massimiliano MARCELLINO, 2012. "Common Drifting Volatility in Large Bayesian VARs," Economics Working Papers ECO2012/08, European University Institute.
    4. Francesco Ravazzolo & Philip Rothman, 2011. "Oil and US GDP: A Real-Time out-of Sample Examination," Working Papers No 2/2011, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    5. Todd E. Clark & Taeyoung Doh, 2011. "A Bayesian evaluation of alternative models of trend inflation," Research Working Paper RWP 11-16, Federal Reserve Bank of Kansas City.
    6. Jamali, Ibrahim & Yamani, Ehab, 2019. "Out-of-sample exchange rate predictability in emerging markets: Fundamentals versus technical analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 241-263.

  35. Todd E. Clark & Michael W. McCracken, 2009. "Nested forecast model comparisons: a new approach to testing equal accuracy," Research Working Paper RWP 09-11, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2016. "Dynamic Predictive Density Combinations for Large Data Sets in Economics and Finance," Tinbergen Institute Discussion Papers 15-084/III, Tinbergen Institute, revised 03 Jul 2017.
    2. Christian Hutter & Enzo Weber, 2015. "Constructing a new leading indicator for unemployment from a survey among German employment agencies," Applied Economics, Taylor & Francis Journals, vol. 47(33), pages 3540-3558, July.
    3. Benjamin K. Johannsen & Elmar Mertens, 2016. "A Time Series Model of Interest Rates With the Effective Lower Bound," Finance and Economics Discussion Series 2016-033, Board of Governors of the Federal Reserve System (U.S.).
    4. Kang, Wensheng & Ratti, Ronald. A. & Vespignani, Joaquin, 2016. "The implications of liquidity expansion in China for the US dollar," Working Papers 2016-02, University of Tasmania, Tasmanian School of Business and Economics.
    5. Ron Alquist & Lutz Kilian & Robert J. Vigfusson, 2011. "Forecasting the price of oil," International Finance Discussion Papers 1022, Board of Governors of the Federal Reserve System (U.S.).
    6. Filip Staněk, 2023. "Optimal out‐of‐sample forecast evaluation under stationarity," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 2249-2279, December.
    7. Baumeister, Christiane & Korobilis, Dimitris & Lee, Thomas K., 2020. "Energy Markets and Global Economic Conditions," CEPR Discussion Papers 14580, C.E.P.R. Discussion Papers.
    8. Bjørnland, Hilde C. & Ravazzolo, Francesco & Thorsrud, Leif Anders, 2017. "Forecasting GDP with global components: This time is different," International Journal of Forecasting, Elsevier, vol. 33(1), pages 153-173.
    9. 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.
    10. Christian Hutter, 2020. "A new indicator for nowcasting employment subject to social security contributions in Germany," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 54(1), pages 1-10, December.
    11. Xiaojie Xu, 2020. "Corn Cash Price Forecasting," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(4), pages 1297-1320, August.
    12. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
    13. Calhoun, Gray, 2014. "Out-Of-Sample Comparisons of Overfit Models," Staff General Research Papers Archive 32462, Iowa State University, Department of Economics.
    14. Kilian, Lutz & Vigfusson, Robert J., 2012. "Do Oil Prices Help Forecast U.S. Real GDP? The Role of Nonlinearities and Asymmetries," CEPR Discussion Papers 8980, C.E.P.R. Discussion Papers.
    15. Raffaella Giacomini & Barbara Rossi, 2013. "Forecasting in macroeconomics," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 17, pages 381-408, Edward Elgar Publishing.
    16. Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2014. "Density forecasts with MIDAS models," Working Paper 2014/10, Norges Bank.
    17. Todd E. Clark & Michael W. McCracken, 2010. "Reality checks and nested forecast model comparisons," Working Papers 2010-032, Federal Reserve Bank of St. Louis.
    18. Andrea CARRIERO & Todd E. CLARK & Massimiliano MARCELLINO, 2012. "Common Drifting Volatility in Large Bayesian VARs," Economics Working Papers ECO2012/08, European University Institute.
    19. Clark, Todd E. & McCracken, Michael W., 2012. "In-sample tests of predictive ability: A new approach," Journal of Econometrics, Elsevier, vol. 170(1), pages 1-14.
    20. Firmin Doko Tchatoka & Qazi Haque, 2020. "On bootstrapping tests of equal forecast accuracy for nested models," School of Economics and Public Policy Working Papers 2020-03, University of Adelaide, School of Economics and Public Policy.
    21. Boriss Siliverstovs, 2015. "Short-term forecasting with mixed-frequency data: A MIDASSO approach," KOF Working papers 15-375, KOF Swiss Economic Institute, ETH Zurich.
    22. Nicolas S. Magner & Nicolás Hardy & Tiago Ferreira & Jaime F. Lavin, 2023. "“Agree to Disagree”: Forecasting Stock Market Implied Volatility Using Financial Report Tone Disagreement Analysis," Mathematics, MDPI, vol. 11(7), pages 1-16, March.
    23. Francesco Ravazzolo & Philip Rothman, 2011. "Oil and US GDP: A Real-Time out-of Sample Examination," Working Papers No 2/2011, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    24. Robert Gausden & Mohammad Hasan, 2022. "A reappraisal of Katona’s adaptive theory of consumer behaviour using U.K. data," Manchester School, University of Manchester, vol. 90(2), pages 122-143, March.
    25. Kiss, Tamás & Mazur, Stepan & Nguyen, Hoang & Österholm, Pär, 2021. "Modelling the Relation between the US Real Economy and the Corporate Bond-Yield Spread in Bayesian VARs with non-Gaussian Disturbances," Working Papers 2021:9, Örebro University, School of Business.
    26. Mayer, Walter J. & Liu, Feng & Dang, Xin, 2017. "Improving the power of the Diebold–Mariano–West test for least squares predictions," International Journal of Forecasting, Elsevier, vol. 33(3), pages 618-626.
    27. Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2021. "A Bayesian Dynamic Compositional Model for Large Density Combinations in Finance," Tinbergen Institute Discussion Papers 21-016/III, Tinbergen Institute.
    28. 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.
    29. Håvard Hungnes, 2020. "Predicting the exchange rate path. The importance of using up-to-date observations in the forecasts," Discussion Papers 934, Statistics Norway, Research Department.
    30. Nikolsko-Rzhevskyy, Alex & Prodan, Ruxandra, 2012. "Markov switching and exchange rate predictability," International Journal of Forecasting, Elsevier, vol. 28(2), pages 353-365.
    31. Akgun, Oguzhan & Pirotte, Alain & Urga, Giovanni & Yang, Zhenlin, 2024. "Equal predictive ability tests based on panel data with applications to OECD and IMF forecasts," International Journal of Forecasting, Elsevier, vol. 40(1), pages 202-228.
    32. Chen, Yi-Ting & Liu, Chu-An, 2023. "Model averaging for asymptotically optimal combined forecasts," Journal of Econometrics, Elsevier, vol. 235(2), pages 592-607.
    33. Todd E. Clark & Taeyoung Doh, 2011. "A Bayesian evaluation of alternative models of trend inflation," Research Working Paper RWP 11-16, Federal Reserve Bank of Kansas City.
    34. Knut Are Aastveit & Tuva Marie Fastbø & Eleonora Granziera & Kenneth Sæterhagen Paulsen & Kjersti Næss Torstensen, 2020. "Nowcasting Norwegian household consumption with debit card transaction data," Working Paper 2020/17, Norges Bank.
    35. Mohr, Matthias & Maurin, Laurent & Guérin, Pierre, 2011. "Trend-cycle decomposition of output and euro area inflation forecasts: a real-time approach based on model combination," Working Paper Series 1384, European Central Bank.
    36. Marcellino, Massimiliano & Carriero, Andrea & Corsello, Francesco, 2019. "The Global Component of Inflation Volatility," CEPR Discussion Papers 13470, C.E.P.R. Discussion Papers.
    37. Hutter, Christian & Weber, Enzo, 2014. "Forecasting with a mismatch-enhanced labor market matching function," IAB-Discussion Paper 201416, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    38. Andreou, Elena & Ghysels, Eric, 2021. "Predicting the VIX and the volatility risk premium: The role of short-run funding spreads Volatility Factors," Journal of Econometrics, Elsevier, vol. 220(2), pages 366-398.
    39. Kang, Wensheng & Ratti, Ronald A. & Vespignani, Joaquin L., 2016. "The implications of monetary expansion in China for the US dollar," Journal of Asian Economics, Elsevier, vol. 46(C), pages 71-84.
    40. Christian Hutter & Enzo Weber, 2017. "Mismatch and the Forecasting Performance of Matching Functions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(1), pages 101-123, February.
    41. In Choi & Hanbat Jeong, 2020. "Differencing versus nondifferencing in factor‐based forecasting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(6), pages 728-750, September.
    42. Knut Are Aastveit & Andr K. Anundsen & Eyo I. Herstad, 2017. "Residential investment and recession predictability," Working Papers No 8/2017, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    43. 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.
    44. Szafranek, Karol, 2019. "Bagged neural networks for forecasting Polish (low) inflation," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1042-1059.
    45. Garratt, Anthony & Mise, Emi, 2014. "Forecasting exchange rates using panel model and model averaging," Economic Modelling, Elsevier, vol. 37(C), pages 32-40.
    46. Hossein Hassani & Emmanuel Sirimal Silva, 2015. "A Kolmogorov-Smirnov Based Test for Comparing the Predictive Accuracy of Two Sets of Forecasts," Econometrics, MDPI, vol. 3(3), pages 1-20, August.
    47. Kichian, Maral & Rumler, Fabio, 2014. "Forecasting Canadian inflation: A semi-structural NKPC approach," Economic Modelling, Elsevier, vol. 43(C), pages 183-191.
    48. Michael W. McCracken, 2019. "Tests of Conditional Predictive Ability: Some Simulation Evidence," Working Papers 2019-11, Federal Reserve Bank of St. Louis.
    49. Johanna Posch & Fabio Rumler, 2015. "Semi‐Structural Forecasting of UK Inflation Based on the Hybrid New Keynesian Phillips Curve," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(2), pages 145-162, March.
    50. Håvard Hungnes, 2020. "Equal predictability test for multi-step-ahead system forecasts invariant to linear transformations," Discussion Papers 931, Statistics Norway, Research Department.
    51. Blasques, F. & Koopman, S.J. & Mallee, M. & Zhang, Z., 2016. "Weighted maximum likelihood for dynamic factor analysis and forecasting with mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 405-417.
    52. Arai, Natsuki, 2014. "Using forecast evaluation to improve the accuracy of the Greenbook forecast," International Journal of Forecasting, Elsevier, vol. 30(1), pages 12-19.
    53. Todd E. Clark & Michael W. McCracken, 2010. "Testing for unconditional predictive ability," Working Papers 2010-031, Federal Reserve Bank of St. Louis.

  36. Todd E. Clark, 2009. "Real-time density forecasts from VARs with stochastic volatility," Research Working Paper RWP 09-08, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Xiaojie Xu, 2017. "Short-run price forecast performance of individual and composite models for 496 corn cash markets," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(14), pages 2593-2620, October.
    2. Francesco Ravazzolo & Shaun P. Vahey, 2010. "Forecast densities for economic aggregates from disaggregate ensembles," Working Paper 2010/02, Norges Bank.
    3. O'Brien, Martin & Velasco, Sofia, 2020. "Unobserved components models with stochastic volatility for extracting trends and cycles in credit," Research Technical Papers 09/RT/20, Central Bank of Ireland.
    4. 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.
    5. Todd E. Clark, 2009. "Is the Great Moderation over? an empirical analysis," Economic Review, Federal Reserve Bank of Kansas City, vol. 94(Q IV), pages 5-42.

  37. Todd E. Clark & Michael W. McCracken, 2009. "In-sample tests of predictive ability: a new approach," Research Working Paper RWP 09-10, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Hsiu-Hsin Ko, 2016. "Exchange Rate Predictability in Finite Samples," The Japanese Economic Review, Japanese Economic Association, vol. 67(3), pages 361-378, September.
    2. Burcu Erik & Marco Jacopo Lombardi & Dubravko Mihaljek & Hyun Song Shin, 2020. "The dollar, bank leverage and real economic activity: an evolving relationship," BIS Working Papers 847, Bank for International Settlements.
    3. Manuel Lukas & Eric Hillebrand, 2014. "Bagging Weak Predictors," CREATES Research Papers 2014-01, Department of Economics and Business Economics, Aarhus University.
    4. Pincheira, Pablo & Selaive, Jorge & Nolazco, Jose Luis, 2017. "Forecasting Inflation in Latin America with Core Measures," MPRA Paper 80496, University Library of Munich, Germany.
    5. Antolin-Diaz, Juan & Drechsel, Thomas & Petrella, Ivan, 2016. "Tracking the slowdown in long-run GDP growth," LSE Research Online Documents on Economics 86243, London School of Economics and Political Science, LSE Library.
    6. Su, Hao & Ying, Chengwei & Zhu, Xiaoneng, 2022. "Disaster risk matters in the bond market," Finance Research Letters, Elsevier, vol. 47(PA).
    7. Calhoun, Gray, 2014. "Out-Of-Sample Comparisons of Overfit Models," Staff General Research Papers Archive 32462, Iowa State University, Department of Economics.
    8. Chauvet, Marcelle & Senyuz, Zeynep & Yoldas, Emre, 2015. "What does financial volatility tell us about macroeconomic fluctuations?," Journal of Economic Dynamics and Control, Elsevier, vol. 52(C), pages 340-360.
    9. Kilian, Lutz & Vigfusson, Robert J., 2012. "Do Oil Prices Help Forecast U.S. Real GDP? The Role of Nonlinearities and Asymmetries," CEPR Discussion Papers 8980, C.E.P.R. Discussion Papers.
    10. Boot, Tom & Pick, Andreas, 2020. "Does modeling a structural break improve forecast accuracy?," Journal of Econometrics, Elsevier, vol. 215(1), pages 35-59.
    11. Petrella, Ivan & Drechsel, Thomas & Antolin-Diaz, Juan, 2014. "Following the Trend: Tracking GDP when Long-Run Growth is Uncertain," CEPR Discussion Papers 10272, C.E.P.R. Discussion Papers.
    12. Tom Boot & Andreas Pick, 2017. "A near optimal test for structural breaks when forecasting under square error loss," Tinbergen Institute Discussion Papers 17-039/III, Tinbergen Institute.
    13. Hsiu-Hsin Ko, 2016. "Exchange Rate Predictability in Finite Samples," The Japanese Economic Review, Springer, vol. 67(3), pages 361-378, September.
    14. Mohan Subbiah & Frank J Fabozzi, 2016. "Equity style allocation: A nonparametric approach," Journal of Asset Management, Palgrave Macmillan, vol. 17(3), pages 141-164, May.
    15. Hossein Hassani & Emmanuel Sirimal Silva, 2015. "A Kolmogorov-Smirnov Based Test for Comparing the Predictive Accuracy of Two Sets of Forecasts," Econometrics, MDPI, vol. 3(3), pages 1-20, August.
    16. Burcu Erik & Marco Jacopo Lombardi & Dubravko Mihaljek & Hyun Song Shin, 2019. "Financial conditions and purchasing managers' indices: exploring the links," BIS Quarterly Review, Bank for International Settlements, September.

  38. Todd E. Clark & Stephen J. Terry, 2009. "Time variation in the inflation passthrough of energy prices," Research Working Paper RWP 09-06, Federal Reserve Bank of Kansas City.

    Cited by:

    1. 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.
    2. Lutz Kilian & Xiaoqing Zhou, 2021. "The Impact of Rising Oil Prices on U.S. Inflation and Inflation Expectations in 2020-23," CESifo Working Paper Series 9455, CESifo.
    3. Francesco Corsello & Alex Tagliabracci, 2023. "Assessing the pass-through of energy prices to inflation in the euro area," Questioni di Economia e Finanza (Occasional Papers) 745, Bank of Italy, Economic Research and International Relations Area.
    4. Jon Ellingsen & Caroline Espegren, 2022. "Lost in transition? Earnings losses of displaced petroleum workers," Working Papers No 06/2022, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    5. Mr. Yasser Abdih & Mr. Ravi Balakrishnan & Baoping Shang, 2016. "What is Keeping U.S. Core Inflation Low: Insights from a Bottom-Up Approach," IMF Working Papers 2016/124, International Monetary Fund.
    6. SEKINE Atsushi & TSURUGA Takayuki, 2016. "Effects of Commodity Price Shocks on Inflation: A Cross-Country Analysis," ESRI Discussion paper series 331, Economic and Social Research Institute (ESRI).
    7. James H. Stock & Mark W. Watson, 2015. "Core Inflation and Trend Inflation," NBER Working Papers 21282, National Bureau of Economic Research, Inc.
    8. Kilian, Lutz & Zhou, Xiaoqing, 2020. "Oil Prices, Gasoline Prices and Inflation Expectations: A New Model and New Facts," CEPR Discussion Papers 15168, C.E.P.R. Discussion Papers.
    9. Cristina Conflitti and Matteo Luciani, 2019. "Oil Price Pass-through into Core Inflation," The Energy Journal, International Association for Energy Economics, vol. 0(Number 6).
    10. Fazal, Rizwan & Rehman, Syed Aziz Ur & Bhatti, M. Ishaq, 2022. "Graph theoretic approach to expose the energy-induced crisis in Pakistan," Energy Policy, Elsevier, vol. 169(C).
    11. Hilde C. Bjørnland & Julia Zhulanova, 2019. "The shale oil boom and the U.S. economy: Spillovers and time-varying effects," Working Paper 2019/14, Norges Bank.
    12. Ioannidis, Christos & Ka, Kook, 2018. "The impact of oil price shocks on the term structure of interest rates," Energy Economics, Elsevier, vol. 72(C), pages 601-620.
    13. Francesca Rondina, 2010. "The role of model uncertainty and learning in the U.S. postwar policy response to oil prices," Working Papers 478, Barcelona School of Economics.
    14. 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.
    15. Richard G. Anderson & Jane M. Binner & Vincent A. Schmidt, 2011. "Connectionist-based rules describing the pass-through of individual goods prices into trend inflation in the United States," Working Papers 2011-007, Federal Reserve Bank of St. Louis.
    16. Binder, Carola Conces, 2018. "Inflation expectations and the price at the pump," Journal of Macroeconomics, Elsevier, vol. 58(C), pages 1-18.
    17. Gorgi, Paolo & Koopman, Siem Jan & Li, Mengheng, 2019. "Forecasting economic time series using score-driven dynamic models with mixed-data sampling," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1735-1747.
    18. Sheng, Xin & Marfatia, Hardik A. & Gupta, Rangan & Ji, Qiang, 2023. "The non-linear response of US state-level tradable and non-tradable inflation to oil shocks: The role of oil-dependence," Research in International Business and Finance, Elsevier, vol. 64(C).
    19. Fasanya, Ismail O. & Awodimila, Crystal P., 2020. "Are commodity prices good predictors of inflation? The African perspective," Resources Policy, Elsevier, vol. 69(C).
    20. Rodriguez, Gabriel & Castillo B., Paul & Calero, Roberto & Salcedo Cisneros, Rodrigo & Ataurima Arellano, Miguel, 2024. "Evolution of the exchange rate pass-through into prices in Peru: An empirical application using TVP-VAR-SV models," Journal of International Money and Finance, Elsevier, vol. 142(C).
    21. Kilian, Lutz & Zhou, Xiaoqing, 2023. "A broader perspective on the inflationary effects of energy price shocks," Energy Economics, Elsevier, vol. 125(C).
    22. Tian, Shuairu & Hamori, Shigeyuki, 2016. "Time-varying price shock transmission and volatility spillover in foreign exchange, bond, equity, and commodity markets: Evidence from the United States," The North American Journal of Economics and Finance, Elsevier, vol. 38(C), pages 163-171.
    23. de Mendonça, Helder Ferreira & Garcia, Pedro Mendes, 2023. "Effects of oil shocks and central bank credibility on price diffusion," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 304-317.
    24. López, Lucia & Odendahl, Florens & Parrága, Susana & Silgado-Gómez, Edgar, 2024. "The pass-through to inflation of gas price shocks," Working Paper Series 2968, European Central Bank.
    25. Ahmed Jamal Pirzada, 2017. "Energy Price Uncertainty and Decreasing Pass-through to Core Inflation," Bristol Economics Discussion Papers 17/681, School of Economics, University of Bristol, UK, revised 30 May 2017.
    26. 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.).
    27. Deborah Gefang & Gary Koop & Simon M. Potter, 2009. "The Dynamics of UK and US Inflation Expectations," Working Paper series 14_09, Rimini Centre for Economic Analysis.
    28. Lutz Kilian & Xiaoqing Zhou, 2022. "Oil prices, gasoline prices, and inflation expectations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 867-881, August.
    29. Fulli-Lemaire, Nicolas, 2013. "Alternative inflation hedging strategies for ALM," MPRA Paper 43755, University Library of Munich, Germany.
    30. Kilian, Lutz & Zhou, Xiaoqing, 2023. "Oil Price Shocks and Inflation," CEPR Discussion Papers 18416, C.E.P.R. Discussion Papers.
    31. Muhammad Khan & Nikolay Nenovsky, 2017. "Monetary Regimes and External Shocks Reaction: Empirical Investigations on Eastern European Economies," Post-Print hal-03831265, HAL.
    32. Bijsterbosch, Martin & Falagiarda, Matteo, 2014. "Credit supply dynamics and economic activity in euro area countries: a time-varying parameter VAR analysis," Working Paper Series 1714, European Central Bank.
    33. Castillo, Paul & Montoro, Carlos & Tuesta, Vicente, 2020. "Inflation, oil price volatility and monetary policy," Journal of Macroeconomics, Elsevier, vol. 66(C).
    34. Bijsterbosch, Martin & Falagiarda, Matteo, 2015. "The macroeconomic impact of financial fragmentation in the euro area: Which role for credit supply?," Journal of International Money and Finance, Elsevier, vol. 54(C), pages 93-115.
    35. Elsayed, Ahmed H. & Hammoudeh, Shawkat & Sousa, Ricardo M., 2021. "Inflation synchronization among the G7and China: The important role of oil inflation," Energy Economics, Elsevier, vol. 100(C).
    36. Matthew Klepacz, 2018. "Price Setting and Volatility: Evidence from Oil Price Volatility Shocks," 2018 Meeting Papers 145, Society for Economic Dynamics.
    37. Shi, Xunpeng & Sun, Sizhong, 2017. "Energy price, regulatory price distortion and economic growth: A case study of China," Energy Economics, Elsevier, vol. 63(C), pages 261-271.
    38. 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.
    39. Pooyan Amir-Ahmadi & Christian Matthes & Mu-Chun Wang, 2016. "Choosing Prior Hyperparameters," Working Paper 16-9, Federal Reserve Bank of Richmond.
    40. Kang, Sang Hoon & Islam, Faridul & Kumar Tiwari, Aviral, 2019. "The dynamic relationships among CO2 emissions, renewable and non-renewable energy sources, and economic growth in India: Evidence from time-varying Bayesian VAR model," Structural Change and Economic Dynamics, Elsevier, vol. 50(C), pages 90-101.
    41. Francesca Rondina, 2017. "The Impact of Oil Price Changes in a New Keynesian Model of the U.S. Economy," Working Papers 1709E, University of Ottawa, Department of Economics.
    42. Zhang, Weiping & Zhuang, Xintian & Lu, Yang & Wang, Jian, 2020. "Spatial linkage of volatility spillovers and its explanation across G20 stock markets: A network framework," International Review of Financial Analysis, Elsevier, vol. 71(C).
    43. Domenico Giannone & Michèle Lenza & Daphné Momferatu & Luca Onorante, 2010. "Short-term inflation projections: a Bayesian vector autoregressive approach," Working Papers ECARES ECARES 2010-011, ULB -- Universite Libre de Bruxelles.
    44. Knotek, Edward S. & Zaman, Saeed, 2021. "Asymmetric responses of consumer spending to energy prices: A threshold VAR approach," Energy Economics, Elsevier, vol. 95(C).
    45. Martin Fukac, 2011. "Have rising oil prices become a greater threat to price stability?," Economic Review, Federal Reserve Bank of Kansas City, vol. 96(Q IV), pages 27-53.
    46. Mustafa Kocoglu, 2023. "Drivers of inflation in Turkey: a new Keynesian Phillips curve perspective," Economic Change and Restructuring, Springer, vol. 56(4), pages 2825-2853, August.
    47. Zhang, Weiping & Zhuang, Xintian & Lu, Yang, 2020. "Spatial spillover effects and risk contagion around G20 stock markets based on volatility network," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    48. Todd E. Clark, 2009. "Is the Great Moderation over? an empirical analysis," Economic Review, Federal Reserve Bank of Kansas City, vol. 94(Q IV), pages 5-42.
    49. Grzegorz Przekota & Anna Szczepańska-Przekota, 2022. "Pro-Inflationary Impact of the Oil Market—A Study for Poland," Energies, MDPI, vol. 15(9), pages 1-19, April.
    50. Fulli-Lemaire, Nicolas, 2012. "Allocating Commodities in Inflation Hedging Portfolios: A Core Driven Global Macro Strategy," MPRA Paper 42852, University Library of Munich, Germany, revised 15 Oct 2012.
    51. Janet L. Yellen, 2015. "Inflation Dynamics and Monetary Policy : A speech at the Philip Gamble Memorial Lecture, University of Massachusetts, Amherst, Amherst, Massachusetts, September 24, 2015," Speech 863, Board of Governors of the Federal Reserve System (U.S.).
    52. Baharumshah, Ahmad Zubaidi & Sirag, Abdalla & Soon, Siew-Voon, 2017. "Asymmetric exchange rate pass-through in an emerging market economy: The case of Mexico," Research in International Business and Finance, Elsevier, vol. 41(C), pages 247-259.
    53. Michelle, Gilmartin, 2016. "A note on the identification and transmission of energy demand and supply shocks," MPRA Paper 76186, University Library of Munich, Germany.
    54. Tiwari, Aviral Kumar & Cunado, Juncal & Hatemi-J, Abdulnasser & Gupta, Rangan, 2019. "Oil price-inflation pass-through in the United States over 1871 to 2018: A wavelet coherency analysis," Structural Change and Economic Dynamics, Elsevier, vol. 50(C), pages 51-55.
    55. Orlowski, Lucjan T., 2017. "Volatility of commodity futures prices and market-implied inflation expectations," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 51(C), pages 133-141.
    56. Ruiz, Miguel Haro & Schult, Christoph & Wunder, Christoph, 2024. "The effects of the Iberian exception mechanism on wholesale electricity prices and consumer inflation: A synthetic-controls approach," IWH Discussion Papers 5/2024, Halle Institute for Economic Research (IWH).
    57. Andreani, Michele & Giri, Federico, 2023. "Not a short-run noise! The low-frequency volatility of energy inflation," Finance Research Letters, Elsevier, vol. 51(C).
    58. Zakaria, Muhammad & Khiam, Shahzeb & Mahmood, Hamid, 2021. "Influence of oil prices on inflation in South Asia: Some new evidence," Resources Policy, Elsevier, vol. 71(C).
    59. Antonio J., Garzón & Luis A., Hierro, 2022. "Inflation, oil prices and exchange rates. The Euro’s dampening effect," Journal of Policy Modeling, Elsevier, vol. 44(1), pages 130-146.
    60. 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.).
    61. Mirza, Nawazish & Naqvi, Bushra & Rizvi, Syed Kumail Abbas & Umar, Muhammad, 2023. "Fiscal or monetary? Efficacy of regulatory regimes and energy trilemma of the inflation reduction act (IRA)," International Review of Financial Analysis, Elsevier, vol. 90(C).
    62. Liu, Xueyong & An, Haizhong & Li, Huajiao & Chen, Zhihua & Feng, Sida & Wen, Shaobo, 2017. "Features of spillover networks in international financial markets: Evidence from the G20 countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 265-278.
    63. Uju Violet Alola & Ojonugwa Usman & Andrew Adewale Alola, 2023. "Is pass-through of the exchange rate to restaurant and hotel prices asymmetric in the US? Role of monetary policy uncertainty," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-19, December.
    64. Sohrab Rafiq, 2014. "What Do Energy Prices Tell Us About UK Inflation?," Economica, London School of Economics and Political Science, vol. 81(322), pages 293-310, April.
    65. He, Yongda & Lin, Boqiang, 2019. "Regime differences and industry heterogeneity of the volatility transmission from the energy price to the PPI," Energy, Elsevier, vol. 176(C), pages 900-916.
    66. Matthew Klepacz, 2021. "Price Setting and Volatility: Evidence from Oil Price Volatility Shocks," International Finance Discussion Papers 1316, Board of Governors of the Federal Reserve System (U.S.).
    67. Tomoyuki Yagi & Yoshiyuki Kurachi & Masato Takahashi & Kotone Yamada & Hiroshi Kawata, 2022. "Pass-Through of Cost-Push Pressures to Consumer Prices," Bank of Japan Working Paper Series 22-E-17, Bank of Japan.

  39. Todd E. Clark & Troy Davig, 2009. "Decomposing the declining volatility of long-term inflation expectations," Research Working Paper RWP 09-05, Federal Reserve Bank of Kansas City.

    Cited by:

    1. D'Agostino, Antonello & Mendicino, Caterina, 2015. "Expectation-driven cycles: time-varying effects," Working Paper Series 1776, European Central Bank.
    2. Kim, Jerim & Kim, Bara & Moon, Kyoung-Sook & Wee, In-Suk, 2012. "Valuation of power options under Heston's stochastic volatility model," Journal of Economic Dynamics and Control, Elsevier, vol. 36(11), pages 1796-1813.
    3. 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.
    4. Keating, John W. & Valcarcel, Victor J., 2017. "What's so great about the Great Moderation?," Journal of Macroeconomics, Elsevier, vol. 51(C), pages 115-142.
    5. Del Negro, Marco & Eusepi, Stefano, 2011. "Fitting observed inflation expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 35(12), pages 2105-2131.
    6. 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.
    7. Benjamin Wong, 2015. "Do Inflation Expectations Propagate the Inflationary Impact of Real Oil Price Shocks?: Evidence from the Michigan Survey," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(8), pages 1673-1689, December.
    8. Granville, Brigitte & Zeng, Ning, 2019. "Time variation in inflation persistence: New evidence from modelling US inflation," Economic Modelling, Elsevier, vol. 81(C), pages 30-39.
    9. Volha Audzei, 2016. "Confidence Cycles and Liquidity Hoarding," Working Papers 2016/07, Czech National Bank.
    10. Travis J. Berge, 2017. "Understanding Survey Based Inflation Expectations," Finance and Economics Discussion Series 2017-046, Board of Governors of the Federal Reserve System (U.S.).
    11. James M. Nason & Gregor W. Smith, 2013. "Reverse Kalman filtering U.S. inflation with sticky professional forecasts," Working Papers 13-34, Federal Reserve Bank of Philadelphia.
    12. 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.).
    13. Netésunajev, Aleksei & Winkelmann, Lars, 2016. "International dynamics of inflation expectations," SFB 649 Discussion Papers 2016-019, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    14. Keating, John W. & Valcarcel, Victor J., 2015. "The Time-Varying Effects Of Permanent And Transitory Shocks To Real Output," Macroeconomic Dynamics, Cambridge University Press, vol. 19(3), pages 477-507, April.
    15. Henzel, Steffen R., 2013. "Fitting survey expectations and uncertainty about trend inflation," Journal of Macroeconomics, Elsevier, vol. 35(C), pages 172-185.
    16. McNeil, James, 2023. "Monetary policy and the term structure of inflation expectations with information frictions," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
    17. Andrea CARRIERO & Todd E. CLARK & Massimiliano MARCELLINO, 2012. "Common Drifting Volatility in Large Bayesian VARs," Economics Working Papers ECO2012/08, European University Institute.
    18. 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).
    19. J. Scott Davis, 2012. "Central bank credibility and the persistence of inflation and inflation expectations," Globalization Institute Working Papers 117, Federal Reserve Bank of Dallas.
    20. James M. Nason & Gregor W. Smith, 2013. "Measuring The Slowly Evolving Trend In Us Inflation With Professional Forecasts," Working Paper 1316, Economics Department, Queen's University.
    21. Benjamin Wong, 2017. "Historical decompositions for nonlinear vector autoregression models," CAMA Working Papers 2017-62, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    22. Christina Anderl & Guglielmo Maria Caporale, 2023. "Functional Shocks to Inflation Expectations and Real Interest Rates and Their Macroeconomic Effects," CESifo Working Paper Series 10656, CESifo.
    23. J. Scott Davis, 2012. "The effect of commodity price shocks on underlying inflation: the role of central bank credibility," Globalization Institute Working Papers 134, Federal Reserve Bank of Dallas.
    24. Todd E. Clark & Taeyoung Doh, 2011. "A Bayesian evaluation of alternative models of trend inflation," Research Working Paper RWP 11-16, Federal Reserve Bank of Kansas City.
    25. Todd E. Clark & Francesco Ravazzolo, 2012. "The macroeconomic forecasting performance of autoregressive models with alternative specifications of time-varying volatility," Working Paper 2012/09, Norges Bank.
    26. Monica Jain, 2018. "Sluggish Forecasts," Staff Working Papers 18-39, Bank of Canada.
    27. Elmar Mertens, 2011. "Measuring the level and uncertainty of trend inflation," Finance and Economics Discussion Series 2011-42, Board of Governors of the Federal Reserve System (U.S.).
    28. Virginia Queijo von Heideken & Ferre De Graeve, 2012. "Fiscal policy in contemporary DSGE models," 2012 Meeting Papers 74, Society for Economic Dynamics.
    29. J. Scott Davis & Adrienne Mack, 2013. "Cross-country variation in the anchoring of inflation expectations," Staff Papers, Federal Reserve Bank of Dallas, issue Oct.
    30. Ascari, Guido & Fasani, Stefano & Grazzini, Jakob & Rossi, Lorenza, 2023. "Endogenous uncertainty and the macroeconomic impact of shocks to inflation expectations," Journal of Monetary Economics, Elsevier, vol. 140(S), pages 48-63.
    31. Mazumder, Sandeep, 2018. "Inflation in Europe after the Great Recession," Economic Modelling, Elsevier, vol. 71(C), pages 202-213.
    32. Valcarcel, Victor J., 2012. "The dynamic adjustments of stock prices to inflation disturbances," Journal of Economics and Business, Elsevier, vol. 64(2), pages 117-144.
    33. Doh, Taeyoung & Smith, A. Lee, 2022. "A new approach to integrating expectations into VAR models," Journal of Monetary Economics, Elsevier, vol. 132(C), pages 24-43.

  40. 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.

    Cited by:

    1. K. Istrefi & A. Piloiu, 2016. "Economic policy uncertainty and inflation expectations," Rue de la Banque, Banque de France, issue 33, november..
    2. Joshua C C Chan & Gary Koop & Simon M Potter, 2012. "A New Model of Trend Inflation," CAMA Working Papers 2012-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    3. 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.
    4. 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.
    5. Coibion, Olivier & Gorodnichenko, Yuriy & Kumar, Saten & Pedemonte, Mathieu, 2020. "Inflation expectations as a policy tool?," Journal of International Economics, Elsevier, vol. 124(C).
    6. Rafiq, Sohrab, 2010. "Fiscal stance, the current account and the real exchange rate: Some empirical estimates from a time-varying framework," Structural Change and Economic Dynamics, Elsevier, vol. 21(4), pages 276-290, November.
    7. Klodiana Istrefi & Anamaria Piloiu, 2013. "Economic Policy Uncertainty, Trust and Inflation Expectations," CESifo Working Paper Series 4294, CESifo.
    8. Gabriele Galati & Peter Heemeijer & Richhild Moessner, 2011. "How do inflation expectations form? New insights from a high-frequency survey," BIS Working Papers 349, Bank for International Settlements.
    9. Mazumder, Sandeep, 2018. "Inflation in Europe after the Great Recession," Economic Modelling, Elsevier, vol. 71(C), pages 202-213.

  41. Todd E. Clark & Michael W. McCracken, 2007. "Averaging forecasts from VARs with uncertain instabilities," Finance and Economics Discussion Series 2007-42, Board of Governors of the Federal Reserve System (U.S.).

    Cited by:

    1. Maheu, John & Song, Yong, 2012. "A new structural break model with application to Canadian inflation forecasting," MPRA Paper 36870, University Library of Munich, Germany.
    2. Bańbura, Marta & Bobeica, Elena, 2020. "Does the Phillips curve help to forecast euro area inflation?," Working Paper Series 2471, European Central Bank.
    3. Pesaran, M.H. & Pick, A., 2008. "Forecasting Random Walks Under Drift Instability," Cambridge Working Papers in Economics 0814, Faculty of Economics, University of Cambridge.
    4. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    5. Dimitris Korobilis, 2013. "Var Forecasting Using Bayesian Variable Selection," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(2), pages 204-230, March.
    6. Buncic, Daniel & Müller, Oliver, 2017. "Measuring the output gap in Switzerland with linear opinion pools," Economic Modelling, Elsevier, vol. 64(C), pages 153-171.
    7. Carlo Altavilla & Matteo Ciccarelli, 2011. "Monetary Policy Analysis in Real-Time. Vintage Combination from a Real-Time Dataset," CESifo Working Paper Series 3372, CESifo.
    8. Yin, Anwen, 2015. "Forecasting and model averaging with structural breaks," ISU General Staff Papers 201501010800005727, Iowa State University, Department of Economics.
    9. Panopoulou, Ekaterini & Vrontos, Spyridon, 2015. "Hedge fund return predictability; To combine forecasts or combine information?," Journal of Banking & Finance, Elsevier, vol. 56(C), pages 103-122.
    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. Berg, Tim Oliver & Henzel, Steffen, 2013. "Point and Density Forecasts for the Euro Area Using Many Predictors: Are Large BVARs Really Superior?," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79783, Verein für Socialpolitik / German Economic Association.
    12. 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.
    13. Andrew C. Chang & Phillip Li, 2018. "Measurement Error In Macroeconomic Data And Economics Research: Data Revisions, Gross Domestic Product, And Gross Domestic Income," Economic Inquiry, Western Economic Association International, vol. 56(3), pages 1846-1869, July.
    14. Edward S. Knotek & Saeed Zaman, 2020. "Real-Time Density Nowcasts of US Inflation: A Model-Combination Approach," Working Papers 20-31, Federal Reserve Bank of Cleveland.
    15. Evanthia Chatzitzisi & Stilianos Fountas & Theodore Panagiotidis, 2019. "Another Look at Calendar Anomalies," Discussion Paper Series 2019_02, Department of Economics, University of Macedonia, revised Feb 2019.
    16. Niu, Linlin & Xu, Xiu & Chen, Ying, 2015. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," BOFIT Discussion Papers 12/2015, Bank of Finland Institute for Emerging Economies (BOFIT).
    17. Longo, Luigi & Riccaboni, Massimo & Rungi, Armando, 2022. "A neural network ensemble approach for GDP forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
    18. Knut Are Aastveit & Jamie L. Cross & Herman K. van Dijk, 2021. "Quantifying time-varying forecast uncertainty and risk for the real price of oil," Working Paper 2021/3, Norges Bank.
    19. Jan J. J. Groen & Richard Paap & Francesco Ravazzolo, 2009. "Real-time inflation forecasting in a changing world," Staff Reports 388, Federal Reserve Bank of New York.
    20. Henzel, Steffen R. & Mayr, Johannes, 2013. "The mechanics of VAR forecast pooling—A DSGE model based Monte Carlo study," The North American Journal of Economics and Finance, Elsevier, vol. 24(C), pages 1-24.
    21. Christian Kascha & Francesco Ravazzolo, 2008. "Combining inflation density forecasts," Working Paper 2008/22, Norges Bank.
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    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.
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    7. Pichette, Lise & Robitaille, Marie-Noëlle & Salameh, Mohanad & St-Amant, Pierre, 2019. "Dismiss the output gaps? To use with caution given their limitations," Economic Modelling, Elsevier, vol. 76(C), pages 199-215.
    8. Aaron J. Amburgey & Michael W. McCracken, 2023. "On the real‐time predictive content of financial condition indices for growth," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(2), pages 137-163, March.
    9. Barnett, Alina & Mumtaz, Haroon & Theodoridis, Konstantinos, 2014. "Forecasting UK GDP growth and inflation under structural change. A comparison of models with time-varying parameters," International Journal of Forecasting, Elsevier, vol. 30(1), pages 129-143.
    10. Graham Elliott & Allan Timmermann, 2008. "Economic Forecasting," Journal of Economic Literature, American Economic Association, vol. 46(1), pages 3-56, March.
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    13. Michael P. Clements & Ana Beatriz Galvão, 2009. "Forecasting US output growth using leading indicators: an appraisal using MIDAS models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(7), pages 1187-1206, November.
    14. Christiane Baumeister & Pierre Guérin & Lutz Kilian, 2014. "Do High-Frequency Financial Data Help Forecast Oil Prices? The MIDAS Touch at Work," Staff Working Papers 14-11, Bank of Canada.
    15. Christiane Baumeister & Lutz Kilian, 2014. "What Central Bankers Need To Know About Forecasting Oil Prices," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 55(3), pages 869-889, August.
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    18. Marcellino, Massimiliano, 2011. "Markov-switching MIDAS models," CEPR Discussion Papers 8234, C.E.P.R. Discussion Papers.
    19. 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.
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    22. 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.
    23. Todd E. Clark & Michael W. McCracken, 2007. "Averaging forecasts from VARs with uncertain instabilities," Finance and Economics Discussion Series 2007-42, Board of Governors of the Federal Reserve System (U.S.).
    24. Corradi, Valentina & Fernandez, Andres & Swanson, Norman R., 2009. "Information in the Revision Process of Real-Time Datasets," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 455-467.
    25. Tanya, Molodtsova & Nikolsko-Rzhevskyy, Alex & Papell, David, 2008. "Taylor Rules and the Euro," MPRA Paper 11348, University Library of Munich, Germany.
    26. Baumeister, Christiane & Kilian, Lutz, 2013. "Are product spreads useful for forecasting? An empirical evaluation of the Verleger hypothesis," CFS Working Paper Series 2013/09, Center for Financial Studies (CFS).
    27. Augustus J. Panton, 2020. "Climate hysteresis and monetary policy," CAMA Working Papers 2020-76, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    28. Edward S. Knotek & Saeed Zaman, 2014. "Nowcasting U.S. Headline and Core Inflation," Working Papers (Old Series) 1403, Federal Reserve Bank of Cleveland.
    29. Chauvet, Marcelle & Senyuz, Zeynep & Yoldas, Emre, 2015. "What does financial volatility tell us about macroeconomic fluctuations?," Journal of Economic Dynamics and Control, Elsevier, vol. 52(C), pages 340-360.
    30. Dean Croushore, 2011. "Frontiers of Real-Time Data Analysis," Journal of Economic Literature, American Economic Association, vol. 49(1), pages 72-100, March.
    31. Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2014. "Density forecasts with MIDAS models," Working Paper 2014/10, Norges Bank.
    32. Nima Nonejad, 2022. "New Findings Regarding the Out-of-Sample Predictive Impact of the Price of Crude Oil on the United States Industrial Production," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 18(1), pages 1-35, March.
    33. Heinisch, Katja, 2016. "A real-time analysis on the importance of hard and soft data for nowcasting German GDP," VfS Annual Conference 2016 (Augsburg): Demographic Change 145864, Verein für Socialpolitik / German Economic Association.
    34. Golinelli, Roberto & Parigi, Giuseppe, 2008. "Real-time squared: A real-time data set for real-time GDP forecasting," International Journal of Forecasting, Elsevier, vol. 24(3), pages 368-385.
    35. Francesco Ravazzolo & Philip Rothman, 2011. "Oil and US GDP: A Real-Time out-of Sample Examination," Working Papers No 2/2011, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    36. Philippe de Peretti & Oren Tapiero, 2014. "A GARCH analysis of dark-pool trades," Post-Print hal-00984834, HAL.
    37. 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.
    38. Lise Pichette & Marie-Noëlle Robitaille, 2017. "Assessing the Business Outlook Survey Indicator Using Real-Time Data," Discussion Papers 17-5, Bank of Canada.
    39. Heij, Christiaan & van Dijk, Dick & Groenen, Patrick J.F., 2011. "Real-time macroeconomic forecasting with leading indicators: An empirical comparison," International Journal of Forecasting, Elsevier, vol. 27(2), pages 466-481, April.
    40. John W. Galbraith & Greg Tkacz, 2013. "Nowcasting GDP: Electronic Payments, Data Vintages and the Timing of Data Releases," CIRANO Working Papers 2013s-25, CIRANO.
    41. 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.
    42. Rapach, David E. & Strauss, Jack K., 2012. "Forecasting US state-level employment growth: An amalgamation approach," International Journal of Forecasting, Elsevier, vol. 28(2), pages 315-327.
    43. Katja Heinisch & Rolf Scheufele, 2019. "Should Forecasters Use Real‐Time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence," German Economic Review, Verein für Socialpolitik, vol. 20(4), pages 170-200, November.
    44. Wang, Yudong & Liu, Li & Wu, Chongfeng, 2017. "Forecasting the real prices of crude oil using forecast combinations over time-varying parameter models," Energy Economics, Elsevier, vol. 66(C), pages 337-348.
    45. Knut Are Aastveit & Tuva Marie Fastbø & Eleonora Granziera & Kenneth Sæterhagen Paulsen & Kjersti Næss Torstensen, 2020. "Nowcasting Norwegian household consumption with debit card transaction data," Working Paper 2020/17, Norges Bank.
    46. Matthieu Lemoine & Gian Luigi Mazzi & Paola Monperrus-Veroni & Frédéric Reynes, 2010. "A new production function estimate of the euro area output gap This paper is based on a report for Eurostat: 'Real time estimation of potential output, output gap, NAIRU and Phillips curve for Euro-zo," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 29-53.
    47. Mohr, Matthias & Maurin, Laurent & Guérin, Pierre, 2011. "Trend-cycle decomposition of output and euro area inflation forecasts: a real-time approach based on model combination," Working Paper Series 1384, European Central Bank.
    48. Benjamin Beckers, 2015. "The Real-Time Predictive Content of Asset Price Bubbles for Macro Forecasts," Discussion Papers of DIW Berlin 1496, DIW Berlin, German Institute for Economic Research.
    49. Calista Cheung & Luke Frymire & Lise Pichette, 2020. "Can the Business Outlook Survey Help Improve Estimates of the Canadian Output Gap?," Discussion Papers 2020-14, Bank of Canada.
    50. Hyun Hak Kim & Norman Swanson, 2013. "Mining Big Data Using Parsimonious Factor and Shrinkage Methods," Departmental Working Papers 201316, Rutgers University, Department of Economics.
    51. Alfonso Mendoza Velázquez & Peter N. Smith, 2013. "Equity Returns and the Business Cycle: The Role of Supply and Demand Shocks," CAMA Working Papers 2013-22, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    52. Francis X. Diebold, 2012. "Comparing Predictive Accuracy, Twenty Years Later: A Personal Perspective on the Use and Abuse of Diebold-Mariano Tests," NBER Working Papers 18391, National Bureau of Economic Research, Inc.
    53. Marcellino, Massimiliano & Musso, Alberto, 2010. "Real time estimates of the euro area output gap: reliability and forecasting performance," Working Paper Series 1157, European Central Bank.
    54. Anthony Garratt & Gary Koop & Emi Mise & Shaun Vahey, 2008. "Real-time Prediction with UK Monetary Aggregates in the Presence of Model Uncertainty," Reserve Bank of New Zealand Discussion Paper Series DP2008/13, Reserve Bank of New Zealand.
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    56. Francesco Ravazzolo & Philip Rothman, 2015. "Oil-Price Density Forecasts of U.S. GDP," Working Papers No 10/2015, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    57. Kocięcki, Andrzej & Kolasa, Marcin & Rubaszek, Michał, 2012. "A Bayesian method of combining judgmental and model-based density forecasts," Economic Modelling, Elsevier, vol. 29(4), pages 1349-1355.
    58. Marcellino, Massimiliano & Foroni, Claudia, 2014. "Markov-Switching Mixed-Frequency VAR Models," CEPR Discussion Papers 9815, C.E.P.R. Discussion Papers.
    59. Marcellino, Massimiliano & Musso, Alberto, 2010. "The Forecasting Performance of Real Time Estimates of the Euro Area Output Gap," CEPR Discussion Papers 7763, C.E.P.R. Discussion Papers.
    60. Guido Bulligan & Roberto Golinelli & Giuseppe Parigi, 2010. "Forecasting industrial production: the role of information and methods," IFC Bulletins chapters, in: Bank for International Settlements (ed.), The IFC's contribution to the 57th ISI Session, Durban, August 2009, volume 33, pages 227-235, Bank for International Settlements.
    61. Akram, Q. Farooq, 2011. "Policy analysis in real time using IMF's monetary model," Economic Modelling, Elsevier, vol. 28(4), pages 1696-1709, July.
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    65. Lise Pichette & Marie-Noëlle Robitaille & Mohanad Salameh & Pierre St-Amant, 2018. "Dismiss the Gap? A Real-Time Assessment of the Usefulness of Canadian Output Gaps in Forecasting Inflation," Staff Working Papers 18-10, Bank of Canada.
    66. Michael P. Clements & Ana Beatriz Galvão, 2007. "Macroeconomic Forecasting with Mixed Frequency Data: Forecasting US Output Growth," Working Papers 616, Queen Mary University of London, School of Economics and Finance.
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    70. Cecilia Frale & Valentina Raponi, 2011. "Revisions in ocial data and forecasting," Working Papers LuissLab 1194, Dipartimento di Economia e Finanza, LUISS Guido Carli.

  43. Todd E. Clark & Michael W. McCracken, 2007. "Forecasting with small macroeconomic VARs in the presence of instabilities," Finance and Economics Discussion Series 2007-41, Board of Governors of the Federal Reserve System (U.S.).

    Cited by:

    1. Michal Rubaszek & Pawel Skrzypczynski, 2007. "Can a simple DSGE model outperform Professional Forecasters?," Working Papers 5, Department of Applied Econometrics, Warsaw School of Economics.
    2. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    3. Carlo Altavilla & Matteo Ciccarelli, 2011. "Monetary Policy Analysis in Real-Time. Vintage Combination from a Real-Time Dataset," CESifo Working Paper Series 3372, CESifo.
    4. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2011. "Bayesian VARs: specification choices and forecast accuracy," Working Papers (Old Series) 1112, Federal Reserve Bank of Cleveland.
    5. D'Agostino, Antonello & Gambetti, Luca & Giannone, Domenico & Giannone, Domenico, 2009. "Macroeconomic Forecasting and Structural Change," Research Technical Papers 8/RT/09, Central Bank of Ireland.
    6. Hendry, David F. & Hubrich, Kirstin, 2010. "Combining disaggregate forecasts or combining disaggregate information to forecast an aggregate," Working Paper Series 1155, European Central Bank.
    7. Colino, Evelyn V. & Irwin, Scott H. & Garcia, Philip, 2008. "How Much Can Outlook Forecasts be Improved? An Application to the U.S. Hog Market," 2008 Conference, April 21-22, 2008, St. Louis, Missouri 37620, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    8. Huang, Tao & Fildes, Robert & Soopramanien, Didier, 2019. "Forecasting retailer product sales in the presence of structural change," European Journal of Operational Research, Elsevier, vol. 279(2), pages 459-470.
    9. Rubaszek, Michal & Skrzypczynski, Pawel, 2008. "On the forecasting performance of a small-scale DSGE model," International Journal of Forecasting, Elsevier, vol. 24(3), pages 498-512.
    10. Edward S. Knotek, 2007. "How useful is Okun's law?," Economic Review, Federal Reserve Bank of Kansas City, vol. 92(Q IV), pages 73-103.
    11. Rossi, Barbara & Sekhposyan, Tatevik, 2010. "Have economic models' forecasting performance for US output growth and inflation changed over time, and when?," International Journal of Forecasting, Elsevier, vol. 26(4), pages 808-835, October.
    12. Karsten R. Gerdrup & Anne Sofie Jore & Christie Smith & Leif Anders Thorsrud, 2009. "Evaluating ensemble density combination - forecasting GDP and inflation," Working Paper 2009/19, Norges Bank.
    13. Albuquerque, Bruno & Baumann, Ursel & Seitz, Franz, 2016. "What does money and credit tell us about real activity in the United States?," The North American Journal of Economics and Finance, Elsevier, vol. 37(C), pages 328-347.
    14. David Hendry & Michael P. Clements, 2010. "Forecasting from Mis-specified Models in the Presence of Unanticipated Location Shifts," Economics Series Working Papers 484, University of Oxford, Department of Economics.

  44. Todd E. Clark & Michael W. McCracken, 2007. "Combining forecasts from nested models," Finance and Economics Discussion Series 2007-43, Board of Governors of the Federal Reserve System (U.S.).

    Cited by:

    1. James H. Stock & Mark W. Watson, 2008. "Phillips Curve Inflation Forecasts," NBER Working Papers 14322, National Bureau of Economic Research, Inc.
    2. Antoine Mandel & Amir Sani, 2017. "A Machine Learning Approach to the Forecast Combination Puzzle," Working Papers halshs-01317974, HAL.
    3. Eric Hillebrand & Tae-Hwy Lee, 2012. "Stein-Rule Estimation and Generalized Shrinkage Methods for Forecasting Using Many Predictors," CREATES Research Papers 2012-18, Department of Economics and Business Economics, Aarhus University.
    4. Avci, Ezgi & Ketter, Wolfgang & van Heck, Eric, 2018. "Managing electricity price modeling risk via ensemble forecasting: The case of Turkey," Energy Policy, Elsevier, vol. 123(C), pages 390-403.
    5. Clark, Todd E. & McCracken, Michael W., 2015. "Nested forecast model comparisons: A new approach to testing equal accuracy," Journal of Econometrics, Elsevier, vol. 186(1), pages 160-177.
    6. Hong, Han & Preston, Bruce, 2012. "Bayesian averaging, prediction and nonnested model selection," Journal of Econometrics, Elsevier, vol. 167(2), pages 358-369.
    7. Todd E. Clark & Michael W. McCracken, 2007. "Averaging forecasts from VARs with uncertain instabilities," Finance and Economics Discussion Series 2007-42, Board of Governors of the Federal Reserve System (U.S.).
    8. 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.
    9. Bordignon, Silvano & Bunn, Derek W. & Lisi, Francesco & Nan, Fany, 2013. "Combining day-ahead forecasts for British electricity prices," Energy Economics, Elsevier, vol. 35(C), pages 88-103.
    10. Hyun Hak Kim, 2013. "Forecasting Macroeconomic Variables Using Data Dimension Reduction Methods: The Case of Korea," Working Papers 2013-26, Economic Research Institute, Bank of Korea.
    11. Leonardo Morales‐Arias & Guilherme V. Moura, 2013. "A conditionally heteroskedastic global inflation model," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 40(4), pages 572-596, August.
    12. Lima, Luiz Renato Regis de Oliveira & Issler, João Victor, 2008. "A panel data approach to economic forecasting: the bias-corrected average forecast," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 668, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    13. Andrea Carriero & Raffaella Giacomini, 2011. "How useful are no-arbitrage restrictions for forecasting the term structure of interest rates?," Post-Print hal-00844809, HAL.
    14. Huiyu Huang & Tae-Hwy Lee, 2010. "To Combine Forecasts or to Combine Information?," Econometric Reviews, Taylor & Francis Journals, vol. 29(5-6), pages 534-570.
    15. 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.
    16. Antoine Mandel & Amir Sani, 2016. "Learning Time-Varying Forecast Combinations," Documents de travail du Centre d'Economie de la Sorbonne 16036r, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Sep 2016.

  45. 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.

    Cited by:

    1. D'Agostino, Antonello & Gambetti, Luca & Giannone, Domenico & Giannone, Domenico, 2009. "Macroeconomic Forecasting and Structural Change," Research Technical Papers 8/RT/09, Central Bank of Ireland.
    2. BRATU SIMIONESCU, Mihaela, 2012. "Two Quantitative Forecasting Methods For Macroeconomic Indicators In Czech Republic," Annals of Spiru Haret University, Economic Series, Universitatea Spiru Haret, vol. 3(1), pages 71-87.
    3. Todd E. Clark & Michael W. McCracken, 2007. "Averaging forecasts from VARs with uncertain instabilities," Finance and Economics Discussion Series 2007-42, Board of Governors of the Federal Reserve System (U.S.).
    4. Kocięcki, Andrzej & Kolasa, Marcin & Rubaszek, Michał, 2012. "A Bayesian method of combining judgmental and model-based density forecasts," Economic Modelling, Elsevier, vol. 29(4), pages 1349-1355.
    5. Çepni, Oğuzhan & Gül, Selçuk & Hacıhasanoğlu, Yavuz Selim & Yılmaz, Muhammed Hasan, 2020. "Global uncertainties and portfolio flow dynamics of the BRICS countries," Research in International Business and Finance, Elsevier, vol. 54(C).

  46. Todd E. Clark & Kenneth D. West, 2005. "Approximately normal tests for equal predictive accuracy in nested models," Research Working Paper RWP 05-05, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Rangan Gupta & Christian Pierdzioch & Aviral K. Tiwari, 2024. "Gasoline Prices and Presidential Approval Ratings of the United States," Working Papers 202427, University of Pretoria, Department of Economics.
    2. Anindya Banerjee & Massimiliano Marcellino, 2008. "Factor-augmented Error Correction Models," Working Papers 335, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    3. Sébastien Laurent & Jeroen V.K. Rombouts & Francesco Violante, 2010. "On the Forecasting Accuracy of Multivariate GARCH Models," Cahiers de recherche 1021, CIRPEE.
    4. Chen, Nan-Kuang & Chen, Shiu-Sheng & Chou, Yu-Hsi, 2013. "Further evidence on bear market predictability: The role of the external finance premium," MPRA Paper 49093, University Library of Munich, Germany.
    5. Gross, Marco, 2011. "Corporate bond spreads and real activity in the euro area - Least Angle Regression forecasting and the probability of the recession," Working Paper Series 1286, European Central Bank.
    6. 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.
    7. Wang, Yudong & Hao, Xianfeng, 2023. "Forecasting the real prices of crude oil: What is the role of parameter instability?," Energy Economics, Elsevier, vol. 117(C).
    8. Yin, Libo & Yang, Sen, 2023. "Oil price returns and firm's fixed investment: A production pattern," Energy Economics, Elsevier, vol. 125(C).
    9. R Naraidoo & I Paya, 2010. "Forecasting Monetary Policy Rules in South Africa," Working Papers 611194, Lancaster University Management School, Economics Department.
    10. Zhang, Li & Wang, Lu & Wang, Xunxiao & Zhang, Yaojie & Pan, Zhigang, 2022. "How macro-variables drive crude oil volatility? Perspective from the STL-based iterated combination method," Resources Policy, Elsevier, vol. 77(C).
    11. Michael J. Dueker & Zacharias Psaradakis & Martin Sola & Fabio Spagnolo, 2013. "State-Dependent Threshold Smooth Transition Autoregressive Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(6), pages 835-854, December.
    12. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2012. "Time-varying Combinations of Predictive Densities using Nonlinear Filtering," Tinbergen Institute Discussion Papers 12-118/III, Tinbergen Institute.
    13. Christian Hutter & Enzo Weber, 2015. "Constructing a new leading indicator for unemployment from a survey among German employment agencies," Applied Economics, Taylor & Francis Journals, vol. 47(33), pages 3540-3558, July.
    14. Viktor Todorov & Yang Zhang, 2022. "Information gains from using short‐dated options for measuring and forecasting volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 368-391, March.
    15. Afees A. Salisu & Ahamuefula E. Ogbonna & Elie Bouri & Rangan Gupta, 2024. "Climate Risks and Prediction of Sectoral REITs Volatility: International Evidence," Working Papers 202434, University of Pretoria, Department of Economics.
    16. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    17. Nasr, Adnen Ben & Lux, Thomas & Ajm, Ahdi Noomen & Gupta, Rangan, 2014. "Forecasting the volatility of the dow jones islamic stock market index: Long memory vs. regime switching," Economics Working Papers 2014-07, Christian-Albrechts-University of Kiel, Department of Economics.
    18. Buncic, Daniel & Gisler, Katja I.M., 2016. "Global equity market volatility spillovers: A broader role for the United States," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1317-1339.
    19. Taylor, Mark, 2014. "Common Macro Factors and Currency Premia," CEPR Discussion Papers 10016, C.E.P.R. Discussion Papers.
    20. David Genesove & James Hansen, 2014. "Predicting Dwelling Prices with Consideration of the Sales Mechanism," RBA Research Discussion Papers rdp2014-09, Reserve Bank of Australia.
    21. Salisu, Afees A. & Akanni, Lateef & Raheem, Ibrahim, 2020. "The COVID-19 global fear index and the predictability of commodity price returns," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    22. Dai, Zhifeng & Dong, Xiaodi & Kang, Jie & Hong, Lianying, 2020. "Forecasting stock market returns: New technical indicators and two-step economic constraint method," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    23. Etienne, Xiaoli, 2015. "Financialization of Agricultural Commodity Markets: Do Financial Data Help to Forecast Agricultural Prices," 2015 Conference, August 9-14, 2015, Milan, Italy 211626, International Association of Agricultural Economists.
    24. Pablo Pincheira, 2008. "Combining Tests of Predictive Ability Theory and Evidence for Chilean and Canadian Exchange Rates," Working Papers Central Bank of Chile 459, Central Bank of Chile.
    25. Chen, Shiu-Sheng, 2013. "Forecasting Crude Oil Price Movements with Oil-Sensitive Stocks," MPRA Paper 49240, University Library of Munich, Germany.
    26. Nicolás Chanut & Mario Marcel C. & Carlos A. Medel V., 2019. "Can economic perception surveys improve macroeconomic forecasting in Chile?," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 22(3), pages 034-097, December.
    27. Ziran Li & Dermot J. Hayes & Keri L. Jacobs, 2018. "The weather premium in the U.S. corn market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(3), pages 359-372, March.
    28. Zhang, Xiaoyun & Guo, Qiang, 2024. "How useful are energy-related uncertainty for oil price volatility forecasting?," Finance Research Letters, Elsevier, vol. 60(C).
    29. Daniele Valenti & Matteo Manera & Alessandro Sbuelz, 2018. "Interpreting the Oil Risk Premium: do Oil Price Shocks Matter?," Working Papers 2018.03, Fondazione Eni Enrico Mattei.
    30. Salisu, Afees A. & Ogbonna, Ahamuefula E. & Vo, Xuan Vinh, 2023. "Oil tail risks and the realized variance of consumer prices in advanced economies," Resources Policy, Elsevier, vol. 83(C).
    31. Zouhaier Dhifaoui & Sami Ben Jabeur & Rabeh Khalfaoui & Muhammad Ali Nasir, 2023. "Time‐varying partial‐directed coherence approach to forecast global energy prices with stochastic volatility model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 2292-2306, December.
    32. Aleksandar Mijatovic & Paul Schneider, 2009. "Empirical asset pricing with nonlinear risk premia," Papers 0911.0928, arXiv.org.
    33. Matteo Bonato & Oğuzhan Çepni & Rangan Gupta & Christian Pierdzioch, 2023. "El Niño, La Niña, and forecastability of the realized variance of agricultural commodity prices: Evidence from a machine learning approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 785-801, July.
    34. Felix Haase, 2024. "Sum-of-the-Parts Revised: Economic Regimes and Flexible Probabilities," Research Papers in Economics 2024-10, University of Trier, Department of Economics.
    35. Carstensen, Kai & Heinrich, Markus & Reif, Magnus & Wolters, Maik H., 2020. "Predicting ordinary and severe recessions with a three-state Markov-switching dynamic factor model," International Journal of Forecasting, Elsevier, vol. 36(3), pages 829-850.
    36. Ron Alquist & Lutz Kilian & Robert J. Vigfusson, 2011. "Forecasting the price of oil," International Finance Discussion Papers 1022, Board of Governors of the Federal Reserve System (U.S.).
    37. Rossi, José Luiz Júnior, 2013. "Liquidity and Exchange Rates," Insper Working Papers wpe_325, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    38. Ivana Komunjer & Michael T. Owyang, 2012. "Multivariate Forecast Evaluation and Rationality Testing," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1066-1080, November.
    39. Cao, Charles & Simin, Timothy & Xiao, Han, 2019. "Predicting the equity premium with the implied volatility spread," MPRA Paper 103651, University Library of Munich, Germany.
    40. Lu, Fei & Ma, Feng & Bouri, Elie & Liao, Yin, 2024. "Do commodity futures have a steering effect on the spot stock market in China? New evidence from volatility forecasting," International Review of Financial Analysis, Elsevier, vol. 94(C).
    41. Salisu, Afees A. & Ogbonna, Ahamuefula E. & Adewuyi, Adeolu, 2020. "Google trends and the predictability of precious metals," Resources Policy, Elsevier, vol. 65(C).
    42. Ghani, Usman & Zhu, Bo & Ghani, Maria & Khan, Nasir & khan, Raja Danish Akbar, 2023. "Role of oil shocks in US stock market volatility: A new insight from GARCH-MIDAS perspective," Resources Policy, Elsevier, vol. 85(PB).
    43. Batten, Jonathan A. & Ciner, Cetin & Lucey, Brian M., 2017. "The dynamic linkages between crude oil and natural gas markets," Energy Economics, Elsevier, vol. 62(C), pages 155-170.
    44. David Iselin & Boriss Siliverstovs, 2013. "Using Newspapers for Tracking the Business Cycle," KOF Working papers 13-337, KOF Swiss Economic Institute, ETH Zurich.
    45. Afees A. Salisu & Rangan Gupta, 2019. "How do Housing Returns in Emerging Countries Respond to Oil Shocks? A MIDAS Touch," Working Papers 201946, University of Pretoria, Department of Economics.
    46. Yin, Anwen, 2015. "Forecasting and model averaging with structural breaks," ISU General Staff Papers 201501010800005727, Iowa State University, Department of Economics.
    47. Wen, Danyan & Liu, Li & Wang, Yudong & Zhang, Yaojie, 2022. "Forecasting crude oil market returns: Enhanced moving average technical indicators," Resources Policy, Elsevier, vol. 76(C).
    48. Launhardt, Patrick & Miebs, Felix, 2020. "Aggregate implied cost of capital, option-implied information and equity premium predictability," Finance Research Letters, Elsevier, vol. 35(C).
    49. 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.
    50. Takeshi Kobayashi, 2021. "Common Factors in the Term Structure of Credit Spreads and Predicting the Macroeconomy in Japan," IJFS, MDPI, vol. 9(2), pages 1-12, April.
    51. Dai, Zhifeng & Zhu, Huan, 2020. "Stock return predictability from a mixed model perspective," Pacific-Basin Finance Journal, Elsevier, vol. 60(C).
    52. Afees A. Salisu & Juncal Cunado & Kazeem Isah & Rangan Gupta, 2020. "Stock Markets and Exchange Rate Behaviour of the BRICS," Working Papers 202086, University of Pretoria, Department of Economics.
    53. Wu, Lan & Xu, Weiju & Huang, Dengshi & Li, Pan, 2022. "Does the volatility spillover effect matter in oil price volatility predictability? Evidence from high-frequency data," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 299-306.
    54. Robert Lehmann & Antje Weyh, 2016. "Forecasting Employment in Europe: Are Survey Results Helpful?," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(1), pages 81-117, September.
    55. Salisu, Afees A. & Ndako, Umar B. & Vo, Xuan Vinh, 2023. "Oil price and the Bitcoin market," Resources Policy, Elsevier, vol. 82(C).
    56. Kappler, Marcus & Schleer, Frauke, 2017. "A financially stressed euro area," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 11, pages 1-37.
    57. Zhang, Jiaming & Xiang, Yitian & Zou, Yang & Guo, Songlin, 2024. "Volatility forecasting of Chinese energy market: Which uncertainty have better performance?," International Review of Financial Analysis, Elsevier, vol. 91(C).
    58. Hashmat Khan & Santosh Upadhayaya, 2017. "Does Business Confidence Matter for Investment?," Carleton Economic Papers 17-13, Carleton University, Department of Economics, revised 20 Mar 2019.
    59. Christophe Amat & Tomasz Michalski & Gilles Stoltz, 2018. "Fundamentals and exchange rate forecastability with simple machine learning methods," Working Papers halshs-01003914, HAL.
    60. Bonato, Matteo & Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian, 2021. "A note on investor happiness and the predictability of realized volatility of gold," Finance Research Letters, Elsevier, vol. 39(C).
    61. Felix Haase & Matthias Neuenkirch, 2020. "Predictability of Bull and Bear Markets: A New Look at Forecasting Stock Market Regimes (and Returns) in the US," Working Paper Series 2020-03, University of Trier, Research Group Quantitative Finance and Risk Analysis.
    62. Kuppenheimer, Gregory & Shelly, Stuart & Strauss, Jack, 2023. "Can machine learning identify sector-level financial ratios that predict sector returns?," Finance Research Letters, Elsevier, vol. 57(C).
    63. Yan Carrière-Swallow & Felipe Labbé, 2010. "Nowcasting With Google Trends in an Emerging Market," Working Papers Central Bank of Chile 588, Central Bank of Chile.
    64. Zhao, Albert Bo & Cheng, Tingting, 2022. "Stock return prediction: Stacking a variety of models," Journal of Empirical Finance, Elsevier, vol. 67(C), pages 288-317.
    65. Eric Ghysels & Leonardo Iania & Jonas Striaukas, 2018. "Quantile-based Inflation Risk Models," Working Paper Research 349, National Bank of Belgium.
    66. Carlos Medel & Michael Pedersen & Pablo Pincheira, 2014. "The Elusive Predictive Ability of Global Inflation," Working Papers Central Bank of Chile 725, Central Bank of Chile.
    67. Pablo Pincheira & Andrés Gatty, 2016. "Forecasting Chilean inflation with international factors," Empirical Economics, Springer, vol. 51(3), pages 981-1010, November.
    68. Andrea Monticini & Francesco Ravazzolo, 2014. "Forecasting the intraday market price of money," DISCE - Working Papers del Dipartimento di Economia e Finanza def010, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    69. Barbara Rossi, 2013. "Exchange Rate Predictability," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1063-1119, December.
    70. He, Qing & Liu, Junyi & Gan, Jingyun & Qian, Zongxin, 2019. "Systemic financial risk and macroeconomic activity in China," Journal of Economics and Business, Elsevier, vol. 102(C), pages 57-63.
    71. Robert Lehmann, 2016. "Economic Growth and Business Cycle Forecasting at the Regional Level," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 65.
    72. Galvão, Ana Beatriz, 2013. "Changes in predictive ability with mixed frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 395-410.
    73. Pesenti, Paolo & Groen, Jan J. J., 2010. "Commodity prices, commodity currencies, and global economic developments," CEPR Discussion Papers 7689, C.E.P.R. Discussion Papers.
    74. Yabei Zhu & Xingguo Luo & Qi Xu, 2023. "Industry variance risk premium, cross‐industry correlation, and expected returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(1), pages 3-32, January.
    75. Chao Liang & Yu Wei & Likun Lei & Feng Ma, 2022. "Global equity market volatility forecasting: New evidence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 594-609, January.
    76. Salisu, Afees & Ogbonna, Ahamuefula & Oloko, Tirimisiyu, 2020. "Pandemics and cryptocurrencies," MPRA Paper 109597, University Library of Munich, Germany.
    77. Charles Engel & Nelson C. Mark & Kenneth D. West, 2008. "Exchange Rate Models Are Not as Bad as You Think," NBER Chapters, in: NBER Macroeconomics Annual 2007, Volume 22, pages 381-441, National Bureau of Economic Research, Inc.
    78. Ye, Wuyi & Xia, Wenjing & Wu, Bin & Chen, Pengzhan, 2022. "Using implied volatility jumps for realized volatility forecasting: Evidence from the Chinese market," International Review of Financial Analysis, Elsevier, vol. 83(C).
    79. Wang, Yudong & Hao, Xianfeng & Wu, Chongfeng, 2021. "Forecasting stock returns: A time-dependent weighted least squares approach," Journal of Financial Markets, Elsevier, vol. 53(C).
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    81. Xi Dong & Yan Li & David E. Rapach & Guofu Zhou, 2022. "Anomalies and the Expected Market Return," Journal of Finance, American Finance Association, vol. 77(1), pages 639-681, February.
    82. Wang, Xiaohu & Xiao, Weilin & Yu, Jun, 2023. "Modeling and forecasting realized volatility with the fractional Ornstein–Uhlenbeck process," Journal of Econometrics, Elsevier, vol. 232(2), pages 389-415.
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    96. Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2024. "Forecasting Realized US Stock Market Volatility: Is there a Role for Economic Policy Uncertainty?," Working Papers 202408, University of Pretoria, Department of Economics.
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    1186. Salisu, Afees A. & Ndako, Umar B. & Vo, Xuan Vinh, 2023. "Transition risk, physical risk, and the realized volatility of oil and natural gas prices," Resources Policy, Elsevier, vol. 81(C).

  47. Todd E. Clark & Kenneth D. West, 2005. "Using Out-of-Sample Mean Squared Prediction Errors to Test the Martingale Difference," NBER Technical Working Papers 0305, National Bureau of Economic Research, Inc.

    Cited by:

    1. Adriana Fernandez & Evan F. Koenig & Alex Nikolsko-Rzhevskyy, 2011. "A real-time historical database for the OECD," Globalization Institute Working Papers 96, Federal Reserve Bank of Dallas.
    2. Lees, Kirdan & Matheson, Troy, 2007. "Mind your ps and qs! Improving ARMA forecasts with RBC priors," Economics Letters, Elsevier, vol. 96(2), pages 275-281, August.
    3. West, Kenneth D., 2006. "Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 3, pages 99-134, Elsevier.
    4. Kenneth D. West & Todd Clark, 2006. "Approximately Normal Tests for Equal Predictive Accuracy in Nested Models," NBER Technical Working Papers 0326, National Bureau of Economic Research, Inc.
    5. Carstensen, Kai & Wohlrabe, Klaus & Ziegler, Christina, 2011. "Predictive ability of business cycle indicators under test: A case study for the Euro area industrial production," Munich Reprints in Economics 19953, University of Munich, Department of Economics.
    6. Campbell, John & Thompson, Samuel P., 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," Scholarly Articles 2622619, Harvard University Department of Economics.
    7. Onur Ince & Tanya Molodtsova, 2013. "Real-Time Out-of-Sample Exchange Rate Predictability," Working Papers 13-03, Department of Economics, Appalachian State University.
    8. Ana María Abarca & Felipe Alarcón & Pablo Pincheira & Jorge Selaive, 2007. "Chilean Nominal Exchange Rate: Forecasting Based Upon Technical Analysis," Working Papers Central Bank of Chile 425, Central Bank of Chile.
    9. Jacob Boudoukh & Matthew Richardson & Robert Whitelaw, 2005. "The Information in Long-Maturity Forward Rates: Implications for Exchange Rates and the Forward Premium Anomaly," NBER Working Papers 11840, National Bureau of Economic Research, Inc.

  48. Todd E. Clark & Michael W. McCracken, 2004. "Improving forecast accuracy by combining recursive and rolling forecasts," Research Working Paper RWP 04-10, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Pesaran, M.H. & Pick, A., 2008. "Forecasting Random Walks Under Drift Instability," Cambridge Working Papers in Economics 0814, Faculty of Economics, University of Cambridge.
    2. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    3. Andrea Bastianin & Matteo Manera, 2020. "A test of time reversibility based on Lmoments with an application to the business cycles of the G7 economies," Working Papers 445, University of Milano-Bicocca, Department of Economics, revised Jun 2020.
    4. Zhao, Albert Bo & Cheng, Tingting, 2022. "Stock return prediction: Stacking a variety of models," Journal of Empirical Finance, Elsevier, vol. 67(C), pages 288-317.
    5. Fotis Papailias & Dimitrios Thomakos, 2015. "Covariance averaging for improved estimation and portfolio allocation," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 29(1), pages 31-59, February.
    6. Chen, Guojin & Liu, Yanzhen & Zhang, Yu, 2020. "Can systemic risk measures predict economic shocks? Evidence from China," China Economic Review, Elsevier, vol. 64(C).
    7. 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.
    8. Cho, Dooyeon, 2021. "On the predictability of the distribution of excess returns in currency markets," International Journal of Forecasting, Elsevier, vol. 37(2), pages 511-530.
    9. Rodolfo C. Moura & Márcio P. Laurini, 2021. "Spillovers and jumps in global markets: A comparative analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5997-6013, October.
    10. Jeongwoo Kim, 2019. "Optimally adjusted last cluster for prediction based on balancing the bias and variance by bootstrapping," PLOS ONE, Public Library of Science, vol. 14(11), pages 1-31, November.
    11. Craig S. Hakkio, 2008. "PCE and CPI inflation differentials: converting inflation forecasts," Economic Review, Federal Reserve Bank of Kansas City, vol. 93(Q I), pages 51-68.
    12. Zhao, Huiru & Guo, Sen, 2016. "An optimized grey model for annual power load forecasting," Energy, Elsevier, vol. 107(C), pages 272-286.
    13. Tan, Pei P. & Galagedera, Don U.A. & Maharaj, Elizabeth A., 2012. "A wavelet based investigation of long memory in stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(7), pages 2330-2341.
    14. Barnett, Alina & Mumtaz, Haroon & Theodoridis, Konstantinos, 2014. "Forecasting UK GDP growth and inflation under structural change. A comparison of models with time-varying parameters," International Journal of Forecasting, Elsevier, vol. 30(1), pages 129-143.
    15. Scott Brave & Charles S. Gascon & William Kluender & Thomas Walstrum, 2019. "Predicting Benchmarked US State Employment Data in Realtime," Working Paper Series WP 2019-11, Federal Reserve Bank of Chicago.
    16. Jana Eklund & George Kapetanios & Simon Price, 2013. "Robust Forecast Methods and Monitoring during Structural Change," Manchester School, University of Manchester, vol. 81, pages 3-27, October.
    17. Henzel, Steffen R. & Mayr, Johannes, 2013. "The mechanics of VAR forecast pooling—A DSGE model based Monte Carlo study," The North American Journal of Economics and Finance, Elsevier, vol. 24(C), pages 1-24.
    18. Luc Bauwens & Gary Koop & Dimitris Korobilis & Jeroen V.K. Rombouts, 2011. "The Contribution of Structural Break Models to Forecasting Macroeconomic Series," Working Paper series 38_11, Rimini Centre for Economic Analysis.
    19. Ke Yang & Langnan Chen & Fengping Tian, 2015. "Realized Volatility Forecast of Stock Index Under Structural Breaks," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(1), pages 57-82, January.
    20. Xiaojie Xu, 2020. "Corn Cash Price Forecasting," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(4), pages 1297-1320, August.
    21. 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.
    22. 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.
    23. Wu, Jyh-Lin & Wang, Yi-Chiuan, 2013. "Fundamentals, forecast combinations and nominal exchange-rate predictability," International Review of Economics & Finance, Elsevier, vol. 25(C), pages 129-145.
    24. Knut Are Aastveit & Karsten R. Gerdrup & Anne Sofie Jore & Leif Anders Thorsrud, 2011. "Nowcasting GDP in real-time: A density combination approach," Working Paper 2011/11, Norges Bank.
    25. Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2010. "Out-of-sample equity premium prediction: economic fundamentals vs. moving-average rules," Working Papers 2010-008, Federal Reserve Bank of St. Louis.
    26. Torben G. Andersen & Rasmus T. Varneskov, 2021. "Testing for Parameter Instability and Structural Change in Persistent Predictive Regressions," NBER Working Papers 28570, National Bureau of Economic Research, Inc.
    27. Giovannelli, Alessandro & Massacci, Daniele & Soccorsi, Stefano, 2021. "Forecasting stock returns with large dimensional factor models," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 252-269.
    28. Fabio Busetti & Juri Marcucci & Giovanni Veronese, 2009. "Comparing forecast accuracy: A Monte Carlo investigation," Temi di discussione (Economic working papers) 723, Bank of Italy, Economic Research and International Relations Area.
    29. Stavroula P. Fameliti & Vasiliki D. Skintzi, 2020. "Predictive ability and economic gains from volatility forecast combinations," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 200-219, March.
    30. Ahmed, Shamim & Liu, Xiaoquan & Valente, Giorgio, 2016. "Can currency-based risk factors help forecast exchange rates?," International Journal of Forecasting, Elsevier, vol. 32(1), pages 75-97.
    31. Knut Are Aastveit & Francesco Ravazzolo & Herman K. van Dijk, 2014. "Combined Density Nowcasting in an Uncertain Economic Environment," Tinbergen Institute Discussion Papers 14-152/III, Tinbergen Institute.
    32. Andre Jungmittag, 2016. "Combination of Forecasts across Estimation Windows: An Application to Air Travel Demand," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(4), pages 373-380, July.
    33. Rubaszek Michal & Karolak Zuzanna & Kwas Marek & Uddin Gazi Salah, 2020. "The role of the threshold effect for the dynamics of futures and spot prices of energy commodities," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(5), pages 1-20, December.
    34. Todd E. Clark & Michael W. McCracken, 2007. "Averaging forecasts from VARs with uncertain instabilities," Finance and Economics Discussion Series 2007-42, Board of Governors of the Federal Reserve System (U.S.).
    35. Atsushi Inoue & Barbara Rossi, 2011. "Out-of-sample forecast tests robust to the choice of window size," Working Papers 11-31, Federal Reserve Bank of Philadelphia.
    36. Charles Hoffreumon & Nicolas van Zeebroeck, 2018. "Forecasting short-term transaction fees on a smart contracts platform," Working Papers TIMES² 2018-028, ULB -- Universite Libre de Bruxelles.
    37. Melo, Luis F. & Loaiza, Rubén A. & Villamizar-Villegas, Mauricio, 2016. "Bayesian combination for inflation forecasts: The effects of a prior based on central banks’ estimates," Economic Systems, Elsevier, vol. 40(3), pages 387-397.
    38. Todd E. Clark & Kenneth D. West, 2004. "Using out-of-sample mean squared prediction errors to test the Martingale difference hypothesis," Research Working Paper RWP 04-03, Federal Reserve Bank of Kansas City.
    39. Norman R. Swanson & Weiqi Xiong & Xiye Yang, 2020. "Predicting interest rates using shrinkage methods, real‐time diffusion indexes, and model combinations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(5), pages 587-613, August.
    40. Zihui Yang & Yinggang Zhou, 2017. "Quantitative Easing and Volatility Spillovers Across Countries and Asset Classes," Management Science, INFORMS, vol. 63(2), pages 333-354, February.
    41. Cai, Zongwu & Juhl, Ted, 2023. "The distribution of rolling regression estimators," Journal of Econometrics, Elsevier, vol. 235(2), pages 1447-1463.
    42. David E. Rapach & Jack K. Strauss, 2008. "Structural breaks and GARCH models of exchange rate volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 65-90.
    43. Colino, Evelyn V. & Irwin, Scott H. & Garcia, Philip, 2008. "How Much Can Outlook Forecasts be Improved? An Application to the U.S. Hog Market," 2008 Conference, April 21-22, 2008, St. Louis, Missouri 37620, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    44. Mihaela SIMIONESCU, 2014. "Improving The Inflation Rate Forecasts Of Romanian Experts Using A Fixed-Effects Models Approach," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 13, pages 87-102, June.
    45. Liao, Xiangcheng & Mahmoud, Ali & Hu, Tiesong & Wang, Jinglin, 2022. "A novel irrigation canal scheduling model adaptable to the spatial-temporal variability of water conveyance loss," Agricultural Water Management, Elsevier, vol. 274(C).
    46. Vellachami, Sanggetha & Hasanov, Akram Shavkatovich & Brooks, Robert, 2023. "Risk transmission from the energy markets to the carbon market: Evidence from the recursive window approach," International Review of Financial Analysis, Elsevier, vol. 89(C).
    47. Yusui Tang & Feng Ma & Yaojie Zhang & Yu Wei, 2022. "Forecasting the oil price realized volatility: A multivariate heterogeneous autoregressive model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4770-4783, October.
    48. Calista Cheung & Frédérick Demers, 2007. "Evaluating Forecasts from Factor Models for Canadian GDP Growth and Core Inflation," Staff Working Papers 07-8, Bank of Canada.
    49. Zongwu Cai & Ted Juhl, 2020. "The Distribution Of Rolling Regression Estimators," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202218, University of Kansas, Department of Economics, revised Dec 2022.
    50. Wang, Yudong & Pan, Zhiyuan & Liu, Li & Wu, Chongfeng, 2019. "Oil price increases and the predictability of equity premium," Journal of Banking & Finance, Elsevier, vol. 102(C), pages 43-58.
    51. Damiano B. Silipo & Giovanni Verga & Sviatlana Hlebik, 2023. "Managerial Beliefs and Banking Behavior," Journal of Financial Services Research, Springer;Western Finance Association, vol. 64(3), pages 401-431, December.
    52. Stephen G. Hall & George S. Tavlas & Yongli Wang & Deborah Gefang, 2024. "Inflation forecasting with rolling windows: An appraisal," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(4), pages 827-851, July.
    53. Marie Bessec, 2010. "Étalonnages du taux de croissance du PIB français sur la base des enquêtes de conjoncture," Économie et Prévision, Programme National Persée, vol. 193(2), pages 77-99.
    54. Leung, Charles Ka Yui & Tang, Edward Chi Ho, 2014. "Availability, Affordability and Volatility: the case of Hong Kong Housing Market," MPRA Paper 58770, University Library of Munich, Germany.
    55. Davide De Gaetano, 2018. "Forecast Combinations in the Presence of Structural Breaks: Evidence from U.S. Equity Markets," Mathematics, MDPI, vol. 6(3), pages 1-19, March.
    56. Isao Ishida & Virmantas Kvedaras, 2015. "Modeling Autoregressive Processes with Moving-Quantiles-Implied Nonlinearity," Econometrics, MDPI, vol. 3(1), pages 1-53, January.
    57. Yaojie Zhang & Yudong Wang & Feng Ma & Yu Wei, 2022. "To jump or not to jump: momentum of jumps in crude oil price volatility prediction," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-31, December.
    58. Caldeira, João F. & Moura, Guilherme V. & Santos, André A.P., 2016. "Predicting the yield curve using forecast combinations," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 79-98.
    59. Mayr, Johannes, 2010. "Forecasting Macroeconomic Aggregates," Munich Dissertations in Economics 11140, University of Munich, Department of Economics.
    60. PERRON, Pierre & YAMAMOTO, Yohei & 山本, 庸平, 2018. "Testing for Changes in Forecasting Performance," Discussion Papers 2018-03, Graduate School of Economics, Hitotsubashi University.
    61. Jianying Xie, 2021. "A New Multivariate Predictive Model for Stock Returns," Papers 2110.01873, arXiv.org.
    62. Karim Barhoumi & Olivier Darné & Laurent Ferrara, 2010. "Are disaggregate data useful for factor analysis in forecasting French GDP?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 132-144.
    63. João F. Caldeira & Rangan Gupta & Hudson S. Torrent, 2020. "Forecasting U.S. Aggregate Stock Market Excess Return: Do Functional Data Analysis Add Economic Value?," Mathematics, MDPI, vol. 8(11), pages 1-16, November.
    64. Aristidou, Chrystalleni & Lee, Kevin & Shields, Kalvinder, 2022. "Fundamentals, regimes and exchange rate forecasts: Insights from a meta exchange rate model," Journal of International Money and Finance, Elsevier, vol. 123(C).
    65. Niu, Zibo & Demirer, Riza & Suleman, Muhammad Tahir & Zhang, Hongwei & Zhu, Xuehong, 2024. "Do industries predict stock market volatility? Evidence from machine learning models," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 90(C).
    66. Sun, Yuying & Hong, Yongmiao & Wang, Shouyang & Zhang, Xinyu, 2023. "Penalized time-varying model averaging," Journal of Econometrics, Elsevier, vol. 235(2), pages 1355-1377.
    67. Hyun Hak Kim & Norman Swanson, 2013. "Mining Big Data Using Parsimonious Factor and Shrinkage Methods," Departmental Working Papers 201316, Rutgers University, Department of Economics.
    68. Kapetanios, George & Labhard, Vincent & Price, Simon, 2008. "Forecast combination and the Bank of England's suite of statistical forecasting models," Economic Modelling, Elsevier, vol. 25(4), pages 772-792, July.
    69. Todd E. Clark & Kenneth D. West, 2005. "Using Out-of-Sample Mean Squared Prediction Errors to Test the Martingale Difference," NBER Technical Working Papers 0305, National Bureau of Economic Research, Inc.
    70. Davide De Gaetano, 2018. "Forecast Combinations for Structural Breaks in Volatility: Evidence from BRICS Countries," JRFM, MDPI, vol. 11(4), pages 1-13, October.
    71. Morales-Arias, Leonardo & Moura, Guilherme V., 2013. "Adaptive forecasting of exchange rates with panel data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 493-509.
    72. 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.
    73. Weijia Peng & Chun Yao, 2023. "Sector-level equity returns predictability with machine learning and market contagion measure," Empirical Economics, Springer, vol. 65(4), pages 1761-1798, October.
    74. Bennett, Donyetta & Mekelburg, Erik & Strauss, Jack & Williams, T.H., 2024. "Unlocking the black box of sentiment and cryptocurrency: What, which, why, when and how?," Global Finance Journal, Elsevier, vol. 60(C).
    75. Benjamin Garcia & Arsenios Skaperdas, 2017. "Inferring the Shadow Rate from Real Activity," Finance and Economics Discussion Series 2017-106, Board of Governors of the Federal Reserve System (U.S.).
    76. 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.
    77. Ming-Chih Lee & Chien-Liang Chiu & Wan-Hsiu Cheng, 2007. "Enhancing Forecast Accuracy By Using Long Estimation Periods," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 1(2), pages 1-9.
    78. Zhang, Zhikai & He, Mengxi & Zhang, Yaojie & Wang, Yudong, 2021. "Realized skewness and the short-term predictability for aggregate stock market volatility," Economic Modelling, Elsevier, vol. 103(C).
    79. Chanont Banternghansa & Michael W. McCracken, 2011. "Real-time forecast averaging with ALFRED," Review, Federal Reserve Bank of St. Louis, vol. 93(Jan), pages 49-66.
    80. Johannes Mayr & Dirk Ulbricht, 2007. "VAR Model Averaging for Multi-Step Forecasting," ifo Working Paper Series 48, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    81. Davide De Gaetano, 2017. "Forecasting With Garch Models Under Structural Breaks: An Approach Based On Combinations Across Estimation Windows," Departmental Working Papers of Economics - University 'Roma Tre' 0219, Department of Economics - University Roma Tre.
    82. Colino, Evelyn V. & Irwin, Scott H. & Garcia, Philip & Etienne, Xiaoli, 2012. "Composite and Outlook Forecast Accuracy," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 37(2), pages 1-19, August.
    83. Yaojie Zhang & Feng Ma & Chao Liang & Yi Zhang, 2021. "Good variance, bad variance, and stock return predictability," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4410-4423, July.
    84. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 328-383, Elsevier.
    85. Graziano Moramarco, 2022. "Measuring Global Macroeconomic Uncertainty and Cross-Country Uncertainty Spillovers," Econometrics, MDPI, vol. 11(1), pages 1-29, December.
    86. Yuqing Feng & Yaojie Zhang & Yudong Wang, 2024. "Out‐of‐sample volatility prediction: Rolling window, expanding window, or both?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(3), pages 567-582, April.
    87. Prasad S Bhattacharya & Dimitrios D Thomakos, 2011. "Improving forecasting performance by window and model averaging," CAMA Working Papers 2011-05, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    88. Wei, Jie & Zhang, Yonghui, 2020. "A time-varying diffusion index forecasting model," Economics Letters, Elsevier, vol. 193(C).
    89. Dellas, Harris & Gibson, Heather D. & Hall, Stephen G. & Tavlas, George S., 2018. "The macroeconomic and fiscal implications of inflation forecast errors," Journal of Economic Dynamics and Control, Elsevier, vol. 93(C), pages 203-217.
    90. Chen, Guojin & Liu, Yanzhen & Zhang, Yu, 2021. "Systemic risk measures and distribution forecasting of macroeconomic shocks," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 178-196.
    91. David Hendry & Michael P. Clements, 2010. "Forecasting from Mis-specified Models in the Presence of Unanticipated Location Shifts," Economics Series Working Papers 484, University of Oxford, Department of Economics.

  49. Todd E. Clark & Kenneth D. West, 2004. "Using out-of-sample mean squared prediction errors to test the Martingale difference hypothesis," Research Working Paper RWP 04-03, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Frédérick Demers & Annie De Champlain, 2005. "Forecasting Core Inflation in Canada: Should We Forecast the Aggregate or the Components?," Staff Working Papers 05-44, Bank of Canada.
    2. Juan José Echavarría & Mauricio Villamizar, 2012. "Great expectations? Evidence from Colombia’s exchange rate survey," Borradores de Economia 735, Banco de la Republica de Colombia.
    3. Sébastien Laurent & Jeroen V.K. Rombouts & Francesco Violante, 2010. "On the Forecasting Accuracy of Multivariate GARCH Models," Cahiers de recherche 1021, CIRPEE.
    4. Tausch, Arno, 2013. "The hallmarks of crisis. A new center-periphery perspective on long cycles," MPRA Paper 48356, University Library of Munich, Germany.
    5. Tobias Adrian & Erkko Etula & Jan J. J. Groen, 2010. "Financial amplification of foreign exchange risk premia," Staff Reports 461, Federal Reserve Bank of New York.
    6. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    7. Engel, Charles & Wu, Steve Pak Yeung, 2023. "Liquidity and Exchange Rates: An Empirical Investigation," University of California at San Diego, Economics Working Paper Series qt4z80w6cd, Department of Economics, UC San Diego.
    8. Benjamin K. Johannsen & Elmar Mertens, 2016. "A Time Series Model of Interest Rates With the Effective Lower Bound," Finance and Economics Discussion Series 2016-033, Board of Governors of the Federal Reserve System (U.S.).
    9. Ron Alquist & Lutz Kilian, 2010. "What do we learn from the price of crude oil futures?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 539-573.
    10. Pablo Pincheira, 2008. "Combining Tests of Predictive Ability Theory and Evidence for Chilean and Canadian Exchange Rates," Working Papers Central Bank of Chile 459, Central Bank of Chile.
    11. Jiahan Li & Ilias Tsiakas & Wei Wang, 2015. "Predicting Exchange Rates Out of Sample: Can Economic Fundamentals Beat the Random Walk?," Journal of Financial Econometrics, Oxford University Press, vol. 13(2), pages 293-341.
    12. Cheung, Yin-Wong & Chinn, Menzie D. & Pascual, Antonio Garcia & Zhang, Yi, 2019. "Exchange rate prediction redux: New models, new data, new currencies," Journal of International Money and Finance, Elsevier, vol. 95(C), pages 332-362.
    13. Philippe Bacchetta & Eric van Wincoop, 2009. "On the Unstable Relationship between Exchange Rates and Macroeconomic Fundamentals," Working Papers 272009, Hong Kong Institute for Monetary Research.
    14. Liu, Xiaochun, 2015. "Modeling time-varying skewness via decomposition for out-of-sample forecast," International Journal of Forecasting, Elsevier, vol. 31(2), pages 296-311.
    15. de Souza Vasconcelos, Camila & Hadad Júnior, Eli, 2023. "Forecasting exchange rate: A bibliometric and content analysis," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 607-628.
    16. Ron Alquist & Lutz Kilian & Robert J. Vigfusson, 2011. "Forecasting the price of oil," International Finance Discussion Papers 1022, Board of Governors of the Federal Reserve System (U.S.).
    17. Rossi, José Luiz Júnior, 2013. "Liquidity and Exchange Rates," Insper Working Papers wpe_325, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    18. Ivana Komunjer & Michael T. Owyang, 2012. "Multivariate Forecast Evaluation and Rationality Testing," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1066-1080, November.
    19. Batten, Jonathan A. & Ciner, Cetin & Lucey, Brian M., 2017. "The dynamic linkages between crude oil and natural gas markets," Energy Economics, Elsevier, vol. 62(C), pages 155-170.
    20. Charles Engel & Steve Pak Yeung Wu, 2021. "Forecasting the U.S. Dollar in the 21st Century," NBER Working Papers 28447, National Bureau of Economic Research, Inc.
    21. Charles Engel & Dohyeon Lee & Chang Liu & Chenxin Liu & Steve Pak Yeung Wu, 2017. "The Uncovered Interest Parity Puzzle, Exchange Rate Forecasting, and Taylor Rules," NBER Working Papers 24059, National Bureau of Economic Research, Inc.
    22. Christophe Amat & Tomasz Michalski & Gilles Stoltz, 2018. "Fundamentals and exchange rate forecastability with simple machine learning methods," Working Papers halshs-01003914, HAL.
    23. Engel, Charles, 2014. "Exchange Rates and Interest Parity," Handbook of International Economics, in: Gopinath, G. & Helpman, . & Rogoff, K. (ed.), Handbook of International Economics, edition 1, volume 4, chapter 0, pages 453-522, Elsevier.
    24. Pablo Pincheira & Andrés Gatty, 2016. "Forecasting Chilean inflation with international factors," Empirical Economics, Springer, vol. 51(3), pages 981-1010, November.
    25. Barbara Rossi, 2013. "Exchange Rate Predictability," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1063-1119, December.
    26. Ana María Abarca G. & Felipe Alarcón G. & Pablo Pincheira B. & Jorge Selaive C., 2007. "Nominal Exchange Rate in Chile: Predictions based on technical analysis," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 10(2), pages 57-80, August.
    27. Caraiani, Petre, 2017. "Evaluating exchange rate forecasts along time and frequency," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 60-81.
    28. Pesenti, Paolo & Groen, Jan J. J., 2010. "Commodity prices, commodity currencies, and global economic developments," CEPR Discussion Papers 7689, C.E.P.R. Discussion Papers.
    29. Charles Engel & Nelson C. Mark & Kenneth D. West, 2008. "Exchange Rate Models Are Not as Bad as You Think," NBER Chapters, in: NBER Macroeconomics Annual 2007, Volume 22, pages 381-441, National Bureau of Economic Research, Inc.
    30. Erkko Etula, 2013. "Broker-Dealer Risk Appetite and Commodity Returns," Journal of Financial Econometrics, Oxford University Press, vol. 11(3), pages 486-521, June.
    31. Darvas, Zsolt & Schepp, Zoltán, 2024. "Exchange rates and fundamentals: Forecasting with long maturity forward rates," Journal of International Money and Finance, Elsevier, vol. 143(C).
    32. Pierre-Olivier Gourinchas & Hélène Rey, 2007. "International Financial Adjustment," Journal of Political Economy, University of Chicago Press, vol. 115(4), pages 665-703, August.
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    26. Matteo Cacciatore & Bruno Feunou & Galip Kemal Ozhan, 2024. "The Neutral Interest Rate: Past, Present and Future," Discussion Papers 2024-03, Bank of Canada.
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    38. John V. Duca & Tao Wu, 2009. "Regulation and the Neo‐Wicksellian Approach to Monetary Policy," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(4), pages 799-807, June.
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    48. Jean-Stephane Mesonnier, 2011. "The forecasting power of real interest rate gaps: an assessment for the Euro area," Applied Economics, Taylor & Francis Journals, vol. 43(2), pages 153-172.
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    50. Krustev, Georgi, 2019. "The natural rate of interest and the financial cycle," Journal of Economic Behavior & Organization, Elsevier, vol. 162(C), pages 193-210.
    51. Roman Horváth, 2007. "Estimating Time-Varying Policy Neutral Rate in Real Time," Working Papers IES 2007/01, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Jan 2007.
    52. James D. Hamilton & Ethan S. Harris & Jan Hatzius & Kenneth D. West, 2015. "The Equilibrium Real Funds Rate: Past, Present and Future," NBER Working Papers 21476, National Bureau of Economic Research, Inc.
    53. Feng Zhu, 2016. "A spectral perspective on natural interest rates in Asia-Pacific: changes and possible drivers," BIS Papers chapters, in: Bank for International Settlements (ed.), Expanding the boundaries of monetary policy in Asia and the Pacific, volume 88, pages 63-149, Bank for International Settlements.
    54. Enrico S. Levrero, 2019. "Estimates of the Natural Rate of Interest and the Stance of Monetary Policies: A Critical Assessment," Working Papers Series 88, Institute for New Economic Thinking.
    55. Ladislav Wintr & Paolo Guarda & Abdelaziz Rouabah, 2005. "Estimating the natural interest rate for the euro area and Luxembourg," BCL working papers 15, Central Bank of Luxembourg.
    56. Sharon Kozicki & Peter A. Tinsley, 2005. "Minding the gap : central bank estimates of the unemployment natural rate," Research Working Paper RWP 05-03, Federal Reserve Bank of Kansas City.
    57. FARAYIBI, Adesoji, 2016. "Stress Testing in the Nigerian Banking Sector," MPRA Paper 73615, University Library of Munich, Germany.
    58. Jens Klose, 2018. "Equilibrium Real Interest Rates for the BRICS Countries," MAGKS Papers on Economics 201814, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    59. Athanasios Orphanides & John C. Williams, 2007. "Robust monetary policy with imperfect knowledge," Working Paper Series 2007-08, Federal Reserve Bank of San Francisco.
    60. Craig S. Hakkio & Andrew Lee Smith, 2017. "Bond Premiums and the Natural Real Rate of Interest," Economic Review, Federal Reserve Bank of Kansas City, issue Q I, pages 5-39.
    61. Thomas Laubach & John C. Williams, 2015. "Measuring the natural rate of interest redux," Working Paper Series 2015-16, Federal Reserve Bank of San Francisco.
    62. Nikolsko-Rzhevskyy, Alex & Papell, David H. & Prodan, Ruxandra, 2019. "The Taylor principles," Journal of Macroeconomics, Elsevier, vol. 62(C).
    63. Matteo Cacciatore & Dmitry Matveev & Rodrigo Sekkel, 2022. "Uncertainty and Monetary Policy Experimentation: Empirical Challenges and Insights from Academic Literature," Discussion Papers 2022-9, Bank of Canada.
    64. Fethi Oğunc & Inci Batmaz, 2009. "Estimating the neutral real interest rate in an emerging market economy," Applied Economics, Taylor & Francis Journals, vol. 43(6), pages 683-693.
    65. Joscha Beckmann & Klaus-Jürgen Gern & Nils Jannsen, 2022. "Should they stay or should they go? Negative interest rate policies under review," International Economics and Economic Policy, Springer, vol. 19(4), pages 885-912, October.
    66. Jean-Philippe Cayen & Marc-André Gosselin & Sharon Kozicki, 2009. "Estimating DSGE-Model-Consistent Trends for Use in Forecasting," Staff Working Papers 09-35, Bank of Canada.
    67. Verbrugge, Randal & Zaman, Saeed, 2023. "The hard road to a soft landing: Evidence from a (modestly) nonlinear structural model," Energy Economics, Elsevier, vol. 123(C).
    68. Horvath, Roman, 2006. "Real-Time Time-Varying Equilibrium Interest Rates: Evidence on the Czech Republic," MPRA Paper 845, University Library of Munich, Germany.
    69. Todd E. Clark & Sharon Kozicki, 2004. "Estimating equilibrium real interest rates in real time," Research Working Paper RWP 04-08, Federal Reserve Bank of Kansas City.
    70. Rafael Cavalcanti De Araújo & Cleomar Gomes Da Silva, 2014. "The Neutral Interest Rate And The Stance Of Monetary Policy In Brazil," Anais do XLI Encontro Nacional de Economia [Proceedings of the 41st Brazilian Economics Meeting] 051, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    71. Wieland, Volker & Beyer, Robert, 2017. "Instability, imprecision and inconsistent use of equilibrium real interest rate estimates," CEPR Discussion Papers 11927, C.E.P.R. Discussion Papers.
    72. Fu, Bowen, 2023. "Measuring the trend real interest rate in a data-rich environment," Journal of Economic Dynamics and Control, Elsevier, vol. 147(C).
    73. Randal J. Verbrugge & Saeed Zaman, 2023. "Post-COVID Inflation Dynamics: Higher for Longer," Working Papers 23-06R, Federal Reserve Bank of Cleveland, revised 20 Jun 2023.
    74. Roman Horvath, 2007. "The Time-Varying Policy Neutral Rate in Real Time: A Predictor for Future Inflation?," Working Papers 2007/4, Czech National Bank.
    75. Kei Imakubo & Haruki Kojima & Jouchi Nakajima, 2018. "The natural yield curve: its concept and measurement," Empirical Economics, Springer, vol. 55(2), pages 551-572, September.
    76. Belke, Ansgar & Klose, Jens, 2020. "Equilibrium real interest rates and the financial cycle: Empirical evidence for Euro area member countries," Economic Modelling, Elsevier, vol. 84(C), pages 357-366.
    77. Andrea Pescatori & Jarkko Turunen, 2016. "Lower for Longer: Neutral Rate in the U.S," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 64(4), pages 708-731, November.
    78. Mésonnier, J-S., 2006. "The Reliability of Macroeconomic Forecasts based on Real Interest Rate Gap Estimates in Real Time: an Assessment for the Euro Area," Working papers 157, Banque de France.
    79. Klose, Jens, 2011. "Asymmetric Taylor reaction functions of the ECB: An approach depending on the state of the economy," The North American Journal of Economics and Finance, Elsevier, vol. 22(2), pages 149-163, August.
    80. Bruno Feunou & Jean-Sébastien Fontaine, 2021. "Debt-Secular Economic Changes and Bond Yields," Staff Working Papers 21-14, Bank of Canada.
    81. Belke, Ansgar & Klose, Jens, 2010. "(How) Do the ECB and the Fed React to Financial Market Uncertainty? – The Taylor Rule in Times of Crisis," Ruhr Economic Papers 166, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    82. Yuli Radev, 2015. "New dynamic disequilibrium," Economic Thought journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 6, pages 65-90.
    83. July Radev, 2017. "Monetary policy and the dynamic disequilibrium," Economic Thought journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 1, pages 96-114.
    84. Moretti, Laura, 2014. "Monetary policy, long real yields and the financial crisis," CFS Working Paper Series 457, Center for Financial Studies (CFS).
    85. Brand, Claus & Bielecki, Marcin & Penalver, Adrian, 2018. "The natural rate of interest: estimates, drivers, and challenges to monetary policy JEL Classification: E52, E43," Occasional Paper Series 217, European Central Bank.
    86. Naohisa Hirakata & Kazutoshi Kan & Akihiro Kanafuji & Yosuke Kido & Yui Kishaba & Tomonori Murakoshi & Takeshi Shinohara, 2019. "The Quarterly Japanese Economic Model (Q-JEM): 2019 version," Bank of Japan Working Paper Series 19-E-7, Bank of Japan.
    87. Nikolsko-Rzhevskyy, Alex & Papell, David H. & Prodan, Ruxandra, 2021. "Policy Rules and Economic Performance," Journal of Macroeconomics, Elsevier, vol. 68(C).
    88. Umino, Shingo, 2014. "Real-time estimation of the equilibrium real interest rate: Evidence from Japan," The North American Journal of Economics and Finance, Elsevier, vol. 28(C), pages 17-32.
    89. Rodrigo Fuentes S & Fabián Gredig U., 2008. "The Neutral Interest Rate: Estimates for Chile," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 11(2), pages 47-58, August.
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  51. Todd E. Clark & Michael W. McCracken, 2003. "The predictive content of the output gap for inflation : resolving in-sample and out-of-sample evidence," Research Working Paper RWP 03-06, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Athanasios Orphanides & Simon van Norden, 2004. "The reliability of inflation forecasts based on output gap estimates in real time," Finance and Economics Discussion Series 2004-68, Board of Governors of the Federal Reserve System (U.S.).
    2. Michael Dotsey & Shigeru Fujita & Tom Stark, 2018. "Do Phillips Curves Conditionally Help to Forecast Inflation?," International Journal of Central Banking, International Journal of Central Banking, vol. 14(4), pages 43-92, September.
    3. Hamza Bennani, 2018. "Media Perception of Fed Chair's Overconfidence and Market Expectations," Working Papers hal-04141795, HAL.
    4. James H. Stock & Mark W. Watson, 2008. "Phillips Curve Inflation Forecasts," NBER Working Papers 14322, National Bureau of Economic Research, Inc.
    5. Alexander Doser & Ricardo Nunes & Nikhil Rao & Viacheslav Sheremirov, 2017. "Inflation expectations and nonlinearities in the Phillips curve," Working Papers 17-11, Federal Reserve Bank of Boston.
    6. Semei Coronado & Rangan Gupta & Saban Nazlioglu & Omar Rojas, 2020. "Time-Varying Causality between Bond and Oil Markets of the United States: Evidence from Over One and Half Centuries of Data," Working Papers 202006, University of Pretoria, Department of Economics.
    7. Pablo Pincheira & Andrés Gatty, 2016. "Forecasting Chilean inflation with international factors," Empirical Economics, Springer, vol. 51(3), pages 981-1010, November.
    8. Martha López P., 2004. "Efficient Policy Rule for Inflation Targeting in Colombia," Money Affairs, CEMLA, vol. 0(1), pages 1-24, January-J.
    9. Ercio Muñoz S. & Alfredo Pistelli M., 2010. "¿Tienen los Terremotos un Impacto Inflacionario en el Corto Plazo? Evidencia para una Muestra de Países," Notas de Investigación Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 13(2), pages 113-127, April.
    10. Güneş Kamber & James Morley & Benjamin Wong, 2017. "Intuitive and Reliable Estimates of the Output Gap from a Beveridge-Nelson Filter," Reserve Bank of New Zealand Discussion Paper Series DP2017/01, Reserve Bank of New Zealand.
    11. Lance J. Bachmeier & Norman R. Swanson, 2003. "Predicting Inflation: Does The Quantity Theory Help?," Departmental Working Papers 200317, Rutgers University, Department of Economics.
    12. Scott Brave & Jonas D. M. Fisher, 2004. "In search of a robust inflation forecast," Economic Perspectives, Federal Reserve Bank of Chicago, vol. 28(Q IV), pages 12-31.
    13. Jeremy M. Piger & Robert H. Rasche, 2006. "Inflation: do expectations trump the gap?," Working Papers 2006-013, Federal Reserve Bank of St. Louis.
    14. César Calderón & Klaus Schmidt Hebbel, 2008. "What Drives Inflation in the World?," Working Papers Central Bank of Chile 491, Central Bank of Chile.
    15. Karlsson, Sune & Österholm, Pär, 2018. "A Note on the Stability of the Swedish Philips Curve," Working Papers 2018:6, Örebro University, School of Business.
    16. Todd E. Clark & Michael W. McCracken, 2007. "Tests of equal predictive ability with real-time data," Research Working Paper RWP 07-06, Federal Reserve Bank of Kansas City.
    17. Kabukçuoğlu, Ayşe & Martínez-García, Enrique, 2018. "Inflation as a global phenomenon—Some implications for inflation modeling and forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 87(C), pages 46-73.
    18. Andrew Keinsley & Sandeep Kumar Rangaraju, 2021. "The Nonlinear Unemployment-Inflation Relationship and the Factors That Define It," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 47(3), pages 354-377, June.
    19. Kenneth D. West & Todd Clark, 2006. "Approximately Normal Tests for Equal Predictive Accuracy in Nested Models," NBER Technical Working Papers 0326, National Bureau of Economic Research, Inc.
    20. Pincheira, Pablo & Selaive, Jorge & Nolazco, Jose Luis, 2017. "Forecasting Inflation in Latin America with Core Measures," MPRA Paper 80496, University Library of Munich, Germany.
    21. Wu, Jyh-Lin & Wang, Yi-Chiuan, 2013. "Fundamentals, forecast combinations and nominal exchange-rate predictability," International Review of Economics & Finance, Elsevier, vol. 25(C), pages 129-145.
    22. Ayse Dur & Enrique Martínez García, 2020. "Mind the Gap!—A Monetarist View of the Open-Economy Phillips Curve," Globalization Institute Working Papers 392, Federal Reserve Bank of Dallas.
    23. Ayse Kabukcuoglu & Enrique Martínez-García, 2016. "What Helps Forecast U.S. Inflation?—Mind the Gap!," Koç University-TUSIAD Economic Research Forum Working Papers 1615, Koc University-TUSIAD Economic Research Forum.
    24. Luis Gonzalo Llosa & Shirley Miller, 2004. "Using Additional Information in Estimating the Output Gap in Peru: a Multivariate Unobserved Component Approach," Money Affairs, CEMLA, vol. 0(1), pages 57-82, January-J.
    25. Clark, Todd E. & McCracken, Michael W., 2015. "Nested forecast model comparisons: A new approach to testing equal accuracy," Journal of Econometrics, Elsevier, vol. 186(1), pages 160-177.
    26. Andrew Ang & Geert Bekaert & Min Wei, 2005. "Do Macro Variables, Asset Markets or Surveys Forecast Inflation Better?," NBER Working Papers 11538, National Bureau of Economic Research, Inc.
    27. Giacomini, Raffaella & Rossi, Barbara, 2006. "Detecting and predicting forecast breakdowns," Working Paper Series 638, European Central Bank.
    28. Todd E. Clark & Michael W. McCracken, 2007. "Averaging forecasts from VARs with uncertain instabilities," Finance and Economics Discussion Series 2007-42, Board of Governors of the Federal Reserve System (U.S.).
    29. Sune Karlsson & Pär Österholm, 2023. "Is the US Phillips curve stable? Evidence from Bayesian vector autoregressions," Scandinavian Journal of Economics, Wiley Blackwell, vol. 125(1), pages 287-314, January.
    30. Camila Figueroa & Jorge Fornero & Pablo García, 2019. "Hindsight vs. Real time measurement of the output gap: Implications for the Phillips curve in the Chilean Case," Working Papers Central Bank of Chile 854, Central Bank of Chile.
    31. Ahmad, Saad & Civelli, Andrea, 2016. "Globalization and inflation: A threshold investigation," Journal of Macroeconomics, Elsevier, vol. 48(C), pages 283-304.
    32. Heaton, Chris, 2015. "Testing for multiple-period predictability between serially dependent time series," International Journal of Forecasting, Elsevier, vol. 31(3), pages 587-597.
    33. 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.
    34. Lillian Kamal, 2014. "Do GAP Models Still have a Role to Play in Forecasting Inflation?," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 8(3), pages 1-12.
    35. Edmond Berisha & David Gabauer & Rangan Gupta & Chi Keung Marco Lau, 2020. "Time-Varying Influence of Household Debt on Inequality in United Kingdom," Working Papers 202017, University of Pretoria, Department of Economics.
    36. James H. Stock & Mark W. Watson, 2006. "Why Has U.S. Inflation Become Harder to Forecast?," NBER Working Papers 12324, National Bureau of Economic Research, Inc.
    37. Gary J. Cornwall & Jeffrey A. Mills & Beau A. Sauley & Huibin Weng, 2019. "Predictive Testing for Granger Causality via Posterior Simulation and Cross-validation," Advances in Econometrics, in: Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part A, volume 40, pages 275-292, Emerald Group Publishing Limited.
    38. Oguzhan Cepni & David Gabauer & Rangan Gupta & Khuliso Ramabulana, 2020. "Time-Varying Spillover of US Trade War on the Growth of Emerging Economies," Working Papers 202002, University of Pretoria, Department of Economics.
    39. Bec, Frédérique & Mogliani, Matteo, 2015. "Nowcasting French GDP in real-time with surveys and “blocked” regressions: Combining forecasts or pooling information?," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1021-1042.
    40. McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, vol. 140(2), pages 719-752, October.
    41. Qin, Ting & Enders, Walter, 2008. "In-sample and out-of-sample properties of linear and nonlinear Taylor rules," Journal of Macroeconomics, Elsevier, vol. 30(1), pages 428-443, March.
    42. Nicholas Apergis & Panagiotis G. Artikis, 2016. "Foreign Exchange Risk, Equity Risk Factors and Economic Growth," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 44(4), pages 425-445, December.
    43. Mayer, Walter J. & Liu, Feng & Dang, Xin, 2017. "Improving the power of the Diebold–Mariano–West test for least squares predictions," International Journal of Forecasting, Elsevier, vol. 33(3), pages 618-626.
    44. Lance Bachmeier & Qi Li & Dandan Liu, 2008. "Should Oil Prices Receive So Much Attention? An Evaluation Of The Predictive Power Of Oil Prices For The U.S. Economy," Economic Inquiry, Western Economic Association International, vol. 46(4), pages 528-539, October.
    45. Zhang, Qian & Li, Zeguang, 2021. "Time-varying risk attitude and the foreign exchange market behavior," Research in International Business and Finance, Elsevier, vol. 57(C).
    46. Christina Anderl & Guglielmo Maria Caporale, 2023. "The Asymmetric Impact of Economic Policy and Oil Price Uncertainty on Inflation: Evidence from Developed and Emerging Economies," CESifo Working Paper Series 10276, CESifo.
    47. Don H. Kim, 2008. "Challenges in macro-finance modeling," Finance and Economics Discussion Series 2008-06, Board of Governors of the Federal Reserve System (U.S.).
    48. Ulrich Gunter, 2019. "Estimating and forecasting with a two-country DSGE model of the Euro area and the USA: the merits of diverging interest-rate rules," Empirical Economics, Springer, vol. 56(4), pages 1283-1323, April.
    49. Clark, Todd E. & McCracken, Michael W., 2006. "The Predictive Content of the Output Gap for Inflation: Resolving In-Sample and Out-of-Sample Evidence," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(5), pages 1127-1148, August.
    50. Andreas Billmeier, 2006. "Measuring a Roller Coaster: Evidence on the Finnish Output Gap," Finnish Economic Papers, Finnish Economic Association, vol. 19(2), pages 69-83, Autumn.
    51. Don H. Kim, 2009. "Challenges in macro-finance modeling," Review, Federal Reserve Bank of St. Louis, vol. 91(Sep), pages 519-544.
    52. Pablo Pincheira & Hernán Rubio, 2010. "The Low Predictive Power of Simple Phillips Curves in Chile: A Real-Time Evaluation," Working Papers Central Bank of Chile 559, Central Bank of Chile.
    53. Luca Agnello & Vítor Castro & Ricardo M. Sousa, 2023. "Interest rate gaps in an uncertain global context: why “too” low (high) for “so” long?," Empirical Economics, Springer, vol. 64(2), pages 539-565, February.
    54. Dieppe, Alistair & Ortega, Eva & D'Agostino, Antonello & Karlsson, Tohmas & Benkovskis, Konstantins & Caivano, Michele & Hurtado, Samuel & Várnai, Tímea, 2011. "Assessing the sensitivity of inflation to economic activity," Working Paper Series 1357, European Central Bank.
    55. Frédérick Demers, 2003. "The Canadian Phillips Curve and Regime Shifting," Staff Working Papers 03-32, Bank of Canada.
    56. Yonglian Wang & Lijun Wang & Han Liu & Yongjing Wang, 2021. "The Robust Causal Relationships Among Domestic Tourism Demand, Carbon Emissions, and Economic Growth in China," SAGE Open, , vol. 11(4), pages 21582440211, October.
    57. Karlsson, Sune & Österholm, Pär, 2018. "Is the US Phillips Curve Stable? Evidence from Bayesian VARs," Working Papers 2018:5, Örebro University, School of Business.
    58. Serhan Cevik & Tianle Zhu, 2020. "Trinity Strikes Back: Monetary Independence And Inflation In The Caribbean," Journal of International Development, John Wiley & Sons, Ltd., vol. 32(3), pages 375-388, April.
    59. Tillmann, Peter, 2010. "The Fed's perceived Phillips curve: Evidence from individual FOMC forecasts," Journal of Macroeconomics, Elsevier, vol. 32(4), pages 1008-1013, December.
    60. Yonglian Wang & Lijun Wang & Changchun Pan, 2022. "Tourism–Growth Nexus in the Presence of Instability," Sustainability, MDPI, vol. 14(4), pages 1-11, February.
    61. Kapetanios, George & Labhard, Vincent & Price, Simon, 2008. "Forecast combination and the Bank of England's suite of statistical forecasting models," Economic Modelling, Elsevier, vol. 25(4), pages 772-792, July.
    62. Rossi, Barbara & Wang, Yiru, 2019. "Vector autoregressive-based Granger causality test in the presence of instabilities," MPRA Paper 101492, University Library of Munich, Germany.
    63. Manzan, Sebastiano & Zerom, Dawit, 2009. "Are Macroeconomic Variables Useful for Forecasting the Distribution of U.S. Inflation?," MPRA Paper 14387, University Library of Munich, Germany.
    64. Knut Are Aastveit & Tørres G. Trovik, 2008. "Estimating the output gap in real time: A factor model approach," Working Paper 2008/23, Norges Bank.
    65. Bjørnland, Hilde C. & Brubakk, Leif & Jore, Anne Sofie, 2006. "Forecasting inflation with an uncertain output gap," Memorandum 11/2006, Oslo University, Department of Economics.
    66. Marcellino, Massimiliano & Musso, Alberto, 2010. "Real time estimates of the euro area output gap: reliability and forecasting performance," Working Paper Series 1157, European Central Bank.
    67. Jean-Stéphane MESONNIER, 2007. "The predictive content of the real interest rate gap for macroeconomic variables in the euro area," Money Macro and Finance (MMF) Research Group Conference 2006 102, Money Macro and Finance Research Group.
    68. Rossi, Barbara & Sekhposyan, Tatevik, 2011. "Understanding models' forecasting performance," Journal of Econometrics, Elsevier, vol. 164(1), pages 158-172, September.
    69. Conti, Antonio M., 2021. "Resurrecting the Phillips Curve in Low-Inflation Times," Economic Modelling, Elsevier, vol. 96(C), pages 172-195.
    70. Mehmet Balcilar & Gizem Uzuner & Festus Victor Bekun & Mark E. Wohar, 2023. "Housing price uncertainty and housing prices in the UK in a time-varying environment," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 50(2), pages 523-549, May.
    71. Quast, Josefine & Wolters, Maik H., 2019. "Reliable Real-time Output Gap Estimates Based on a Modified Hamilton Filter," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203535, Verein für Socialpolitik / German Economic Association.
    72. Dong Jin Lee & Jai Hyung Yoon, 2012. "The New Keynesian Phillips Curves in Multiple Quantiles and the Asymmetry of Monetary Policy," Working papers 2012-03, University of Connecticut, Department of Economics.
    73. 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.
    74. Anthony Garratt & Gary Koop & Emi Mise & Shaun Vahey, 2008. "Real-time Prediction with UK Monetary Aggregates in the Presence of Model Uncertainty," Reserve Bank of New Zealand Discussion Paper Series DP2008/13, Reserve Bank of New Zealand.
    75. Michał Hulej & Grzegorz Grabek, 2015. "Output gap measure based on survey data," NBP Working Papers 200, Narodowy Bank Polski.
    76. Lee, Dong Jin & Yoon, Jai Hyung, 2016. "The New Keynesian Phillips Curve in multiple quantiles and the asymmetry of monetary policy," Economic Modelling, Elsevier, vol. 55(C), pages 102-114.
    77. Driver, Ciaran & Trapani, Lorenzo & Urga, Giovanni, 2013. "On the use of cross-sectional measures of forecast uncertainty," International Journal of Forecasting, Elsevier, vol. 29(3), pages 367-377.
    78. Adriana Arreaza & Enid Blanco & Miguel Dorta, 2004. "A Small Scale Macroeconomic Model for Venezuela," Money Affairs, CEMLA, vol. 0(1), pages 25-38, January-J.
    79. Serhan Cevik, João Tovar Jalles, 2023. "Eye of the Storm: The Impact of Climate Shocks on Inflation and Growth," Working Papers REM 2023/0276, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    80. Troy Matheson, 2006. "Phillips curve forecasting in a small open economy," Reserve Bank of New Zealand Discussion Paper Series DP2006/01, Reserve Bank of New Zealand.
    81. Yiru Wang & Barbara Rossi, 2019. "VAR-based Granger-causality test in the presence of instabilities," Economics Working Papers 1642, Department of Economics and Business, Universitat Pompeu Fabra.
    82. Mésonnier, J-S., 2006. "The Reliability of Macroeconomic Forecasts based on Real Interest Rate Gap Estimates in Real Time: an Assessment for the Euro Area," Working papers 157, Banque de France.
    83. Wayne Robinson, 2004. "Real Shocks, Credibility & Stabilization Policy in a Small Open Economy," Money Affairs, CEMLA, vol. 0(1), pages 39-55, January-J.
    84. Dong Jin Lee, 2009. "Testing Parameter Stability in Quantile Models: An Application to the U.S. Inflation Process," Working papers 2009-26, University of Connecticut, Department of Economics.
    85. Don H Kim & Athanasios Orphanides, 2007. "The bond market term premium: what is it, and how can we measure it?," BIS Quarterly Review, Bank for International Settlements, June.
    86. Todd E. Clark & Taisuke Nakata, 2008. "Has the behavior of inflation and long-term inflation expectations changed?," Economic Review, Federal Reserve Bank of Kansas City, vol. 93(Q I), pages 17-50.
    87. Massimo Guidolin & Manuela Pedio, 2022. "Switching Coefficients or Automatic Variable Selection: An Application in Forecasting Commodity Returns," Forecasting, MDPI, vol. 4(1), pages 1-32, February.
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    89. Daniel Borup & Bent Jesper Christensen & Yunus Emre Ergemen, 2019. "Assessing predictive accuracy in panel data models with long-range dependence," CREATES Research Papers 2019-04, Department of Economics and Business Economics, Aarhus University.
    90. Mr. Serhan Cevik & João Tovar Jalles, 2023. "Eye of the Storm: The Impact of Climate Shocks on Inflation and Growth," IMF Working Papers 2023/087, International Monetary Fund.
    91. James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, February.
    92. Todd E. Clark & Michael W. McCracken, 2010. "Testing for unconditional predictive ability," Working Papers 2010-031, Federal Reserve Bank of St. Louis.

  52. Todd E. Clark, 2003. "Disaggregate evidence on the persistence of consumer price inflation," Research Working Paper RWP 03-11, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Frédérick Demers & Annie De Champlain, 2005. "Forecasting Core Inflation in Canada: Should We Forecast the Aggregate or the Components?," Staff Working Papers 05-44, Bank of Canada.
    2. Jan Babecký & Fabrizio Coricelli & Roman Horváth, 2009. "Assessing Inflation Persistence: Micro Evidence on an Inflation Targeting Economy," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 59(2), pages 102-127, June.
    3. Christian Bauer & Sebastian Weber, 2016. "The Efficiency of Monetary Policy when Guiding Inflation Expectations," Research Papers in Economics 2016-14, University of Trier, Department of Economics.
    4. Simone Elmer & Thomas Maag, 2009. "The Persistence of Inflation in Switzerland," KOF Working papers 09-235, KOF Swiss Economic Institute, ETH Zurich.
    5. Terence Tai Leung Chong & M. S. Rafiq & Tingting Juni Zhu & Zhang Wu, 2019. "Are Prices Sticky In Large Developing Economies? An Empirical Comparison Of China And India," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 64(02), pages 341-363, March.
    6. Lünnemann, Patrick & Mathä, Thomas Y., 2005. "Regulated and services' prices and inflation persistence," Working Paper Series 466, European Central Bank.
    7. Francis Leni Anguyo & Rangan Gupta & Kevin Kotzé, 2017. "Inflation Dynamics in Uganda: A Quantile Regression Approach," Working Papers 201772, University of Pretoria, Department of Economics.
    8. Altissimo, Filippo & Mojon, Benoit & Zaffaroni, Paolo, 2009. "Can aggregation explain the persistence of inflation?," Journal of Monetary Economics, Elsevier, vol. 56(2), pages 231-241, March.
    9. Laura Mayoral, 2009. "Heterogeneous dynamics, aggregation and the persistence of economic shocks," UFAE and IAE Working Papers 786.09, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
    10. Jari Hännikäinen, 2016. "When does the yield curve contain predictive power? Evidence from a data-rich environment," Working Papers 1603, Tampere University, Faculty of Management and Business, Economics.
    11. Cristina Conflitti and Matteo Luciani, 2019. "Oil Price Pass-through into Core Inflation," The Energy Journal, International Association for Energy Economics, vol. 0(Number 6).
    12. Ian Babetskii & Fabrizio Coricelli & Roman Horváth, 2007. "Measuring and Explaining Inflation Persistence: Disaggregate Evidence on the Czech Republic," Working Papers IES 2007/22, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Aug 2007.
    13. Roy Cerqueti & Mauro Costantini & Luciano Gutierrez, 2009. "New panel tests to assess inflation persistence," Working Papers 54-2009, Macerata University, Department of Finance and Economic Sciences, revised Oct 2009.
    14. Andrade, P. & Zachariadis, M., 2012. "Global versus local shocks in micro price dynamics," Working papers 365, Banque de France.
    15. Logan Rangasamy, 2009. "Inflation Persistence And Core Inflation: The Case Of South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 77(3), pages 430-444, September.
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    34. Francesco Ravazzolo & Shaun P. Vahey, 2010. "Forecast densities for economic aggregates from disaggregate ensembles," Working Paper 2010/02, Norges Bank.
    35. Laura Mayoral, 2013. "Heterogeneous Dynamics, Aggregation, And The Persistence Of Economic Shocks," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 54(4), pages 1295-1307, November.
    36. Erdenebat Bataa & Denise R. Osborn & Marianne Sensier & Dick van Dijk, 2008. "Identifying Changes in Mean, Seasonality, Persistence and Volatility for G7 and Euro Area Inflation," Centre for Growth and Business Cycle Research Discussion Paper Series 109, Economics, The University of Manchester.
    37. Guillermo Carlomagno & Nicolas Eterovic & L. G. Hernández-Román, 2023. "Disentangling Demand and Supply Inflation Shocks from Chilean Electronic Payment Data," Working Papers Central Bank of Chile 986, Central Bank of Chile.
    38. Carlomagno, Guillermo, 2014. "The pairwise approach to model a large set of disaggregates with common trends," DES - Working Papers. Statistics and Econometrics. WS ws141309, Universidad Carlos III de Madrid. Departamento de Estadística.
    39. Kumar, Ankit & Dash, Pradyumna, 2020. "Changing transmission of monetary policy on disaggregate inflation in India," Economic Modelling, Elsevier, vol. 92(C), pages 109-125.
    40. Pino, Gabriel, 2013. "Forecasting disaggregates by sectors and regions : the case of inflation in the euro area and Spain," DES - Working Papers. Statistics and Econometrics. WS ws130807, Universidad Carlos III de Madrid. Departamento de Estadística.
    41. Khundrakpam, Jeevan K., 2008. "How Persistent is Indian Inflationary Process, Has it Changed?," MPRA Paper 50927, University Library of Munich, Germany.
    42. Katsurako Sonoda, 2006. "An Empirical Analysis of Price Stickiness and Price Revision Behavior in Japan Using Micro CPI Data," Bank of Japan Working Paper Series 06-E-8, Bank of Japan.
    43. Byrne, Joseph P & Fazio, Giorgio & Fiess, Norbert, 2010. "Optimism and commitment: An elementary theory of bargaining and war," SIRE Discussion Papers 2010-102, Scottish Institute for Research in Economics (SIRE).
    44. Troy Davig & Taeyoung Doh, 2014. "Monetary Policy Regime Shifts and Inflation Persistence," The Review of Economics and Statistics, MIT Press, vol. 96(5), pages 862-875, December.
    45. Mr. James P Walsh, 2011. "Reconsidering the Role of Food Prices in Inflation," IMF Working Papers 2011/071, International Monetary Fund.
    46. Choi, Chi-Young & Matsubara, Kiyoshi, 2007. "Heterogeneity in the persistence of relative prices: What do the Japanese cities tell us?," Journal of the Japanese and International Economies, Elsevier, vol. 21(2), pages 260-286, June.
    47. Chiara Perricone, 2013. "Clustering Macroeconomic Variables," CEIS Research Paper 283, Tor Vergata University, CEIS, revised 11 Jun 2013.
    48. Chi-Young Choi & Joo Yong Lee & Róisín O'Sullivan, 2015. "Monetary Policy Regime Change and Regional Inflation Dynamics: Looking through the Lens of Sector-Level Data for Korea," Working Papers 2015-20, Economic Research Institute, Bank of Korea.
    49. Hasan Engin Duran & Burak Dindaroğlu, 2021. "Regional inflation persistence in Turkey," Growth and Change, Wiley Blackwell, vol. 52(1), pages 460-491, March.
    50. Carlomagno, Guillermo, 2016. "Discovering common trends in a large set of disaggregates: statistical procedures and their properties," DES - Working Papers. Statistics and Econometrics. WS ws1519, Universidad Carlos III de Madrid. Departamento de Estadística.
    51. Karl Whelan, 2005. "Testing parameter stability : a wild bootstrap approach," Open Access publications 10197/225, School of Economics, University College Dublin.
    52. Agnieszka Leszczynska & Katarzyna Hertel, 2013. "Inflation persistence – a disaggregated approach," EcoMod2013 5692, EcoMod.
    53. Gadzinski, Gregory & Orlandi, Fabrice, 2004. "Inflation persistence in the European Union, the euro area, and the United States," Working Paper Series 414, European Central Bank.
    54. Logan Rangasamy, 2011. "Food Inflation In South Africa: Some Implications For Economic Policy," South African Journal of Economics, Economic Society of South Africa, vol. 79(2), pages 184-201, June.
    55. Blazej Mazur, 2015. "Density forecasts based on disaggregate data: nowcasting Polish inflation," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 15, pages 71-87.
    56. Antoni Espasa & Eva Senra, 2017. "Twenty-Two Years of Inflation Assessment and Forecasting Experience at the Bulletin of EU & US Inflation and Macroeconomic Analysis," Econometrics, MDPI, vol. 5(4), pages 1-28, October.
    57. Pankaj Kumar, 2015. "Can Univariate Time Series Models of Inflation Help Discriminate Between Alternative Sources of Inflation PersistenceAuthor-Name: Naveen Srinivasan," Working Papers 2015-104, Madras School of Economics,Chennai,India.
    58. Rangan Gupta & Charl Jooste & Omid Ranjbar, 2017. "South Africa’s inflation persistence: a quantile regression framework," Economic Change and Restructuring, Springer, vol. 50(4), pages 367-386, November.
    59. Caglayan, Mustafa & Filiztekin, Alpay, 2015. "Price dynamics and market segmentation," Economics Letters, Elsevier, vol. 134(C), pages 94-97.
    60. Richard S. J. Tol & Francisco Estrada & Carlos Gay-García, 2012. "The persistence of shocks in GDP and the estimation of the potential economic costs of climate change," Working Paper Series 4312, Department of Economics, University of Sussex Business School.
    61. Kato, Ryo & Okuda, Tatsushi & Tsuruga, Takayuki, 2021. "Sectoral inflation persistence, market concentration, and imperfect common knowledge," Journal of Economic Behavior & Organization, Elsevier, vol. 192(C), pages 500-517.
    62. Giannoni, Marc & Mihov, Ilian & Boivin, Jean, 2007. "Sticky Prices and Monetary Policy: Evidence from Disaggregated US Data," CEPR Discussion Papers 6101, C.E.P.R. Discussion Papers.
    63. César Castro & Rebeca Jiménez-Rodríguez & Pilar Poncela & Eva Senra, 2017. "A new look at oil price pass-through into inflation: evidence from disaggregated European data," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 34(1), pages 55-82, April.
    64. Senra, Eva, 2017. "22 Years of inflation assessment and forecasting experience at the bulletin of EU & US inflation and macroeconomic analysis," DES - Working Papers. Statistics and Econometrics. WS 24678, Universidad Carlos III de Madrid. Departamento de Estadística.
    65. Binder, Carola Conces, 2016. "Estimation of historical inflation expectations," Explorations in Economic History, Elsevier, vol. 61(C), pages 1-31.
    66. Chong, Terence Tai Leung & Wu, Zhang, 2018. "Price Rigidity in China: Empirical Results at Home and Abroad," MPRA Paper 92013, University Library of Munich, Germany.
    67. Filippo Altissimo & Benoit Mojon & Paolo Zaffaroni, 2007. "Fast micro and slow macro: can aggregation explain the persistence of inflation?," Working Paper Series WP-07-02, Federal Reserve Bank of Chicago.
    68. Dixon, Huw & Kara, Engin, 2006. "Understanding inflation persistence: a comparison of different models," Working Paper Series 672, European Central Bank.
    69. Fröhling, Annette & Lommatzsch, Kirsten, 2011. "Output sensitivity of inflation in the euro area: Indirect evidence from disaggregated consumer prices," Discussion Paper Series 1: Economic Studies 2011,25, Deutsche Bundesbank.
    70. Rangan Gupta & Charl Jooste & Omid Ranjbar, 2015. "The Changing Dynamics of South Africa's Inflation Persistence: Evidence from a Quantile Regression Framework," Working Papers 201563, University of Pretoria, Department of Economics.
    71. Shintani, Mototsugu & Guo, Zi-Yi, 2011. "Finite Sample Performance of Principal Components Estimators for Dynamic Factor Models: Asymptotic vs. Bootstrap Approximations," EconStor Preprints 167627, ZBW - Leibniz Information Centre for Economics.
    72. Kim, Dukpa, 2011. "Estimating a common deterministic time trend break in large panels with cross sectional dependence," Journal of Econometrics, Elsevier, vol. 164(2), pages 310-330, October.
    73. Gantungalag Altansukh & Ralf Becker & George Bratsiotis & Denise R. Osborn, 2018. "Structural Breaks in International Inflation Linkages for OECD Countries," Centre for Growth and Business Cycle Research Discussion Paper Series 240, Economics, The University of Manchester.
    74. Steven Cook, 2009. "A re-examination of the stationarity of inflation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(6), pages 1047-1053.
    75. Ramos Francia Manuel & Capistrán Carlos, 2006. "Inflation Dynamics in Latin America," Working Papers 2006-11, Banco de México.
    76. Carlomagno, Guillermo, 2015. "Forecasting a large set of disaggregates with common trends and outliers," DES - Working Papers. Statistics and Econometrics. WS ws1518, Universidad Carlos III de Madrid. Departamento de Estadística.
    77. James Yetman, 2009. "Hong Kong Consumer Prices are Flexible," Working Papers 052009, Hong Kong Institute for Monetary Research.
    78. Christiane Baumeister & Philip Liu & Haroon Mumtaz, 2012. "Changes in the Effects of Monetary Policy on Disaggregate Price Dynamics," Staff Working Papers 12-13, Bank of Canada.
    79. Rafal Raciborski, 2008. "Searching for additional sources of inflation persistence : the micro-price panel data approach," Working Paper Research 132, National Bank of Belgium.
    80. Kushal Banik Chowdhury & Nityananda Sarkar, 2015. "The Effect of Inflation on Inflation Uncertainty in the G7 Countries: A Double Threshold GARCH Model," International Econometric Review (IER), Econometric Research Association, vol. 7(1), pages 34-50, April.
    81. Tianfeng Li & June Wei, 2015. "Multiple Structural Breaks and Inflation Persistence: Evidence from China," Asian Economic Journal, East Asian Economic Association, vol. 29(1), pages 1-20, March.
    82. Sofiane H. Sekioua, 2004. "Real interest parity (RIP) over the 20th century: New evidence based on confidence intervals for the dominant root and half-lives of shocks," Money Macro and Finance (MMF) Research Group Conference 2004 91, Money Macro and Finance Research Group.
    83. Viacheslav Kramkov, 2023. "Does CPI disaggregation improve inflation forecast accuracy?," Bank of Russia Working Paper Series wps112, Bank of Russia.
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  53. Todd E. Clark & Michael W. McCracken, 2002. "Forecast-based model selection in the presence of structural breaks," Research Working Paper RWP 02-05, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Jorge Selaive & Vicente Tuesta, 2004. "Can Fluctuations in the Consumption-Wealth Ratio Help to Predict Exchange Rates?," International Finance 0404014, University Library of Munich, Germany.
    2. Inoue, Atsushi & Kilian, Lutz, 2002. "In-sample or out-of-sample tests of predictability: which one should we use?," Working Paper Series 195, European Central Bank.
    3. Ayse Kabukcuoglu & Enrique Martínez-García, 2016. "What Helps Forecast U.S. Inflation?—Mind the Gap!," Koç University-TUSIAD Economic Research Forum Working Papers 1615, Koc University-TUSIAD Economic Research Forum.
    4. Clark, Todd E. & McCracken, Michael W., 2006. "The Predictive Content of the Output Gap for Inflation: Resolving In-Sample and Out-of-Sample Evidence," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(5), pages 1127-1148, August.
    5. Corradi, Valentina & Swanson, Norman R., 2006. "Predictive density and conditional confidence interval accuracy tests," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 187-228.
    6. Rapach, David E. & Wohar, Mark E. & Rangvid, Jesper, 2005. "Macro variables and international stock return predictability," International Journal of Forecasting, Elsevier, vol. 21(1), pages 137-166.
    7. Burns, Kelly & Moosa, Imad A., 2015. "Enhancing the forecasting power of exchange rate models by introducing nonlinearity: Does it work?," Economic Modelling, Elsevier, vol. 50(C), pages 27-39.

  54. Todd E. Clark & Michael W. McCracken, 2001. "Evaluating long-horizon forecasts," Research Working Paper RWP 01-14, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Athanasios Orphanides & Simon van Norden, 2004. "The reliability of inflation forecasts based on output gap estimates in real time," Finance and Economics Discussion Series 2004-68, Board of Governors of the Federal Reserve System (U.S.).
    2. Martin D. D. Evans & Richard K. Lyons, 2017. "Meese-Rogoff Redux: Micro-Based Exchange-Rate Forecasting," World Scientific Book Chapters, in: Studies in Foreign Exchange Economics, chapter 11, pages 457-475, World Scientific Publishing Co. Pte. Ltd..
    3. Nelson C. Mark & Donggyu Sul, 2004. "The Use of Predictive Regressions at Alternative Horizons in Finance and Economics," Finance 0409032, University Library of Munich, Germany.
    4. O. De Bandt & E. Michaux & C. Bruneau & A. Flageollet, 2007. "Forecasting inflation using economic indicators: the case of France," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(1), pages 1-22.
    5. Michael Steiner, 2009. "Predicting premiums for the market, size, value, and momentum factors," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 23(2), pages 137-155, June.
    6. Gabriel Moser & Fabio Rumler & Johann Scharler, 2004. "Forecasting Austrian Inflation," Working Papers 91, Oesterreichische Nationalbank (Austrian Central Bank).
    7. Boucher, Christophe, 2006. "Stock prices-inflation puzzle and the predictability of stock market returns," Economics Letters, Elsevier, vol. 90(2), pages 205-212, February.
    8. Todd E. Clark & Kenneth D. West, 2004. "Using out-of-sample mean squared prediction errors to test the Martingale difference hypothesis," Research Working Paper RWP 04-03, Federal Reserve Bank of Kansas City.
    9. Rapach, David E. & Wohar, Mark E., 2006. "In-sample vs. out-of-sample tests of stock return predictability in the context of data mining," Journal of Empirical Finance, Elsevier, vol. 13(2), pages 231-247, March.
    10. McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, vol. 140(2), pages 719-752, October.
    11. Mehmet Balcilar & Rangan Gupta & Stephen M. Miller, 2012. "The Out-of-Sample Forecasting Performance of Non-Linear Models of Regional Housing Prices in the US," Working papers 2012-12, University of Connecticut, Department of Economics.
    12. Clark, Todd E. & McCracken, Michael W., 2006. "The Predictive Content of the Output Gap for Inflation: Resolving In-Sample and Out-of-Sample Evidence," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(5), pages 1127-1148, August.
    13. Norman Swanson & Valentina Corradi, 2006. "Nonparametric Bootstrap Procedures for Predictive Inference Based on Recursive Estimation Schemes," Departmental Working Papers 200618, Rutgers University, Department of Economics.
    14. Rapach, David E. & Wohar, Mark E., 2006. "The out-of-sample forecasting performance of nonlinear models of real exchange rate behavior," International Journal of Forecasting, Elsevier, vol. 22(2), pages 341-361.
    15. Mestre, Ricardo, 2007. "Are survey-based inflation expections in the euro area informative?," Working Paper Series 721, European Central Bank.
    16. Barbara Rossi, 2007. "Expectations hypotheses tests at Long Horizons," Econometrics Journal, Royal Economic Society, vol. 10(3), pages 554-579, November.
    17. Marie Bessec & Othman Bouabdallah, 2005. "What causes the forecasting failure of Markov-Switching models? A Monte Carlo study," Econometrics 0503018, University Library of Munich, Germany.
    18. Todd E. Clark & Kenneth D. West, 2005. "Using Out-of-Sample Mean Squared Prediction Errors to Test the Martingale Difference," NBER Technical Working Papers 0305, National Bureau of Economic Research, Inc.
    19. Todd E. Clark & Michael W. McCracken, 2002. "Forecast-based model selection in the presence of structural breaks," Research Working Paper RWP 02-05, Federal Reserve Bank of Kansas City.
    20. 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.
    21. 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.
    22. Rapach, David E. & Wohar, Mark E. & Rangvid, Jesper, 2005. "Macro variables and international stock return predictability," International Journal of Forecasting, Elsevier, vol. 21(1), pages 137-166.

  55. Todd E. Clark, 2000. "Can out-of-sample forecast comparisons help prevent overfitting?," Research Working Paper RWP 00-05, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Makin, Anthony J. & Ratnasiri, Shyama, 2015. "Competitiveness and government expenditure: The Australian example," Economic Modelling, Elsevier, vol. 49(C), pages 154-161.
    2. Ana María Abarca G. & Felipe Alarcón G. & Pablo Pincheira B. & Jorge Selaive C., 2007. "Nominal Exchange Rate in Chile: Predictions based on technical analysis," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 10(2), pages 57-80, August.
    3. Jacques Peeperkorn & Yudhvir Seetharam, 2016. "A learning-augmented approach to pricing risk in South Africa," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 6(1), pages 117-139, April.
    4. Todd E. Clark & Michael W. McCracken, 2001. "Evaluating long-horizon forecasts," Research Working Paper RWP 01-14, Federal Reserve Bank of Kansas City.
    5. Medel, Carlos A., 2012. "¿Akaike o Schwarz? ¿Cuál elegir para predecir el PIB chileno? [Akaike or Schwarz? Which One is a Better Predictor of Chilean GDP?]," MPRA Paper 35950, University Library of Munich, Germany.
    6. Gerhard Hambusch & Sherrill Shaffer, 2016. "Forecasting bank leverage: an alternative to regulatory early warning models," Journal of Regulatory Economics, Springer, vol. 50(1), pages 38-69, August.
    7. Karlsson, Sune & Österholm, Pär, 2018. "A Note on the Stability of the Swedish Philips Curve," Working Papers 2018:6, Örebro University, School of Business.
    8. Pao, H.T., 2009. "Forecasting energy consumption in Taiwan using hybrid nonlinear models," Energy, Elsevier, vol. 34(10), pages 1438-1446.
    9. López, Ramón & Sepúlveda, Kevin A., 2022. "The effects of domestic demand shocks on inflation in a small open economy: Chile in the period 2000–2021," Revista CEPAL, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), December.
    10. Parigi, Giuseppe & Golinelli, Roberto, 2005. "Short-Run Italian GDP Forecasting and Real-Time Data," CEPR Discussion Papers 5302, C.E.P.R. Discussion Papers.
    11. Zachary McGurk & Adam Nowak & Joshua C. Hall, 2019. "Stock Returns and Investor Sentiment: Textual Analysis and Social Media," Working Papers 19-03, Department of Economics, West Virginia University.
    12. Rangel José Gonzalo, 2009. "Macroeconomic News, Announcements, and Stock Market Jump Intensity Dynamics," Working Papers 2009-15, Banco de México.
    13. Pincheira, Pablo & Selaive, Jorge & Nolazco, Jose Luis, 2017. "Forecasting Inflation in Latin America with Core Measures," MPRA Paper 80496, University Library of Munich, Germany.
    14. Ismaël Rafaï & Thierry Blayac & Dimitri Dubois & Sébastien Duchêne & Phu Nguyen-Van & Bruno Ventelou & Marc Willinger, 2023. "Stated preferences outperform elicited preferences for predicting reported compliance with Covid-19 prophylactic measures," Post-Print hal-04192470, HAL.
    15. Carlos A. Medel, 2013. "How informative are in-sample information criteria to forecasting? The case of Chilean GDP," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 50(1), pages 133-161, May.
    16. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
    17. Naresh Bansal & Jack Strauss & Alireza Nasseh, 2015. "Can we consistently forecast a firm’s earnings? Using combination forecast methods to predict the EPS of Dow firms," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 39(1), pages 1-22, January.
    18. Christian Glocker & Serguei Kaniovski, 2020. "Macroeconometric Forecasting Using a Cluster of Dynamic Factor Models," WIFO Working Papers 614, WIFO.
    19. Calhoun, Gray, 2014. "Out-Of-Sample Comparisons of Overfit Models," Staff General Research Papers Archive 32462, Iowa State University, Department of Economics.
    20. Medel, Carlos A., 2014. "Probabilidad Clásica de Sobreajuste con Criterios de Información: Estimaciones con Series Macroeconómicas Chilenas [Classical Probability of Overfitting with Information Criteria: Estimations with ," MPRA Paper 57401, University Library of Munich, Germany.
    21. Pereda, Javier, 2010. "Estimación de la Tasa Natural de Interés para el Perú: Un Enfoque Financiero," Working Papers 2010-018, Banco Central de Reserva del Perú.
    22. Gupta, Rangan & Modise, Mampho P., 2013. "Macroeconomic Variables and South African Stock Return Predictability," Economic Modelling, Elsevier, vol. 30(C), pages 612-622.
    23. Daniel Fernández, 2011. "Suficiencia del capital y previsiones de la banca uruguaya por su exposición al sector industrial," Monetaria, CEMLA, vol. 0(4), pages 517-589, octubre-d.
    24. Gary J. Cornwall & Jeffrey A. Mills & Beau A. Sauley & Huibin Weng, 2019. "Predictive Testing for Granger Causality via Posterior Simulation and Cross-validation," Advances in Econometrics, in: Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part A, volume 40, pages 275-292, Emerald Group Publishing Limited.
    25. Golinelli, Roberto & Parigi, Giuseppe, 2008. "Real-time squared: A real-time data set for real-time GDP forecasting," International Journal of Forecasting, Elsevier, vol. 24(3), pages 368-385.
    26. Ryan Compton & Syeed Khan, 2010. "An examination of the stability of short-run Canadian stock predictability," Economics Bulletin, AccessEcon, vol. 30(2), pages 1293-1306.
    27. McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, vol. 140(2), pages 719-752, October.
    28. Österholm, Pär, 2009. "Improving Unemployment Rate Forecasts Using Survey Data," Working Papers 112, National Institute of Economic Research.
    29. Fujiwara, Ippei & Koga, Maiko, 2004. "A Statistical Forecasting Method for Inflation Forecasting: Hitting Every Vector Autoregression and Forecasting under Model Uncertainty," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 22(1), pages 123-142, March.
    30. Mogliani, Matteo & Darné, Olivier & Pluyaud, Bertrand, 2017. "The new MIBA model: Real-time nowcasting of French GDP using the Banque de France's monthly business survey," Economic Modelling, Elsevier, vol. 64(C), pages 26-39.
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    Cited by:

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    49. Tae-Hwy Lee & Ekaterina Seregina & Yaojue Xu, 2023. "Elicitability and Encompassing for Volatility Forecasts by Bregman Functions," Working Papers 202311, University of California at Riverside, Department of Economics.
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    245. 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.
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    251. 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.
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    255. Edgar J. Sánchez Carrera & Vanesa Avalos-Gaytán & Yajaira Cardona Valdés, 2019. "Synchronization of globalized economies," Working Papers 1909, University of Urbino Carlo Bo, Department of Economics, Society & Politics - Scientific Committee - L. Stefanini & G. Travaglini, revised 2019.

  58. Todd E. Clark & Kwanho Shin, 1998. "The sources of fluctuations within and across countries," Research Working Paper 98-04, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Salvador BARROS & Marius BRÜLHART & Robert J.R. ELLIOTT & Marianne SENSIER, 2001. "A Tale of Two Cycles: Co-Fluctuations Between UK Regions and the Euro Zone," Cahiers de Recherches Economiques du Département d'économie 01.10, Université de Lausanne, Faculté des HEC, Département d’économie.
    2. Dees, S. & di Mauro, F. & Pesaran, M.H. & Smith, L.V., 2005. "Exploring the International Linkages of the Euro Area: a Global VAR Analysis," Cambridge Working Papers in Economics 0518, Faculty of Economics, University of Cambridge.
    3. António Afonso & Davide Furceri, 2007. "Sectoral Business Cycle Synchronization in the European Union," Working Papers Department of Economics 2007/02, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
    4. Carsten Hefeker, 2001. "Federal Monetary Policy," CESifo Working Paper Series 422, CESifo.
    5. Svaleryd, Helena & Vlachos, Jonas, 1999. "Markets for Risk and Openness to Trade: How are they Related?," SSE/EFI Working Paper Series in Economics and Finance 327, Stockholm School of Economics, revised 28 Aug 2001.
    6. Svatopluk Kapounek & Jitka Pomenkova, 2012. "Spurious synchronization of business cycles: Dynamic correlation analysis of V4 countries," MENDELU Working Papers in Business and Economics 2012-22, Mendel University in Brno, Faculty of Business and Economics.
    7. Ralph Chami & Gregory D. Hess, 2002. "For Better or For Worse? State-Level Marital Formation and Risk Sharing," CESifo Working Paper Series 702, CESifo.
    8. Clark, Todd E. & van Wincoop, Eric, 2001. "Borders and business cycles," Journal of International Economics, Elsevier, vol. 55(1), pages 59-85, October.
    9. Necati Tekatli, 2007. "Understanding Sources of the Change in International Business Cycles," UFAE and IAE Working Papers 731.08, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
    10. Kajal Lahiri & Gultekin Isiklar, 2010. "Estimating International Transmission of Shocks Using GDP Forecasts: India and Its Trading Partners," Discussion Papers 10-06, University at Albany, SUNY, Department of Economics.
    11. Martin Gächter & Aleksandra Riedl & Doris Ritzberger-Grünwald, 2012. "Business Cycle Synchronization in the Euro Area and the Impact of the Financial Crisis," Monetary Policy & the Economy, Oesterreichische Nationalbank (Austrian Central Bank), issue 2, pages 33-60.
    12. Christian Ariel Volpe Martincus & Andrea Molinari, 2005. "Regional Business Cycles and National Economic Borders - What are the Effects of Trade in Developing Countries?," ERSA conference papers ersa05p93, European Regional Science Association.
    13. Jean Boivin & Marc Giannoni, 2008. "Global Forces and Monetary Policy Effectiveness," NBER Working Papers 13736, National Bureau of Economic Research, Inc.
    14. Del Negro, Marco, 2002. "Asymmetric shocks among U.S. states," Journal of International Economics, Elsevier, vol. 56(2), pages 273-297, March.
    15. Pablo Guerrón-Quintana, 2012. "Common and idiosyncratic disturbances in developed small open economies," Working Papers 12-3, Federal Reserve Bank of Philadelphia.
    16. Jürgen Bierbaumer & Werner Hölzl, 2015. "Business Cycle Dynamics and Firm Heterogeneity. Evidence for Austria Using Survey Data," WIFO Working Papers 504, WIFO.
    17. M. Ayhan Kose & Christopher Otrok & Charles H. Whiteman, 2003. "International Business Cycles: World, Region, and Country-Specific Factors," American Economic Review, American Economic Association, vol. 93(4), pages 1216-1239, September.
    18. Furceri, Davide & Loungani, Prakash & Pizzuto, Pietro, 2022. "Moving closer? Comparing regional adjustments to shocks in EMU and the United States," Journal of International Money and Finance, Elsevier, vol. 120(C).
    19. D. Furceri & G. Karras, 2008. "Business-cycle synchronization in the EMU," Applied Economics, Taylor & Francis Journals, vol. 40(12), pages 1491-1501.
    20. Geoffrey Hewings, 2008. "On some conundra in regional science," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 42(2), pages 251-265, June.
    21. Economidou, Claire & Kool, Clemens, 2009. "European economic integration and (a)symmetry of macroeconomic fluctuations," Economic Modelling, Elsevier, vol. 26(4), pages 778-787, July.
    22. Marianne Baxter & Michael A. Kouparitsas, 2004. "Determinants of Business Cycle Comovement: A Robust Analysis," NBER Working Papers 10725, National Bureau of Economic Research, Inc.
    23. Ansgar BELKE & Jens H. HEINE, 2010. "Specialisation Patterns and the Synchronicity of Regional Employment Cycles in Europe," EcoMod2004 330600020, EcoMod.
    24. Carlino, Gerald A. & DeFina, Robert H. & Sill, Keith, 2001. "Sectoral Shocks and Metropolitan Employment Growth," Journal of Urban Economics, Elsevier, vol. 50(3), pages 396-417, November.
    25. Knut Are Aastveit & Hilde C. Bjørnland & Leif Anders Thorsrud, 2011. "The world is not enough! Small open economies and regional dependence," Working Paper 2011/16, Norges Bank.
    26. Konstantakis, Konstantinos N. & Michaelides, Panayotis G., 2014. "Transmission of the debt crisis: From EU15 to USA or vice versa? A GVAR approach," Journal of Economics and Business, Elsevier, vol. 76(C), pages 115-132.
    27. Coulson, N. Edward, 1999. "Sectoral sources of metropolitan growth," Regional Science and Urban Economics, Elsevier, vol. 29(6), pages 723-743, November.
    28. Kalemli-Ozcan, Sebnem & Sorensen, Bent E. & Yosha, Oved, 2001. "Economic integration, industrial specialization, and the asymmetry of macroeconomic fluctuations," Journal of International Economics, Elsevier, vol. 55(1), pages 107-137, October.
    29. Yuriy Gorodnichenko, 2005. "Reduced-Rank Identification of Structural Shocks in VARs," Macroeconomics 0512011, University Library of Munich, Germany.
    30. Davide Furceri, 2002. "Risk-sharing e architettura istituzionale delle politiche di stabilizzazione nell'UME: aspetti metodologici e verifica empirica," Rivista di Politica Economica, SIPI Spa, vol. 92(6), pages 175-210, November-.
    31. Ansgar Belke & Jens Heine, 2007. "On the endogeneity of an exogenous OCA-criterion: specialisation and the correlation of regional business cycles in Europe," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 34(1), pages 15-44, March.
    32. Partridge, Mark D. & Rickman, Dan S., 2003. "The waxing and waning of regional economies: the chicken-egg question of jobs versus people," Journal of Urban Economics, Elsevier, vol. 53(1), pages 76-97, January.
    33. Sungyup Chung & Geoffrey J.D. Hewings, 2015. "Competitive and Complementary Relationship between Regional Economies: A Study of the Great Lake States," Spatial Economic Analysis, Taylor & Francis Journals, vol. 10(2), pages 205-229, June.
    34. Christian Matthes & Felipe Schwartzman, 2019. "What Do Sectoral Dynamics Tell Us About the Origins of Business Cycles?," Working Paper 19-9, Federal Reserve Bank of Richmond.
    35. Thomas Walker & David Norman, 2004. "Co-movement of Australian State Business Cycles," Econometric Society 2004 Australasian Meetings 334, Econometric Society.
    36. Vlachos, Jonas, 2005. "Does Labour Market Risk Increase the Size of the Public Sector? Evidence from Swedish Municipalities," CEPR Discussion Papers 5091, C.E.P.R. Discussion Papers.
    37. Svaleryd, Helena & Vlachos, Jonas, 2000. "Does Financial Development Lead to Trade Liberalization?," Research Papers in Economics 2000:11, Stockholm University, Department of Economics.
    38. Ossama Mikhail, 2004. "No More Rocking Horses: Trading Business-Cycle Depth for Duration Using an Economy-Specific Characteristic," Macroeconomics 0402026, University Library of Munich, Germany.
    39. Beate Schirwitz & Christian Seiler & Klaus Wohlrabe, 2009. "Regionale Konjunkturzyklen in Deutschland – Teil III: Konvergenz," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 62(15), pages 23-32, August.
    40. Ṣebnem Kalemli-Özcan & Bent E. Sorensen & Oved Yosha, 1999. "Industrial specialization and the asymmetry of shocks across regions," Research Working Paper 99-06, Federal Reserve Bank of Kansas City.
    41. Michael Fratantoni & Scott Schuh, 2000. "Monetary policy, housing investment, and heterogeneous regional markets," Working Papers 00-1, Federal Reserve Bank of Boston.
    42. Rafiq, M.S., 2011. "The optimality of a gulf currency union: Commonalities and idiosyncrasies," Economic Modelling, Elsevier, vol. 28(1-2), pages 728-740, January.
    43. Gerald A. Carlino, 2003. "A confluence of events? explaining fluctuations in local employment," Business Review, Federal Reserve Bank of Philadelphia, issue Q1, pages 6-12.

  59. Todd E. Clark, 1997. "Do producer prices help predict consumer prices?," Research Working Paper 97-09, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Chihying, Hsiao & Chen, Pu, 2007. "Learning Causal Relations in Multivariate Time Series Data," Economics Discussion Papers 2007-15, Kiel Institute for the World Economy (IfW Kiel).
    2. Jonsson, Magnus & Palmqvist, Stefan, 2004. "Do Higher Wages Cause Inflation?," Working Paper Series 159, Sveriges Riksbank (Central Bank of Sweden).
    3. Gregory D. Hess & Mark E. Schweitzer, 2000. "Does wage inflation cause price inflation?," Policy Discussion Papers, Federal Reserve Bank of Cleveland, issue Apr.
    4. Carbajal-De-Nova, Carolina, 2021. "Wages and inflation in Mexican manufacturing. A two-period comparison: 1994-2003 and 2007-2016," MPRA Paper 109555, University Library of Munich, Germany.

  60. Todd E. Clark, 1996. "Finite-sample properties of tests for forecast equivalence," Research Working Paper RWP 96-03, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Frédérick Demers & Annie De Champlain, 2005. "Forecasting Core Inflation in Canada: Should We Forecast the Aggregate or the Components?," Staff Working Papers 05-44, Bank of Canada.
    2. Hendry, David F. & Hubrich, Kirstin, 2006. "Forecasting economic aggregates by disaggregates," Working Paper Series 589, European Central Bank.
    3. Martin Lettau & Sydney C. Ludvigson, 1999. "Consumption, aggregate wealth and expected stock returns," Staff Reports 77, Federal Reserve Bank of New York.
    4. West, K.D. & McCracken, M.W., 1997. "Regression-Based Tests of Predictive Ability," Working papers 9710, Wisconsin Madison - Social Systems.
    5. Pär Österholm & Mr. Helge Berger, 2008. "Does Money Growth Granger-Cause Inflation in the Euro Area? Evidence from Out-of-Sample Forecasts Using Bayesian VARs," IMF Working Papers 2008/053, International Monetary Fund.
    6. Todd E. Clark & Michael McCracken, 1999. "Tests of Equal Forecast Accuracy and Encompassing for Nested Models," Computing in Economics and Finance 1999 1241, Society for Computational Economics.

  61. Todd E. Clark, 1996. "The responses of prices at different stages of production to monetary policy shocks," Research Working Paper 96-12, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Akdi, Yilmaz & Berument, Hakan & Mümin Cilasun, Seyit, 2006. "The relationship between different price indices: Evidence from Turkey," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 360(2), pages 483-492.
    2. James C. MacGee & Pedro S. Amaral, 2010. "A Multi-sectoral Approach to the U.S. Great Depression," 2010 Meeting Papers 1242, Society for Economic Dynamics.
    3. Lian An & Jian Wang, 2011. "Exchange rate pass-through: evidence based on vector autoregression with sign restrictions," Globalization Institute Working Papers 70, Federal Reserve Bank of Dallas.
    4. Mohamed Ilyes Gritli, 2021. "Price inflation and exchange rate pass‐through in Tunisia," African Development Review, African Development Bank, vol. 33(4), pages 715-728, December.
    5. Heng-fu Zou, 2023. "Recent Studies on Macro Dynamics and Finance," CEMA Working Papers 632, China Economics and Management Academy, Central University of Finance and Economics.
    6. Kevin X. D. Huang & Zheng Liu, 2003. "Inflation to target : what inflation to target?," Research Working Paper RWP 03-10, Federal Reserve Bank of Kansas City.
    7. Kevin X. D. Huang & Zheng Liu, 2004. "Multiple stages of processing and the quantity anomaly in international business cycle models," Research Working Paper RWP 04-05, Federal Reserve Bank of Kansas City.
    8. Kevin Huang, 2006. "Specific factors meet intermediate inputs: implications for the persistence problem," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 9(3), pages 483-507, July.
    9. K. Huang & Z. Liu & L. Phaneuf, "undated". "Staggered contracts, intermediate goods and the dynamic effects of monetary shocks on output, inflation and real wages," Working Papers 2000-20, Utah State University, Department of Economics.
    10. Huang, Kevin X. D. & Liu, Zheng, 2001. "Production chains and general equilibrium aggregate dynamics," Journal of Monetary Economics, Elsevier, vol. 48(2), pages 437-462, October.
    11. Kevin X. D. Huang & Jonathan L. Willis, 2018. "Sectoral Interactions and Monetary Policy under Costly Price Adjustments," Annals of Economics and Finance, Society for AEF, vol. 19(2), pages 337-374, November.
    12. Jonathan McCarthy, 2000. "Pass-through of exchange rates and import prices to domestic inflation in some industrialized economies," Staff Reports 111, Federal Reserve Bank of New York.
    13. Ng, Serena, 2003. "Can sticky prices account for the variations and persistence in real exchange rates?," Journal of International Money and Finance, Elsevier, vol. 22(1), pages 65-85, February.
    14. Felipe Morandé & Matías Tapia, 2002. "Exchange Rate Policy in Chile: From the Band to Floating and Beyond," Working Papers wp192, University of Chile, Department of Economics.
    15. Gong Liutang & Wang Chan & Zou Heng-Fu, 2020. "Optimal monetary policy in a model of vertical production and trade with reference currency," The B.E. Journal of Macroeconomics, De Gruyter, vol. 20(1), pages 1-21, January.
    16. Georgios Bampinas & Theodore Panagiotidis, 2016. "Hedging Inflation with Individual US stocks: A long-run portfolio analysis," Working Paper series 16-11, Rimini Centre for Economic Analysis.
    17. Todd E. Clark, 2006. "Disaggregate evidence on the persistence of consumer price inflation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 563-587, July.
    18. Kevin X. D. Huang, 2005. "Specific factors meet intermediate inputs: implications for strategic complementarities and persistence," Working Papers 04-7, Federal Reserve Bank of Philadelphia.
    19. Winkelried, Diego, 2012. "Traspaso del tipo de cambio y metas de inflación en el Perú," Revista Estudios Económicos, Banco Central de Reserva del Perú, issue 23, pages 9-24.
    20. Kevin X.D. Huang & Zheng Liu & Louis Phaneuf, 2004. "Why Does the Cyclical Behavior of Real Wages Change Over Time?," American Economic Review, American Economic Association, vol. 94(4), pages 836-856, September.
    21. Shantanu Dutta & Mark Bergen & Daniel Levy, 2004. "Price Flexibility in Channels of Distribution: Evidence from Scanner Data," Macroeconomics 0402018, University Library of Munich, Germany.
    22. Liutang Gong & Chan Wang & Heng-fu Zou, 2017. "Optimal Exchange-Rate Policy in a Model of Local-Currency Pricing with Vertical Production and Trade," CEMA Working Papers 603, China Economics and Management Academy, Central University of Finance and Economics.
    23. Huang, Kevin X.D. & Liu, Zheng, 2005. "Inflation targeting: What inflation rate to target?," Journal of Monetary Economics, Elsevier, vol. 52(8), pages 1435-1462, November.
    24. Brad E. Strum, 2010. "Inflation persistence, backward-looking firms, and monetary policy in an input-output economy," Finance and Economics Discussion Series 2010-55, Board of Governors of the Federal Reserve System (U.S.).
    25. Juan manuel Julio & Héctor manuel Zárate, 2008. "The Price Setting Behavior in Colombia: evidence from PPI micro data," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República, vol. 26(56), pages 12-44, June.
    26. Takatoshi Ito & Kiyotaka Sato, 2006. "Exchange Rate Changes and Inflation in Post-Crisis Asian Economies: VAR Analysis of the Exchange Rate Pass-Through (Subsequently published in "Journal of Money, Credit and Banking", Volume 4," CARF F-Series CARF-F-063, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    27. Noussair, Charles & Plott, Charles & Riezman, Raymond, 2007. "Production, trade, prices, exchange rates and equilibration in large experimental economies," European Economic Review, Elsevier, vol. 51(1), pages 49-76, January.
    28. Rachel Male, 2010. "Business Cycle Persistence in Developing Countries: How Successful is a DSGE Model with a Vertical Production Chain and Sticky Prices?," Working Papers 672, Queen Mary University of London, School of Economics and Finance.
    29. Balke, Nathan S. & Wynne, Mark A., 2007. "The relative price effects of monetary shocks," Journal of Macroeconomics, Elsevier, vol. 29(1), pages 19-36, March.
    30. Felipe Morandé L. & Matías Tapia G., 2002. "Exchange Rate Policy in Chile: the Abandonment of the Band and the Floating Experience," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 5(3), pages 67-94, December.
    31. Noussair, C.N. & Plott, C. & Riezman, R., 2007. "Production, trade and exchange rates in large experimental economies," Other publications TiSEM 3bf683fe-0650-4e8a-8682-c, Tilburg University, School of Economics and Management.
    32. Takatoshi Ito & Kiyotaka Sato, 2006. "Exchange Rate Changes and Inflation in Post-Crisis Asian Economies: VAR Analysis of the Exchange Rate Pass-Through," CIRJE F-Series CIRJE-F-406, CIRJE, Faculty of Economics, University of Tokyo.
    33. Jian Wang, 2007. "Home bias, exchange rate disconnect, and optimal exchange rate policy," Working Papers 0701, Federal Reserve Bank of Dallas.
    34. Rao, Nasir Hamid & Bukhari, Syed Kalim Hyder, 2010. "Asymmetric Shocks and Co-movement of Price Indices," MPRA Paper 28723, University Library of Munich, Germany.
    35. Zeng, Shihong & Nan, Xin & Liu, Chao & Chen, Jiuying, 2017. "The response of the Beijing carbon emissions allowance price (BJC) to macroeconomic and energy price indices," Energy Policy, Elsevier, vol. 106(C), pages 111-121.
    36. Mr. Leo Bonato & Mr. Andreas Billmeier, 2002. "Exchange Rate Pass-Through and Monetary Policy in Croatia," IMF Working Papers 2002/109, International Monetary Fund.
    37. Schenkelberg, Heike, 2011. "Why are Prices Sticky? Evidence from Business Survey Data," Discussion Papers in Economics 12158, University of Munich, Department of Economics.
    38. Louis Phaneuf & Nooman Rebei, 2008. "Production Stages and the Transmission of Technological Progress," Cahiers de recherche 0802, CIRPEE.
    39. Niclas Andrén & Lars Oxelheim, 2011. "Exchange rate regime shift and price patterns," International Journal of Managerial Finance, Emerald Group Publishing Limited, vol. 7(2), pages 153-178, April.
    40. Julio J. Rotemberg & Michael Woodford, 1999. "The Cyclical Behavior of Prices and Costs," NBER Working Papers 6909, National Bureau of Economic Research, Inc.
    41. Diego Winkelried, 2014. "Exchange rate pass-through and inflation targeting in Peru," Empirical Economics, Springer, vol. 46(4), pages 1181-1196, June.
    42. Besnik Fetai, 2011. "Exchange Rate Pass-Through in Transition Economies: The Case of the Republic of Macedonia," William Davidson Institute Working Papers Series wp1014, William Davidson Institute at the University of Michigan.
    43. Devereux, Michael B. & Engel, Charles, 2007. "Expenditure switching versus real exchange rate stabilization: Competing objectives for exchange rate policy," Journal of Monetary Economics, Elsevier, vol. 54(8), pages 2346-2374, November.
    44. Onmus-Baykal Elif, 2011. "How Costly is CPI Inflation Targeting: A Two Sector Model with No Labor Mobility," The B.E. Journal of Macroeconomics, De Gruyter, vol. 11(1), pages 1-32, January.
    45. Gong, Liutang & Wang, Chan & Zou, Heng-fu, 2016. "Optimal monetary policy with international trade in intermediate inputs," Journal of International Money and Finance, Elsevier, vol. 65(C), pages 140-165.
    46. Singh, Aarti & Tornielli di Crestvolant, Stefano, 2018. "Transmission of monetary policy shocks: do input-output interactions matter?," Working Papers 2018-12, University of Sydney, School of Economics.
    47. Takatoshi Ito & Yuri N. Sasaki & Kiyotaka Sato, 2005. "Pass-Through of Exchange Rate Changes and Macroeconomic Shocks to Domestic Inflation in East Asian Countries," Discussion papers 05020, Research Institute of Economy, Trade and Industry (RIETI).
    48. Latorre, Concepción & Gómez-Plana, Antonio G., 2010. "Multinationals in the Motor vehicles industry: A general equilibrium analysis for a Transition Economy," Conference papers 332025, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    49. Marzinotto, Benedicta, 2009. "Beyond monetary credibility: The impact of globalisation on the output-inflation trade-off in euro-area countries," The North American Journal of Economics and Finance, Elsevier, vol. 20(2), pages 162-176, August.
    50. Chan Wang & Heng-fu Zou, 2015. "Optimal Monetary Policy Under a Global Dollar Standard: The Effect of Vertical Trade and Production," Open Economies Review, Springer, vol. 26(1), pages 121-137, February.
    51. Tiwari, Aviral Kumar & Mutascu, Mihai & Andries, Alin Marius, 2013. "Decomposing time-frequency relationship between producer price and consumer price indices in Romania through wavelet analysis," Economic Modelling, Elsevier, vol. 31(C), pages 151-159.
    52. Erwan Gautier, 2008. "The behaviour of producer prices: evidence from French PPI micro data," Empirical Economics, Springer, vol. 35(2), pages 301-332, September.
    53. Gu, Gyun Cheol, 2012. "Denial, Rationalization, and the Administered Price Thesis," MPRA Paper 42594, University Library of Munich, Germany.
    54. Kevin X. D. Huang & Zheng Liu, 1999. "Chain of production as a monetary propagation mechanism," Discussion Paper / Institute for Empirical Macroeconomics 130, Federal Reserve Bank of Minneapolis.
    55. Eleanor Doyle, 2004. "Exchange rate pass-through in a small open economy: the Anglo-Irish case," Applied Economics, Taylor & Francis Journals, vol. 36(5), pages 443-455.
    56. Simon Bilo, 2021. "Hayek’s Theory of Business Cycles: A Theory That Will Remain Obscure?," Journal of Private Enterprise, The Association of Private Enterprise Education, vol. 36(Fall 2021), pages 27-47.
    57. Toyoichiro Shirota, 2021. "Cost of Sticky Prices under Multiple Stages of Production," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 53(5), pages 1211-1222, August.
    58. Chan Wang & Heng-fu Zou, 2013. "Optimal monetary policy in open economies: the role of reference currency in vertical production and trade," CEMA Working Papers 586, China Economics and Management Academy, Central University of Finance and Economics.
    59. Yoshibumi Makabe & Yosuke Matsumoto & Wataru Hirata, 2023. "Estimating Pipeline Pressures in New Keynesian Phillips Curves: A Bayesian VAR-GMM Approach," Bank of Japan Working Paper Series 23-E-13, Bank of Japan.

  62. Todd E. Clark, 1995. "Small sample properties of estimators of non-linear models of covariance structure," Research Working Paper 95-01, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Andrew E. Clark, 2003. "Unemployment as a Social Norm: Psychological Evidence from Panel Data," Journal of Labor Economics, University of Chicago Press, vol. 21(2), pages 289-322, April.
    2. Gustavsson, Magnus, 2004. "Trends in the Transitory Variance of Earnings: Evidence from Sweden 1960-1990 and a Comparison with the United States," Working Paper Series 2004:11, Uppsala University, Department of Economics.
    3. Michael Baker & Gary Solon, 2003. "Earnings Dynamics and Inequality among Canadian Men, 1976-1992: Evidence from Longitudinal Income Tax Records," Journal of Labor Economics, University of Chicago Press, vol. 21(2), pages 267-288, April.
    4. Magnus Gustavsson, 2007. "The 1990s rise in Swedish earnings inequality -- persistent or transitory?," Applied Economics, Taylor & Francis Journals, vol. 39(1), pages 25-30.
    5. Aedin Doris & Donal O'Neill & Olive Sweetman, 2010. "Identification of the Covariance Structure of Earnings using the GMM Estimator," Economics Department Working Paper Series n208-10.pdf, Department of Economics, National University of Ireland - Maynooth.
    6. Damba Lkhagvasuren, 2009. "Large Locational Differences in Unemployment Despite High Labor Mobility: Impact of Moving Cost on Aggregate Unemployment and Welfare," Working Papers 09009, Concordia University, Department of Economics, revised Mar 2010.
    7. Toda, Alexis Akira & Walsh, Kieran James, 2017. "Fat tails and spurious estimation of consumption-based asset pricing models," University of California at San Diego, Economics Working Paper Series qt8df3x7gw, Department of Economics, UC San Diego.
    8. Hanns de la Fuente-Mella & Rolando Rubilar & Karime Chahuán-Jiménez & Víctor Leiva, 2021. "Modeling COVID-19 Cases Statistically and Evaluating Their Effect on the Economy of Countries," Mathematics, MDPI, vol. 9(13), pages 1-13, July.
    9. Vanesa Jorda & Jos Mar a Sarabia & Markus J ntti, 2020. "Estimation of Income Inequality from Grouped Data," LIS Working papers 804, LIS Cross-National Data Center in Luxembourg.
    10. Clark, Todd E, 1998. "Employment Fluctuations in U.S. Regions and Industries: The Roles of National, Region-Specific, and Industry-Specific Shocks," Journal of Labor Economics, University of Chicago Press, vol. 16(1), pages 202-229, January.
    11. Taisuke Nakata & Christopher Tonetti, 2015. "Small Sample Properties of Bayesian Estimators of Labor Income Processes," Journal of Applied Economics, Taylor & Francis Journals, vol. 18(1), pages 121-148, May.
    12. Andrew Shephard & Xu Cheng & Alejándro Sanchez-Becerra, 2023. "How to weight in moments matchings: A new approach and applications to earnings dynamics," CeMMAP working papers 13/23, Institute for Fiscal Studies.
    13. Bhashkar Mazumder, 2002. "The Mis-Measurement of Permanent Earnings: New Evidence from Social Security Earnings Data," Working Papers 02-12, Center for Economic Studies, U.S. Census Bureau.
    14. Kezdi, Gabor & Hahn, Jinyong & Solon, Gary, 2002. "Jackknife minimum distance estimation," Economics Letters, Elsevier, vol. 76(1), pages 35-45, June.
    15. Eric S. Lin & Ta-Sheng Chou, 2018. "Finite-sample refinement of GMM approach to nonlinear models under heteroskedasticity of unknown form," Econometric Reviews, Taylor & Francis Journals, vol. 37(1), pages 1-28, January.
    16. Timm Bönke & Matthias Giesecke & Holger Lüthen, 2015. "The Dynamics of Earnings in Germany: Evidence from Social Security Records," Discussion Papers of DIW Berlin 1514, DIW Berlin, German Institute for Economic Research.
    17. Myck, Michal & Ochmann, Richard & Qari, Salmai, 2008. "Dynamics of Earnings and Hourly Wages in Germany," IZA Discussion Papers 3751, Institute of Labor Economics (IZA).
    18. Christian Bredemeier & Jan Gravert & Falko Juessen, 2019. "Estimating Labor Supply Elasticities with Joint Borrowing Constraints of Couples," Journal of Labor Economics, University of Chicago Press, vol. 37(4), pages 1215-1265.
    19. Ostrovsky Yuri, 2010. "Long-Run Earnings Inequality and Earnings Instability among Canadian Men Revisited, 1985-2005," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 10(1), pages 1-34, March.
    20. Jason Allen & Allan Gregory & Katsumi Shimotsu, 2008. "Empirical Likelihood Block Bootstrapping," Staff Working Papers 08-18, Bank of Canada.
    21. Artem Prokhorov, 2010. "Second Order Bias of Quasi-MLE for Covariance Structure Models," Working Papers 10001, Concordia University, Department of Economics.
    22. Yuriy Gorodnichenko, 2005. "Reduced-Rank Identification of Structural Shocks in VARs," Macroeconomics 0512011, University Library of Munich, Germany.
    23. George Kapetanios & Tony Yates, 2010. "Estimating time variation in measurement error from data revisions: an application to backcasting and forecasting in dynamic models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(5), pages 869-893.
    24. Yasutomo Murasawa, 2009. "Do coincident indicators have one-factor structure?," Empirical Economics, Springer, vol. 36(2), pages 339-365, May.
    25. Yuriy Gorodnichenko, 2007. "Using Firm Optimization to Evaluate and Estimate Returns to Scale," NBER Working Papers 13666, National Bureau of Economic Research, Inc.
    26. Joachim Inkmann, 2000. "Finite Sample Properties of One-Step, Two-Step and Bootstrap Empirical Likelihood Approaches to Efficient GMM Estimation," Econometric Society World Congress 2000 Contributed Papers 0332, Econometric Society.
    27. George Kapetanios & Tony Yates, 2004. "Estimating time-variation in measurement error from data revisions; an application to forecasting in dynamic models," Bank of England working papers 238, Bank of England.
    28. Gustavsson, Magnus, 2002. "Earnings Dynamics and Inequality during Macroeconomic Turbulence: Sweden 1991-1999," Working Paper Series 2002:20, Uppsala University, Department of Economics.
    29. 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.
    30. Sologon, Denisa Maria & O'Donoghue, Cathal, 2009. "Earnings Dynamics and Inequality among Men across 14 EU Countries, 1994-2001: Evidence from ECHP," IZA Discussion Papers 4012, Institute of Labor Economics (IZA).
    31. SOLOGON Denisa & VAN KERM Philippe, 2014. "Earnings dynamics, foreign workers and the stability of inequality trends in Luxembourg 1988-2009," LISER Working Paper Series 2014-03, Luxembourg Institute of Socio-Economic Research (LISER).
    32. Albert Maydeu-Olivares, 1999. "Thurstonian modeling of ranking data via mean and covariance structure analysis," Psychometrika, Springer;The Psychometric Society, vol. 64(3), pages 325-340, September.
    33. Gustafsson, Johan & Holmberg, Johan, 2019. "Earning dynamics in Sweden: The recent evolution of permanent inequality and earnings volatility," Umeå Economic Studies 963, Umeå University, Department of Economics.

  63. Todd E. Clark, 1993. "Cross-country evidence on long run growth and inflation," Research Working Paper 93-05, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Manoel Bittencourt, 2008. "Inflation and Financial Development: Evidence from Brazil," Working Papers 067, Economic Research Southern Africa.
    2. Orphanides, Athanasios & Wieland, Volker, 2000. "Inflation zone targeting," European Economic Review, Elsevier, vol. 44(7), pages 1351-1387, June.
    3. Muhammad Farooq Arby & Amjad Ali, 2017. "Threshold Inflation in Pakistan," SBP Research Bulletin, State Bank of Pakistan, Research Department, vol. 13, pages 1-19.
    4. Andres, Javier & Domenech, Rafael & Molinas, Cesar, 1996. "Macroeconomic performance and convergence in OECD countries," European Economic Review, Elsevier, vol. 40(9), pages 1683-1704, December.
    5. Ramaprasad Bhar, 2010. "Stochastic Filtering with Applications in Finance," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 7736, August.
    6. Coenen, Günter & Orphanides, Athanasios & Wieland, Volker, 2003. "Price stability and monetary policy effectiveness when nominal interest rates are bounded at zero," CFS Working Paper Series 2003/13, Center for Financial Studies (CFS).
    7. Daniel L. Thornton, 1996. "The costs and benefits of price stability: an assessment of Howitt's rule," Review, Federal Reserve Bank of St. Louis, vol. 78(Mar), pages 23-38.
    8. Ruth A. Judson & Athanasios Orphanides, "undated". "Inflation, Volatility, and Growth," Finance and Economics Discussion Series 1996-19, Board of Governors of the Federal Reserve System (U.S.), revised 10 Dec 2019.
    9. F. Heylen & L. Pozzi & J. Vandewege, 2004. "Inflation crises, human capital formation and growth," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 04/260, Ghent University, Faculty of Economics and Business Administration.
    10. Neil R. Ericsson & John S. Irons & Ralph W. Tryon, 2001. "Output and inflation in the long run," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 241-253.
    11. Brian O'Reilly, 1998. "The Benefits of Low Inflation: Taking Shock "A nickel ain't worth a dime any more" [Yogi Berra]," Technical Reports 83, Bank of Canada.
    12. Lindh, Thomas & Malmberg, Bo, 1998. "Age structure and inflation - a Wicksellian interpretation of the OECD data," Journal of Economic Behavior & Organization, Elsevier, vol. 36(1), pages 19-37, July.
    13. Metiu, Norbert & Prieto, Esteban, 2023. "The macroeconomic effects of inflation uncertainty," Discussion Papers 32/2023, Deutsche Bundesbank.
    14. Grier, Robin & Grier, Kevin B., 2006. "On the real effects of inflation and inflation uncertainty in Mexico," Journal of Development Economics, Elsevier, vol. 80(2), pages 478-500, August.
    15. George C. Bitros & Epameinondas E. Panas, 2005. "The inflation-productivity trade-off revisited," Macroeconomics 0512012, University Library of Munich, Germany.
    16. Apergis, Nicholas & Eleftheriou, Sophia, 2002. "Interest rates, inflation, and stock prices: the case of the Athens Stock Exchange," Journal of Policy Modeling, Elsevier, vol. 24(3), pages 231-236, June.
    17. Noha Emara, 2012. "Inflation Volatility, Institutions, and Economic Growth," Global Journal of Emerging Market Economies, Emerging Markets Forum, vol. 4(1), pages 29-53, January.
    18. Girijasankar Mallik & Anis Chowdhury, 2011. "Effect of inflation uncertainty, output uncertainty and oil price on inflation and growth in Australia," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 38(4), pages 414-429, September.
    19. Mustafa Caglayan & Ozge Kandemir Kocaaslan & Kostas Mouratidis, 2016. "Regime Dependent Effects of Inflation Uncertainty on Real Growth: A Markov Switching Approach," Scottish Journal of Political Economy, Scottish Economic Society, vol. 63(2), pages 135-155, May.
    20. Bittencourt, Manoel, 2012. "Inflation and economic growth in Latin America: Some panel time-series evidence," Economic Modelling, Elsevier, vol. 29(2), pages 333-340.
    21. Elisabeth Huybens & Bruce D. Smith, 1997. "Inflation, Financial Markets and Long-Run Real Activity," Working Papers 9707, Centro de Investigacion Economica, ITAM.
    22. Loizides, John & Vamvoukas, George, 2005. "Government Expenditure and Economic Growth: Evidence from Trivariate Causality Testing," Journal of Applied Economics, Universidad del CEMA, vol. 8(1), pages 1-28, May.
    23. Hachicha, Ahmed & Lean Hooi Hooi, 2013. "Inflation, inflation uncertainty and output in Tunisia," Economics Discussion Papers 2013-1, Kiel Institute for the World Economy (IfW Kiel).
    24. Karen H. Johnson & David H. Small & Ralph W. Tryon, 1999. "Monetary policy and price stability," International Finance Discussion Papers 641, Board of Governors of the Federal Reserve System (U.S.).
    25. Michelle L. Barnes, 2000. "Threshold Relationships among Inflation, Financial Market Development and Growth," School of Economics and Public Policy Working Papers 2000-04, University of Adelaide, School of Economics and Public Policy.
    26. Doho, Libaud Rudy Aurelien & Somé, Sobom Matthieu & Banto, Jean Michel, 2023. "Inflation and west African sectoral stock price indices: An asymmetric kernel method analysis," Emerging Markets Review, Elsevier, vol. 54(C).
    27. Hunter Humphries & Stephen Knowles, 1998. "Does agriculture contribute to economic growth? Some empirical evidence," Applied Economics, Taylor & Francis Journals, vol. 30(6), pages 775-781.
    28. Kushal Banik Chowdhury & Nityananda Sarkar, 2019. "Regime Dependent Effect Of Output Growth On Output Growth Uncertainty: Evidence From Oecd Countries," Bulletin of Economic Research, Wiley Blackwell, vol. 71(3), pages 257-282, July.
    29. Binder, Carola C., 2017. "Measuring uncertainty based on rounding: New method and application to inflation expectations," Journal of Monetary Economics, Elsevier, vol. 90(C), pages 1-12.
    30. Daniel Bolton & W. Robert & J. Alexander, 2001. "The differing consequences of low and high rates of inflation," Applied Economics Letters, Taylor & Francis Journals, vol. 8(6), pages 411-414.
    31. Aribah Aslam, 2020. "The hotly debate of human capital and economic growth: why institutions may matter?," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(4), pages 1351-1362, August.
    32. Kyriakos C. Neanidis & Christos S. Savva, 2010. "Macroeconomic Uncertainty, Inflation and Growth: Regime-Dependent Effects in the G7," Centre for Growth and Business Cycle Research Discussion Paper Series 145, Economics, The University of Manchester.
    33. R. I. Udegbunam, 2002. "Openness, Stock Market Development, and Industrial Growth in Nigeria," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 41(1), pages 69-92.
    34. Georgios Bitros & Epaminondas Panas, 2005. "Another look at the inflation-productivity trade-off," Macroeconomics 0506001, University Library of Munich, Germany.
    35. Mustafa Caglayan & Ozge Kandemir & Kostas Mouratidis, 2012. "The Impact of Inflation Uncertainty on Economic Growth: A MRS-IV Approach," Working Papers 2012025, The University of Sheffield, Department of Economics.
    36. Bonga-Bonga, Lumengo & Ahiakpor, Ferdinand, 2015. "Determinants of Economic Growth in Sub-Saharan Africa: The case of Ghana," MPRA Paper 66923, University Library of Munich, Germany.
    37. Mustafa Caglayan & Ozge Kandemir & Kostas Mouratidis, 2011. "Real effects of inflation uncertainty in the US," Working Papers 2011002, The University of Sheffield, Department of Economics, revised Feb 2015.
    38. Hongyi Li & Heng-fu Zou, 2002. "Inflation, Growth, and Income Distribution: A Cross-Country Study," CEMA Working Papers 85, China Economics and Management Academy, Central University of Finance and Economics.
    39. Hendrickson, Joshua R. & Salter, Alexander William, 2016. "Money, liquidity, and the structure of production," Journal of Economic Dynamics and Control, Elsevier, vol. 73(C), pages 314-328.
    40. Abu N. M. Wahid & Muhammad Shahbaz & Pervaz Azim, 2011. "Inflation and Financial Sector Correlation: The Case of Bangladesh," International Journal of Economics and Financial Issues, Econjournals, vol. 1(4), pages 145-152.
    41. Javier Andrés & Ignacio Hernando & J. David López-Salido, 1999. "Assessing the benefits of price stability: The international experience," Estudios Económicos, Banco de España, number 69.
    42. F. Heylen & A. Schollaert & G. Everaert & L. Pozzi, 2003. "Inflation and human capital formation : theory and panel data evidence," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 03/174, Ghent University, Faculty of Economics and Business Administration.
    43. Mustafa Caglayan & Feng Jiang, 2006. "Reexamining the linkages between inflation and output growth: A bivariate ARFIMA-FIGARCH approach," Working Papers 2006_8, Business School - Economics, University of Glasgow.
    44. Emara, Noha, 2012. "Inflation volatility, financial institutions and sovereign debt rating," MPRA Paper 68688, University Library of Munich, Germany.
    45. Narayan, Seema & Narayan, Paresh Kumar, 2013. "The inflation–output nexus: Empirical evidence from India, South Africa, and Brazil," Research in International Business and Finance, Elsevier, vol. 28(C), pages 19-34.
    46. Manoel Bittencourt & Reneé Eyden & Monaheng Seleteng, 2015. "Inflation and Economic Growth: Evidence from the Southern African Development Community," South African Journal of Economics, Economic Society of South Africa, vol. 83(3), pages 411-424, September.
    47. Wilson, Bradley Kemp, 2006. "The links between inflation, inflation uncertainty and output growth: New time series evidence from Japan," Journal of Macroeconomics, Elsevier, vol. 28(3), pages 609-620, September.

  64. Todd E. Clark, 1993. "Rents and prices of housing across areas of the U.S.: a cross-section examination of the present value model," Research Working Paper 93-04, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Clark, Todd E., 1995. "Rents and prices of housing across areas of the United States. A cross-section examination of the present value model," Regional Science and Urban Economics, Elsevier, vol. 25(2), pages 237-247, April.
    2. Brian Micallef & Nathaniel Debono, 2020. "The rental sector and the housing block in STREAM," CBM Working Papers WP/03/2020, Central Bank of Malta.

  65. Todd E. Clark, 1992. "Business cycle fluctuations in U.S. regions and industries: the roles of national, region-specific, and industry-specific shocks," Research Working Paper 92-05, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Cribari-Neto, Francisco, 1996. "On time series econometrics," The Quarterly Review of Economics and Finance, Elsevier, vol. 36(Supplemen), pages 37-60.
    2. David D. Selover & Roderick V. Jensen & John Kroll, 2005. "Mode‐Locking and Regional Business Cycle Synchronization," Journal of Regional Science, Wiley Blackwell, vol. 45(4), pages 703-745, November.
    3. Joshua L. Rosenbloom & William A. Sundstrom, 1997. "The Sources of Regional Variation in the Severity of the Great Depression: Evidence from U.S. Manufacturing, 1919-1937," NBER Working Papers 6288, National Bureau of Economic Research, Inc.
    4. Atish R. Ghosh & Holger C. Wolf, 1997. "Geographical and Sectoral Shocks in the U.S. Business Cycle," NBER Working Papers 6180, National Bureau of Economic Research, Inc.
    5. Jonathan McCarthy & Charles Steindel, 1996. "The relative importance of national and regional factors in the New York Metropolitan economy," Research Paper 9621, Federal Reserve Bank of New York.
    6. Cribari-Neto, Francisco, 1993. "Unit roots, random walks and the sources of business cycles: a survey," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 47(3), July.

Articles

  1. Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino & Michael Pfarrhofer, 2024. "Investigating Growth-at-Risk Using a Multicountry Nonparametric Quantile Factor Model," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(4), pages 1302-1317, October.
    See citations under working paper version above.
  2. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2024. "Addressing COVID-19 Outliers in BVARs with Stochastic Volatility," The Review of Economics and Statistics, MIT Press, vol. 106(5), pages 1403-1417, September.
    See citations under working paper version above.
  3. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2024. "Capturing Macro‐Economic Tail Risks with Bayesian Vector Autoregressions," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 56(5), pages 1099-1127, August.
    See citations under working paper version above.
  4. Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino & Michael Pfarrhofer, 2023. "Tail Forecasting With Multivariate Bayesian Additive Regression Trees," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(3), pages 979-1022, August.
    See citations under working paper version above.
  5. Todd E. Clark & Matthew V. Gordon, 2023. "The Impacts of Supply Chain Disruptions on Inflation," Economic Commentary, Federal Reserve Bank of Cleveland, vol. 2023(08), pages 1-8, May.

    Cited by:

    1. Xiwen Bai & Jesús Fernández-Villaverde & Yiliang Li & Francesco Zanetti, 2024. "The Causal Effects of Global Supply Chain Disruptions on Macroeconomic Outcomes: Evidence and Theory," CESifo Working Paper Series 10930, CESifo.
    2. Paula Bejarano Carbo, 2024. "The Nature of the Inflationary Surprise in Europe and the USA," National Institute of Economic and Social Research (NIESR) Discussion Papers 554, National Institute of Economic and Social Research.
    3. Christopher Healy & Chengcheng Jia, 2023. "Monetary Policy since the Onset of the COVID-19 Pandemic: A Path-Dependent Interpretation," Economic Commentary, Federal Reserve Bank of Cleveland, vol. 2023(12), pages 1-8, July.

  6. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022. "Nowcasting tail risk to economic activity at a weekly frequency," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 843-866, August.
    See citations under working paper version above.
  7. Yu Bai & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022. "Macroeconomic forecasting in a multi‐country context," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1230-1255, September.
    See citations under working paper version above.
  8. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano, 2021. "Using time-varying volatility for identification in Vector Autoregressions: An application to endogenous uncertainty," Journal of Econometrics, Elsevier, vol. 225(1), pages 47-73.
    See citations under working paper version above.
  9. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2021. "No‐arbitrage priors, drifting volatilities, and the term structure of interest rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 495-516, August.
    See citations under working paper version above.
  10. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2020. "Assessing international commonality in macroeconomic uncertainty and its effects," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(3), pages 273-293, April.
    See citations under working paper version above.
  11. Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2020. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," The Review of Economics and Statistics, MIT Press, vol. 102(1), pages 17-33, March.
    See citations under working paper version above.
  12. 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.

    Cited by:

    1. 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.
    2. Jongrim Ha & M. Ayhan Kose & Franziska Ohnsorge, 2022. "Global Stagflation," Koç University-TUSIAD Economic Research Forum Working Papers 2204, Koc University-TUSIAD Economic Research Forum.
    3. Ha, Jongrim & Kose, M. Ayhan & Ohnsorge, Franziska, 2021. "Inflation During the Pandemic: What Happened? What is Next?," MPRA Paper 108677, University Library of Munich, Germany.
    4. Bognanni, Mark, 2022. "Comment on “Large Bayesian vector autoregressions with stochastic volatility and non-conjugate priors”," Journal of Econometrics, Elsevier, vol. 227(2), pages 498-505.
    5. 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.
    6. 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.
    7. Joshua C. C. Chan, 2022. "Comparing Stochastic Volatility Specifications for Large Bayesian VARs," Papers 2208.13255, arXiv.org.
    8. 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.
    9. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    10. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    11. Ramis Khabibullin & Sergei Seleznev, 2022. "Fast Estimation of Bayesian State Space Models Using Amortized Simulation-Based Inference," Bank of Russia Working Paper Series wps104, Bank of Russia.
    12. Javier Sánchez García & Salvador Cruz Rambaud, 2022. "Machine Learning Regularization Methods in High-Dimensional Monetary and Financial VARs," Mathematics, MDPI, vol. 10(6), pages 1-15, March.
    13. Mike Tsionas & Marwan Izzeldin & Lorenzo Trapani, 2019. "Bayesian estimation of large dimensional time varying VARs using copulas," Papers 1912.12527, arXiv.org.
    14. Joshua C.C. Chan & Rodney W. Strachan, 2020. "Bayesian state space models in macroeconometrics," CAMA Working Papers 2020-90, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    15. 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.
    16. Bańbura, Marta & Leiva-Leon, Danilo & Menz, Jan-Oliver, 2021. "Do inflation expectations improve model-based inflation forecasts?," Working Paper Series 2604, European Central Bank.
    17. Leonardo Nogueira Ferreira & Silvia Miranda-Agrippino & Giovanni Ricco, 2023. "Bayesian Local Projections," Working Papers Series 581, Central Bank of Brazil, Research Department.
    18. Edward S. Knotek & Saeed Zaman, 2020. "Real-Time Density Nowcasts of US Inflation: A Model-Combination Approach," Working Papers 20-31, Federal Reserve Bank of Cleveland.
    19. David Alaminos & M. Belén Salas & Manuel A. Fernández-Gámez, 2022. "Quantum Computing and Deep Learning Methods for GDP Growth Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 803-829, February.
    20. Florian Huber & Gary Koop, 2021. "Subspace Shrinkage in Conjugate Bayesian Vector Autoregressions," Papers 2107.07804, arXiv.org.
    21. Chen, Zhengyang & Valcarcel, Victor J., 2021. "Monetary transmission in money markets: The not-so-elusive missing piece of the puzzle," Journal of Economic Dynamics and Control, Elsevier, vol. 131(C).
    22. Baumeister, Christiane & Korobilis, Dimitris & Lee, Thomas K., 2020. "Energy Markets and Global Economic Conditions," CEPR Discussion Papers 14580, C.E.P.R. Discussion Papers.
    23. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2021. "Using Time-Varying Volatility for Identification in Vector Autoregressions: An Application to Endogenous Uncertainty," CEPR Discussion Papers 16346, C.E.P.R. Discussion Papers.
    24. Sebastian Ankargren & Paulina Jon'eus, 2019. "Simulation smoothing for nowcasting with large mixed-frequency VARs," Papers 1907.01075, arXiv.org.
    25. 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.
    26. Sokol, Andrej, 2021. "Fan charts 2.0: flexible forecast distributions with expert judgement," Working Paper Series 2624, European Central Bank.
    27. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano & Mertens, Elmar, 2022. "Addressing COVID-19 outliers in BVARs with stochastic volatility," Discussion Papers 13/2022, Deutsche Bundesbank.
    28. Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2022. "Capturing Macroeconomic Tail Risks with Bayesian Vector Autoregressions," CEPR Discussion Papers 17512, C.E.P.R. Discussion Papers.
    29. 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.
    30. Helmut Lutkepohl & Fei Shang & Luis Uzeda & Tomasz Wo'zniak, 2024. "Partial Identification of Heteroskedastic Structural VARs: Theory and Bayesian Inference," Papers 2404.11057, arXiv.org.
    31. Joshua C.C. Chan & Xuewen Yu, 2020. "Fast and accurate variational inference for large Bayesian VARs with stochastic volatility," CAMA Working Papers 2020-108, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    32. Joshua C. C. Chan, 2019. "Asymmetric conjugate priors for large Bayesian VARs," CAMA Working Papers 2019-51, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    33. Dimitris Korobilis, 2022. "A new algorithm for structural restrictions in Bayesian vector autoregressions," Papers 2206.06892, arXiv.org.
    34. 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.
    35. Antonio Pacifico, 2022. "Structural Compressed Panel VAR with Stochastic Volatility: A Robust Bayesian Model Averaging Procedure," Econometrics, MDPI, vol. 10(3), pages 1-24, July.
    36. 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.
    37. 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.
    38. 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.
    39. Joshua C.C. Chan & Eric Eisenstat & Chenghan Hou & Gary Koop, 2018. "Composite Likelihood Methods for Large Bayesian VARs with Stochastic Volatility," Working Paper Series 44, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
    40. 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.
    41. Florian Huber & Gary Koop & Massimiliano Marcellino & Tobias Scheckel, 2024. "Bayesian modelling of VAR precision matrices using stochastic block networks," Papers 2407.16349, arXiv.org.
    42. Bańbura, Marta & Brenna, Federica & Paredes, Joan & Ravazzolo, Francesco, 2021. "Combining Bayesian VARs with survey density forecasts: does it pay off?," Working Paper Series 2543, European Central Bank.
    43. Zheng, Tingguo & Ye, Shiqi & Hong, Yongmiao, 2023. "Fast estimation of a large TVP-VAR model with score-driven volatilities," Journal of Economic Dynamics and Control, Elsevier, vol. 157(C).
    44. Juan Antolin-Diaz & Ivan Petrella & Juan F. Rubio-Ramirez, 2021. "Dividend Momentum and Stock Return Predictability: A Bayesian Approach," FRB Atlanta Working Paper 2021-25, Federal Reserve Bank of Atlanta.
    45. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2021. "Forecasting with Shadow-Rate VARs," Working Papers 21-09, Federal Reserve Bank of Cleveland.
    46. 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.
    47. Kashif Yousuf & Serena Ng, 2019. "Boosting High Dimensional Predictive Regressions with Time Varying Parameters," Papers 1910.03109, arXiv.org.
    48. 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.
    49. Dimitris Korobilis & Kenichi Shimizu, 2022. "Bayesian Approaches to Shrinkage and Sparse Estimation," Working Paper series 22-02, Rimini Centre for Economic Analysis.
    50. 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.
    51. Michael Pfarrhofer & Anna Stelzer, 2019. "The international effects of central bank information shocks," Papers 1912.03158, arXiv.org.
    52. 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.
    53. Boeck, Maximilian & Feldkircher, Martin, 2021. "The Impact of Monetary Policy on Yield Curve Expectations," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 887-901.
    54. Tsionas, Mike G. & Izzeldin, Marwan & Trapani, Lorenzo, 2022. "Estimation of large dimensional time varying VARs using copulas," European Economic Review, Elsevier, vol. 141(C).
    55. 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.
    56. Florian Huber & Gary Koop, 2023. "Fast and Order-invariant Inference in Bayesian VARs with Non-Parametric Shocks," Papers 2305.16827, arXiv.org.
    57. Zhang, Wen, 2022. "China’s government spending and global inflation dynamics: The role of the oil price channel," Energy Economics, Elsevier, vol. 110(C).
    58. Li, Chenxing & Maheu, John M & Yang, Qiao, 2022. "An Infinite Hidden Markov Model with Stochastic Volatility," MPRA Paper 115456, University Library of Munich, Germany.
    59. Bai, Yu & Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2022. "Macroeconomic Forecasting in a Multi-country Context," CEPR Discussion Papers 16994, C.E.P.R. Discussion Papers.
    60. Florian Huber & Massimiliano Marcellino, 2023. "Coarsened Bayesian VARs -- Correcting BVARs for Incorrect Specification," Papers 2304.07856, arXiv.org, revised May 2023.
    61. Rub'en Loaiza-Maya & Didier Nibbering, 2022. "Efficient variational approximations for state space models," Papers 2210.11010, arXiv.org, revised Jun 2023.
    62. Florian Huber & Luca Rossini, 2020. "Inference in Bayesian Additive Vector Autoregressive Tree Models," Papers 2006.16333, arXiv.org, revised Mar 2021.
    63. Sebastian Ankargren & Paulina Jon'eus, 2019. "Estimating Large Mixed-Frequency Bayesian VAR Models," Papers 1912.02231, arXiv.org.
    64. Clements, Michael P. & Galvao, Ana Beatriz, 2020. "Density Forecasting with BVAR Models under Macroeconomic Data Uncertainty," EMF Research Papers 36, Economic Modelling and Forecasting Group.
    65. 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.
    66. Michael P. Clements & Ana Beatriz Galvão, 2023. "Density forecasting with Bayesian Vector Autoregressive models under macroeconomic data uncertainty," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(2), pages 164-185, March.
    67. 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.
    68. Loaiza-Maya, Rubén & Smith, Michael Stanley & Nott, David J. & Danaher, Peter J., 2022. "Fast and accurate variational inference for models with many latent variables," Journal of Econometrics, Elsevier, vol. 230(2), pages 339-362.
    69. 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.
    70. 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).
    71. Jonas E. Arias & Juan F. Rubio-Ramirez & Minchul Shin, 2021. "Macroeconomic Forecasting and Variable Ordering in Multivariate Stochastic Volatility Models," Working Papers 21-21, Federal Reserve Bank of Philadelphia.
    72. Tsionas, Mike, 2022. "Efficiency estimation using probabilistic regression trees with an application to Chilean manufacturing industries," International Journal of Production Economics, Elsevier, vol. 249(C).
    73. 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.
    74. 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.
    75. Nadja Klein & Michael Stanley Smith & David J. Nott, 2020. "Deep Distributional Time Series Models and the Probabilistic Forecasting of Intraday Electricity Prices," Papers 2010.01844, arXiv.org, revised May 2021.
    76. Anna Pajor & Justyna Wróblewska & Łukasz Kwiatkowski & Jacek Osiewalski, 2024. "Hybrid SV‐GARCH, t‐GARCH and Markov‐switching covariance structures in VEC models—Which is better from a predictive perspective?," International Statistical Review, International Statistical Institute, vol. 92(1), pages 62-86, April.
    77. Philippe Goulet Coulombe & Mikael Frenette & Karin Klieber, 2023. "From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks," Papers 2311.16333, arXiv.org, revised Apr 2024.
    78. Gao, Shen & Hou, Chenghan & Nguyen, Bao H., 2021. "Forecasting natural gas prices using highly flexible time-varying parameter models," Economic Modelling, Elsevier, vol. 105(C).
    79. 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.
    80. Lukas Berend & Jan Pruser, 2024. "The Transmission of Monetary Policy via Common Cycles in the Euro Area," Papers 2410.05741, arXiv.org, revised Oct 2024.
    81. Dimitris Korobilis, 2020. "Sign restrictions in high-dimensional vector autoregressions," Working Paper series 20-09, Rimini Centre for Economic Analysis.
    82. 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.
    83. Zens, Gregor & Böck, Maximilian & Zörner, Thomas O., 2020. "The heterogeneous impact of monetary policy on the US labor market," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
    84. 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.
    85. 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).
    86. Nadja Klein & Michael Stanley Smith & David J. Nott, 2023. "Deep distributional time series models and the probabilistic forecasting of intraday electricity prices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 493-511, June.
    87. Cross, Jamie L. & Hou, Chenghan & Nguyen, Bao H., 2021. "On the China factor in the world oil market: A regime switching approach11We thank Hilde Bjørnland, Tatsuyoshi Okimoto, Ippei Fujiwara, Knut Aastveit, Leif Anders Thorsrud, Francesco Ravazzolo, Renee ," Energy Economics, Elsevier, vol. 95(C).
    88. Hauzenberger, Niko & Pfarrhofer, Michael & Stelzer, Anna, 2021. "On the effectiveness of the European Central Bank’s conventional and unconventional policies under uncertainty," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 822-845.
    89. 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.
    90. 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.
    91. Andrea Carriero & Francesco Corsello & Massimiliano Marcellino, 2020. "The economic drivers of volatility and uncertainty," Temi di discussione (Economic working papers) 1285, Bank of Italy, Economic Research and International Relations Area.
    92. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano & Mertens, Elmar, 2023. "Shadow-rate VARs," Discussion Papers 14/2023, Deutsche Bundesbank.
    93. Botelho, Vasco & Foroni, Claudia & Renzetti, Andrea, 2023. "Labour at risk," Working Paper Series 2840, European Central Bank.
    94. Luis Gruber & Gregor Kastner, 2022. "Forecasting macroeconomic data with Bayesian VARs: Sparse or dense? It depends!," Papers 2206.04902, arXiv.org, revised Jul 2023.
    95. Saeed Zaman, 2021. "A Unified Framework to Estimate Macroeconomic Stars," Working Papers 21-23R2, Federal Reserve Bank of Cleveland, revised 31 May 2024.
    96. Todd E. Clark & Matthew V. Gordon & Saeed Zaman, 2023. "Forecasting Core Inflation and Its Goods, Housing, and Supercore Components," Working Papers 23-34, Federal Reserve Bank of Cleveland.

  13. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2018. "Measuring Uncertainty and Its Impact on the Economy," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 799-815, December.
    See citations under working paper version above.
  14. 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.
  15. Knut Are Aastveit & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2017. "Have Standard VARS Remained Stable Since the Crisis?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(5), pages 931-951, August.
    See citations under working paper version above.
  16. Todd E. Clark & Michael W. McCracken, 2017. "Tests of Predictive Ability for Vector Autoregressions Used for Conditional Forecasting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(3), pages 533-553, April.

    Cited by:

    1. 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.
    2. Michael W. McCracken & Joseph T. McGillicuddy, 2019. "An empirical investigation of direct and iterated multistep conditional forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(2), pages 181-204, March.
    3. Kontogeorgos, Georgios & Lambrias, Kyriacos, 2019. "An analysis of the Eurosystem/ECB projections," Working Paper Series 2291, European Central Bank.
    4. Chen, Chaoyi & Gospodinov, Nikolay & Maynard, Alex & Pesavento, Elena, 2022. "Long-horizon stock valuation and return forecasts based on demographic projections," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 190-215.
    5. Giusto Andrea & İşcan Talan B., 2018. "The Rescaled VAR Model with an Application to Mixed-Frequency Macroeconomic Forecasting," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(4), pages 1-16, September.
    6. Arai, Natsuki, 2020. "Investigating the inefficiency of the CBO’s budgetary projections," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1290-1300.

  17. Fabian Krüger & Todd E. Clark & Francesco Ravazzolo, 2017. "Using Entropic Tilting to Combine BVAR Forecasts With External Nowcasts," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(3), pages 470-485, July.
    See citations under working paper version above.
  18. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2016. "Common Drifting Volatility in Large Bayesian VARs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(3), pages 375-390, July.
    See citations under working paper version above.
  19. Todd E. Clark & Francesco Ravazzolo, 2015. "Macroeconomic Forecasting Performance under Alternative Specifications of Time‐Varying Volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(4), pages 551-575, June.

    Cited by:

    1. Christian Hotz‐Behofsits & Florian Huber & Thomas Otto Zörner, 2018. "Predicting crypto‐currencies using sparse non‐Gaussian state space models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(6), pages 627-640, September.
    2. Matei Demetrescu & Christoph Hanck & Robinson Kruse‐Becher, 2022. "Robust inference under time‐varying volatility: A real‐time evaluation of professional forecasters," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 1010-1030, August.
    3. Krüger, Fabian & Nolte, Ingmar, 2016. "Disagreement versus uncertainty: Evidence from distribution forecasts," Journal of Banking & Finance, Elsevier, vol. 72(S), pages 172-186.
    4. Benjamin K. Johannsen & Elmar Mertens, 2016. "A Time Series Model of Interest Rates With the Effective Lower Bound," Finance and Economics Discussion Series 2016-033, Board of Governors of the Federal Reserve System (U.S.).
    5. Gergely Ganics & Barbara Rossi & Tatevik Sekhposyan, 2019. "From fixed-event to fixed-horizon density forecasts: Obtaining measures of multi-horizon uncertainty from survey density forecasts," Economics Working Papers 1689, Department of Economics and Business, Universitat Pompeu Fabra.
    6. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022. "Nowcasting tail risk to economic activity at a weekly frequency," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 843-866, August.
    7. 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.
    8. Thomas A. Lubik & Christian Matthes, 2019. "How Likely Is the Zero Lower Bound?," Economic Quarterly, Federal Reserve Bank of Richmond, issue 1Q, pages 41-54.
    9. Joshua C. C. Chan, 2022. "Comparing Stochastic Volatility Specifications for Large Bayesian VARs," Papers 2208.13255, arXiv.org.
    10. Huang, Yingying & Duan, Kun & Urquhart, Andrew, 2023. "Time-varying dependence between Bitcoin and green financial assets: A comparison between pre- and post-COVID-19 periods," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    11. Dominik Bertsche & Robin Braun, 2018. "Identification of Structural Vector Autoregressions by Stochastic Volatility," Working Paper Series of the Department of Economics, University of Konstanz 2018-03, Department of Economics, University of Konstanz.
    12. Virbickaite, Audrone & Nguyen, Hoang & Tran, Minh-Ngoc, 2023. "Bayesian Predictive Distributions of Oil Returns Using Mixed Data Sampling Volatility Models," Working Papers 2023:7, Örebro University, School of Business.
    13. Rozina Shaheen, 2019. "Impact of Fiscal Policy on Consumption and Labor Supply under a Time-Varying Structural VAR Model," Economies, MDPI, vol. 7(2), pages 1-15, June.
    14. Dimitrakopoulos, Stefanos, 2017. "Semiparametric Bayesian inference for time-varying parameter regression models with stochastic volatility," Economics Letters, Elsevier, vol. 150(C), pages 10-14.
    15. Dimitrakopoulos, Stefanos, 2017. "The semiparametric asymmetric stochastic volatility model with time-varying parameters: The case of US inflation," Economics Letters, Elsevier, vol. 155(C), pages 14-18.
    16. Berg, Tim Oliver & Henzel, Steffen, 2013. "Point and Density Forecasts for the Euro Area Using Many Predictors: Are Large BVARs Really Superior?," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79783, Verein für Socialpolitik / German Economic Association.
    17. Michele Lenza & Giorgio E. Primiceri, 2022. "How to estimate a vector autoregression after March 2020," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 688-699, June.
    18. Joshua C.C. Chan & Rodney W. Strachan, 2020. "Bayesian state space models in macroeconometrics," CAMA Working Papers 2020-90, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    19. Davide Pettenuzzo & Antonio Gargano & Allan Timmermann, 2014. "Bond Return Predictability: Economic Value and Links to the Macroeconomy," Working Papers 75R, Brandeis University, Department of Economics and International Business School, revised Jul 2016.
    20. David Alaminos & M. Belén Salas & Manuel A. Fernández-Gámez, 2022. "Quantum Computing and Deep Learning Methods for GDP Growth Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 803-829, February.
    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. Koop, G & Korobilis, D, 2018. "Forecasting with High-Dimensional Panel VARs," Essex Finance Centre Working Papers 21329, University of Essex, Essex Business School.
    23. Tino Werner, 2022. "Elicitability of Instance and Object Ranking," Decision Analysis, INFORMS, vol. 19(2), pages 123-140, June.
    24. Ellington, Michael, 2022. "Fat tails, serial dependence, and implied volatility index connections," European Journal of Operational Research, Elsevier, vol. 299(2), pages 768-779.
    25. Baumeister, Christiane & Korobilis, Dimitris & Lee, Thomas K., 2020. "Energy Markets and Global Economic Conditions," CEPR Discussion Papers 14580, C.E.P.R. Discussion Papers.
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    159. Matteo Iacopini & Francesco Ravazzolo & Luca Rossini, 2022. "Bayesian Multivariate Quantile Regression with alternative Time-varying Volatility Specifications," Papers 2211.16121, arXiv.org, revised Aug 2024.
    160. Denis Belomestny & Ekaterina Krymova & Andrey Polbin, 2020. "Estimating TVP-VAR models with time invariant long-run multipliers," Papers 2008.00718, arXiv.org.

  20. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015. "Bayesian VARs: Specification Choices and Forecast Accuracy," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(1), pages 46-73, January.
    See citations under working paper version above.
  21. Todd E. Clark & Edward S. Knotek & Saeed Zaman, 2015. "Measuring Inflation Forecast Uncertainty," Economic Commentary, Federal Reserve Bank of Cleveland, vol. 2015(03), pages 1-6, March.

    Cited by:

    1. Verbrugge, Randal & Zaman, Saeed, 2024. "Improving inflation forecasts using robust measures," International Journal of Forecasting, Elsevier, vol. 40(2), pages 735-745.
    2. Tumala, Mohammed M & Olubusoye, Olusanya E & Yaaba, Baba N & Yaya, OlaOluwa S & Akanbi, Olawale B, 2017. "Investigating Predictors of Inflation in Nigeria: BMA and WALS Techniques," MPRA Paper 88773, University Library of Munich, Germany, revised Feb 2018.
    3. 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.

  22. Clark, Todd E. & McCracken, Michael W., 2015. "Nested forecast model comparisons: A new approach to testing equal accuracy," Journal of Econometrics, Elsevier, vol. 186(1), pages 160-177.
    See citations under working paper version above.
  23. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015. "Realtime nowcasting with a Bayesian mixed frequency model with stochastic volatility," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(4), pages 837-862, October.
    See citations under working paper version above.
  24. Todd E. Clark, 2014. "The Importance of Trend Inflation in the Search for Missing Disinflation," Economic Commentary, Federal Reserve Bank of Cleveland, issue Aug.

    Cited by:

    1. Karlsson, Sune & Österholm, Pär, 2018. "A Note on the Stability of the Swedish Philips Curve," Working Papers 2018:6, Örebro University, School of Business.
    2. Sune Karlsson & Pär Österholm, 2023. "Is the US Phillips curve stable? Evidence from Bayesian vector autoregressions," Scandinavian Journal of Economics, Wiley Blackwell, vol. 125(1), pages 287-314, January.
    3. Łukasz Rawdanowicz & Romain Bouis & Kei-Ichiro Inaba & Ane Kathrine Christensen, 2014. "Secular Stagnation: Evidence and Implications for Economic Policy," OECD Economics Department Working Papers 1169, OECD Publishing.
    4. Özer Karagedikli & C. John McDermott, 2018. "Inflation expectations and low inflation in New Zealand," New Zealand Economic Papers, Taylor & Francis Journals, vol. 52(3), pages 277-288, September.
    5. Conti, Antonio M., 2021. "Resurrecting the Phillips Curve in Low-Inflation Times," Economic Modelling, Elsevier, vol. 96(C), pages 172-195.

  25. Todd E. Clark & Edward S. Knotek, 2014. "2013 Annual Report Why Inflation Is Very Low, and Why It Matters," Annual Report, Federal Reserve Bank of Cleveland, pages 1-42.

    Cited by:

    1. Edward S. Knotek & Saeed Zaman, 2014. "On the Relationships between Wages, Prices, and Economic Activity," Economic Commentary, Federal Reserve Bank of Cleveland, issue Aug.

  26. Clark, Todd E. & Doh, Taeyoung, 2014. "Evaluating alternative models of trend inflation," International Journal of Forecasting, Elsevier, vol. 30(3), pages 426-448.

    Cited by:

    1. Jaromir Baxa & Miroslav Plasil & Borek Vasicek, 2013. "Inflation and the Steeplechase Between Economic Activity Variables," Working Papers 2013/15, Czech National Bank.
    2. Bańbura, Marta & Bobeica, Elena, 2020. "Does the Phillips curve help to forecast euro area inflation?," Working Paper Series 2471, European Central Bank.
    3. Juan Angel Garcia & Aubrey Poon, 2022. "Inflation trends in Asia: implications for central banks [Are Phillips curves useful for forecasting inflation?]," Oxford Economic Papers, Oxford University Press, vol. 74(3), pages 671-700.
    4. Bańbura, Marta & Leiva-Leon, Danilo & Menz, Jan-Oliver, 2021. "Do inflation expectations improve model-based inflation forecasts?," Working Paper Series 2604, European Central Bank.
    5. Mónica Correa-López & Matías Pacce & Kathi Schlepper, 2019. "Exploring trend inFLation dynamics in Euro Area countries," Working Papers 1909, Banco de España.
    6. Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2022. "A Model of the Fed's View on Inflation," The Review of Economics and Statistics, MIT Press, vol. 104(4), pages 686-704, October.
    7. Luis Uzeda, 2016. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," ANU Working Papers in Economics and Econometrics 2016-632, Australian National University, College of Business and Economics, School of Economics.
    8. Michael D. Bauer & Glenn D. Rudebusch, 2019. "Interest Rates Under Falling Stars," Working Paper Series 2017-16, Federal Reserve Bank of San Francisco.
    9. 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.
    10. Verbrugge, Randal & Zaman, Saeed, 2024. "Improving inflation forecasts using robust measures," International Journal of Forecasting, Elsevier, vol. 40(2), pages 735-745.
    11. 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.
    12. Joshua C.C. Chan & Yong Song, 2018. "Measuring Inflation Expectations Uncertainty Using High‐Frequency Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(6), pages 1139-1166, September.
    13. Karlsson, Sune & Österholm, Pär, 2018. "A Note on the Stability of the Swedish Philips Curve," Working Papers 2018:6, Örebro University, School of Business.
    14. 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.
    15. 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.
    16. Behera, Harendra Kumar & Patra, Michael Debabrata, 2022. "Measuring trend inflation in India," Journal of Asian Economics, Elsevier, vol. 80(C).
    17. William Chen & Marco Del Negro & Michele Lenza & Giorgio E. Primiceri & Andrea Tambalotti, 2020. "What’s Up with the Phillips Curve?," Liberty Street Economics 20200918a, Federal Reserve Bank of New York.
    18. Travis J. Berge, 2017. "Understanding Survey Based Inflation Expectations," Finance and Economics Discussion Series 2017-046, Board of Governors of the Federal Reserve System (U.S.).
    19. Österholm, Pär & Poon, Aubrey, 2022. "Trend Inflation in Sweden," Working Papers 2022:2, Örebro University, School of Business.
    20. Manuel Gonzalez-Astudillo, 2018. "An Output Gap Measure for the Euro Area : Exploiting Country-Level and Cross-Sectional Data Heterogeneity," Finance and Economics Discussion Series 2018-040, Board of Governors of the Federal Reserve System (U.S.).
    21. Svetlana Makarova, 2018. "European Central Bank Footprints On Inflation Forecast Uncertainty," Economic Inquiry, Western Economic Association International, vol. 56(1), pages 637-652, January.
    22. 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.
    23. Giacomo Sbrana & Andrea Silvestrini & Fabrizio Venditti, 2015. "Short term inflation forecasting: the M.E.T.A. approach," Temi di discussione (Economic working papers) 1016, Bank of Italy, Economic Research and International Relations Area.
    24. Sune Karlsson & Pär Österholm, 2023. "Is the US Phillips curve stable? Evidence from Bayesian vector autoregressions," Scandinavian Journal of Economics, Wiley Blackwell, vol. 125(1), pages 287-314, January.
    25. Marc Giannoni & Domenico Giannone & Andrea Tambalotti & Marco Del Negro, 2017. "Safety, Liquidity, and the Natural Rate of Interest," 2017 Meeting Papers 803, Society for Economic Dynamics.
    26. Bańbura, Marta & Bobeica, Elena, 2020. "PCCI – a data-rich measure of underlying inflation in the euro area," Statistics Paper Series 38, European Central Bank.
    27. 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.
    28. Stephen McKnight & Alexander Mihailov & Fabio Rumler, 2018. "NKPC-Based Inflation Forecasts with a Time-Varying Trend," Serie documentos de trabajo del Centro de Estudios Económicos 2018-05, El Colegio de México, Centro de Estudios Económicos.
    29. Michal Andrle & Miroslav Plasil, 2017. "System Priors for Econometric Time Series," Working Papers 2017/01, Czech National Bank.
    30. Nikita D. Fokin & Ekaterina V. Malikova & Andrey V. Polbin, 2024. "Time-varying parameters error correction model for real ruble exchange rate and oil prices: What has changed due to capital control and sanctions?," Russian Journal of Economics, ARPHA Platform, vol. 10(1), pages 20-33, March.
    31. Philippe Goulet Coulombe & Karin Klieber & Christophe Barrette & Maximilian Goebel, 2024. "Maximally Forward-Looking Core Inflation," Papers 2404.05209, arXiv.org.
    32. Belomestny, Denis & Krymova, Ekaterina & Polbin, Andrey, 2021. "Bayesian TVP-VARX models with time invariant long-run multipliers," Economic Modelling, Elsevier, vol. 101(C).
    33. 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.
    34. Michael W. McCracken & Michael T. Owyang & Tatevik Sekhposyan, 2015. "Real-Time Forecasting and Scenario Analysis using a Large Mixed-Frequency Bayesian VAR," Working Papers 2015-030, Federal Reserve Bank of St. Louis, revised 10 Apr 2020.
    35. Karlsson, Sune & Österholm, Pär, 2018. "Is the US Phillips Curve Stable? Evidence from Bayesian VARs," Working Papers 2018:5, Örebro University, School of Business.
    36. Marek Jarociński & Michele Lenza, 2018. "An Inflation‐Predicting Measure of the Output Gap in the Euro Area," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(6), pages 1189-1224, September.
    37. Todd E. Clark & Michael W. McCracken, 2014. "Evaluating Conditional Forecasts from Vector Autoregressions," Working Papers (Old Series) 1413, Federal Reserve Bank of Cleveland.
    38. Jeremy J. Nalewaik, 2016. "Non-Linear Phillips Curves with Inflation Regime-Switching," Finance and Economics Discussion Series 2016-078, Board of Governors of the Federal Reserve System (U.S.).
    39. Christopher J. Erceg & James Hebden & Michael T. Kiley & J. David López-Salido & Robert J. Tetlow, 2018. "Some Implications of Uncertainty and Misperception for Monetary Policy," Finance and Economics Discussion Series 2018-059, Board of Governors of the Federal Reserve System (U.S.).
    40. Alessandro Barbarino & Travis J. Berge & Han Chen & Andrea Stella, 2020. "Which Output Gap Estimates Are Stable in Real Time and Why?," Finance and Economics Discussion Series 2020-102, Board of Governors of the Federal Reserve System (U.S.).
    41. 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.
    42. Kim, Insu & Kim, Young Se, 2019. "Inattentive agents and inflation forecast error dynamics: A Bayesian DSGE approach," Journal of Macroeconomics, Elsevier, vol. 62(C).
    43. 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.
    44. Andrle, Michal & Plašil, Miroslav, 2018. "Econometrics with system priors," Economics Letters, Elsevier, vol. 172(C), pages 134-137.
    45. Beechey, Meredith & Österholm, Pär & Poon, Aubrey, 2023. "Estimating the US trend short-term interest rate," Finance Research Letters, Elsevier, vol. 55(PA).
    46. Davide Delle Monache & Ivan Petrella & Fabrizio Venditti, 2016. "Common Faith or Parting Ways? A Time Varying Parameters Factor Analysis of Euro-Area Inflation," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 539-565, Emerald Group Publishing Limited.
    47. Kaihatsu, Sohei & Nakajima, Jouchi, 2018. "Has trend inflation shifted?: An empirical analysis with an equally-spaced regime-switching model," Economic Analysis and Policy, Elsevier, vol. 59(C), pages 69-83.
    48. Denis Belomestny & Ekaterina Krymova & Andrey Polbin, 2020. "Estimating TVP-VAR models with time invariant long-run multipliers," Papers 2008.00718, arXiv.org.
    49. Todd E. Clark, 2014. "The Importance of Trend Inflation in the Search for Missing Disinflation," Economic Commentary, Federal Reserve Bank of Cleveland, issue Aug.
    50. Jeremy J. Nalewaik, 2016. "Inflation Expectations and the Stabilization of Inflation : Alternative Hypotheses," Finance and Economics Discussion Series 2016-035, Board of Governors of the Federal Reserve System (U.S.).

  27. Todd E. Clark & Michael W. Mccracken, 2014. "Tests Of Equal Forecast Accuracy For Overlapping Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(3), pages 415-430, April.
    See citations under working paper version above.
  28. Todd E. Clark & Saeed Zaman, 2013. "Forecasting implications of the recent decline in inflation," Economic Commentary, Federal Reserve Bank of Cleveland, issue Nov.

    Cited by:

    1. Randal J. Verbrugge & Saeed Zaman, 2023. "Post-COVID Inflation Dynamics: Higher for Longer," Working Papers 23-06R, Federal Reserve Bank of Cleveland, revised 20 Jun 2023.
    2. Edward S. Knotek & Saeed Zaman, 2014. "The Slowdown in Residential Investment and Future Prospects," Economic Commentary, Federal Reserve Bank of Cleveland, issue May.

  29. Clark, Todd E. & McCracken, Michael W., 2012. "In-sample tests of predictive ability: A new approach," Journal of Econometrics, Elsevier, vol. 170(1), pages 1-14.
    See citations under working paper version above.
  30. Todd E. Clark, 2012. "Policy rules in macroeconomic forecasting models," Economic Commentary, Federal Reserve Bank of Cleveland, issue Oct.

    Cited by:

    1. Nadav Ben Zeev & Christopher M. Gunn & Hashmat Khan, 2015. "Monetary News Shocks," Carleton Economic Papers 15-02, Carleton University, Department of Economics, revised 17 Feb 2017.

  31. Clark, Todd E., 2011. "Real-Time Density Forecasts From Bayesian Vector Autoregressions With Stochastic Volatility," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(3), pages 327-341.

    Cited by:

    1. 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.
    2. 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.
    3. Christian Hotz‐Behofsits & Florian Huber & Thomas Otto Zörner, 2018. "Predicting crypto‐currencies using sparse non‐Gaussian state space models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(6), pages 627-640, September.
    4. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    5. Benjamin K. Johannsen & Elmar Mertens, 2016. "A Time Series Model of Interest Rates With the Effective Lower Bound," Finance and Economics Discussion Series 2016-033, Board of Governors of the Federal Reserve System (U.S.).
    6. FUJII Daisuke & NAKATA Taisuke, 2021. "Covid-19 and Output in Japan," Discussion papers 21004, Research Institute of Economy, Trade and Industry (RIETI).
    7. Carriero, Andrea & Galvão, Ana Beatriz & Kapetanios, George, 2019. "A comprehensive evaluation of macroeconomic forecasting methods," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1226-1239.
    8. 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.
    9. Joshua C. C. Chan, 2022. "Comparing Stochastic Volatility Specifications for Large Bayesian VARs," Papers 2208.13255, arXiv.org.
    10. Dominik Bertsche & Robin Braun, 2018. "Identification of Structural Vector Autoregressions by Stochastic Volatility," Working Paper Series of the Department of Economics, University of Konstanz 2018-03, Department of Economics, University of Konstanz.
    11. Rozina Shaheen, 2019. "Impact of Fiscal Policy on Consumption and Labor Supply under a Time-Varying Structural VAR Model," Economies, MDPI, vol. 7(2), pages 1-15, June.
    12. Roberto Casarin, 2014. "A Note on Tractable State-Space Model for Symmetric Positive-Definite Matrices," Working Papers 2014:23, Department of Economics, University of Venice "Ca' Foscari".
    13. Todd E. Clark & Saeed Zaman, 2013. "Forecasting implications of the recent decline in inflation," Economic Commentary, Federal Reserve Bank of Cleveland, issue Nov.
    14. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    15. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    16. Denis Koshelev & Alexey Ponomarenko & Sergei Seleznev, 2023. "Amortized Neural Networks for Agent-Based Model Forecasting," Bank of Russia Working Paper Series wps115, Bank of Russia.
    17. Berg, Tim Oliver & Henzel, Steffen, 2013. "Point and Density Forecasts for the Euro Area Using Many Predictors: Are Large BVARs Really Superior?," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79783, Verein für Socialpolitik / German Economic Association.
    18. Sebastiano Manzan, 2015. "Forecasting the Distribution of Economic Variables in a Data-Rich Environment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(1), pages 144-164, January.
    19. Jonas Dovern & Hans Manner, 2018. "Order Invariant Tests for Proper Calibration of Multivariate Density Forecasts," CESifo Working Paper Series 7023, CESifo.
    20. Galvao, Ana Beatriz & Garratt, Anthony & Mitchell, James, 2020. "Does Judgment Improve Macroeconomic Density Forecasts?," EMF Research Papers 33, Economic Modelling and Forecasting Group.
    21. Mike Tsionas & Marwan Izzeldin & Lorenzo Trapani, 2019. "Bayesian estimation of large dimensional time varying VARs using copulas," Papers 1912.12527, arXiv.org.
    22. Joshua C.C. Chan & Rodney W. Strachan, 2020. "Bayesian state space models in macroeconometrics," CAMA Working Papers 2020-90, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    23. 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.
    24. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015. "Realtime nowcasting with a Bayesian mixed frequency model with stochastic volatility," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(4), pages 837-862, October.
    25. Bańbura, Marta & Leiva-Leon, Danilo & Menz, Jan-Oliver, 2021. "Do inflation expectations improve model-based inflation forecasts?," Working Paper Series 2604, European Central Bank.
    26. Mónica Correa-López & Matías Pacce & Kathi Schlepper, 2019. "Exploring trend inFLation dynamics in Euro Area countries," Working Papers 1909, Banco de España.
    27. Jonas Dovern & Martin Feldkircher & Florian Huber, 2015. "Does Joint Modelling of the World Economy Pay Off? Evaluating Global Forecasts from a Bayesian GVAR," Working Papers 200, Oesterreichische Nationalbank (Austrian Central Bank).
    28. Frank Schorfheide & Dongho Song, 2020. "Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic," PIER Working Paper Archive 20-039, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    29. Dick Dijk & Siem Jan Koopman & Michel Wel & Jonathan H. Wright, 2014. "Forecasting interest rates with shifting endpoints," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(5), pages 693-712, August.
    30. Silvia Miranda-Agrippino & Giovanni Ricco, 2018. "Bayesian vector autoregressions," Documents de Travail de l'OFCE 2018-18, Observatoire Francais des Conjonctures Economiques (OFCE).
    31. Edward S. Knotek & Saeed Zaman, 2020. "Real-Time Density Nowcasts of US Inflation: A Model-Combination Approach," Working Papers 20-31, Federal Reserve Bank of Cleveland.
    32. David Alaminos & M. Belén Salas & Manuel A. Fernández-Gámez, 2022. "Quantum Computing and Deep Learning Methods for GDP Growth Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 803-829, February.
    33. Gaglianone, Wagner Piazza & Guillén, Osmani Teixeira de Carvalho & Figueiredo, Francisco Marcos Rodrigues, 2018. "Estimating inflation persistence by quantile autoregression with quantile-specific unit roots," Economic Modelling, Elsevier, vol. 73(C), pages 407-430.
    34. 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.
    35. Zhang, Erhua & Wu, Jilin, 2020. "Adaptive estimation of AR∞ models with time-varying variances," Economics Letters, Elsevier, vol. 197(C).
    36. Wojciech Charemza & Carlos Diaz & Svetlana Makarova, 2014. "Term Structure Of Inflation Forecast Uncertainties And Skew Normal Distributions," Discussion Papers in Economics 14/01, Division of Economics, School of Business, University of Leicester.
    37. 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.
    38. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2021. "Using Time-Varying Volatility for Identification in Vector Autoregressions: An Application to Endogenous Uncertainty," CEPR Discussion Papers 16346, C.E.P.R. Discussion Papers.
    39. Barbara Rossi & Tatevik Sehkposyan, 2013. "Evaluating Predictive Densities of US Output Growth and Inflation in a Large Macroeconomic Data Set," Working Papers 689, Barcelona School of Economics.
    40. Huber, Florian, 2016. "Density forecasting using Bayesian global vector autoregressions with stochastic volatility," International Journal of Forecasting, Elsevier, vol. 32(3), pages 818-837.
    41. Davide Pettenuzzo & Konstantinos Metaxoglou & Aaron Smith, 2016. "Option-Implied Equity Premium Predictions via Entropic TiltinG," Working Papers 99R, Brandeis University, Department of Economics and International Business School, revised Aug 2016.
    42. Sebastian Ankargren & Paulina Jon'eus, 2019. "Simulation smoothing for nowcasting with large mixed-frequency VARs," Papers 1907.01075, arXiv.org.
    43. 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.
    44. Hanck, Christoph & Demetrescu, Matei & Kruse, Robinson, 2015. "Fixed-b Asymptotics for t-Statistics in the Presence of Time-Varying Volatility," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112916, Verein für Socialpolitik / German Economic Association.
    45. 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.
    46. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano & Mertens, Elmar, 2022. "Addressing COVID-19 outliers in BVARs with stochastic volatility," Discussion Papers 13/2022, Deutsche Bundesbank.
    47. Barbara Rossi & Tatevik Sekhposyan, 2015. "Alternative Tests for Correct Specification of Conditional Predictive Densities," Working Papers 758, Barcelona School of Economics.
    48. Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2022. "Capturing Macroeconomic Tail Risks with Bayesian Vector Autoregressions," CEPR Discussion Papers 17512, C.E.P.R. Discussion Papers.
    49. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2011. "Bayesian VARs: specification choices and forecast accuracy," Working Papers (Old Series) 1112, Federal Reserve Bank of Cleveland.
    50. Ruben Loaiza-Maya & Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Andres Ramirez Hassan, 2020. "Optimal probabilistic forecasts: When do they work?," Monash Econometrics and Business Statistics Working Papers 33/20, Monash University, Department of Econometrics and Business Statistics.
    51. Chiara Scotti, 2023. "Financial Shocks in an Uncertain Economy," Working Papers 2308, Federal Reserve Bank of Dallas.
    52. Antonello D'Agostino & Domenico Giannone & Michele Lenza & Michele Modugno, 2015. "Nowcasting Business Cycles: a Bayesian Approach to Dynamic Heterogeneous Factor Models," Finance and Economics Discussion Series 2015-66, Board of Governors of the Federal Reserve System (U.S.).
    53. Garratt, Anthony & Mitchell, James & Vahey, Shaun P., 2014. "Probability Forecasting for Inflation Warnings from the Federal Reserve," EMF Research Papers 07, Economic Modelling and Forecasting Group.
    54. 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.
    55. Hou, Chenghan, 2017. "Infinite hidden markov switching VARs with application to macroeconomic forecast," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1025-1043.
    56. Dovern, Jonas & Manner, Hans, 2016. "Robust Evaluation of Multivariate Density Forecasts," VfS Annual Conference 2016 (Augsburg): Demographic Change 145547, Verein für Socialpolitik / German Economic Association.
    57. Joshua C.C. Chan & Xuewen Yu, 2020. "Fast and accurate variational inference for large Bayesian VARs with stochastic volatility," CAMA Working Papers 2020-108, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    58. Piergiorgio Alessandri & Haroon Mumtaz, 2021. "The macroeconomic cost of climate volatility," Papers 2108.01617, arXiv.org, revised Feb 2022.
    59. Karlsson, Sune & Österholm, Pär, 2018. "A Note on the Stability of the Swedish Philips Curve," Working Papers 2018:6, Örebro University, School of Business.
    60. 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.
    61. Joshua C. C. Chan, 2019. "Asymmetric conjugate priors for large Bayesian VARs," CAMA Working Papers 2019-51, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    62. Davide Pettenuzzo & Rossen Valkanov & Allan Timmermann, 2014. "A Bayesian MIDAS Approach to Modeling First and Second Moment Dynamics," Working Papers 76, Brandeis University, Department of Economics and International Business School.
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    204. Awijen, Haithem & Ben Zaied, Younes & Nguyen, Duc Khuong & Sensoy, Ahmet, 2020. "Endogenous Financial Uncertainty and Macroeconomic Volatility: Evidence from the United States," MPRA Paper 101276, University Library of Munich, Germany, revised Jun 2020.
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    206. Huber, Florian & Pfarrhofer, Michael & Zörner, Thomas O., 2018. "Stochastic model specification in Markov switching vector error correction models," Working Papers in Economics 2018-3, University of Salzburg.
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    214. 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.
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    218. Francesco Ravazzolo & Philip Rothman, 2015. "Oil-Price Density Forecasts of U.S. GDP," Working Papers No 10/2015, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    219. 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.
    220. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2016. "Large Vector Autoregressions with Stochastic Volatility and Flexible Priors," Working Papers (Old Series) 1617, Federal Reserve Bank of Cleveland.
    221. Michael Connolly & Taeyoung Doh, 2012. "The state space representation and estimation of a time-varying parameter VAR with stochastic volatility," Research Working Paper RWP 12-04, Federal Reserve Bank of Kansas City.
    222. Piergiorgio Alessandri & Haroon Mumtaz, 2014. "Financial indicators and density forecasts for US output and inflation," Temi di discussione (Economic working papers) 977, Bank of Italy, Economic Research and International Relations Area.
    223. 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.
    224. Saeed Zaman, 2013. "Improving inflation forecasts in the medium to long term," Economic Commentary, Federal Reserve Bank of Cleveland, issue Nov.
    225. Dimitrios P. Louzis, 2016. "Macroeconomic forecasting and structural changes in steady states," Working Papers 204, Bank of Greece.
    226. Kiss, Tamás & Mazur, Stepan & Nguyen, Hoang, 2022. "Predicting returns and dividend growth — The role of non-Gaussian innovations," Finance Research Letters, Elsevier, vol. 46(PA).
    227. 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.
    228. Zens, Gregor & Böck, Maximilian & Zörner, Thomas O., 2020. "The heterogeneous impact of monetary policy on the US labor market," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
    229. 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.
    230. Carriero, Andrea & Mumtaz, Haroon & Theophilopoulou, Angeliki, 2015. "Macroeconomic information, structural change, and the prediction of fiscal aggregates," International Journal of Forecasting, Elsevier, vol. 31(2), pages 325-348.
    231. Flavio Pérez Rojo & Gabriel Rodríguez, 2023. "Jane Haldimand Marcet: Impact of Monetary Policy Shocks in the Peruvian Economy Over Time," Documentos de Trabajo / Working Papers 2023-523, Departamento de Economía - Pontificia Universidad Católica del Perú.
    232. 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.
    233. 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.
    234. 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.
    235. Joshua Chan, 2023. "BVARs and Stochastic Volatility," Papers 2310.14438, arXiv.org.
    236. Hauzenberger, Niko & Pfarrhofer, Michael & Stelzer, Anna, 2021. "On the effectiveness of the European Central Bank’s conventional and unconventional policies under uncertainty," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 822-845.
    237. Fresoli, Diego & Ruiz, Esther & Pascual, Lorenzo, 2015. "Bootstrap multi-step forecasts of non-Gaussian VAR models," International Journal of Forecasting, Elsevier, vol. 31(3), pages 834-848.
    238. S. Avouyi-Dovi & C. Labonne & R. Lecat & S. Ray, 2017. "Insight from a Time-Varying VAR Model with Stochastic Volatility of the French Housing and Credit Markets," Working papers 620, Banque de France.
    239. Peter McAdam & Anders Warne, 2024. "Density forecast combinations: The real‐time dimension," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1153-1172, August.
    240. Spånberg, Erik & Shahnazarian, Hovick, 2019. "The importance of the financial system for the current account in Sweden: A sectoral approach," International Economics, Elsevier, vol. 158(C), pages 91-103.
    241. 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).
    242. Leopoldo Catania & Alessandra Luati & Pierluigi Vallarino, 2021. "Economic vulnerability is state dependent," CREATES Research Papers 2021-09, Department of Economics and Business Economics, Aarhus University.
    243. Legrand, Romain, 2018. "Time-Varying Vector Autoregressions: Efficient Estimation, Random Inertia and Random Mean," MPRA Paper 88925, University Library of Munich, Germany.
    244. Apostolos Ampountolas, 2019. "Forecasting hotel demand uncertainty using time series Bayesian VAR models," Tourism Economics, , vol. 25(5), pages 734-756, August.
    245. Edward S. Knotek & Saeed Zaman, 2013. "When Might the Federal Funds Rate Lift Off? Computing the Probabilities of Crossing Unemployment and Inflation Thresholds," Economic Commentary, Federal Reserve Bank of Cleveland, issue Dec.
    246. Gambetti, Luca & Musso, Alberto, 2020. "The effects of the ECB’s expanded asset purchase programme," European Economic Review, Elsevier, vol. 130(C).
    247. 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.).
    248. Boriss Siliverstovs, 2020. "Assessing nowcast accuracy of US GDP growth in real time: the role of booms and busts," Empirical Economics, Springer, vol. 58(1), pages 7-27, January.
    249. Nadiia Shapovalenko, 2021. "A BVAR Model for Forecasting Ukrainian Inflation," IHEID Working Papers 05-2021, Economics Section, The Graduate Institute of International Studies.
    250. Knut Are Aastveit & James Mitchell & Francesco Ravazzolo & Herman van Dijk, 2018. "The Evolution of Forecast Density Combinations in Economics," Tinbergen Institute Discussion Papers 18-069/III, Tinbergen Institute.
    251. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano & Mertens, Elmar, 2023. "Shadow-rate VARs," Discussion Papers 14/2023, Deutsche Bundesbank.
    252. Jaqueline Terra Moura Marins, 2024. "Predictability of Exchange Rate Density Forecasts for Emerging Economies in the Short Run," Working Papers Series 588, Central Bank of Brazil, Research Department.
    253. Joshua C. C. Chan & Yaling Qi, 2024. "Large Bayesian Tensor VARs with Stochastic Volatility," Papers 2409.16132, arXiv.org.
    254. Wagner Piazza Gaglianone & Jaqueline Terra Moura Marins, 2014. "Risk Assessment of the Brazilian FX Rate," Working Papers Series 344, Central Bank of Brazil, Research Department.
    255. Todd E. Clark & Michael W. McCracken, 2013. "Evaluating the accuracy of forecasts from vector autoregressions," Working Papers 2013-010, Federal Reserve Bank of St. Louis.
    256. Roberto Casarin & Domenico Sartore & Marco Tronzano, 2018. "A Bayesian Markov-Switching Correlation Model for Contagion Analysis on Exchange Rate Markets," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 101-114, January.

  32. Clark, Todd E. & Davig, Troy, 2011. "Decomposing the declining volatility of long-term inflation expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 35(7), pages 981-999, July.
    See citations under working paper version above.
  33. Todd E. Clark & Michael W. McCracken, 2011. "Reality Checks and Comparisons of Nested Predictive Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 53-66, February.

    Cited by:

    1. 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.
    2. Michael W. McCracken & Serena Ng, 2016. "FRED-MD: A Monthly Database for Macroeconomic Research," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 574-589, October.
    3. Granziera, Eleonora & Sekhposyan, Tatevik, 2019. "Predicting relative forecasting performance: An empirical investigation," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1636-1657.
    4. Andrea Carriero & Davide Pettenuzzo & Shubhranshu Shekhar, 2024. "Macroeconomic Forecasting with Large Language Models," Papers 2407.00890, arXiv.org.
    5. Gonçalves, Sílvia & McCracken, Michael W. & Perron, Benoit, 2017. "Tests of equal accuracy for nested models with estimated factors," Journal of Econometrics, Elsevier, vol. 198(2), pages 231-252.
    6. Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2018. "Comparing the Forecasting Performances of Linear Models for Electricity Prices with High RES Penetration," Working Papers No 2/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    7. Grégory Levieuge, 2017. "Explaining and forecasting bank loans. Good times and crisis," Applied Economics, Taylor & Francis Journals, vol. 49(8), pages 823-843, February.
    8. Xiaojie Xu, 2020. "Corn Cash Price Forecasting," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(4), pages 1297-1320, August.
    9. Todd E. Clark & Michael W. Mccracken, 2014. "Tests Of Equal Forecast Accuracy For Overlapping Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(3), pages 415-430, April.
    10. Clark, Todd E. & McCracken, Michael W., 2015. "Nested forecast model comparisons: A new approach to testing equal accuracy," Journal of Econometrics, Elsevier, vol. 186(1), pages 160-177.
    11. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
    12. Ahmed, Shamim & Liu, Xiaoquan & Valente, Giorgio, 2016. "Can currency-based risk factors help forecast exchange rates?," International Journal of Forecasting, Elsevier, vol. 32(1), pages 75-97.
    13. 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.
    14. Khalaf, Lynda & Saunders, Charles J., 2017. "Monte Carlo forecast evaluation with persistent data," International Journal of Forecasting, Elsevier, vol. 33(1), pages 1-10.
    15. Ahmed, Shamim & Tsvetanov, Daniel, 2016. "The predictive performance of commodity futures risk factors," Journal of Banking & Finance, Elsevier, vol. 71(C), pages 20-36.
    16. Rudan Wang & Bruce Morley & Javier Ordóñez, 2015. "The Taylor Rule, Wealth Effects and the Exchange Rate," Working Papers 2015/08, Economics Department, Universitat Jaume I, Castellón (Spain).
    17. Wang, Rudan & Morley, Bruce & Stamatogiannis, Michalis P., 2019. "Forecasting the exchange rate using nonlinear Taylor rule based models," International Journal of Forecasting, Elsevier, vol. 35(2), pages 429-442.
    18. Kolev, Gueorgui I. & Karapandza, Rasa, 2017. "Out-of-sample equity premium predictability and sample split–invariant inference," Journal of Banking & Finance, Elsevier, vol. 84(C), pages 188-201.
    19. Jaqueson K. Galimberti, 2020. "Forecasting GDP Growth from Outer Space," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(4), pages 697-722, August.
    20. Firmin Doko Tchatoka & Qazi Haque, 2020. "On bootstrapping tests of equal forecast accuracy for nested models," School of Economics and Public Policy Working Papers 2020-03, University of Adelaide, School of Economics and Public Policy.
    21. 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.
    22. Wada, Tatsuma, 2022. "Out-of-sample forecasting of foreign exchange rates: The band spectral regression and LASSO," Journal of International Money and Finance, Elsevier, vol. 128(C).
    23. Dichtl, Hubert & Drobetz, Wolfgang & Neuhierl, Andreas & Wendt, Viktoria-Sophie, 2021. "Data snooping in equity premium prediction," International Journal of Forecasting, Elsevier, vol. 37(1), pages 72-94.
    24. Nima Nonejad, 2021. "Crude oil price point forecasts of the Norwegian GDP growth rate," Empirical Economics, Springer, vol. 61(5), pages 2913-2930, November.
    25. Tarassow, Artur, 2019. "Forecasting U.S. money growth using economic uncertainty measures and regularisation techniques," International Journal of Forecasting, Elsevier, vol. 35(2), pages 443-457.
    26. Zeng-Hua Lu, 2019. "Extended MinP Tests for Global and Multiple testing," Papers 1911.04696, arXiv.org, revised Aug 2024.
    27. Daniel Borup & Jonas N. Eriksen & Mads M. Kjær & Martin Thyrsgaard, 2024. "Predicting Bond Return Predictability," Management Science, INFORMS, vol. 70(2), pages 931-951, February.
    28. Hubrich, Kirstin & Granziera, Eleonora & Moon, Hyungsik Roger, 2013. "A predictability test for a small number of nested models," Working Paper Series 1580, European Central Bank.
    29. Hollstein, Fabian & Nguyen, Duc Binh Benno & Prokopczuk, Marcel & Wese Simen, Chardin, 2019. "International tail risk and World Fear," Journal of International Money and Finance, Elsevier, vol. 93(C), pages 244-259.
    30. Christian Hutter & Enzo Weber, 2017. "Mismatch and the Forecasting Performance of Matching Functions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(1), pages 101-123, February.
    31. Sander, Magnus, 2018. "Market timing over the business cycle," Journal of Empirical Finance, Elsevier, vol. 46(C), pages 130-145.
    32. Karen Miranda & Pilar Poncela & Esther Ruiz, 2022. "Dynamic factor models: Does the specification matter?," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 13(1), pages 397-428, May.
    33. Amélie Charles & Olivier Darné & Jae H Kim, 2017. "International Stock Return Predictability: Evidence from New Statistical Tests," Post-Print hal-01626101, HAL.
    34. Enoch Cheng & Clemens C. Struck, 2019. "Time-Series Momentum: A Monte-Carlo Approach," Working Papers 201906, School of Economics, University College Dublin.
    35. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 328-383, Elsevier.
    36. Tobback, Ellen & Naudts, Hans & Daelemans, Walter & Junqué de Fortuny, Enric & Martens, David, 2018. "Belgian economic policy uncertainty index: Improvement through text mining," International Journal of Forecasting, Elsevier, vol. 34(2), pages 355-365.

  34. 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.
    See citations under working paper version above.
  35. Todd E. Clark & Stephen J. Terry, 2010. "Time Variation in the Inflation Passthrough of Energy Prices," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(7), pages 1419-1433, October.
    See citations under working paper version above.
  36. Clark, Todd E. & McCracken, Michael W., 2009. "Tests of Equal Predictive Ability With Real-Time Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 441-454.
    See citations under working paper version above.
  37. Todd E. Clark, 2009. "Is the Great Moderation over? an empirical analysis," Economic Review, Federal Reserve Bank of Kansas City, vol. 94(Q IV), pages 5-42.

    Cited by:

    1. Xuan, Chunji & Kim, Chang-Jin & Kim, Dong Heon, 2019. "New dynamics of consumption and output," Journal of Macroeconomics, Elsevier, vol. 60(C), pages 50-59.
    2. Keating, John W. & Valcarcel, Victor J., 2017. "What's so great about the Great Moderation?," Journal of Macroeconomics, Elsevier, vol. 51(C), pages 115-142.
    3. Luzzetti, Matthew N. & Neumuller, Seth, 2016. "Learning and the dynamics of consumer unsecured debt and bankruptcies," Journal of Economic Dynamics and Control, Elsevier, vol. 67(C), pages 22-39.
    4. Amélie Charles & Olivier Darné & Laurent Ferrara, 2018. "Does The Great Recession Imply The End Of The Great Moderation? International Evidence," Economic Inquiry, Western Economic Association International, vol. 56(2), pages 745-760, April.
    5. Everaert, Gerdie & Iseringhausen, Martin, 2018. "Measuring the international dimension of output volatility," Journal of International Money and Finance, Elsevier, vol. 81(C), pages 20-39.
    6. Hanck, Christoph & Demetrescu, Matei & Kruse, Robinson, 2015. "Fixed-b Asymptotics for t-Statistics in the Presence of Time-Varying Volatility," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112916, Verein für Socialpolitik / German Economic Association.
    7. David Harris & Hsein Kew & A. M. Robert Taylor, 2020. "Level Shift Estimation in the Presence of Non-stationary Volatility with an Application to the Unit Root Testing Problem," Monash Econometrics and Business Statistics Working Papers 8/20, Monash University, Department of Econometrics and Business Statistics.
    8. Markus Heinrich & Magnus Reif, 2018. "Forecasting using mixed-frequency VARs with time-varying parameters," ifo Working Paper Series 273, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    9. Matei Demetrescu & Christoph Hanck, 2013. "Nonlinear IV panel unit root testing under structural breaks in the error variance," Statistical Papers, Springer, vol. 54(4), pages 1043-1066, November.
    10. Spierdijk, Laura & Umar, Zaghum, 2015. "Stocks, bonds, T-bills and inflation hedging: From great moderation to great recession," Journal of Economics and Business, Elsevier, vol. 79(C), pages 1-37.
    11. Máximo Camacho & Gabriel Pérez Quirós & Hugo Rodríguez Mendizábal, 2011. "High-growth recoveries, inventories and the great moderation," Post-Print hal-00828978, HAL.
    12. Giuseppe Cavaliere & Morten Ørregaard Nielsen & Robert Taylor, 2017. "Quasi-Maximum Likelihood Estimation and Bootstrap Inference in Fractional Time Series Models with Heteroskedasticity of Unknown Form," CREATES Research Papers 2017-02, Department of Economics and Business Economics, Aarhus University.
    13. Ahn, Dong-Hyun & Min, Byoung-Kyu & Yoon, Bohyun, 2019. "Why has the size effect disappeared?," Journal of Banking & Finance, Elsevier, vol. 102(C), pages 256-276.
    14. Heinrich, Markus, 2020. "Does the Current State of the Business Cycle matter for Real-Time Forecasting? A Mixed-Frequency Threshold VAR approach," EconStor Preprints 219312, ZBW - Leibniz Information Centre for Economics.
    15. Matei Demetrescu & Christoph Hanck & Robinson Kruse, 2016. "Fixed-b Inference in the Presence of Time-Varying Volatility," CREATES Research Papers 2016-01, Department of Economics and Business Economics, Aarhus University.
    16. Selgin, George & Lastrapes, William D. & White, Lawrence H., 2012. "Has the Fed been a failure?," Journal of Macroeconomics, Elsevier, vol. 34(3), pages 569-596.
    17. Demetrescu, Matei & Kruse, Robinson, 2015. "Testing heteroskedastic time series for normality," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113221, Verein für Socialpolitik / German Economic Association.
    18. Ambrose, Brent W. & Coulson, N. Edward & Yoshida, Jiro, 2017. "Inflation Rates Are Very Different When Housing Rents Are Accurately Measured," HIT-REFINED Working Paper Series 71, Institute of Economic Research, Hitotsubashi University.
    19. James Morley & Aarti Singh, 2016. "Inventory Shocks and the Great Moderation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 48(4), pages 699-728, June.
    20. Smales, Lee A. & Apergis, Nick, 2016. "The influence of FOMC member characteristics on the monetary policy decision-making process," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 216-231.
    21. Matei Demetrescu & Christoph Hanck & Adina I. Tarcolea, 2014. "Iv-Based Cointegration Testing In Dependent Panels With Time-Varying Variance," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(5), pages 393-406, August.
    22. 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.
    23. Demetrescu, Matei & Salish, Nazarii, 2024. "(Structural) VAR models with ignored changes in mean and volatility," International Journal of Forecasting, Elsevier, vol. 40(2), pages 840-854.
    24. 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.
    25. Orhan Erem Atesagaoglu, 2017. "Taxes, Financial Markets and the Great Moderation," Bogazici Journal, Review of Social, Economic and Administrative Studies, Bogazici University, Department of Economics, vol. 31(2), pages 83-115.
    26. Demetrescu, Matei & Hacıoğlu Hoke, Sinem, 2019. "Predictive regressions under asymmetric loss: Factor augmentation and model selection," International Journal of Forecasting, Elsevier, vol. 35(1), pages 80-99.
    27. Ludvigson, Sydney C., 2013. "Advances in Consumption-Based Asset Pricing: Empirical Tests," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 799-906, Elsevier.
    28. 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.
    29. Breitung, Jörg & Demetrescu, Matei, 2015. "Instrumental variable and variable addition based inference in predictive regressions," Journal of Econometrics, Elsevier, vol. 187(1), pages 358-375.
    30. Valcarcel, Victor J. & Wohar, Mark E., 2013. "Changes in the oil price-inflation pass-through," Journal of Economics and Business, Elsevier, vol. 68(C), pages 24-42.
    31. Gamber, Edward N. & Smith, Julie K. & Weiss, Matthew A., 2011. "Forecast errors before and during the Great Moderation," Journal of Economics and Business, Elsevier, vol. 63(4), pages 278-289, July.
    32. James Morley & Aarti Singh, 2012. "Inventory Mistakes and the Great Moderation," Discussion Papers 2012-42, School of Economics, The University of New South Wales.
    33. Friedrich Lucke, 2022. "The Great Moderation and the Financial Cycle," Working Papers REM 2022/0238, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    34. Ha,Jongrim & Ivanova,Anna & Ohnsorge,Franziska Lieselotte & Unsal Portillo Ocando,Derya Filiz, 2019. "Inflation : Concepts, Evolution, and Correlates," Policy Research Working Paper Series 8738, The World Bank.
    35. Valcarcel, Victor J., 2012. "The dynamic adjustments of stock prices to inflation disturbances," Journal of Economics and Business, Elsevier, vol. 64(2), pages 117-144.

  38. Todd E. Clark & Michael W. McCracken, 2009. "Improving Forecast Accuracy By Combining Recursive And Rolling Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 50(2), pages 363-395, May.
    See citations under working paper version above.
  39. 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.
    See citations under working paper version above.
  40. Todd E. Clark & Taisuke Nakata, 2008. "Has the behavior of inflation and long-term inflation expectations changed?," Economic Review, Federal Reserve Bank of Kansas City, vol. 93(Q I), pages 17-50.

    Cited by:

    1. Maria Demertzis & Massimiliano Marcellino & Nicola Viegi, 2008. "A Measure for Credibility: Tracking US Monetary Developments," Economics Working Papers ECO2008/38, European University Institute.
    2. Reicher, Christopher Phillip & Utlaut, Johannes Friederich, 2011. "The effect of inflation on real commodity prices," Kiel Working Papers 1704, Kiel Institute for the World Economy (IfW Kiel).
    3. Riccardo M Masolo & Francesca Monti, 2021. "Ambiguity, Monetary Policy and Trend Inflation," Journal of the European Economic Association, European Economic Association, vol. 19(2), pages 839-871.
    4. Bosworth, Barry & Flaaen, Aaron, 2009. "America's Financial Crisis: The End of an Era," ADBI Working Papers 142, Asian Development Bank Institute.
    5. Kose,Ayhan & Matsuoka,Hideaki & Panizza,Ugo G. & Vorisek,Dana Lauren, 2019. "Inflation Expectations : Review and Evidence," Policy Research Working Paper Series 8785, The World Bank.
    6. Bharat Trehan, 2009. "Survey measures of expected inflation and the inflation process," Working Paper Series 2009-10, Federal Reserve Bank of San Francisco.
    7. Carrasco, Carlos A., 2013. "El Nuevo Consenso Macroeconómico y la mediocridad del crecimiento económico en México [New Consensus Macroeconomics and the mediocrity of economic growth in Mexico]," MPRA Paper 53391, University Library of Munich, Germany.
    8. Reicher Christopher Phillip & Utlaut Johannes Friederich, 2013. "Monetary policy shocks and real commodity prices," The B.E. Journal of Macroeconomics, De Gruyter, vol. 13(1), pages 715-749, October.
    9. 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.
    10. Gabriele Galati & Peter Heemeijer & Richhild Moessner, 2011. "How do inflation expectations form? New insights from a high-frequency survey," BIS Working Papers 349, Bank for International Settlements.
    11. Bodo Herzog, 2015. "Anchoring of expectations: The role of credible targets in a game experiment," Journal of Economic and Financial Studies (JEFS), LAR Center Press, vol. 3(6), pages 1-15, December.
    12. Gerunov, Anton, 2013. "Връзка Между Икономическите Очаквания И Стопанската Динамика В Ес-27 [Linkages Between Expectations and Economic Dynamics in EU-27]," MPRA Paper 68795, University Library of Munich, Germany.

  41. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    See citations under working paper version above.
  42. Clark, Todd E. & McCracken, Michael W., 2006. "The Predictive Content of the Output Gap for Inflation: Resolving In-Sample and Out-of-Sample Evidence," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(5), pages 1127-1148, August.
    See citations under working paper version above.
  43. Clark, Todd E. & West, Kenneth D., 2006. "Using out-of-sample mean squared prediction errors to test the martingale difference hypothesis," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 155-186.
    See citations under working paper version above.
  44. Todd E. Clark, 2006. "Disaggregate evidence on the persistence of consumer price inflation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 563-587.
    See citations under working paper version above.
  45. Todd E. Clark & Taisuke Nakata, 2006. "The trend growth rate of employment : past, present, and future," Economic Review, Federal Reserve Bank of Kansas City, vol. 91(Q I), pages 43-85.

    Cited by:

    1. Paraskevi Salamaliki, 2015. "Economic Policy Uncertainty and Economic Activity: A Focus on Infrequent Structural Shifts," Working Paper Series of the Department of Economics, University of Konstanz 2015-08, Department of Economics, University of Konstanz.
    2. C. Alan Garner, 2008. "Is commercial real estate reliving the 1980s and early 1990s?," Economic Review, Federal Reserve Bank of Kansas City, vol. 93(Q III), pages 89-115.
    3. Riccardo DiCecio & Kristie M. Engemann & Michael T. Owyang & Christopher H. Wheeler, 2008. "Changing trends in the labor force: a survey," Review, Federal Reserve Bank of St. Louis, vol. 90(Jan), pages 47-62.

  46. Clark, Todd E. & Kozicki, Sharon, 2005. "Estimating equilibrium real interest rates in real time," The North American Journal of Economics and Finance, Elsevier, vol. 16(3), pages 395-413, December.
    See citations under working paper version above.
  47. 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.

    Cited by:

    1. Frédérick Demers & Annie De Champlain, 2005. "Forecasting Core Inflation in Canada: Should We Forecast the Aggregate or the Components?," Staff Working Papers 05-44, Bank of Canada.
    2. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    3. Mario Porqueddu & Fabrizio Venditti, 2012. "Do food commodity prices have asymmetric effects on Euro-Area inflation?," Temi di discussione (Economic working papers) 878, Bank of Italy, Economic Research and International Relations Area.
    4. Yin, Anwen, 2015. "Forecasting and model averaging with structural breaks," ISU General Staff Papers 201501010800005727, Iowa State University, Department of Economics.
    5. Akhter Faroque & William Veloce & Jean-Francois Lamarche, 2012. "Have structural changes eliminated the out-of-sample ability of financial variables to forecast real activity after the mid-1980s? Evidence from the Canadian economy," Applied Economics, Taylor & Francis Journals, vol. 44(30), pages 3965-3985, October.
    6. Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2013. "Biofuels and Food Prices: Searching for the Causal Link," Working Papers 239, University of Milano-Bicocca, Department of Economics, revised Mar 2013.
    7. Galvão, Ana Beatriz, 2013. "Changes in predictive ability with mixed frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 395-410.
    8. Adrian Austin & Swarna Dutt, 2015. "Exchange Rates and Fundamentals: A New Look at the Evidence on Long-Horizon Predictability," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 43(1), pages 147-159, March.
    9. West, Kenneth D., 2006. "Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 3, pages 99-134, Elsevier.
    10. Fabian Baetje & Lukas Menkhoff, 2016. "Equity Premium Prediction: Are Economic and Technical Indicators Unstable?," Discussion Papers of DIW Berlin 1552, DIW Berlin, German Institute for Economic Research.
    11. John Y. Campbell & Samuel B. Thompson, 2005. "Predicting the Equity Premium Out of Sample: Can Anything Beat the Historical Average?," NBER Working Papers 11468, National Bureau of Economic Research, Inc.
    12. Cremaschini, Alessandro & Maruotti, Antonello, 2023. "A finite mixture analysis of structural breaks in the G-7 gross domestic product series," Research in Economics, Elsevier, vol. 77(1), pages 76-90.
    13. Cai Zongwu & Chen Linna & Fang Ying, 2012. "A New Forecasting Model for USD/CNY Exchange Rate," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(3), pages 1-20, September.
    14. Gantungalag Altansukh & Denise R. Osborn, 2022. "Using structural break inference for forecasting time series," Empirical Economics, Springer, vol. 63(1), pages 1-41, July.
    15. Marilena Furno, 2011. "Goodness of Fit and Misspecification in Quantile Regressions," Journal of Educational and Behavioral Statistics, , vol. 36(1), pages 105-131, February.
    16. Elena Andreou & Eric Ghysels & Andros Kourtellos, 2013. "Should Macroeconomic Forecasters Use Daily Financial Data and How?," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(2), pages 240-251, April.
    17. Zachary McGurk & Adam Nowak & Joshua C. Hall, 2019. "Stock Returns and Investor Sentiment: Textual Analysis and Social Media," Working Papers 19-03, Department of Economics, West Virginia University.
    18. Clark, Todd E. & McCracken, Michael W., 2015. "Nested forecast model comparisons: A new approach to testing equal accuracy," Journal of Econometrics, Elsevier, vol. 186(1), pages 160-177.
    19. Tian, Jing & Anderson, Heather M., 2014. "Forecast combinations under structural break uncertainty," International Journal of Forecasting, Elsevier, vol. 30(1), pages 161-175.
    20. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
    21. Fabio Busetti & Juri Marcucci & Giovanni Veronese, 2009. "Comparing forecast accuracy: A Monte Carlo investigation," Temi di discussione (Economic working papers) 723, Bank of Italy, Economic Research and International Relations Area.
    22. Atsushi Inoue & Barbara Rossi, 2011. "Out-of-sample forecast tests robust to the choice of window size," Working Papers 11-31, Federal Reserve Bank of Philadelphia.
    23. Rossi, Barbara & Giacomini, Raffaella, 2005. "How Stable is the Forecasting Performance of the Yield Curve for Outpot Growth?," Working Papers 05-08, Duke University, Department of Economics.
    24. Pincheira, Pablo M. & West, Kenneth D., 2016. "A comparison of some out-of-sample tests of predictability in iterated multi-step-ahead forecasts," Research in Economics, Elsevier, vol. 70(2), pages 304-319.
    25. Raffaella Giacomini & Barbara Rossi, 2013. "Forecasting in macroeconomics," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 17, pages 381-408, Edward Elgar Publishing.
    26. Barry Eichengreen & Ashoka Mody & Milan Nedeljkovic & Lucio Sarno, 2012. "How the Subprime Crisis Went Global: Evidence from Bank Credit Default Swap Spreads," Working papers 21, National Bank of Serbia.
    27. Jing Tian & Heather M. Anderson, 2011. "Forecasting Under Strucural Break Uncertainty," Monash Econometrics and Business Statistics Working Papers 8/11, Monash University, Department of Econometrics and Business Statistics.
    28. Gary J. Cornwall & Jeffrey A. Mills & Beau A. Sauley & Huibin Weng, 2019. "Predictive Testing for Granger Causality via Posterior Simulation and Cross-validation," Advances in Econometrics, in: Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part A, volume 40, pages 275-292, Emerald Group Publishing Limited.
    29. Clark, Todd E. & McCracken, Michael W., 2012. "In-sample tests of predictive ability: A new approach," Journal of Econometrics, Elsevier, vol. 170(1), pages 1-14.
    30. McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, vol. 140(2), pages 719-752, October.
    31. Smith Aaron, 2012. "Markov Breaks in Regression Models," Journal of Time Series Econometrics, De Gruyter, vol. 4(1), pages 1-35, May.
    32. Lance Bachmeier & Qi Li & Dandan Liu, 2008. "Should Oil Prices Receive So Much Attention? An Evaluation Of The Predictive Power Of Oil Prices For The U.S. Economy," Economic Inquiry, Western Economic Association International, vol. 46(4), pages 528-539, October.
    33. Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2014. "Causality and predictability in distribution: The ethanol–food price relation revisited," Energy Economics, Elsevier, vol. 42(C), pages 152-160.
    34. Zachary McGurk & Adam Nowak, 2014. "The Relationship Between Stock Returns and Investor Sentiment: Evidence from Social Media," Working Papers 14-38, Department of Economics, West Virginia University.
    35. Yi-Ting Chen, 2016. "Testing for Granger Causality in Moments," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(2), pages 265-288, April.
    36. Barbara Rossi, 2005. "Are Exchange Rates Really Random Walks? Some Evidence Robust to Parameter Instability," International Finance 0503006, University Library of Munich, Germany.
    37. 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.
    38. Junsoo Lee & John A. List & Mark Strazicich, 2005. "Nonrenewable Resource Prices: Deterministic or Stochastic Trends?," NBER Working Papers 11487, National Bureau of Economic Research, Inc.
    39. Hubrich, Kirstin & Granziera, Eleonora & Moon, Hyungsik Roger, 2013. "A predictability test for a small number of nested models," Working Paper Series 1580, European Central Bank.
    40. McGurk, Zachary, 2020. "US real estate inflation prediction: Exchange rates and net foreign assets," The Quarterly Review of Economics and Finance, Elsevier, vol. 75(C), pages 53-66.
    41. Marcellino, Massimiliano & Musso, Alberto, 2010. "Real time estimates of the euro area output gap: reliability and forecasting performance," Working Paper Series 1157, European Central Bank.
    42. Jing Tian & Qing Zhou, 2018. "Improving equity premium forecasts by incorporating structural break uncertainty," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(S1), pages 619-656, November.
    43. Rossi, Barbara & Sekhposyan, Tatevik, 2011. "Understanding models' forecasting performance," Journal of Econometrics, Elsevier, vol. 164(1), pages 158-172, September.
    44. Dudek, Sławomir, 2008. "Consumer Survey Data and short-term forecasting of households consumption expenditures in Poland," MPRA Paper 19818, University Library of Munich, Germany.
    45. Alessandro Casini, 2018. "Tests for Forecast Instability and Forecast Failure under a Continuous Record Asymptotic Framework," Papers 1803.10883, arXiv.org, revised Dec 2018.
    46. Marcellino, Massimiliano & Musso, Alberto, 2010. "The Forecasting Performance of Real Time Estimates of the Euro Area Output Gap," CEPR Discussion Papers 7763, C.E.P.R. Discussion Papers.
    47. Rossi, Barbara & Sekhposyan, Tatevik, 2010. "Have economic models' forecasting performance for US output growth and inflation changed over time, and when?," International Journal of Forecasting, Elsevier, vol. 26(4), pages 808-835, October.
    48. Shiu-Sheng Chen, 2005. "A note on in-sample and out-of-sample tests for Granger causality," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(6), pages 453-464.
    49. Pablo Pincheira & Nicolás Hardy & Felipe Muñoz, 2021. "“Go Wild for a While!”: A New Test for Forecast Evaluation in Nested Models," Mathematics, MDPI, vol. 9(18), pages 1-28, September.
    50. Brooks, Chris & Burke, Simon P. & Stanescu, Silvia, 2016. "Finite sample weighting of recursive forecast errors," International Journal of Forecasting, Elsevier, vol. 32(2), pages 458-474.
    51. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 328-383, Elsevier.
    52. Pincheira, Pablo & Hardy, Nicolás & Muñoz, Felipe, 2021. ""Go wild for a while!": A new asymptotically Normal test for forecast evaluation in nested models," MPRA Paper 105368, University Library of Munich, Germany.
    53. Todd E. Clark & Michael W. McCracken, 2010. "Testing for unconditional predictive ability," Working Papers 2010-031, Federal Reserve Bank of St. Louis.

  48. Todd Clark & Michael McCracken, 2005. "Evaluating Direct Multistep Forecasts," Econometric Reviews, Taylor & Francis Journals, vol. 24(4), pages 369-404.

    Cited by:

    1. R Naraidoo & I Paya, 2010. "Forecasting Monetary Policy Rules in South Africa," Working Papers 611194, Lancaster University Management School, Economics Department.
    2. Norman R. Swanson & Nii Ayi Armah, 2011. "Predictive Inference Under Model Misspecification with an Application to Assessing the Marginal Predictive Content of Money for Output," Departmental Working Papers 201103, Rutgers University, Department of Economics.
    3. Arratibel, Olga & Leiner-Killinger, Nadine & Kamps, Christophe, 2009. "Inflation forecasting in the new EU Member States," Working Paper Series 1015, European Central Bank.
    4. Pablo Pincheira, 2008. "Combining Tests of Predictive Ability Theory and Evidence for Chilean and Canadian Exchange Rates," Working Papers Central Bank of Chile 459, Central Bank of Chile.
    5. Berger, Helge & Österholm, Pär, 2008. "Does money growth granger-cause inflation in the Euro Area? Evidence from output-of-sample forecasts using Bayesian VARs," Discussion Papers 2008/10, Free University Berlin, School of Business & Economics.
    6. Ricardo Mestre & Peter McAdam, 2011. "Is forecasting with large models informative? Assessing the role of judgement in macroeconomic forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(3), pages 303-324, April.
    7. Ron Alquist & Lutz Kilian & Robert J. Vigfusson, 2011. "Forecasting the price of oil," International Finance Discussion Papers 1022, Board of Governors of the Federal Reserve System (U.S.).
    8. Altug, Sumru & Çakmaklı, Cem, 2016. "Forecasting inflation using survey expectations and target inflation: Evidence for Brazil and Turkey," International Journal of Forecasting, Elsevier, vol. 32(1), pages 138-153.
    9. Chevillon, Guillaume, 2009. "Multi-step forecasting in emerging economies: An investigation of the South African GDP," International Journal of Forecasting, Elsevier, vol. 25(3), pages 602-628, July.
    10. Mario Forni & Luca Gambetti, 2014. "Government Spending Shocks in Open Economy VARs," Center for Economic Research (RECent) 105, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    11. Michael W. McCracken & Serena Ng, 2016. "FRED-MD: A Monthly Database for Macroeconomic Research," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 574-589, October.
    12. Galvão, Ana Beatriz, 2013. "Changes in predictive ability with mixed frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 395-410.
    13. Peter Reinhard HANSEN & Allan TIMMERMANN, 2012. "Choice of Sample Split in Out-of-Sample Forecast Evaluation," Economics Working Papers ECO2012/10, European University Institute.
    14. Clements, Michael P. & Galvao, Ana Beatriz, 2006. "Macroeconomic Forecasting with Mixed Frequency Data: Forecasting US output growth and inflation," Economic Research Papers 269743, University of Warwick - Department of Economics.
    15. Luke Hartigan & Tom Rosewall, 2024. "Nowcasting Quarterly GDP Growth during the COVID-19 Crisis Using a Monthly Activity Indicator," RBA Research Discussion Papers rdp2024-04, Reserve Bank of Australia.
    16. Ruthira Naraidoo & Ivan Paya, 2010. "Forecasting Monetary Rules in South Africa," Working Papers 201007, University of Pretoria, Department of Economics.
    17. Molodtsova, Tanya & Nikolsko-Rzhevskyy, Alex & Papell, David H., 2008. "Taylor rules with real-time data: A tale of two countries and one exchange rate," Journal of Monetary Economics, Elsevier, vol. 55(Supplemen), pages 63-79, October.
    18. Boriss Siliverstovs & Kinstantin Kholodilim, 2009. "On selection of components for a diffusion index model: it's not the size, it's how you use it," Applied Economics Letters, Taylor & Francis Journals, vol. 16(12), pages 1249-1254.
    19. Mark E. Wohar & David E. Rapach, 2007. "Forecasting the recent behavior of US business fixed investment spending: an analysis of competing models This is a significantly revised version of our previous paper, 'Forecasting US Business Fixed ," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(1), pages 33-51.
    20. Jordan, Steven J. & Vivian, Andrew & Wohar, Mark E., 2017. "Forecasting market returns: bagging or combining?," International Journal of Forecasting, Elsevier, vol. 33(1), pages 102-120.
    21. Vivian, Andrew & Wohar, Mark E., 2013. "The output gap and stock returns: Do cyclical fluctuations predict portfolio returns?," International Review of Financial Analysis, Elsevier, vol. 26(C), pages 40-50.
    22. Gonçalves, Sílvia & McCracken, Michael W. & Perron, Benoit, 2017. "Tests of equal accuracy for nested models with estimated factors," Journal of Econometrics, Elsevier, vol. 198(2), pages 231-252.
    23. Todd E. Clark & Michael W. McCracken, 2007. "Tests of equal predictive ability with real-time data," Research Working Paper RWP 07-06, Federal Reserve Bank of Kansas City.
    24. Antonello D'Agostino & Paolo Surico, 2009. "Does Global Liquidity Help to Forecast U.S. Inflation?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(2‐3), pages 479-489, March.
    25. Kabukçuoğlu, Ayşe & Martínez-García, Enrique, 2018. "Inflation as a global phenomenon—Some implications for inflation modeling and forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 87(C), pages 46-73.
    26. Richard A. Ashley & Kwok Ping Tsang, 2014. "Credible Granger-Causality Inference with Modest Sample Lengths: A Cross-Sample Validation Approach," Econometrics, MDPI, vol. 2(1), pages 1-20, March.
    27. Marcellino, Massimiliano, 2011. "Markov-switching MIDAS models," CEPR Discussion Papers 8234, C.E.P.R. Discussion Papers.
    28. Laurent Ferrara & Massimiliano Marcellino & Matteo Mogliani, 2015. "Macroeconomic forecasting during the Great Recession: the return of non-linearity?," Post-Print hal-01635951, HAL.
    29. Kirstin Hubrich & Kenneth D. West, 2008. "Forecast Evaluation of Small Nested Model Sets," NBER Working Papers 14601, National Bureau of Economic Research, Inc.
    30. Todd E. Clark & Michael W. Mccracken, 2014. "Tests Of Equal Forecast Accuracy For Overlapping Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(3), pages 415-430, April.
    31. Kenneth D. West & Todd Clark, 2006. "Approximately Normal Tests for Equal Predictive Accuracy in Nested Models," NBER Technical Working Papers 0326, National Bureau of Economic Research, Inc.
    32. Pincheira, Pablo & Selaive, Jorge & Nolazco, Jose Luis, 2017. "Forecasting Inflation in Latin America with Core Measures," MPRA Paper 80496, University Library of Munich, Germany.
    33. Berger, Helge & Österholm, Pär, 2008. "Does money matter for U.S. inflation? Evidence from Bayesian VARs," Discussion Papers 2008/9, Free University Berlin, School of Business & Economics.
    34. Ayse Kabukcuoglu & Enrique Martínez-García, 2016. "What Helps Forecast U.S. Inflation?—Mind the Gap!," Koç University-TUSIAD Economic Research Forum Working Papers 1615, Koc University-TUSIAD Economic Research Forum.
    35. Jack Fosten, 2016. "Forecast evaluation with factor-augmented models," University of East Anglia School of Economics Working Paper Series 2016-05, School of Economics, University of East Anglia, Norwich, UK..
    36. Clark, Todd E. & McCracken, Michael W., 2015. "Nested forecast model comparisons: A new approach to testing equal accuracy," Journal of Econometrics, Elsevier, vol. 186(1), pages 160-177.
    37. Peter Reinhard Hansen & Allan Timmermann, 2015. "Comment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(1), pages 17-21, January.
    38. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
    39. Fabio Busetti & Juri Marcucci & Giovanni Veronese, 2009. "Comparing forecast accuracy: A Monte Carlo investigation," Temi di discussione (Economic working papers) 723, Bank of Italy, Economic Research and International Relations Area.
    40. 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.
    41. Pablo Pincheira Brown & Nicolás Hardy, 2024. "Correlation‐based tests of predictability," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 1835-1858, September.
    42. Coble, David & Pincheira, Pablo, 2017. "Nowcasting Building Permits with Google Trends," MPRA Paper 76514, University Library of Munich, Germany.
    43. Atsushi Inoue & Barbara Rossi, 2011. "Out-of-sample forecast tests robust to the choice of window size," Working Papers 11-31, Federal Reserve Bank of Philadelphia.
    44. Kenneth S. Rogoff & Vania Stavrakeva, 2008. "The Continuing Puzzle of Short Horizon Exchange Rate Forecasting," NBER Working Papers 14071, National Bureau of Economic Research, Inc.
    45. Steven J. Jordan & Andrew Vivian & Mark E. Wohar, 2015. "Location, location, location: currency effects and return predictability?," Applied Economics, Taylor & Francis Journals, vol. 47(18), pages 1883-1898, April.
    46. Bulkley, George & Harris, Richard D.F. & Nawosah, Vivekanand, 2015. "Can behavioral biases explain the rejections of the expectation hypothesis of the term structure of interest rates?," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 179-193.
    47. Calhoun, Gray, 2014. "Out-Of-Sample Comparisons of Overfit Models," Staff General Research Papers Archive 32462, Iowa State University, Department of Economics.
    48. Rudan Wang & Bruce Morley & Javier Ordóñez, 2015. "The Taylor Rule, Wealth Effects and the Exchange Rate," Working Papers 2015/08, Economics Department, Universitat Jaume I, Castellón (Spain).
    49. LAURENT, Sébastien & VIOLANTE, Francesco, 2012. "Volatility forecasts evaluation and comparison," LIDAM Reprints CORE 2414, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    50. Bob Nobay & Ivan Paya & David A. Peel, 2010. "Inflation Dynamics in the U.S.: Global but Not Local Mean Reversion," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(1), pages 135-150, February.
    51. Pincheira, Pablo M. & West, Kenneth D., 2016. "A comparison of some out-of-sample tests of predictability in iterated multi-step-ahead forecasts," Research in Economics, Elsevier, vol. 70(2), pages 304-319.
    52. 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.
    53. Hofmann, Boris, 2008. "Do monetary indicators lead euro area inflation?," Working Paper Series 867, European Central Bank.
    54. Pincheira, Pablo & Selaive, Jorge & Nolazco, Jose Luis, 2016. "The Evasive Predictive Ability of Core Inflation," MPRA Paper 68704, University Library of Munich, Germany.
    55. Peter Reinhard Hansen & Allan Timmermann, 2012. "Equivalence Between Out-of-Sample Forecast Comparisons and Wald Statistics," Economics Working Papers ECO2012/24, European University Institute.
    56. Todd E. Clark & Michael W. McCracken, 2010. "Reality checks and nested forecast model comparisons," Working Papers 2010-032, Federal Reserve Bank of St. Louis.
    57. Norman Swanson & Richard Urbach, 2013. "Prediction and Simulation Using Simple Models Characterized by Nonstationarity and Seasonality," Departmental Working Papers 201323, Rutgers University, Department of Economics.
    58. Jack Fosten & Daniel Gutknecht, 2021. "Horizon confidence sets," Empirical Economics, Springer, vol. 61(2), pages 667-692, August.
    59. David E. Rapach & Jack K. Strauss, 2008. "Structural breaks and GARCH models of exchange rate volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 65-90.
    60. Pär Österholm & Mr. Helge Berger, 2008. "Does Money Growth Granger-Cause Inflation in the Euro Area? Evidence from Out-of-Sample Forecasts Using Bayesian VARs," IMF Working Papers 2008/053, International Monetary Fund.
    61. Gagnon, Marie-Hélène & Power, Gabriel J. & Toupin, Dominique, 2023. "The sum of all fears: Forecasting international returns using option-implied risk measures," Journal of Banking & Finance, Elsevier, vol. 146(C).
    62. Panopoulou, Ekaterini, 2007. "Predictive financial models of the euro area: A new evaluation test," International Journal of Forecasting, Elsevier, vol. 23(4), pages 695-705.
    63. Firmin Doko Tchatoka & Qazi Haque, 2020. "On bootstrapping tests of equal forecast accuracy for nested models," School of Economics and Public Policy Working Papers 2020-03, University of Adelaide, School of Economics and Public Policy.
    64. Roi D. Taussig, 2017. "Stickiness of employee expenses and implications for stock returns," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 7(2), pages 297-309, August.
    65. Li, Jia & Patton, Andrew J., 2018. "Asymptotic inference about predictive accuracy using high frequency data," Journal of Econometrics, Elsevier, vol. 203(2), pages 223-240.
    66. Kevin L. Kliesen, 2008. "Oil and the U.S. macroeconomy: an update and a simple forecasting exercise," Review, Federal Reserve Bank of St. Louis, vol. 90(Sep), pages 505-516.
    67. GIOT, Pierre & PETITJEAN, Mikael, 2006. "International stock return predictability: statistical evidence and economic significance," LIDAM Discussion Papers CORE 2006088, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    68. Hardy, Nicolás & Ferreira, Tiago & Quinteros, Maria J. & Magner, Nicolás S., 2023. "“Watch your tone!”: Forecasting mining industry commodity prices with financial report tone," Resources Policy, Elsevier, vol. 86(PA).
    69. Magnus Gustavsson & Pär Österholm, 2010. "The presence of unemployment hysteresis in the OECD: what can we learn from out-of-sample forecasts?," Empirical Economics, Springer, vol. 38(3), pages 779-792, June.
    70. Papantonis, Ioannis & Rompolis, Leonidas & Tzavalis, Elias, 2023. "Improving variance forecasts: The role of Realized Variance features," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1221-1237.
    71. Clements, Michael P. & Galvão, Ana Beatriz, 2013. "Forecasting with vector autoregressive models of data vintages: US output growth and inflation," International Journal of Forecasting, Elsevier, vol. 29(4), pages 698-714.
    72. Österholm, Pär, 2009. "Improving Unemployment Rate Forecasts Using Survey Data," Working Papers 112, National Institute of Economic Research.
    73. Jean-Stephane Mesonnier, 2011. "The forecasting power of real interest rate gaps: an assessment for the Euro area," Applied Economics, Taylor & Francis Journals, vol. 43(2), pages 153-172.
    74. Sousa, Ricardo M. & Vivian, Andrew & Wohar, Mark E., 2016. "Predicting asset returns in the BRICS: The role of macroeconomic and fundamental predictors," International Review of Economics & Finance, Elsevier, vol. 41(C), pages 122-143.
    75. Mogliani, Matteo & Darné, Olivier & Pluyaud, Bertrand, 2017. "The new MIBA model: Real-time nowcasting of French GDP using the Banque de France's monthly business survey," Economic Modelling, Elsevier, vol. 64(C), pages 26-39.
    76. Costantini, Mauro & Kunst, Robert M., 2021. "On using predictive-ability tests in the selection of time-series prediction models: A Monte Carlo evaluation," International Journal of Forecasting, Elsevier, vol. 37(2), pages 445-460.
    77. Nikolsko-Rzhevskyy, Alex & Prodan, Ruxandra, 2012. "Markov switching and exchange rate predictability," International Journal of Forecasting, Elsevier, vol. 28(2), pages 353-365.
    78. Andersson, Magnus & D'Agostino, Antonello, 2008. "Are sectoral stock prices useful for predicting euro area GDP?," Research Technical Papers 2/RT/08, Central Bank of Ireland.
    79. Pincheira, Pablo & Hardy, Nicolas, 2018. "Forecasting Base Metal Prices with Commodity Currencies," MPRA Paper 83564, University Library of Munich, Germany.
    80. Ayse Kabukcuoglu & Enrique Martínez García & Mehmet A. Soytas, 2017. "Exploring the Nexus Between Inflation and Globalization Under Inflation Targeting Through the Lens of New Zealand’s Experience," Globalization Institute Working Papers 308, Federal Reserve Bank of Dallas.
    81. P H Franses & R Legerstee, 2011. "Experts' adjustment to model-based SKU-level forecasts: does the forecast horizon matter?," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(3), pages 537-543, March.
    82. Rapach, David E. & Strauss, Jack K., 2012. "Forecasting US state-level employment growth: An amalgamation approach," International Journal of Forecasting, Elsevier, vol. 28(2), pages 315-327.
    83. Mohr, Matthias & Maurin, Laurent & Guérin, Pierre, 2011. "Trend-cycle decomposition of output and euro area inflation forecasts: a real-time approach based on model combination," Working Paper Series 1384, European Central Bank.
    84. Wright, Jonathan H. & Zhou, Hao, 2009. "Bond risk premia and realized jump risk," Journal of Banking & Finance, Elsevier, vol. 33(12), pages 2333-2345, December.
    85. Hubrich, Kirstin & Granziera, Eleonora & Moon, Hyungsik Roger, 2013. "A predictability test for a small number of nested models," Working Paper Series 1580, European Central Bank.
    86. Kevin L. Kliesen, 2007. "How well does employment predict output?," Review, Federal Reserve Bank of St. Louis, vol. 89(Sep), pages 433-446.
    87. McGurk, Zachary, 2020. "US real estate inflation prediction: Exchange rates and net foreign assets," The Quarterly Review of Economics and Finance, Elsevier, vol. 75(C), pages 53-66.
    88. Norman R. Swanson & Nii Ayi Armah, 2011. "Some Variables are More Worthy Than Others: New Diffusion Index Evidence on the Monitoring of Key Economic Indicators," Departmental Working Papers 201115, Rutgers University, Department of Economics.
    89. Ekaterini Panopoulou & Sotiria Plastira, 2014. "Fama French factors and US stock return predictability," Journal of Asset Management, Palgrave Macmillan, vol. 15(2), pages 110-128, April.
    90. Todd E. Clark & Michael W. McCracken, 2014. "Evaluating Conditional Forecasts from Vector Autoregressions," Working Papers (Old Series) 1413, Federal Reserve Bank of Cleveland.
    91. Pincheira, Pablo, 2017. "A Power Booster Factor for Out-of-Sample Tests of Predictability," MPRA Paper 77027, University Library of Munich, Germany.
    92. Jean-Stéphane MESONNIER, 2007. "The predictive content of the real interest rate gap for macroeconomic variables in the euro area," Money Macro and Finance (MMF) Research Group Conference 2006 102, Money Macro and Finance Research Group.
    93. Kurennoy, Alexey (Куренной, Алексей), 2015. "Evaluation of the Forecasting Quality [Оценка Качества Прогнозирования]," Published Papers mak7, Russian Presidential Academy of National Economy and Public Administration.
    94. Ekaterini Panopoulou & Nikitas Pittis & Sarantis Kalyvitis, 2006. "Looking far in the past: Revisiting the growth-returns nexus with non-parametric tests," The Institute for International Integration Studies Discussion Paper Series iiisdp134, IIIS.
    95. Valseth, Siri, 2016. "Informed trading in Hybrid Bond Markets," UiS Working Papers in Economics and Finance 2016/13, University of Stavanger.
    96. Chava, Sudheer & Gallmeyer, Michael & Park, Heungju, 2015. "Credit conditions and stock return predictability," Journal of Monetary Economics, Elsevier, vol. 74(C), pages 117-132.
    97. 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.
    98. Driver, Ciaran & Trapani, Lorenzo & Urga, Giovanni, 2013. "On the use of cross-sectional measures of forecast uncertainty," International Journal of Forecasting, Elsevier, vol. 29(3), pages 367-377.
    99. Haskamp, Ulrich, 2017. "Forecasting exchange rates: The time-varying relationship between exchange rates and Taylor rule fundamentals," Ruhr Economic Papers 704, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    100. Mésonnier, J-S., 2006. "The Reliability of Macroeconomic Forecasts based on Real Interest Rate Gap Estimates in Real Time: an Assessment for the Euro Area," Working papers 157, Banque de France.
    101. Söderberg, Jonas, 2008. "Do Macroeconomic Variables Forecast Changes in Liquidity? An Out-of-sample Study on the Order-driven Stock Markets in Scandinavia," CAFO Working Papers 2009:10, Linnaeus University, Centre for Labour Market Policy Research (CAFO), School of Business and Economics.
    102. Kichian, Maral & Rumler, Fabio, 2014. "Forecasting Canadian inflation: A semi-structural NKPC approach," Economic Modelling, Elsevier, vol. 43(C), pages 183-191.
    103. Onur Ince, 2013. "Forecasting Exchange Rates Out-of-Sample with Panel Methods and Real-Time Data," Working Papers 13-04, Department of Economics, Appalachian State University.
    104. Berger, Helge & Österholm, Pär, 2008. "Does money still matter for U.S. output?," Discussion Papers 2008/7, Free University Berlin, School of Business & Economics.
    105. Jean-Yves Pitarakis, 2020. "A Novel Approach to Predictive Accuracy Testing in Nested Environments," Papers 2008.08387, arXiv.org, revised Oct 2023.
    106. Johanna Posch & Fabio Rumler, 2015. "Semi‐Structural Forecasting of UK Inflation Based on the Hybrid New Keynesian Phillips Curve," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(2), pages 145-162, March.
    107. Doyle, Matthew, 2006. "Empirical Phillips Curves in OECD Countries: Has There Been A Common Breakdown?," Staff General Research Papers Archive 12684, Iowa State University, Department of Economics.
    108. Brooks, Chris & Burke, Simon P. & Stanescu, Silvia, 2016. "Finite sample weighting of recursive forecast errors," International Journal of Forecasting, Elsevier, vol. 32(2), pages 458-474.
    109. A A Syntetos & N C Georgantzas & J E Boylan & B C Dangerfield, 2011. "Judgement and supply chain dynamics," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(6), pages 1138-1158, June.
    110. Cláudia Duarte, 2014. "Autoregressive augmentation of MIDAS regressions," Working Papers w201401, Banco de Portugal, Economics and Research Department.
    111. Pablo Pincheira Brown & Nicolás Hardy, 2023. "Forecasting base metal prices with exchange rate expectations," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 2341-2362, December.
    112. Jon Faust & Jonathan H. Wright, 2018. "Risk Premia in the 8:30 Economy," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 8(03), pages 1-19, September.
    113. Medel, Carlos A., 2015. "A Critical Review of Posch, J. and F. Rumler (2015), 'Semi-Structural Forecasting of UK Inflation Based on the Hybrid New Keynesian Phillips Curve,' Journal of Forecasting 34(2): 145-62," MPRA Paper 65665, University Library of Munich, Germany.
    114. Duarte, Cláudia & Rodrigues, Paulo M.M. & Rua, António, 2017. "A mixed frequency approach to the forecasting of private consumption with ATM/POS data," International Journal of Forecasting, Elsevier, vol. 33(1), pages 61-75.
    115. Michael P. Clements & Ana Beatriz Galvão, 2007. "Macroeconomic Forecasting with Mixed Frequency Data: Forecasting US Output Growth," Working Papers 616, Queen Mary University of London, School of Economics and Finance.
    116. Todd E. Clark & Michael W. McCracken, 2010. "Testing for unconditional predictive ability," Working Papers 2010-031, Federal Reserve Bank of St. Louis.

  49. Todd E. Clark, 2004. "Can out-of-sample forecast comparisons help prevent overfitting?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(2), pages 115-139.
    See citations under working paper version above.
  50. Todd E. Clark, 2004. "An evaluation of the decline in goods inflation," Economic Review, Federal Reserve Bank of Kansas City, vol. 89(Q II), pages 19-51.

    Cited by:

    1. Miljkovic, Dragan & Jin, Hyun Joung & Paul, Rodney, 2007. "The Role of Productivity Growth and Farmers' Income Protection Policies in the Decline of Relative Farm Prices in the United States," Agribusiness & Applied Economics Report 9368, North Dakota State University, Department of Agribusiness and Applied Economics.
    2. 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.
    3. Gernot Pehnelt, 2007. "Globalisation and Inflation in OECD Countries," Jena Economics Research Papers 2007-055, Friedrich-Schiller-University Jena.
    4. Mr. Benjamin L Hunt, 2007. "U.K. Inflation and Relative Prices over the Last Decade: How Important was Globalization?," IMF Working Papers 2007/208, International Monetary Fund.
    5. Cobb, Marcus P A, 2018. "Improving Underlying Scenarios for Aggregate Forecasts: A Multi-level Combination Approach," MPRA Paper 88593, University Library of Munich, Germany.
    6. Robert W. Rich & Randal J. Verbrugge & Saeed Zaman, 2022. "Adjusting Median and Trimmed-Mean Inflation Rates for Bias Based on Skewness," Economic Commentary, Federal Reserve Bank of Cleveland, vol. 2022(05), pages 1-7, March.

  51. Clark, Todd E. & McCracken, Michael W., 2001. "Tests of equal forecast accuracy and encompassing for nested models," Journal of Econometrics, Elsevier, vol. 105(1), pages 85-110, November.
    See citations under working paper version above.
  52. Clark, Todd E. & van Wincoop, Eric, 2001. "Borders and business cycles," Journal of International Economics, Elsevier, vol. 55(1), pages 59-85, October.
    See citations under working paper version above.
  53. Todd E. Clark, 2001. "Comparing measures of core inflation," Economic Review, Federal Reserve Bank of Kansas City, vol. 86(Q II), pages 5-31.

    Cited by:

    1. James H. Stock & Mark W. Watson, 2015. "Core Inflation and Trend Inflation," NBER Working Papers 21282, National Bureau of Economic Research, Inc.
    2. Gatt, William, 2014. "An evaluation of core inflation measures for Malta," MPRA Paper 61250, University Library of Munich, Germany.
    3. Boysen-Hogrefe, Jens & Dovern, Jonas & Gern, Klaus-Jürgen & Jannsen, Nils & Van Roye, Björn & Scheide, Joachim & Boss, Alfred & Groll, Dominik & Meier, Carsten-Patrick, 2010. "Weltkonjunktur und deutsche Konjunktur im Winter 2009," Kiel Discussion Papers 470/471, Kiel Institute for the World Economy (IfW Kiel).
    4. Oğuz Atuk & Mustafa Utku Özmen, 2009. "Design and evaluation of core inflation measures for Turkey," IFC Working Papers 3, Bank for International Settlements.
    5. Priyanka Sahu, 2021. "A Study on the Dynamic Behaviour of Headline Versus Core Inflation: Evidence from India," Global Business Review, International Management Institute, vol. 22(6), pages 1574-1593, December.
    6. Kemp-Benedict, Eric, 2012. "Material needs and aggregate demand," MPRA Paper 39960, University Library of Munich, Germany.
    7. Choi, Chi-Young & O'Sullivan, Róisín, 2013. "Heterogeneous response of disaggregate inflation to monetary policy regime change: The role of price stickiness," Journal of Economic Dynamics and Control, Elsevier, vol. 37(9), pages 1814-1832.
    8. Dowd, Kevin & Cotter, John & Loh, Lixia, 2011. "U.S. Core Inflation: A Wavelet Analysis," Macroeconomic Dynamics, Cambridge University Press, vol. 15(4), pages 513-536, September.
    9. Pincheira, Pablo & Selaive, Jorge & Nolazco, Jose Luis, 2017. "Forecasting Inflation in Latin America with Core Measures," MPRA Paper 80496, University Library of Munich, Germany.
    10. Jushan Bai & Serena Ng, 2001. "A Panic Attack on Unit Roots and Cointegration," Economics Working Paper Archive 469, The Johns Hopkins University,Department of Economics.
    11. Bermingham, Colin, 2006. "How Useful is Core Inflation for Forecasting Headline Inflation?," Research Technical Papers 11/RT/06, Central Bank of Ireland.
    12. Mazumder, Sandeep, 2014. "The sacrifice ratio and core inflation," Journal of Macroeconomics, Elsevier, vol. 40(C), pages 400-421.
    13. Joice John & Abhiman Das & Sanjay Singh, 2016. "An Application of Quah and Vahey’s SVAR Methodology for Estimating Core Inflation in India: A Note," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 14(1), pages 151-158, June.
    14. Tierney, Heather L.R., 2010. "Real-Time Data Revisions and the PCE Measure of Inflation," MPRA Paper 22387, University Library of Munich, Germany, revised Apr 2010.
    15. Bańbura, Marta & Bobeica, Elena, 2020. "PCCI – a data-rich measure of underlying inflation in the euro area," Statistics Paper Series 38, European Central Bank.
    16. Stefano Eusepi & Bart Hobijn & Andrea Tambalotti, 2011. "CONDI: A Cost-of-Nominal-Distortions Index," American Economic Journal: Macroeconomics, American Economic Association, vol. 3(3), pages 53-91, July.
    17. Stephen G Cecchetti & Richhild Moessner, 2008. "Commodity prices and inflation dynamics," BIS Quarterly Review, Bank for International Settlements, December.
    18. Mark A. Wynne, 2008. "Core inflation: a review of some conceptual issues," Review, Federal Reserve Bank of St. Louis, vol. 90(May), pages 205-228.
    19. Robert W. Rich & Charles Steindel, 2005. "A review of core inflation and an evaluation of its measures," Staff Reports 236, Federal Reserve Bank of New York.
    20. Linda S. Goldberg & Michael W. Klein, 2005. "Establishing Credibility: Evolving Perceptions of the European Central Bank," The Institute for International Integration Studies Discussion Paper Series iiisdp105, IIIS.
    21. Philippe Goulet Coulombe & Karin Klieber & Christophe Barrette & Maximilian Goebel, 2024. "Maximally Forward-Looking Core Inflation," Papers 2404.05209, arXiv.org.
    22. Castañeda, Juan Carlos & Chang, Rodrigo, 2023. "Evaluating core inflation measures: A statistical inference approach," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 4(4).
    23. Mazumder, Sandeep, 2017. "Output gains from accelerating core inflation," Journal of Macroeconomics, Elsevier, vol. 51(C), pages 63-74.
    24. Altansukh, Gantungalag & Becker, Ralf & Bratsiotis, George J. & Osborn, Denise R., 2017. "What is the Globalisation of Inflation?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 74, pages 1-27.
    25. Bermingham, Colin, 2010. "A critical assessment of existing estimates of US core inflation," Journal of Macroeconomics, Elsevier, vol. 32(4), pages 993-1007, December.
    26. Stefano Siviero & Giovanni Veronese, 2011. "A policy-sensible benchmark core inflation measure," Oxford Economic Papers, Oxford University Press, vol. 63(4), pages 648-672, December.
    27. Jamie Armour, 2006. "An Evaluation of Core Inflation Measures," Staff Working Papers 06-10, Bank of Canada.
    28. Chrigui Zouhair & Boujelbene Younes, 2009. "The Opportunities for Adopting Inflation Targeting in Tunisia: a Cointegration Study and Transmission Channels of Monetary Policy," Transition Studies Review, Springer;Central Eastern European University Network (CEEUN), vol. 16(3), pages 671-692, October.
    29. Eric Kemp-Benedict, 2019. "Convergence of actual, warranted, and natural growth rates in a Kaleckian-Harrodian-classical model," Working Papers PKWP1913, Post Keynesian Economics Society (PKES).
    30. Guillermo Carlomagno & Jorge Fornero & Andrés Sansone, 2021. "Toward a general framework for constructing and evaluating core inflation measures," Working Papers Central Bank of Chile 913, Central Bank of Chile.
    31. Kitov, Ivan & Kitov, Oleg, 2008. "Long-term linear trends in consumer price indices," MPRA Paper 6900, University Library of Munich, Germany.
    32. Necati Tekatli, 2010. "A New Core Inflation Indicator for Turkey (Turkiye Ekonomisi Icin Yeni Bir Cekirdek Enflasyon Gostergesi)," Working Papers 1019, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    33. Ashima Goyal & Arjun Singh, 2007. "Through a Glass Darkly," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 1(2), pages 139-166, April.
    34. Virginie Traclet, 2004. "Monetary and Fiscal Policies in Canada: Some Interesting Principles for EMU?," Staff Working Papers 04-28, Bank of Canada.
    35. Heather L. R. Tierney, 2019. "Forecasting with the Nonparametric Exclusion-from-Core Inflation Persistence Model Using Real-Time Data," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 25(1), pages 39-63, February.
    36. James Ming Chen & Mobeen Ur Rehman, 2021. "A Pattern New in Every Moment: The Temporal Clustering of Markets for Crude Oil, Refined Fuels, and Other Commodities," Energies, MDPI, vol. 14(19), pages 1-58, September.
    37. Gamber, Edward N. & Smith, Julie K. & Eftimoiu, Raluca, 2015. "The dynamic relationship between core and headline inflation," Journal of Economics and Business, Elsevier, vol. 81(C), pages 38-53.
    38. Robert W. Rich & Charles Steindel, 2007. "A comparison of measures of core inflation," Economic Policy Review, Federal Reserve Bank of New York, vol. 13(Dec), pages 19-38.
    39. Colin Bermingham, 2007. "How Useful is Core Inflation for Forecasting Headline Inflation?," The Economic and Social Review, Economic and Social Studies, vol. 38(3), pages 355-377.
    40. Boss, Alfred & Dovern, Jonas & Groll, Dominik & Meier, Carsten-Patrick & van Roye, Björn & Scheide, Joachim, 2010. "Aufschwung lässt auf sich warten," Open Access Publications from Kiel Institute for the World Economy 32954, Kiel Institute for the World Economy (IfW Kiel).
    41. Hervé Le Bihan & Danilo Leiva-León & Matías Pacce, 2023. "Underlying inflation and asymetric risks," Working Papers 2319, Banco de España.
    42. Misati, Roseline Nyakerario & Munene, Olive, 2015. "Second Round Effects And Pass-Through Of Food Prices To Inflation In Kenya," International Journal of Food and Agricultural Economics (IJFAEC), Alanya Alaaddin Keykubat University, Department of Economics and Finance, vol. 3(3), pages 1-13, July.
    43. Döhrn, Roland & Barabas, György & Gebhardt, Heinz & Middendorf, Torge & Schäfer, Günter & Zimmermann, Tobias, 2008. "Die wirtschaftliche Entwicklung im Inland: Konjunktur im Zwischentief," RWI Konjunkturberichte, RWI - Leibniz-Institut für Wirtschaftsforschung, vol. 59(1), pages 31-82.
    44. Abdul Aleem & Amine Lahiani, 2011. "Estimation and evaluation of core inflation measures," Applied Economics, Taylor & Francis Journals, vol. 43(25), pages 3619-3629.

  54. Todd E. Clark, 1999. "A comparison of the CPI and the PCE price index," Economic Review, Federal Reserve Bank of Kansas City, vol. 84(Q III), pages 15-29.

    Cited by:

    1. Craig S. Hakkio, 2008. "PCE and CPI inflation differentials: converting inflation forecasts," Economic Review, Federal Reserve Bank of Kansas City, vol. 93(Q I), pages 51-68.
    2. Andrew Bauer & Nicholas Haltom & William B. Peterman, 2004. "Examining contributions to core consumer inflation measures," FRB Atlanta Working Paper 2004-7, Federal Reserve Bank of Atlanta.
    3. Andrew Bauer & Nicholas Haltom & William B. Peterman, 2004. "Decomposing inflation," Economic Review, Federal Reserve Bank of Atlanta, vol. 89(Q 1), pages 39-51.
    4. Fan Ding & Alexander L. Wolman, 2005. "Inflation and changing expenditure shares," Economic Quarterly, Federal Reserve Bank of Richmond, vol. 91(Win), pages 1-20.
    5. Emmanuel Carré, 2013. "La cible d'inflation de la Fed : continuité ou rupture ?," Post-Print hal-01419130, HAL.
    6. Andrew Ang & Geert Bekaert & Min Wei, 2005. "Do Macro Variables, Asset Markets or Surveys Forecast Inflation Better?," NBER Working Papers 11538, National Bureau of Economic Research, Inc.
    7. David Fielding & Paul Mizen, 2008. "Evidence on the Functional Relationship between Relative Price Variability and Inflation with Implications for Monetary Policy," Economica, London School of Economics and Political Science, vol. 75(300), pages 683-699, November.
    8. Christopher Kent, 2004. "Discussion of 'Inflation Measurement for Central Bankers'," RBA Annual Conference Volume (Discontinued), in: Christopher Kent & Simon Guttmann (ed.),The Future of Inflation Targeting, Reserve Bank of Australia.
    9. Binner, J.M. & Tino, P. & Tepper, J. & Anderson, R. & Jones, B. & Kendall, G., 2010. "Does money matter in inflation forecasting?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4793-4808.
    10. Hanson, Michael S., 2004. "The "price puzzle" reconsidered," Journal of Monetary Economics, Elsevier, vol. 51(7), pages 1385-1413, October.
    11. Stefano Eusepi & Bart Hobijn & Andrea Tambalotti, 2011. "CONDI: A Cost-of-Nominal-Distortions Index," American Economic Journal: Macroeconomics, American Economic Association, vol. 3(3), pages 53-91, July.
    12. Robert W. Rich & Donald Rissmiller, 2001. "Structural change in U.S. wage determination," Staff Reports 117, Federal Reserve Bank of New York.
    13. William C. Whitesell, 2005. "An inflation goal with multiple reference measures," Finance and Economics Discussion Series 2005-62, Board of Governors of the Federal Reserve System (U.S.).
    14. Roberto M. Billi & George A. Kahn, 2008. "What is the optimal inflation rate?," Economic Review, Federal Reserve Bank of Kansas City, vol. 93(Q II), pages 5-28.
    15. Ricardo Reis, 2005. "A Dynamic Measure of Inflation," NBER Working Papers 11746, National Bureau of Economic Research, Inc.

  55. Todd E. Clark, 1999. "The Responses Of Prices At Different Stages Of Production To Monetary Policy Shocks," The Review of Economics and Statistics, MIT Press, vol. 81(3), pages 420-433, August.
    See citations under working paper version above.
  56. Clark, Todd E, 1998. "Employment Fluctuations in U.S. Regions and Industries: The Roles of National, Region-Specific, and Industry-Specific Shocks," Journal of Labor Economics, University of Chicago Press, vol. 16(1), pages 202-229, January.

    Cited by:

    1. Theodore M. Crone, 2003. "An alternative definition of economic regions in the U.S. based on similarities in state business cycles," Working Papers 03-23, Federal Reserve Bank of Philadelphia.
    2. Aki Kangasharju & Sari Pekkala, 2001. "Regional Labour Market Adjustment: Are Positive and Negative Shocks Different?," ERSA conference papers ersa01p196, European Regional Science Association.
    3. 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.
    4. Shu-hen Chiang, 2009. "The effects of regional diversity on national unemployment through inter-regional migration: new evidence from Taiwan," Applied Economics, Taylor & Francis Journals, vol. 41(19), pages 2505-2511.
    5. Breandán Ó'hUallacháin, 2008. "Regional growth transition clubs in the United States," Papers in Regional Science, Wiley Blackwell, vol. 87(1), pages 33-53, March.
    6. Michael T. Owyang & David E. Rapach & Howard J. Wall, 2008. "States and the business cycle," Working Papers 2007-050, Federal Reserve Bank of St. Louis.
    7. Mejía-Reyes, Pablo & Rendón-Rojas, Liliana & Vergara-González, Reyna & Aroca, Patricio, 2018. "International synchronization of the Mexican states business cycles: Explaining factors," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 278-288.
    8. Groenwold, Nicolaas & Lee, Guoping & Chen, Anping, 2008. "Inter-regional spillovers in China: The importance of common shocks and the definition of the regions," China Economic Review, Elsevier, vol. 19(1), pages 32-52, March.
    9. Pi-Fem Hsu, 2008. "Sources of employment fluctuations in Taiwan's industries and regions," Applied Economics, Taylor & Francis Journals, vol. 40(17), pages 2279-2293.
    10. Shu-hen Chiang, 2016. "Rising residential rents in Chinese mega cities: The role of monetary policy," Urban Studies, Urban Studies Journal Limited, vol. 53(16), pages 3493-3509, December.
    11. Clark, Todd E. & van Wincoop, Eric, 2001. "Borders and business cycles," Journal of International Economics, Elsevier, vol. 55(1), pages 59-85, October.
    12. Gregory D. Hess & Kwanho Shin, 1997. "Risk sharing by households within and across regions and industries," Research Working Paper 97-07, Federal Reserve Bank of Kansas City.
    13. Guenter W. Beck & Kirstin Hubrich & Massimiliano Marcellino, 2016. "On the Importance of Sectoral and Regional Shocks for Price‐Setting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1234-1253, November.
    14. Michael T. Owyang & Jeremy Piger & Howard J. Wall, 2005. "Business Cycle Phases in U.S. States," The Review of Economics and Statistics, MIT Press, vol. 87(4), pages 604-616, November.
    15. Arabinda Basistha, 2023. "Estimation of short‐run predictive factor for US growth using state employment data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(1), pages 34-50, January.
    16. Casto Montero Kuscevic, 2014. "Okun’s law and urban spillovers in US unemployment," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 53(3), pages 719-730, November.
    17. Ron Martin & Peter Sunley & Ben Gardiner & Peter Tyler, 2016. "How Regions React to Recessions: Resilience and the Role of Economic Structure," Regional Studies, Taylor & Francis Journals, vol. 50(4), pages 561-585, April.
    18. Steven J. Davis & R. Jason Faberman & John Haltiwanger & Ron Jarmin & Javier Miranda, 2008. "Business Volatility, Job Destruction, and Unemployment," NBER Working Papers 14300, National Bureau of Economic Research, Inc.
    19. Di Caro, Paolo, 2014. "Regional recessions and recoveries in theory and practice: a resilience-based overview," MPRA Paper 60300, University Library of Munich, Germany.
    20. Del Negro, Marco, 2002. "Asymmetric shocks among U.S. states," Journal of International Economics, Elsevier, vol. 56(2), pages 273-297, March.
    21. Wall, Howard J., 2011. "The Employment Cycles of Neighboring Cities," MPRA Paper 29410, University Library of Munich, Germany.
    22. Kangasharju, Aki & Pekkala, Sari, 2002. "Adjustment to Regional Labour Market Shocks," Discussion Papers 274, VATT Institute for Economic Research.
    23. Nicolaas Groenewold & Guoping Lee & Anping Chen, 2006. "Inter-Regional Output Spillovers of Policy Shocks in China," Economics Discussion / Working Papers 06-26, The University of Western Australia, Department of Economics.
    24. Theodore M. Crone, 2004. "A redefinition of economic regions in the U.S," Working Papers 04-12, Federal Reserve Bank of Philadelphia.
    25. Glendon, Spencer P. & Vigdor, Jacob L., 2003. "Thy neighbor's jobs: geography and labor market dynamics," Regional Science and Urban Economics, Elsevier, vol. 33(6), pages 663-693, October.
    26. Owyang, Michael T. & Piger, Jeremy & Wall, Howard J., 2013. "Discordant city employment cycles," Regional Science and Urban Economics, Elsevier, vol. 43(2), pages 367-384.
    27. Carlino, Gerald A. & DeFina, Robert H., 2004. "How strong is co-movement in employment over the business cycle? Evidence from state/sector data," Journal of Urban Economics, Elsevier, vol. 55(2), pages 298-315, March.
    28. André van Stel & Martin Carree & Emilio Congregado & Antonio Golpe, 2013. "Self-employment and Job Generation in Metropolitan Areas, 1969-2009," Scales Research Reports H201306, EIM Business and Policy Research.
    29. Vasile-Aurel Caus & Daniel Badulescu & Mircea Cristian Gherman, 2017. "Using Wavelets In Economics. An Application On The Analysis Of Wage-Price Relation," Oradea Journal of Business and Economics, University of Oradea, Faculty of Economics, vol. 2(1), pages 32-42, March.
    30. Michael Anderson & Jason Bram, 2001. "Declining manufacturing employment in the New York-New Jersey region: 1969-99," Current Issues in Economics and Finance, Federal Reserve Bank of New York, vol. 7(Jan).
    31. Partridge, Mark D. & Rickman, Dan S., 1999. "Which comes first, jobs or people? An analysis of the recent stylized facts," Economics Letters, Elsevier, vol. 64(1), pages 117-123, July.
    32. Geoffrey Hewings, 2008. "On some conundra in regional science," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 42(2), pages 251-265, June.
    33. 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.
    34. Shu-hen Chiang, 2009. "The effects of industrial diversification on regional unemployment in Taiwan: is the portfolio theory applicable?," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 43(4), pages 947-962, December.
    35. 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.
    36. Nicolaas Groenewold & Lee Guoping & Chen Anping, 2007. "Regional output spillovers in China: Estimates from a VAR model," Papers in Regional Science, Wiley Blackwell, vol. 86(1), pages 101-122, March.
    37. Carlino, Gerald A. & DeFina, Robert H. & Sill, Keith, 2001. "Sectoral Shocks and Metropolitan Employment Growth," Journal of Urban Economics, Elsevier, vol. 50(3), pages 396-417, November.
    38. Carlos Lamarche & Alberto Porto & Walter Sosa Escudero, 1998. "Aspectos Regionales del Desempleo en la Argentina," IIE, Working Papers 008, IIE, Universidad Nacional de La Plata.
    39. Howley, P.; & Knight, S.;, 2018. "Taking pleasure from neighbours’ misfortune: Comparison effects, social norms and the well-being of the unemployed," Health, Econometrics and Data Group (HEDG) Working Papers 18/02, HEDG, c/o Department of Economics, University of York.
    40. Coulson, N. Edward, 1999. "Sectoral sources of metropolitan growth," Regional Science and Urban Economics, Elsevier, vol. 29(6), pages 723-743, November.
    41. Fratantoni, Michael & Schuh, Scott, 2003. "Monetary Policy, Housing, and Heterogeneous Regional Markets," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 35(4), pages 557-589, August.
    42. Chortareas, Georgios & Kapetanios, George & Ventouri, Alexia, 2016. "Credit market freedom and cost efficiency in US state banking," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 173-185.
    43. Partridge, Mark D. & Rickman, Dan S., 2003. "The waxing and waning of regional economies: the chicken-egg question of jobs versus people," Journal of Urban Economics, Elsevier, vol. 53(1), pages 76-97, January.
    44. Nath, Hiranya K., 2016. "A note on the cyclical behavior of sectoral employment in the U.S," Economic Analysis and Policy, Elsevier, vol. 50(C), pages 52-61.
    45. Dick van Dijk & Dennis Fok & Philip Hans Franses, 2005. "A multi-level panel STAR model for US manufacturing sectors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(6), pages 811-827.
    46. Vlachos, Jonas, 2005. "Does Labour Market Risk Increase the Size of the Public Sector? Evidence from Swedish Municipalities," CEPR Discussion Papers 5091, C.E.P.R. Discussion Papers.
    47. Bradley Ewing & Jamie Kruse & Mark Thompson, 2009. "Twister! Employment responses to the 3 May 1999 Oklahoma City tornado," Applied Economics, Taylor & Francis Journals, vol. 41(6), pages 691-702.
    48. Steven Cassou & Jesús Vázquez, 2014. "Employment comovements at the sectoral level over the business cycle," Empirical Economics, Springer, vol. 46(4), pages 1301-1323, June.
    49. Vidhi Chhaochharia & George M. Korniotis & Alok Kumar, 2020. "Prozac for depressed states? Effect of mood on local economic recessions," Review of Financial Economics, John Wiley & Sons, vol. 38(2), pages 245-274, April.
    50. 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.
    51. Mark D. Partridge & Dan S. Rickman, 2002. "Did The New Economy Vanquish The Regional Business Cycle?," Contemporary Economic Policy, Western Economic Association International, vol. 20(4), pages 456-469, October.
    52. Shu‐hen Chiang, 2012. "The sources of metropolitan unemployment fluctuations in the Greater Taipei metropolitan area," Papers in Regional Science, Wiley Blackwell, vol. 91(4), pages 775-793, November.
    53. XIE, Xiao-ting & LIAO, Le-huan, 2015. "云南省县域经济差异的空间分析 [A spatial analysis of the county-level differences in economic growth rates in Yunnan province]," MPRA Paper 68820, University Library of Munich, Germany, revised 20 Aug 2015.
    54. Christian L. Redfearn, 2000. "The Composition of Metropolitan Employment and the Correlation of Housing Prices Across Metropolitan Areas," Working Paper 8641, USC Lusk Center for Real Estate.
    55. Ewing, Bradley T. & Kruse, Jamie Brown & Thompson, Mark A., 2004. "Employment Dynamics and the Nashville Tornado," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 34(4), pages 1-14.
    56. Nicolaas Groenewold & Guoping Lee & Anping Chen, 2006. "Inter-Regional Output Spillovers in China: Disentangling National from Regional Shocks," Economics Discussion / Working Papers 06-25, The University of Western Australia, Department of Economics.
    57. Rafiq, M.S., 2011. "The optimality of a gulf currency union: Commonalities and idiosyncrasies," Economic Modelling, Elsevier, vol. 28(1), pages 728-740.
    58. Rafiq, M.S., 2011. "The optimality of a gulf currency union: Commonalities and idiosyncrasies," Economic Modelling, Elsevier, vol. 28(1-2), pages 728-740, January.
    59. Gerald A. Carlino, 2003. "A confluence of events? explaining fluctuations in local employment," Business Review, Federal Reserve Bank of Philadelphia, issue Q1, pages 6-12.

  57. Clark, Todd E, 1997. "Cross-country Evidence on Long-Run Growth and Inflation," Economic Inquiry, Western Economic Association International, vol. 35(1), pages 70-81, January.
    See citations under working paper version above.
  58. Clark, Todd E, 1996. "Small-Sample Properties of Estimators of Nonlinear Models of Covariance Structure," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 367-373, July.
    See citations under working paper version above.
  59. Todd E. Clark, 1995. "Do producer prices lead consumer prices?," Economic Review, Federal Reserve Bank of Kansas City, vol. 80(Q III), pages 25-39.

    Cited by:

    1. Ülke, Volkan & Ergun, Ugur, 2013. "The Relationship between Consumer Price and Producer Price Indices in Turkey," MPRA Paper 59437, University Library of Munich, Germany.
    2. Yusuf V. Topuz & Hassan Yazdifar & Sunil Sahadev, 2018. "The relation between the producer and consumer price indices: a two-country study," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 17(3), pages 122-130, June.
    3. Jing Sun & Jinhui Xu & Xin Cheng & Jichao Miao & Hairong Mu, 2023. "Dynamic causality between PPI and CPI in China: A rolling window bootstrap approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 1279-1289, April.
    4. Sidaoui José Julián & Capistrán Carlos & Chiquiar Daniel & Ramos Francia Manuel, 2009. "A Note on the Predictive Content of PPI over CPI Inflation: The Case of Mexico," Working Papers 2009-14, Banco de México.
    5. Carlos Huertas C. & Munir A. Jalil. B., 2000. "Relación Entre El Índice De Precios Del Productor (Ipp) Y El Índice De Precios Al Consumidor (Ipc)," Borradores de Economia 3449, Banco de la Republica.
    6. Xiangyun Gao & Haizhong An & Weiqiong Zhong, 2013. "Features of the Correlation Structure of Price Indices," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-9, April.
    7. Tiwari, Aviral Kumar & Suresh K.G., & Arouri, Mohamed & Teulon, Frédéric, 2014. "Causality between consumer price and producer price: Evidence from Mexico," Economic Modelling, Elsevier, vol. 36(C), pages 432-440.
    8. Niclas Andrén & Lars Oxelheim, 2011. "Exchange rate regime shift and price patterns," International Journal of Managerial Finance, Emerald Group Publishing Limited, vol. 7(2), pages 153-178, April.
    9. Muhammad, Shahbaz & Kumar, A.T.K. & Mohammad, Iqbal Tahir, 2012. "Does CPI Granger-Cause WPI? New Extensions from Frequency Domain Approach in Pakistan," MPRA Paper 38816, University Library of Munich, Germany, revised 14 May 2012.
    10. Tiwari, Aviral & Shahbaz, Muhammad, 2010. "Modelling the Relationship between Whole Sale Price and Consumer Price Indices: Cointegration and Causality Analysis for India," MPRA Paper 27333, University Library of Munich, Germany.
    11. Ivo da Rocha Lima Filho, Roberto, 2019. "Does PPI lead CPI IN Brazil?," International Journal of Production Economics, Elsevier, vol. 214(C), pages 73-79.
    12. Tiwari, Aviral Kumar, 2012. "An empirical investigation of causality between producers' price and consumers' price indices in Australia in frequency domain," Economic Modelling, Elsevier, vol. 29(5), pages 1571-1578.
    13. Tiwari, Aviral Kumar & Mutascu, Mihai & Andries, Alin Marius, 2013. "Decomposing time-frequency relationship between producer price and consumer price indices in Romania through wavelet analysis," Economic Modelling, Elsevier, vol. 31(C), pages 151-159.
    14. Ahlander, Edvin & Carlsson, Mikael & Klein, Mathias, 2023. "Price Pass-Through Along the Supply Chain:Evidence from PPI and CPI Microdata," Working Paper Series 426, Sveriges Riksbank (Central Bank of Sweden).
    15. Robert Lehmann & Timo Wollmershäuser, 2017. "Die Inflation kommt zurück! Immer mehr Firmen in Deutschland wollen ihre Preise anheben," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 70(05), pages 16-21, March.
    16. Mohd, Rafede & Masih, Mansur, 2018. "Testing the asymmetric and lead-lag relationship between CPI and PPI: an application of the ARDL and NARDL approaches," MPRA Paper 112500, University Library of Munich, Germany.
    17. George, Edward I. & Sun, Dongchu & Ni, Shawn, 2008. "Bayesian stochastic search for VAR model restrictions," Journal of Econometrics, Elsevier, vol. 142(1), pages 553-580, January.
    18. Gerba, Eddie, 2015. "Have the US macro-financial linkages changed? The balance sheet dimension," LSE Research Online Documents on Economics 59886, London School of Economics and Political Science, LSE Library.
    19. Gibson, Heather D. & Lazaretou, Sophia, 2001. "Leading inflation indicators for Greece," Economic Modelling, Elsevier, vol. 18(3), pages 325-348, August.
    20. He, Yongda & Lin, Boqiang, 2019. "Regime differences and industry heterogeneity of the volatility transmission from the energy price to the PPI," Energy, Elsevier, vol. 176(C), pages 900-916.

  60. Clark, Todd E., 1995. "Rents and prices of housing across areas of the United States. A cross-section examination of the present value model," Regional Science and Urban Economics, Elsevier, vol. 25(2), pages 237-247, April.

    Cited by:

    1. Rosés, Joan R., 2011. "Spanish housing markets during the first phase of the rural-urban transition process," IFCS - Working Papers in Economic History.WH wp11-08, Universidad Carlos III de Madrid. Instituto Figuerola.
    2. Winters, John V., 2009. "Wages and prices: Are workers fully compensated for cost of living differences?," Regional Science and Urban Economics, Elsevier, vol. 39(5), pages 632-643, September.
    3. Arthur Grimes & Andrew Aitken, 2007. "House Prices and Rents: Socio-Economic Impacts and Prospects," Working Papers 07_01, Motu Economic and Public Policy Research.
    4. Alex S. MacNevin, 1997. "Marginal Effective Tax Rates On Canadian Rental Housing Investments: an Asset Pricing Model Approach," Public Finance Review, , vol. 25(3), pages 306-326, May.
    5. Carmona, Juan & Lampe, Markus & Rosés, Joan, 2017. "Housing affordability during the urban transition in Spain," LSE Research Online Documents on Economics 68886, London School of Economics and Political Science, LSE Library.
    6. Winters, John V., 2012. "Differences in Quality of Life Estimates Using Rents and Home Values," IZA Discussion Papers 6703, Institute of Labor Economics (IZA).
    7. Rickman, Dan S. & Guettabi, Mouhcine, 2013. "The Great Recession and Nonmetropolitan America," MPRA Paper 44829, University Library of Munich, Germany.
    8. Joshua Gallin, 2008. "The Long‐Run Relationship Between House Prices and Rents," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 36(4), pages 635-658, December.
    9. Vyacheslav Mikhed & Petr Zemčík, 2009. "Testing for Bubbles in Housing Markets: A Panel Data Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 38(4), pages 366-386, May.
    10. Badi H. Baltagi & Jing Li, 2015. "Cointegration of Matched Home Purchases and Rental Price Indexes: Evidence from Singapore," Center for Policy Research Working Papers 185, Center for Policy Research, Maxwell School, Syracuse University.
    11. Gavin A. Wood & Rachel Ong, 2013. "When and Why Do Landlords Retain Property Investments?," Urban Studies, Urban Studies Journal Limited, vol. 50(16), pages 3243-3261, December.
    12. Vyacheslav Mikhed & Petr Zemcik, 2007. "Testing for Bubbles in Housing Markets: A Panel Data Approach," CERGE-EI Working Papers wp338, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    13. Ge Bao & Guoliang Feng, 2018. "Testing the Dividend Discount Model in Housing Markets: the Role of Risk," The Journal of Real Estate Finance and Economics, Springer, vol. 57(4), pages 677-701, November.
    14. Rosés, Joan R., 2012. "Housing markets during the rural-urban transition : evidence from early 20th century Spain," IFCS - Working Papers in Economic History.WH wp12-10, Universidad Carlos III de Madrid. Instituto Figuerola.
    15. Galina An & Charles Becker & Enoch Cheng, 2021. "Bubbling Away: Forecasting Real Estate Prices, Rents, and Bubbles in a Transition Economy," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 63(2), pages 263-317, June.
    16. Tsai, I-Chun & Chiang, Shu-Hen, 2019. "Exuberance and spillovers in housing markets: Evidence from first- and second-tier cities in China," Regional Science and Urban Economics, Elsevier, vol. 77(C), pages 75-86.
    17. Petr Zemcik, 2011. "Is There a Real Estate Bubble in the Czech Republic?," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 61(1), pages 49-66, January.
    18. Jung, Hosung & Lee, Jieun, 2017. "The effects of macroprudential policies on house prices: Evidence from an event study using Korean real transaction data," Journal of Financial Stability, Elsevier, vol. 31(C), pages 167-185.
    19. Joshua H. Gallin, 2004. "The long-run relationship between house prices and rents," Finance and Economics Discussion Series 2004-50, Board of Governors of the Federal Reserve System (U.S.).
    20. Rose Neng Lai & Robert A. Van Order, 2020. "A Tale of Two Countries: Comparing the US and Chinese Housing Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 61(3), pages 505-547, October.
    21. Sharpe, Jamie, 2019. "Re-evaluating the impact of immigration on the U.S. rental housing market," Journal of Urban Economics, Elsevier, vol. 111(C), pages 14-34.
    22. Waltl, Sofie R., 2018. "Estimating quantile-specific rental yields for residential housing in Sydney," Regional Science and Urban Economics, Elsevier, vol. 68(C), pages 204-225.
    23. Petr Zemcik, 2009. "Housing Markets in Central and Eastern Europe: Is There a Bubble in the Czech Republic?," CERGE-EI Working Papers wp390, The Center for Economic Research and Graduate Education - Economics Institute, Prague.

  61. Todd E. Clark, 1994. "Nominal GDP targeting rules: can they stabilize the economy?," Economic Review, Federal Reserve Bank of Kansas City, vol. 79(Q III), pages 11-25.

    Cited by:

    1. Fair, Ray C. & Howrey, E. Philip, 1996. "Evaluating alternative monetary policy rules," Journal of Monetary Economics, Elsevier, vol. 38(2), pages 173-193, October.
    2. Billi, Roberto M., 2012. "Output Gaps and Robust Monetary Policy Rules," Working Paper Series 260, Sveriges Riksbank (Central Bank of Sweden).
    3. Veetil, Vipin P. & Wagner, Richard E., 2018. "Nominal GDP stabilization: Chasing a mirage," The Quarterly Review of Economics and Finance, Elsevier, vol. 67(C), pages 227-236.
    4. Ray Fair, 2001. "Optimal Control and Stochastic Simulation of Large Nonlinear Models with Rational Expectations," Yale School of Management Working Papers ysm202, Yale School of Management, revised 24 Sep 2001.
    5. Ray C. Fair, 2001. "Actual Federal Reserve policy behavior and interest rate rules," Economic Policy Review, Federal Reserve Bank of New York, issue Mar, pages 61-72.
    6. Bilal Bagis, 2017. "Central Banking in the New Era," Eurasian Journal of Economics and Finance, Eurasian Publications, vol. 5(4), pages 197-225.
    7. Thornton, Saranna Robinson, 2000. "How do broader monetary aggregates and divisia measures of money perform in McCallum's adaptive monetary rule?," Journal of Economics and Business, Elsevier, vol. 52(1-2), pages 181-204.
    8. Thornton, Saranna R., 1998. "Suitable policy instruments for monetary rules," Journal of Economics and Business, Elsevier, vol. 50(4), pages 379-397, July.
    9. Ray C. Fair, 2000. "Estimated, Calibrated, and Optimal Interest Rate Rules," Cowles Foundation Discussion Papers 1258, Cowles Foundation for Research in Economics, Yale University.

Chapters

  1. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
    See citations under working paper version above.Sorry, no citations of chapters recorded.
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