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James Mitchell

Not to be confused with: James L. Mitchell

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. Galvao, Ana Beatriz & Mitchell, James, 2020. "Real-Time Perceptions of Historical GDP Data Uncertainty," EMF Research Papers 35, Economic Modelling and Forecasting Group.

    Mentioned in:

    1. Density Forecasts and Density Realizations
      by Francis Diebold in No Hesitations on 2020-08-10 18:53:00
  2. Ida Wolden Bache & Anne Sofie Jore & James Mitchell & Shaun P. Vahey, 2009. "Combining VAR and DSGE forecast densities," Working Paper 2009/23, Norges Bank.

    Mentioned in:

    1. DSGE models and forecasting
      by Christian Zimmermann in NEP-DGE blog on 2009-12-21 06:35:25

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. James Mitchell & Kenneth F. Wallis, 2011. "Evaluating density forecasts: forecast combinations, model mixtures, calibration and sharpness," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(6), pages 1023-1040, September.

    Mentioned in:

    1. Evaluating density forecasts: forecast combinations, model mixtures, calibration and sharpness (Journal of Applied Econometrics 2011) in ReplicationWiki ()
  2. Anne Sofie Jore & James Mitchell & Shaun P. Vahey, 2010. "Combining forecast densities from VARs with uncertain instabilities," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 621-634.

    Mentioned in:

    1. Combining forecast densities from VARs with uncertain instabilities (Journal of Applied Econometrics 2010) in ReplicationWiki ()

Working papers

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

    Cited by:

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

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

    Cited by:

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

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

    Cited by:

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

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

    Cited by:

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

  5. Galvão, Ana Beatriz & Mitchell, James, 2021. "Communicating Data Uncertainty: Multi-Wave Experimental Evidence for U.K. GDP," CEPR Discussion Papers 16417, C.E.P.R. Discussion Papers.

    Cited by:

    1. Johnny Runge, 2021. "Communicating Data Uncertainty on GDP and Unemployment: Interviews with the UK Public," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2021-07, Economic Statistics Centre of Excellence (ESCoE).

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

    Cited by:

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

  7. Galvao, Ana Beatriz & Garratt, Anthony & Mitchell, James, 2020. "Does Judgment Improve Macroeconomic Density Forecasts?," EMF Research Papers 33, Economic Modelling and Forecasting Group.

    Cited by:

    1. Bańbura, Marta & Leiva-Leon, Danilo & Menz, Jan-Oliver, 2021. "Do inflation expectations improve model-based inflation forecasts?," Working Paper Series 2604, European Central Bank.
    2. 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.
    3. 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.
    4. Yongchen Zhao, 2023. "Uncertainty of Household Inflation Expectations: Reconciling Point and Density Forecasts," Working Papers 2023-09, Towson University, Department of Economics, revised Dec 2023.

  8. Mitchell, James & Weale, Martin, 2019. "Forecasting with Unknown Unknowns: Censoring and Fat Tails on the Bank of England's Monetary Policy Committee," EMF Research Papers 27, Economic Modelling and Forecasting Group.

    Cited by:

    1. 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.
    2. Carola Conces Binder & Rodrigo Sekkel, 2023. "Central Bank Forecasting: A Survey," Staff Working Papers 23-18, Bank of Canada.
    3. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2020. "Capturing Macroeconomic Tail Risks with Bayesian Vector Autoregressions," Working Papers 20-02R, Federal Reserve Bank of Cleveland, revised 22 Sep 2020.
    4. 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.
    5. Rossi, Barbara & Ganics, Gergely & Sekhposyan, Tatevik, 2020. "From Fixed-event to Fixed-horizon Density Forecasts: Obtaining Measures of Multi-horizon Uncertainty from Survey Density Foreca," CEPR Discussion Papers 14267, C.E.P.R. Discussion Papers.
    6. Ryan Rholes & Luba Petersen, 2020. "Should central banks communicate uncertainty in their projections?," Discussion Papers dp20-01, Department of Economics, Simon Fraser University.

  9. Ana Beatriz Galvão & James Mitchell & Johnny Runge, 2019. "Communicating Data Uncertainty: Experimental Evidence for U.K. GDP," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2019-20, Economic Statistics Centre of Excellence (ESCoE).

    Cited by:

    1. 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.
    2. Ana Beatriz Galvão & James Mitchell, 2023. "Real‐Time Perceptions of Historical GDP Data Uncertainty," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 457-481, June.
    3. Johnny Runge & Nathan Hudson-Sharp, 2020. "Public Understanding of Economics and Economic Statistics," Economic Statistics Centre of Excellence (ESCoE) Occasional Papers ESCOE-OP-03, Economic Statistics Centre of Excellence (ESCoE).
    4. Mazzi Gian Luigi & Mitchell James & Carausu Florabela, 2021. "Measuring and Communicating the Uncertainty in Official Economic Statistics," Journal of Official Statistics, Sciendo, vol. 37(2), pages 289-316, June.

  10. Ana Beatriz Galvão & James Mitchell, 2019. "Measuring Data Uncertainty: An Application using the Bank of England's "Fan Charts" for Historical GDP Growth," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2019-08, Economic Statistics Centre of Excellence (ESCoE).

    Cited by:

    1. Knüppel, Malte & Krüger, Fabian & Pohle, Marc-Oliver, 2022. "Score-based calibration testing for multivariate forecast distributions," Discussion Papers 50/2022, Deutsche Bundesbank.
    2. Barbara Rossi, 2019. "Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them," Economics Working Papers 1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
    3. Nikoleta Anesti & Ana Beatriz Galvão & Silvia Miranda‐Agrippino, 2022. "Uncertain Kingdom: Nowcasting Gross Domestic Product and its revisions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 42-62, January.
    4. Joshy Easaw & Christian Grimme, 2021. "The Impact of Aggregate Uncertainty on Firm-Level Uncertainty," CESifo Working Paper Series 8934, CESifo.

  11. van der Bles, Anne Marthe & van der Liden, Sander & Freeman, Alessandra L. J. & Mitchell, James & Galvao, Ana Beatriz & Spiegelhalter, David J., 2019. "Communicating uncertainty about facts, numbers, and science," EMF Research Papers 22, Economic Modelling and Forecasting Group.

    Cited by:

    1. Carol Nash, 2021. "Challenges to Learners in Interpreting Self as Other, Post COVID-19," Challenges, MDPI, vol. 12(2), pages 1-24, November.
    2. Teigen, Karl Halvor & Juanchich, Marie & Løhre, Erik, 2022. "What is a “likely” amount? Representative (modal) values are considered likely even when their probabilities are low," Organizational Behavior and Human Decision Processes, Elsevier, vol. 171(C).
    3. Ana Beatriz Galvão & James Mitchell, 2019. "Measuring Data Uncertainty: An Application using the Bank of England's "Fan Charts" for Historical GDP Growth," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2019-08, Economic Statistics Centre of Excellence (ESCoE).
    4. Galvao, Ana Beatriz & Mitchell, James & Runge, Johnny, 2019. "Communicating Data Uncertainty: Experimental Evidence for U.K. GDP," EMF Research Papers 30, Economic Modelling and Forecasting Group.
    5. Ana Beatriz Galvão & James Mitchell, 2023. "Real‐Time Perceptions of Historical GDP Data Uncertainty," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 457-481, June.
    6. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    7. Friederike Hendriks & Regina Jucks, 2020. "Does Scientific Uncertainty in News Articles Affect Readers’ Trust and Decision-Making?," Media and Communication, Cogitatio Press, vol. 8(2), pages 401-412.
    8. Robin Gregory & Theresa Satterfield & David R. Boyd, 2020. "People, Pipelines, and Probabilities: Clarifying Significance and Uncertainty in Environmental Impact Assessments," Risk Analysis, John Wiley & Sons, vol. 40(2), pages 218-226, February.
    9. Schils, René L.M. & van Voorn, George A.K. & Grassini, Patricio & van Ittersum, Martin K., 2022. "Uncertainty is more than a number or colour: Involving experts in uncertainty assessments of yield gaps," Agricultural Systems, Elsevier, vol. 195(C).
    10. Dominic Balog‐Way & Katherine McComas & John Besley, 2020. "The Evolving Field of Risk Communication," Risk Analysis, John Wiley & Sons, vol. 40(S1), pages 2240-2262, November.
    11. Aljoscha Minnich & Hauke Roggenkamp & Andreas Lange, 2023. "Ambiguity Attitudes and Surprises: Experimental Evidence on Communicating New Information within a Large Population Sample," CESifo Working Paper Series 10783, CESifo.
    12. Bholat, David & Broughton, Nida & Ter Meer, Janna & Walczak, Eryk, 2019. "Enhancing central bank communications using simple and relatable information," Journal of Monetary Economics, Elsevier, vol. 108(C), pages 1-15.
    13. Liliana Cori & Olivia Curzio & Gabriele Donzelli & Elisa Bustaffa & Fabrizio Bianchi, 2022. "A Systematic Review of Radon Risk Perception, Awareness, and Knowledge: Risk Communication Options," Sustainability, MDPI, vol. 14(17), pages 1-27, August.

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

    Cited by:

    1. Huber, Florian & Koop, Gary & Onorante, Luca & Pfarrhofer, Michael & Schreiner, Josef, 2023. "Nowcasting in a pandemic using non-parametric mixed frequency VARs," Journal of Econometrics, Elsevier, vol. 232(1), pages 52-69.
    2. Meredith M. Paker, 2020. "The Jobless Recovery After the 1980-1981 UK Recession," Oxford Economic and Social History Working Papers _182, University of Oxford, Department of Economics.
    3. 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.
    4. Tony Chernis & Calista Cheung & Gabriella Velasco, 2017. "A Three-Frequency Dynamic Factor Model for Nowcasting Canadian Provincial GDP Growth," Discussion Papers 17-8, Bank of Canada.
    5. Sensier, Marianne & Devine, Fiona, 2020. "Understanding Regional Economic Performance And Resilience In The Uk: Trends Since The Global Financial Crisis," National Institute Economic Review, National Institute of Economic and Social Research, vol. 253, pages 18-28, August.
    6. Deborah Gefang & Gary Koop & Aubrey Poon, 2020. "Computationally Efficient Inference in Large Bayesian Mixed Frequency VARs," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2020-07, Economic Statistics Centre of Excellence (ESCoE).
    7. María Gil & Danilo Leiva-Leon & Javier J. Pérez & Alberto Urtasun, 2019. "An application of dynamic factor models to nowcast regional economic activity in Spain," Occasional Papers 1904, Banco de España.
    8. Luke Mosley & Idris A. Eckley & Alex Gibberd, 2022. "Sparse temporal disaggregation," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 2203-2233, October.
    9. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2020. "Regional output growth in the United Kingdom: More timely and higher frequency estimates from 1970," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(2), pages 176-197, March.
    10. Luke Mosley & Idris Eckley & Alex Gibberd, 2021. "Sparse Temporal Disaggregation," Papers 2108.05783, arXiv.org, revised Oct 2022.

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

    Cited by:

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

  14. 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.

    Cited by:

    1. Li, Li & Kang, Yanfei & Li, Feng, 2023. "Bayesian forecast combination using time-varying features," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1287-1302.
    2. Barbara Rossi, 2019. "Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them," Economics Working Papers 1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
    3. Nalan Basturk & Agnieszka Borowska & Stefano Grassi & Lennart Hoogerheide & Herman K. van Dijk, 2018. "Forecast Density Combinations of Dynamic Models and Data Driven Portfolio Strategies," Working Paper 2018/10, Norges Bank.
    4. 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.
    5. 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.
    6. Michael K. Adjemian & Valentina G. Bruno & Michel A. Robe, 2020. "Incorporating Uncertainty into USDA Commodity Price Forecasts," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(2), pages 696-712, March.
    7. Kenichiro McAlinn & Kosaku Takanashi, 2019. "Mean-shift least squares model averaging," Papers 1912.01194, arXiv.org.
    8. Yuru Sun & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Gael M. Martin, 2023. "Optimal probabilistic forecasts for risk management," Papers 2303.01651, arXiv.org.
    9. David Kohns & Tibor Szendrei, 2020. "Horseshoe Prior Bayesian Quantile Regression," Papers 2006.07655, arXiv.org, revised Mar 2021.
    10. Roberto Casarin & Stefano Grassi & Francesco Ravazzollo & Herman K. van Dijk, 2019. "Forecast Density Combinations with Dynamic Learning for Large Data Sets in Economics and Finance," Tinbergen Institute Discussion Papers 19-025/III, Tinbergen Institute.
    11. 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.
    12. K=osaku Takanashi & Kenichiro McAlinn, 2019. "Equivariant online predictions of non-stationary time series," Papers 1911.08662, arXiv.org, revised Jun 2023.

  15. Stephen Wright & James Mitchell & Donald Robertson, 2018. "R2 bounds for predictive models: what univariate properties tell us about multivariate predictability," Birkbeck Working Papers in Economics and Finance 1804, Birkbeck, Department of Economics, Mathematics & Statistics.

    Cited by:

    1. Ana Beatriz Galvão & James Mitchell, 2019. "Measuring Data Uncertainty: An Application using the Bank of England's "Fan Charts" for Historical GDP Growth," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2019-08, Economic Statistics Centre of Excellence (ESCoE).
    2. Ana Beatriz Galvão & James Mitchell, 2023. "Real‐Time Perceptions of Historical GDP Data Uncertainty," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 457-481, June.
    3. Mihaela-Eugenia VASILACHE, 2018. "Forecasting the Trend of Art Market," Computational Methods in Social Sciences (CMSS), "Nicolae Titulescu" University of Bucharest, Faculty of Economic Sciences, vol. 6(1), pages 82-93, June.
    4. 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.
    5. Tommaso Proietti, 2021. "Predictability, real time estimation, and the formulation of unobserved components models," Econometric Reviews, Taylor & Francis Journals, vol. 40(5), pages 433-454, April.
    6. Julien Champagne & Guillaume Poulin‐Bellisle & Rodrigo Sekkel, 2020. "Introducing the Bank of Canada staff economic projections database," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 114-129, January.

  16. Fawcett, Nicholas & Kapetanios, George & Mitchell, James & Price, Simon, 2014. "Generalised density forecast combinations," Bank of England working papers 492, Bank of England.

    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. Li, Li & Kang, Yanfei & Li, Feng, 2023. "Bayesian forecast combination using time-varying features," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1287-1302.
    3. Pauwels, Laurent & Radchenko, Peter & Vasnev, Andrey, 2019. "Higher Moment Constraints for Predictive Density Combinations," Working Papers BAWP-2019-01, University of Sydney Business School, Discipline of Business Analytics.
    4. Emilio Zanetti Chini, 2018. "Forecaster’s utility and forecasts coherence," CREATES Research Papers 2018-01, Department of Economics and Business Economics, Aarhus University.
    5. Florian Eckert & Rob J Hyndman & Anastasios Panagiotelis, 2019. "Forecasting Swiss Exports Using Bayesian Forecast Reconciliation," Monash Econometrics and Business Statistics Working Papers 14/19, Monash University, Department of Econometrics and Business Statistics.
    6. Deak, S. & Levine, P. & Mirza, A. & Pearlman, J., 2019. "Designing Robust Monetary Policy Using Prediction Pools," Working Papers 19/11, Department of Economics, City University London.
    7. Roberto Casarin & Fabrizio Leisen & German Molina & Enrique Ter Horst, 2014. "A Bayesian Beta Markov Random Field calibration of the term structure of implied risk neutral densities," Working Papers 2014:22, Department of Economics, University of Venice "Ca' Foscari".
    8. Davide Pettenuzzo & Francesco Ravazzolo, 2014. "Optimal portfolio choice under decision-based model combinations," Working Paper 2014/15, Norges Bank.
    9. Ruben Loaiza‐Maya & Gael M. Martin & David T. Frazier, 2021. "Focused Bayesian prediction," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 517-543, August.
    10. Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2019. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Working Paper 2019/2, Norges Bank.
    11. Yi-Ting Chen & Chu-An Liu, 2021. "Model Averaging for Asymptotically Optimal Combined Forecasts," IEAS Working Paper : academic research 21-A002, Institute of Economics, Academia Sinica, Taipei, Taiwan.
    12. Marco Del Negro & Raiden B. Hasegawa & Frank Schorfheide, 2014. "Dynamic Prediction Pools: An Investigation of Financial Frictions and Forecasting Performance," PIER Working Paper Archive 14-034, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    13. 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.
    14. Gael M. Martin & Rub'en Loaiza-Maya & David T. Frazier & Worapree Maneesoonthorn & Andr'es Ram'irez Hassan, 2020. "Optimal probabilistic forecasts: When do they work?," Papers 2009.09592, arXiv.org.
    15. Steel, Mark F. J., 2017. "Model Averaging and its Use in Economics," MPRA Paper 90110, University Library of Munich, Germany, revised 16 Nov 2018.
    16. Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2015. "Bayesian nonparametric calibration and combination of predictive distributions," Working Paper 2015/03, Norges Bank.
    17. Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2021. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates," Working Papers 21-06, Federal Reserve Bank of Philadelphia.
    18. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    19. Jin, Xin & Maheu, John M. & Yang, Qiao, 2022. "Infinite Markov pooling of predictive distributions," Journal of Econometrics, Elsevier, vol. 228(2), pages 302-321.
    20. Taylor, James W. & Jeon, Jooyoung, 2018. "Probabilistic forecasting of wave height for offshore wind turbine maintenance," European Journal of Operational Research, Elsevier, vol. 267(3), pages 877-890.
    21. Roberto Casarin & Giulia Mantoan & Francesco Ravazzolo, 2016. "Bayesian Calibration of Generalized Pools of Predictive Distributions," Econometrics, MDPI, vol. 4(1), pages 1-24, March.
    22. Roberto Casarin & Fausto Corradin & Francesco Ravazzolo & Domenico Sartore, 2018. "A scoring rule for factor and autoregressive models under misspecification," Working Papers 2018:18, Department of Economics, University of Venice "Ca' Foscari".
    23. McAlinn, Kenichiro & West, Mike, 2019. "Dynamic Bayesian predictive synthesis in time series forecasting," Journal of Econometrics, Elsevier, vol. 210(1), pages 155-169.
    24. 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".
    25. Daniele Bianchi & Kenichiro McAlinn, 2018. "Large-Scale Dynamic Predictive Regressions," Papers 1803.06738, arXiv.org.
    26. Hasumi, Ryo & Iiboshi, Hirokuni & Matsumae, Tatsuyoshi & Nakamura, Daisuke, 2019. "Does a financial accelerator improve forecasts during financial crises? Evidence from Japan with prediction-pooling methods," Journal of Asian Economics, Elsevier, vol. 60(C), pages 45-68.
    27. Kenichiro McAlinn & Kosaku Takanashi, 2019. "Mean-shift least squares model averaging," Papers 1912.01194, arXiv.org.
    28. Pauwels, Laurent L. & Vasnev, Andrey L., 2016. "A note on the estimation of optimal weights for density forecast combinations," International Journal of Forecasting, Elsevier, vol. 32(2), pages 391-397.
    29. 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.
    30. Fabio Busetti, 2017. "Quantile Aggregation of Density Forecasts," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(4), pages 495-512, August.
    31. Lan Bai & Xiafei Li & Yu Wei & Guiwu Wei, 2022. "Does crude oil futures price really help to predict spot oil price? New evidence from density forecasting," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3694-3712, July.
    32. 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.
    33. Wang, Xiaoqian & Hyndman, Rob J. & Li, Feng & Kang, Yanfei, 2023. "Forecast combinations: An over 50-year review," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1518-1547.
    34. 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.
    35. K=osaku Takanashi & Kenichiro McAlinn, 2019. "Equivariant online predictions of non-stationary time series," Papers 1911.08662, arXiv.org, revised Jun 2023.
    36. Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2019. "Density Forecasting," BEMPS - Bozen Economics & Management Paper Series BEMPS59, Faculty of Economics and Management at the Free University of Bozen.
    37. McAdam, Peter & Warne, Anders, 2020. "Density forecast combinations: the real-time dimension," Working Paper Series 2378, European Central Bank.

  17. 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.

    Cited by:

    1. Kenny, Geoff & Kostka, Thomas & Masera, Federico, 2014. "Density characteristics and density forecast performance: a panel analysis," Working Paper Series 1679, European Central Bank.
    2. Lan Bai & Xiafei Li & Yu Wei & Guiwu Wei, 2022. "Does crude oil futures price really help to predict spot oil price? New evidence from density forecasting," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3694-3712, July.
    3. 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.

  18. Mitchell, James, 2013. "The Recalibrated and Copula Opinion Pools," EMF Research Papers 02, Economic Modelling and Forecasting Group.

    Cited by:

    1. Jared A. Beekman & Ronald F. A. Woodaman & Dennis M. Buede, 2020. "A Review of Probabilistic Opinion Pooling Algorithms with Application to Insider Threat Detection," Decision Analysis, INFORMS, vol. 17(1), pages 39-55, March.
    2. 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.

  19. James Mitchell & George Kapetanios & Yongcheol Shin, 2012. "A Nonlinear Panel Data Model of Cross-Sectional Dependence," Discussion Papers in Economics 12/01, Division of Economics, School of Business, University of Leicester.

    Cited by:

    1. Rafiq, Shuddhasattwa & Salim, Ruhul & Nielsen, Ingrid, 2016. "Urbanization, openness, emissions, and energy intensity: A study of increasingly urbanized emerging economies," Energy Economics, Elsevier, vol. 56(C), pages 20-28.
    2. Frohm, Erik & Gunnella, Vanessa, 2017. "Sectoral interlinkages in global value chains: spillovers and network effects," Working Paper Series 2064, European Central Bank.
    3. Hacioglu Hoke, Sinem & Kapetanios, George, 2017. "Common correlated effect cross-sectional dependence corrections for non-linear conditional mean panel models," Bank of England working papers 683, Bank of England.
    4. Shuddhasattwa Rafiq & Ruhul Salim & Pasquale M Sgro, 2018. "Energy, unemployment and trade," Applied Economics, Taylor & Francis Journals, vol. 50(47), pages 5122-5134, October.
    5. Erik Frohm & Vanessa Gunnella, 2021. "Spillovers in global production networks," Review of International Economics, Wiley Blackwell, vol. 29(3), pages 663-680, August.
    6. Orea, Luis & Álvarez, Inmaculada C., 2017. "A new stochastic frontier model with cross-sectional effects in both noise and inefficiency terms," Efficiency Series Papers 2017/04, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    7. Rossi, Francesca & Lieberman, Offer, 2023. "Spatial autoregressions with an extended parameter space and similarity-based weights," Journal of Econometrics, Elsevier, vol. 235(2), pages 1770-1798.
    8. Coe, Patrick J & Vahey, Shaun P., 2014. "Probablistic Prediction of the US Great Recession with Historical Expert," EMF Research Papers 06, Economic Modelling and Forecasting Group.
    9. Christis Katsouris, 2023. "Estimation and Inference in Threshold Predictive Regression Models with Locally Explosive Regressors," Papers 2305.00860, arXiv.org, revised May 2023.
    10. Fawcett, Nicholas & Kapetanios, George & Mitchell, James & Price, Simon, 2014. "Generalised density forecast combinations," Bank of England working papers 492, Bank of England.
    11. Eunju Hwang & Dong Wan Shin, 2017. "Stationary bootstrapping for common mean change detection in cross-sectionally dependent panels," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 80(6), pages 767-787, November.
    12. Saptorshee Kanto Chakraborty & Massimiliano Mazzanti, 2021. "Renewable Electricity and Economic Growth relationship in the long run: panel data econometric evidence from the OECD," SEEDS Working Papers 0421, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Apr 2021.
    13. Sinem Hacıoğlu Hoke & George Kapetanios, 2021. "Common correlated effect cross‐sectional dependence corrections for nonlinear conditional mean panel models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(1), pages 125-150, January.
    14. Yang, Qin & Du, Qiang & Razzaq, Asif & Shang, Yunfeng, 2022. "How volatility in green financing, clean energy, and green economic practices derive sustainable performance through ESG indicators? A sectoral study of G7 countries," Resources Policy, Elsevier, vol. 75(C).
    15. Efthymios G. Tsionas & Panayotis G. Michaelides, 2016. "A Spatial Stochastic Frontier Model with Spillovers: Evidence for Italian Regions," Scottish Journal of Political Economy, Scottish Economic Society, vol. 63(3), pages 243-257, July.
    16. Gunnella, Vanessa & Al-Haschimi, Alexander & Benkovskis, Konstantins & Chiacchio, Francesco & de Soyres, François & Di Lupidio, Benedetta & Fidora, Michael & Franco-Bedoya, Sebastian & Frohm, Erik & G, 2019. "The impact of global value chains on the euro area economy," Occasional Paper Series 221, European Central Bank.
    17. Munzel, Andreas, 2016. "Assisting consumers in detecting fake reviews: The role of identity information disclosure and consensus," Journal of Retailing and Consumer Services, Elsevier, vol. 32(C), pages 96-108.
    18. Tong, Howell, 2015. "Threshold models in time series analysis—Some reflections," Journal of Econometrics, Elsevier, vol. 189(2), pages 485-491.
    19. Rafiq, Shuddhasattwa & Salim, Ruhul & Apergis, Nicholas, 2016. "Agriculture, trade openness and emissions: an empirical analysis and policy options," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 60(2), April.

  20. James Mitchell & Richard J. Smith & Martin R. Weale, 2011. "Efficient Aggregation of Panel Qualitative Survey Data," Discussion Papers in Economics 11/53, Division of Economics, School of Business, University of Leicester.

    Cited by:

    1. Kevin Lee & Michael Mahony & Paul Mizen, 2020. "The CBI Suite of Business Surveys," Economic Statistics Centre of Excellence (ESCoE) Technical Reports ESCOE-TR-08, Economic Statistics Centre of Excellence (ESCoE).
    2. Fornaro, Paolo, 2016. "Predicting Finnish economic activity using firm-level data," International Journal of Forecasting, Elsevier, vol. 32(1), pages 10-19.
    3. Alex Botsis & Kevin Lee, 2022. "Nowcasting Using Firm-Level Survey Data; Tracking UK Output Fluctuations and Recessionary Events," Economic Statistics Centre of Excellence (ESCoE) Technical Reports ESCOE-TR-20, Economic Statistics Centre of Excellence (ESCoE).

  21. Mitchell, J. & Solomou, S. & Weale, M., 2011. "Monthly GDP Estimates for Inter-War Britain," Cambridge Working Papers in Economics 1155, Faculty of Economics, University of Cambridge.

    Cited by:

    1. James Foreman-Peck, 2014. "Great recessions compared," Investigaciones de Historia Económica - Economic History Research (IHE-EHR), Journal of the Spanish Economic History Association, Asociación Española de Historia Económica, vol. 10(02), pages 92-103.
    2. Crafts, Nicholas & Mills, Terence, 2013. "Rearmament to the Rescue? New Estimates of the Impact of ‘Keynesian’ Policies in 1930s’ Britain," The Warwick Economics Research Paper Series (TWERPS) 1018, University of Warwick, Department of Economics.
    3. Crafts, Nicholas & Mills, Terence C, 2012. "Fiscal Policy in a Depressed Economy: Was There a ‘Free Lunch’ in 1930s’ Britain?," CAGE Online Working Paper Series 106, Competitive Advantage in the Global Economy (CAGE).
    4. Nicholas Crafts, 2014. "What Does the 1930s' Experience Tell Us about the Future of the Eurozone?," Journal of Common Market Studies, Wiley Blackwell, vol. 52(4), pages 713-727, July.
    5. Albers, Thilo Nils Hendrik, 2018. "The prelude and global impact of the Great Depression: Evidence from a new macroeconomic dataset," Explorations in Economic History, Elsevier, vol. 70(C), pages 150-163.
    6. James Cloyne & Nicholas Dimsdale & Natacha Postel-Vinay, 2018. "Taxes and Growth: New Narrative Evidence from Interwar Britain," NBER Working Papers 24659, National Bureau of Economic Research, Inc.
    7. Albers, Thilo & Uebele, Martin, 2015. "The global impact of the great depression," LSE Research Online Documents on Economics 64491, London School of Economics and Political Science, LSE Library.
    8. Ruttachai Seelajaroen & Pornanong Budsaratragoon & Boonlert Jitmaneeroj, 2020. "Do monetary policy transparency and central bank communication reduce interest rate disagreement?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 368-393, April.
    9. Ronicle, David, 2022. "Turning in the widening gyre: monetary and fiscal policy in interwar Britain," Bank of England working papers 968, Bank of England.
    10. Bosupeng, Mpho, 2015. "Exports Multiplicity and The Dutch Disease," MPRA Paper 77919, University Library of Munich, Germany, revised 2015.
    11. Karau, Sören, 2020. "Buried in the vaults of central banks: Monetary gold hoarding and the slide into the Great Depression," Discussion Papers 63/2020, Deutsche Bundesbank.

  22. Anthony Garratt & James Mitchell & Shaun P. Vahey, 2011. "Measuring Output Gap Nowcast Uncertainty," CAMA Working Papers 2011-16, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

    Cited by:

    1. Buncic, Daniel & Müller, Oliver, 2017. "Measuring the output gap in Switzerland with linear opinion pools," Economic Modelling, Elsevier, vol. 64(C), pages 153-171.
    2. Florian Eckert & Nina Mühlebach, 2021. "Global and Local Components of Output Gaps," KOF Working papers 21-497, KOF Swiss Economic Institute, ETH Zurich.
    3. Yu-Fan Huang & Sui Luo, 2018. "Potential output and inflation dynamics after the Great Recession," Empirical Economics, Springer, vol. 55(2), pages 495-517, September.
    4. Berger, Tino & Morley, James & Wong, Benjamin, 2023. "Nowcasting the output gap," Journal of Econometrics, Elsevier, vol. 232(1), pages 18-34.
      • 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.
    5. António Rua & Miguel de Carvalho, 2014. "Real-time nowcasting the US output gap: Singular spectrum analysis at work," Working Papers w201416, Banco de Portugal, Economics and Research Department.
    6. 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.
    7. Lenza, Michele & Jarociński, Marek, 2016. "An inflation-predicting measure of the output gap in the euro area," Working Paper Series 1966, European Central Bank.
    8. Tommaso Proietti & Martyna Marczak & Gianluigi Mazzi, 2015. "EuroMInd-D: A Density Estimate of Monthly Gross Domestic Product for the Euro Area," CEIS Research Paper 340, Tor Vergata University, CEIS, revised 10 Apr 2015.
    9. Anthony Garratt & Timo Henckel & Shaun P. Vahey, 2019. "Empirically-transformed linear opinion pools," CAMA Working Papers 2019-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    10. 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.
    11. 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.
    12. Bańbura, Marta & Bobeica, Elena, 2023. "Does the Phillips curve help to forecast euro area inflation?," International Journal of Forecasting, Elsevier, vol. 39(1), pages 364-390.
    13. James Morley & Benjamin Wong, 2017. "Estimating and accounting for the output gap with large Bayesian vector autoregressions," CAMA Working Papers 2017-46, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    14. Chalmovianský, Jakub & Němec, Daniel, 2022. "Assessing uncertainty of output gap estimates: Evidence from Visegrad countries," Economic Modelling, Elsevier, vol. 116(C).
    15. Travis J. Berge, 2023. "Time-Varying Uncertainty of the Federal Reserve's Output Gap Estimate," The Review of Economics and Statistics, MIT Press, vol. 105(5), pages 1191-1206, September.
    16. 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.
    17. James Morley, 2019. "The business cycle: periodic pandemic or rollercoaster ride?," International Journal of Economic Policy Studies, Springer, vol. 13(2), pages 425-431, August.
    18. Florian Eckert & Nina Mühlebach, 2023. "Global and local components of output gaps," Empirical Economics, Springer, vol. 65(5), pages 2301-2331, November.

  23. Dr Silvia Lui & Dr Martin Weale & Dr. James Mitchell, 2009. "The utility of expectational data: Firm-level evidence using matched qualitative-quantitative UK surveys," National Institute of Economic and Social Research (NIESR) Discussion Papers 343, National Institute of Economic and Social Research.

    Cited by:

    1. Boneva, Lena & Cloyne, James & Weale, Martin & Wieladek, Tomasz, 2018. "Firms' Expectations of New Orders, Employment, Costs and Prices: Evidence from Micro Data," CEPR Discussion Papers 12722, C.E.P.R. Discussion Papers.
    2. Puah, Chin-Hong & Wong, Shirly Siew-Ling & Habibullah, Muzafar Shah, 2012. "Rationality of business operational forecasts: evidence from Malaysian distributive trade sector," MPRA Paper 37599, University Library of Munich, Germany.
    3. Lahiri, Kajal & Zhao, Yongchen, 2015. "Quantifying survey expectations: A critical review and generalization of the Carlson–Parkin method," International Journal of Forecasting, Elsevier, vol. 31(1), pages 51-62.
    4. Kevin Lee & Michael Mahony & Paul Mizen, 2020. "The CBI Suite of Business Surveys," Economic Statistics Centre of Excellence (ESCoE) Technical Reports ESCOE-TR-08, Economic Statistics Centre of Excellence (ESCoE).
    5. Lena Boneva & James Cloyne & Martin Weale & Tomasz Wieladek, 2020. "Firms' Price, Cost and Activity Expectations: Evidence from Micro Data," The Economic Journal, Royal Economic Society, vol. 130(627), pages 555-586.
    6. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“Tracking economic growth by evolving expectations via genetic programming: A two-step approach”," IREA Working Papers 201801, University of Barcelona, Research Institute of Applied Economics, revised Jan 2018.
    7. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "A Data-Driven Approach to Construct Survey-Based Indicators by Means of Evolutionary Algorithms," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 135(1), pages 1-14, January.
    8. Abhiman Das & Kajal Lahiri & Yongchen Zhao, 2018. "Inflation Expectations in India: Learning from Household Tendency Surveys," Working Papers 2018-03, Towson University, Department of Economics, revised Aug 2018.
    9. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "“Let the data do the talking: Empirical modelling of survey-based expectations by means of genetic programming”," AQR Working Papers 201706, University of Barcelona, Regional Quantitative Analysis Group, revised May 2017.
    10. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Evolutionary Computation for Macroeconomic Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 833-849, February.
    11. Antonecchia, Gianluca, 2023. "Heterogeneous expectations, forecast accuracy and firms’ credit demand," European Economic Review, Elsevier, vol. 154(C).
    12. Oscar Claveria & Enric Monte & Salvador Torra, 2015. "“Self-organizing map analysis of agents’ expectations. Different patterns of anticipation of the 2008 financial crisis”," AQR Working Papers 201508, University of Barcelona, Regional Quantitative Analysis Group, revised Mar 2015.
    13. Breitung, Jörg & Schmeling, Maik, 2011. "Quantifying survey expectations: What's wrong with the probability approach?," Hannover Economic Papers (HEP) dp-485, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    14. Ferrando, Annalisa & Ganoulis, Ioannis & Preuss, Carsten, 2019. "Firms’ expectations on the availability of credit since the financial crisis," Working Paper Series 2341, European Central Bank.
    15. Guizzardi, Andrea & Stacchini, Annalisa, 2015. "Real-time forecasting regional tourism with business sentiment surveys," Tourism Management, Elsevier, vol. 47(C), pages 213-223.
    16. Kjetil Martinsen & Francesco Ravazzolo & Fredrik Wulfsberg, 2011. "Forecasting macroeconomic variables using disaggregate survey data," Working Paper 2011/04, Norges Bank.
    17. Alex Botsis & Kevin Lee, 2022. "Nowcasting Using Firm-Level Survey Data; Tracking UK Output Fluctuations and Recessionary Events," Economic Statistics Centre of Excellence (ESCoE) Technical Reports ESCOE-TR-20, Economic Statistics Centre of Excellence (ESCoE).
    18. Kajal Lahiri & Yongchen Zhao, 2013. "Quantifying Heterogeneous Survey Expectations: The Carlson-Parkin Method Revisited," Discussion Papers 13-08, University at Albany, SUNY, Department of Economics.

  24. Anthony Garratt & James Mitchell & Shaun P. Vahey & Elizabeth C. Wakerly, 2009. "Real-time Inflation Forecast Densities from Ensemble Phillips Curves," Birkbeck Working Papers in Economics and Finance 0910, Birkbeck, Department of Economics, Mathematics & Statistics.

    Cited by:

    1. Gian Luigi Mazzi & James Mitchell & Gaetana Montana, 2014. "Density Nowcasts and Model Combination: Nowcasting Euro-Area GDP Growth over the 2008–09 Recession," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(2), pages 233-256, April.
    2. 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.
    3. Pauwels, Laurent & Vasnev, Andrey, 2013. "Forecast combination for U.S. recessions with real-time data," Working Papers 02/2013, University of Sydney Business School, Discipline of Business Analytics.
    4. Francesco Ravazzolo & Shaun P. Vahey, 2010. "Forecast densities for economic aggregates from disaggregate ensembles," Working Paper 2010/02, Norges Bank.
    5. Mohsen Khezri & Seyed Ehsan Hosseinidoust & Mohammad Kazem Naziri, 2019. "Investigating the Temporary and Permanent Influential Variables on Iran Inflation Using TVP-DMA Models," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 23(1), pages 209-234, Winter.
    6. Bo Zhang & Jamie Cross & Na Guo, 2020. "Time-Varying Trend Models for Forecasting Inflation in Australia," Working Papers No 09/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    7. Bjørnland, Hilde C. & Gerdrup, Karsten & Jore, Anne Sofie & Smith, Christie & Thorsrud, Leif Anders, 2011. "Weights and pools for a Norwegian density combination," The North American Journal of Economics and Finance, Elsevier, vol. 22(1), pages 61-76, January.
    8. Anthony Garratt & Timo Henckel & Shaun P. Vahey, 2019. "Empirically-transformed linear opinion pools," CAMA Working Papers 2019-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    9. McElroy, Tucker S. & Wildi, Marc, 2020. "The Multivariate Linear Prediction Problem: Model-Based and Direct Filtering Solutions," Econometrics and Statistics, Elsevier, vol. 14(C), pages 112-130.
    10. 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.
    11. 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.
    12. Siemsen, Thomas & Vilsmeier, Johannes, 2018. "On a quest for robustness: About model risk, randomness and discretion in credit risk stress tests," Discussion Papers 31/2018, Deutsche Bundesbank.
    13. Garratt, Anthony & Mitchell, James & Vahey, Shaun P., 2014. "Measuring output gap nowcast uncertainty," International Journal of Forecasting, Elsevier, vol. 30(2), pages 268-279.
    14. Na Guo & Bo Zhang & Jamie L. Cross, 2022. "Time‐varying trend models for forecasting inflation in Australia," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 316-330, March.
    15. 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.
    16. Yang, Dazhi & van der Meer, Dennis, 2021. "Post-processing in solar forecasting: Ten overarching thinking tools," Renewable and Sustainable Energy Reviews, Elsevier, vol. 140(C).
    17. Mitchell, James, 2013. "The Recalibrated and Copula Opinion Pools," EMF Research Papers 02, Economic Modelling and Forecasting Group.
    18. Pauwels, Laurent L. & Vasnev, Andrey L., 2016. "A note on the estimation of optimal weights for density forecast combinations," International Journal of Forecasting, Elsevier, vol. 32(2), pages 391-397.
    19. 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.
    20. Li, Gang & Wu, Doris Chenguang & Zhou, Menglin & Liu, Anyu, 2019. "The combination of interval forecasts in tourism," Annals of Tourism Research, Elsevier, vol. 75(C), pages 363-378.
    21. Tavakolian , Hossein & Babaee , Majid & Shakeri , Abbas, 2018. "How Fluctuations in Macroeconomic Indicators Affect Inflation in Iran," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 13(3), pages 267-289, July.
    22. 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.

  25. Ida Wolden Bache & James Mitchell & Francesco Ravazzolo & Shaun P. Vahey, 2009. "Macro modelling with many models," Working Paper 2009/15, Norges Bank.

    Cited by:

    1. Francesco Ravazzolo & Shaun P. Vahey, 2010. "Forecast densities for economic aggregates from disaggregate ensembles," Working Paper 2010/02, Norges Bank.
    2. 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.
    3. Garratt, Anthony & Mitchell, James & Vahey, Shaun P., 2014. "Measuring output gap nowcast uncertainty," International Journal of Forecasting, Elsevier, vol. 30(2), pages 268-279.
    4. 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.
    5. Anthony Garratt & James Mitchell & Shaun P. Vahey & Elizabeth C. Wakerly, 2010. "Real-time Inflation Forecast Densities from Ensemble Phillips Curves," CAMA Working Papers 2010-34, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    6. Tony Chernis & Taylor Webley, 2022. "Nowcasting Canadian GDP with Density Combinations," Discussion Papers 2022-12, Bank of Canada.
    7. Tony Chernis, 2023. "Combining Large Numbers of Density Predictions with Bayesian Predictive Synthesis," Staff Working Papers 23-45, Bank of Canada.
    8. Francesco Ravazzolo & Shaun P Vahey, 2010. "Measuring Core Inflation in Australia with Disaggregate Ensembles," RBA Annual Conference Volume (Discontinued), in: Renée Fry & Callum Jones & Christopher Kent (ed.),Inflation in an Era of Relative Price Shocks, Reserve Bank of Australia.
    9. Chris McDonald & Leif Anders Thorsrud, 2011. "Evaluating density forecasts: model combination strategies versus the RBNZ," Reserve Bank of New Zealand Discussion Paper Series DP2011/03, Reserve Bank of New Zealand.
    10. Cobb, Marcus P A, 2017. "Aggregate Density Forecasting from Disaggregate Components Using Large VARs," MPRA Paper 76849, University Library of Munich, Germany.

  26. Mitchell, J. & Solomou, S. & Weale, M., 2009. "Monthly and Quarterly GDP Estimates for Interwar Britain," Cambridge Working Papers in Economics 0949, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Thomas, Ryland & Hills, Sally & Dimsdale, Nicholas, 2010. "The UK recession in context — what do three centuries of data tell us?," Bank of England Quarterly Bulletin, Bank of England, vol. 50(4), pages 277-291.

  27. Anthony Garratt & James Mitchell & Shaun P. Vahey, 2009. "Measuring Output Gap Uncertainty," Birkbeck Working Papers in Economics and Finance 0909, Birkbeck, Department of Economics, Mathematics & Statistics.

    Cited by:

    1. Francesco Ravazzolo & Shaun P. Vahey, 2010. "Forecast densities for economic aggregates from disaggregate ensembles," Working Paper 2010/02, Norges Bank.
    2. Paulo Mauricio Sánchez Beltrán & Luis Fernando Melo Velandia, 2013. "Combinación de brechas del producto colombiano," Borradores de Economia 10973, Banco de la Republica.
    3. 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.
    4. 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.
    5. Paulo M. Sánchez & Luis Fernando Melo, 2013. "Combinación de brechas del producto colombiano," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República, vol. 31(72), pages 74-82, December.
    6. Guérin, Pierre & Maurin, Laurent & Mohr, Matthias, 2015. "Trend-Cycle Decomposition Of Output And Euro Area Inflation Forecasts: A Real-Time Approach Based On Model Combination," Macroeconomic Dynamics, Cambridge University Press, vol. 19(2), pages 363-393, March.
    7. Juan Manuel Julio, 2011. "Data Revisions and the Output Gap," Borradores de Economia 642, Banco de la Republica de Colombia.
    8. Anthony Garratt & James Mitchell & Shaun P. Vahey & Elizabeth C. Wakerly, 2010. "Real-time Inflation Forecast Densities from Ensemble Phillips Curves," CAMA Working Papers 2010-34, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    9. Xueting Yu & Yuhan Zhu & Guangming Lv, 2020. "Analysis of the Impact of China’s GDP Data Revision on Monetary Policy from the Perspective of Uncertainty," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 56(6), pages 1251-1274, May.
    10. Dr. James Mitchell, 2009. "Macro Modelling with Many Models," National Institute of Economic and Social Research (NIESR) Discussion Papers 337, National Institute of Economic and Social Research.
    11. 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.
    12. Mamdouh Abdelmoula M. ABDELSALAM, 2017. "Improving Phillips Curve’s Inflation Forecasts under Misspecification," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 54-76, September.
    13. Francesco Ravazzolo & Shaun P Vahey, 2010. "Measuring Core Inflation in Australia with Disaggregate Ensembles," RBA Annual Conference Volume (Discontinued), in: Renée Fry & Callum Jones & Christopher Kent (ed.),Inflation in an Era of Relative Price Shocks, Reserve Bank of Australia.

  28. Ida Wolden Bache & Anne Sofie Jore & James Mitchell & Shaun P. Vahey, 2009. "Combining VAR and DSGE forecast densities," Working Paper 2009/23, Norges Bank.

    Cited by:

    1. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    2. Barbara Rossi & Tatevik Sekhposyan, 2015. "Alternative Tests for Correct Specification of Conditional Predictive Densities," Working Papers 758, Barcelona School of Economics.
    3. Gian Luigi Mazzi & James Mitchell & Gaetana Montana, 2014. "Density Nowcasts and Model Combination: Nowcasting Euro-Area GDP Growth over the 2008–09 Recession," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(2), pages 233-256, April.
    4. Wolters, Maik Hendrik, 2012. "Evaluating point and density forecasts of DSGE models," MPRA Paper 36147, University Library of Munich, Germany.
    5. Tommaso Proietti & Martyna Marczak & Gianluigi Mazzi, 2015. "EuroMInd-D: A Density Estimate of Monthly Gross Domestic Product for the Euro Area," CEIS Research Paper 340, Tor Vergata University, CEIS, revised 10 Apr 2015.
    6. Raffaella Giacomini & Barbara Rossi, 2014. "Forecasting in Nonstationary Environments: What Works and What Doesn't in Reduced-Form and Structural Models," Working Papers 819, Barcelona School of Economics.
    7. Rodríguez, Gabriel, 2017. "Modeling Latin-American stock and Forex markets volatility: Empirical application of a model with random level shifts and genuine long memory," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 393-420.
    8. Nalban, Valeriu, 2018. "Forecasting with DSGE models: What frictions are important?," Economic Modelling, Elsevier, vol. 68(C), pages 190-204.
    9. 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.
    10. Periklis Gogas & Theophilos Papadimitriou & Elvira Takli, 2013. "Comparison of simple sum and Divisia monetary aggregates in GDP forecasting: a support vector machines approach," Economics Bulletin, AccessEcon, vol. 33(2), pages 1101-1115.
    11. 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.
    12. Malte Knüppel, 2015. "Evaluating the Calibration of Multi-Step-Ahead Density Forecasts Using Raw Moments," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 270-281, April.
    13. 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.
    14. 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.
    15. Valeriu Nalban, 2015. "Do Bayesian Vector Autoregressive models improve density forecasting accuracy? The case of the Czech Republic and Romania," International Journal of Economic Sciences, International Institute of Social and Economic Sciences, vol. 4(1), pages 60-74, March.
    16. Jakub Ryšánek, 2010. "Combining VAR Forecast Densities Using Fast Fourier Transform," Acta Oeconomica Pragensia, Prague University of Economics and Business, vol. 2010(5), pages 72-88.
    17. Diebold, Francis X. & Schorfheide, Frank & Shin, Minchul, 2017. "Real-time forecast evaluation of DSGE models with stochastic volatility," CFS Working Paper Series 577, Center for Financial Studies (CFS).
    18. Dr. James Mitchell, 2009. "Macro Modelling with Many Models," National Institute of Economic and Social Research (NIESR) Discussion Papers 337, National Institute of Economic and Social Research.
    19. Pauwels, Laurent L. & Vasnev, Andrey L., 2016. "A note on the estimation of optimal weights for density forecast combinations," International Journal of Forecasting, Elsevier, vol. 32(2), pages 391-397.
    20. 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.
    21. 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.
    22. Hoornweg, V., 2013. "Some Tools for Robustifying Econometric Analyses," Econometric Institute Research Papers 50163, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    23. Liu, Li & Wang, Yudong & Yang, Li, 2018. "Predictability of crude oil prices: An investor perspective," Energy Economics, Elsevier, vol. 75(C), pages 193-205.
    24. Rossi, Barbara & Gürkaynak, Refet & Kısacıkoğlu, Burçin, 2013. "Do DSGE Models Forecast More Accurately Out-of-Sample than VAR Models?," CEPR Discussion Papers 9576, C.E.P.R. Discussion Papers.

  29. Dr Silvia Lui & Dr Martin Weale & Dr. James Mitchell, 2008. "Qualitative Business Surveys: Signal or Noise?," National Institute of Economic and Social Research (NIESR) Discussion Papers 323, National Institute of Economic and Social Research.

    Cited by:

    1. Kedai Cheng & Derek S. Young, 2023. "An Approach for Specifying Trimming and Winsorization Cutoffs," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 28(2), pages 299-323, June.
    2. Driver, Ciaran & Muñoz-Bugarin, Jair, 2019. "Financial constraints on investment: Effects of firm size and the financial crisis," Research in International Business and Finance, Elsevier, vol. 47(C), pages 441-457.
    3. Ruediger Bachmann & Steffen Elstner, 2013. "Firms' Optimism and Pessimism," CESifo Working Paper Series 4176, CESifo.
    4. Lahiri, Kajal & Zhao, Yongchen, 2015. "Quantifying survey expectations: A critical review and generalization of the Carlson–Parkin method," International Journal of Forecasting, Elsevier, vol. 31(1), pages 51-62.
    5. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“Tracking economic growth by evolving expectations via genetic programming: A two-step approach”," IREA Working Papers 201801, University of Barcelona, Research Institute of Applied Economics, revised Jan 2018.
    6. M. Caivano & A. Harvey, 2013. "Time series models with an EGB2 conditional distribution," Cambridge Working Papers in Economics 1325, Faculty of Economics, University of Cambridge.
    7. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "A Data-Driven Approach to Construct Survey-Based Indicators by Means of Evolutionary Algorithms," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 135(1), pages 1-14, January.
    8. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "“Let the data do the talking: Empirical modelling of survey-based expectations by means of genetic programming”," AQR Working Papers 201706, University of Barcelona, Regional Quantitative Analysis Group, revised May 2017.
    9. Ciaran Driver, 2019. "Trade liberalization and South African manufacturing: Looking back with data," WIDER Working Paper Series wp-2019-30, World Institute for Development Economic Research (UNU-WIDER).
    10. Mazzi Gian Luigi & Mitchell James & Carausu Florabela, 2021. "Measuring and Communicating the Uncertainty in Official Economic Statistics," Journal of Official Statistics, Sciendo, vol. 37(2), pages 289-316, June.
    11. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Evolutionary Computation for Macroeconomic Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 833-849, February.
    12. Daniel Kaufmann & Rolf Scheufele, 2015. "Business tendency surveys and macroeconomic fluctuations," KOF Working papers 15-378, KOF Swiss Economic Institute, ETH Zurich.
    13. Raïsa Basselier & David Antonio Liedo & Geert Langenus, 2018. "Nowcasting Real Economic Activity in the Euro Area: Assessing the Impact of Qualitative Surveys," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(1), pages 1-46, April.
    14. Breitung, Jörg & Schmeling, Maik, 2011. "Quantifying survey expectations: What's wrong with the probability approach?," Hannover Economic Papers (HEP) dp-485, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    15. Corder, Matthew & Weale, Martin, 2011. "Banking crises and recessions: what can leading indicators tell us?," Discussion Papers 33, Monetary Policy Committee Unit, Bank of England.
    16. Frohm, Erik, 2020. "Price-setting and economic slack: Evidence from firm-level survey data," Journal of Macroeconomics, Elsevier, vol. 65(C).
    17. Guizzardi, Andrea & Stacchini, Annalisa, 2015. "Real-time forecasting regional tourism with business sentiment surveys," Tourism Management, Elsevier, vol. 47(C), pages 213-223.
    18. Alexandros Botsis & Christoph Gortz & Plutarchos Sakellaris, 2023. "Quantifying Qualitative Survey Data: New Insights on the (Ir)Rationality of Firms' Forecasts," Discussion Papers 23-06, Department of Economics, University of Birmingham.
    19. Kjetil Martinsen & Francesco Ravazzolo & Fredrik Wulfsberg, 2011. "Forecasting macroeconomic variables using disaggregate survey data," Working Paper 2011/04, Norges Bank.
    20. Boneva, Lena & CLoyne, James & Weale, Martin & Wieladek, Tomasz, 2016. "Firms’ expectations and price-setting: evidence from micro data," Discussion Papers 48, Monetary Policy Committee Unit, Bank of England.
    21. Alex Botsis & Kevin Lee, 2022. "Nowcasting Using Firm-Level Survey Data; Tracking UK Output Fluctuations and Recessionary Events," Economic Statistics Centre of Excellence (ESCoE) Technical Reports ESCOE-TR-20, Economic Statistics Centre of Excellence (ESCoE).
    22. Luboš Marek & Stanislava Hronová & Richard Hindls, 2019. "Možnosti odhadů krátkodobých makroekonomických agregátů na základě výsledků konjunkturních průzkumů [Possibilities of Estimations of Short-term Macroeconomic Aggregates Based on Business Survey Res," Politická ekonomie, Prague University of Economics and Business, vol. 2019(4), pages 347-370.
    23. Kajal Lahiri & Yongchen Zhao, 2013. "Quantifying Heterogeneous Survey Expectations: The Carlson-Parkin Method Revisited," Discussion Papers 13-08, University at Albany, SUNY, Department of Economics.

  30. Anne-Sofie Jore & James Mitchell & Shaun P. Vahey, 2008. "Combining forecast densities from VARs with uncertain instabilities," Working Paper 2008/01, Norges Bank.

    Cited by:

    1. Li, Li & Kang, Yanfei & Li, Feng, 2023. "Bayesian forecast combination using time-varying features," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1287-1302.
    2. 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.
    3. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    4. 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.
    5. Pauwels, Laurent & Radchenko, Peter & Vasnev, Andrey, 2019. "Higher Moment Constraints for Predictive Density Combinations," Working Papers BAWP-2019-01, University of Sydney Business School, Discipline of Business Analytics.
    6. Gian Luigi Mazzi & James Mitchell & Gaetana Montana, 2014. "Density Nowcasts and Model Combination: Nowcasting Euro-Area GDP Growth over the 2008–09 Recession," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(2), pages 233-256, April.
    7. 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.
    8. Davide Pettenuzzo & Francesco Ravazzolo, 2014. "Optimal portfolio choice under decision-based model combinations," Working Paper 2014/15, Norges Bank.
    9. Francesco Ravazzolo & Shaun P. Vahey, 2010. "Forecast densities for economic aggregates from disaggregate ensembles," Working Paper 2010/02, Norges Bank.
    10. Hilde C. Bjørnland & Karsten Gerdrup & Anne Sofie Jore & Christie Smith & Leif Anders Thorsrud, 2012. "Does Forecast Combination Improve Norges Bank Inflation Forecasts?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(2), pages 163-179, April.
    11. Barbara Rossi & Tatevik Sekhposyan, 2013. "Evaluating predictive densities of U.S. output growth and inflation in a large macroeconomic data set," Economics Working Papers 1370, Department of Economics and Business, Universitat Pompeu Fabra.
    12. Ruben Loaiza‐Maya & Gael M. Martin & David T. Frazier, 2021. "Focused Bayesian prediction," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 517-543, August.
    13. Paulo Mauricio Sánchez Beltrán & Luis Fernando Melo Velandia, 2013. "Combinación de brechas del producto colombiano," Borradores de Economia 10973, Banco de la Republica.
    14. 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.
    15. Wagner Piazza Gaglianone & Luiz Renato Lima, 2014. "Constructing Optimal Density Forecasts From Point Forecast Combinations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(5), pages 736-757, August.
    16. Hugo Gerard & Kristoffer Nimark, 2008. "Combining Multivariate Density Forecasts Using Predictive Criteria," RBA Research Discussion Papers rdp2008-02, Reserve Bank of Australia.
    17. Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2019. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Working Paper 2019/2, Norges Bank.
    18. Cristina Conflitti & Christine De Mol & Domenico Giannone, 2012. "Optimal Combination of Survey Forecasts," Working Papers ECARES ECARES 2012-023, ULB -- Universite Libre de Bruxelles.
    19. Allayioti, Anastasia & Venditti, Fabrizio, 2024. "The role of comovement and time-varying dynamics in forecasting commodity prices," Working Paper Series 2901, European Central Bank.
    20. 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.
    21. Bjørnland, Hilde C. & Gerdrup, Karsten & Jore, Anne Sofie & Smith, Christie & Thorsrud, Leif Anders, 2011. "Weights and pools for a Norwegian density combination," The North American Journal of Economics and Finance, Elsevier, vol. 22(1), pages 61-76, January.
    22. Michael S. Smith & Shaun P. Vahey, 2016. "Asymmetric Forecast Densities for U.S. Macroeconomic Variables from a Gaussian Copula Model of Cross-Sectional and Serial Dependence," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(3), pages 416-434, July.
    23. Tomáš Jeřábek & Jakub Trojan & Radka Šperková, 2013. "Predictive performance of DSGE model for small open economy - the case study of Czech Republic," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 61(7), pages 2229-2238.
    24. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2011. "Combining Predictive Densities using Bayesian Filtering with Applications to US Economics Data," Tinbergen Institute Discussion Papers 11-003/4, Tinbergen Institute.
    25. 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.
    26. Kirdan Lees, 2009. "Overview of a recent Reserve Bank workshop: nowcasting with model combination," Reserve Bank of New Zealand Bulletin, Reserve Bank of New Zealand, vol. 72, pages 31-33, March.
    27. Götz, T.B. & Hecq, A.W. & Urbain, J.R.Y.J., 2014. "Combining distributions of real-time forecasts: An application to U.S. growth," Research Memorandum 027, Maastricht University, Graduate School of Business and Economics (GSBE).
    28. Knut Are Aastveit & Jamie Cross & Herman K. van Dijk, 2021. "Quantifying time-varying forecast uncertainty and risk for the real price of oil," Tinbergen Institute Discussion Papers 21-053/III, Tinbergen Institute.
    29. Tommaso Proietti & Martyna Marczak & Gianluigi Mazzi, 2015. "EuroMInd-D: A Density Estimate of Monthly Gross Domestic Product for the Euro Area," CEIS Research Paper 340, Tor Vergata University, CEIS, revised 10 Apr 2015.
    30. Jonathan Berrisch & Florian Ziel, 2023. "Multivariate Probabilistic CRPS Learning with an Application to Day-Ahead Electricity Prices," Papers 2303.10019, arXiv.org, revised Feb 2024.
    31. Raffaella Giacomini & Barbara Rossi, 2014. "Forecasting in Nonstationary Environments: What Works and What Doesn't in Reduced-Form and Structural Models," Working Papers 819, Barcelona School of Economics.
    32. Anthony Garratt & Timo Henckel & Shaun P. Vahey, 2019. "Empirically-transformed linear opinion pools," CAMA Working Papers 2019-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    33. Rodríguez, Gabriel, 2017. "Modeling Latin-American stock and Forex markets volatility: Empirical application of a model with random level shifts and genuine long memory," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 393-420.
    34. Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2015. "Bayesian nonparametric calibration and combination of predictive distributions," Working Paper 2015/03, Norges Bank.
    35. Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2021. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates," Working Papers 21-06, Federal Reserve Bank of Philadelphia.
    36. 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.
    37. 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.
    38. 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.
    39. 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.
    40. Galvao, Ana Beatriz & Garratt, Anthony & Mitchell, James, 2020. "Does Judgment Improve Macroeconomic Density Forecasts?," EMF Research Papers 33, Economic Modelling and Forecasting Group.
    41. 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.
    42. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    43. 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.
    44. 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.
    45. Garratt, Anthony & Mitchell, James & Vahey, Shaun P., 2014. "Measuring output gap nowcast uncertainty," International Journal of Forecasting, Elsevier, vol. 30(2), pages 268-279.
    46. Michael Stanley Smith & Thomas S. Shively, 2018. "Econometric Modeling of Regional Electricity Spot Prices in the Australian Market," Papers 1804.08218, arXiv.org.
    47. Piergiorgio Alessandri & Haroon Mumtaz, 2017. "Financial conditions and density forecasts for US output and inflation," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 24, pages 66-78, March.
    48. Malte Knüppel, 2015. "Evaluating the Calibration of Multi-Step-Ahead Density Forecasts Using Raw Moments," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 270-281, April.
    49. Matteo Luciani & Lorenzo Ricci, 2014. "Nowcasting Norway," International Journal of Central Banking, International Journal of Central Banking, vol. 10(4), pages 215-248, December.
    50. Paulo M. Sánchez & Luis Fernando Melo, 2013. "Combinación de brechas del producto colombiano," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República, vol. 31(72), pages 74-82, December.
    51. Constantin Bürgi & Tara M. Sinclair, 2015. "A Nonparametric Approach to Identifying a Subset of Forecasters that Outperforms the Simple Average," Working Papers 2015-006, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    52. Coe, Patrick J & Vahey, Shaun P., 2014. "Probablistic Prediction of the US Great Recession with Historical Expert," EMF Research Papers 06, Economic Modelling and Forecasting Group.
    53. Geoff Kenny & Thomas Kostka & Federico Masera, 2015. "Can Macroeconomists Forecast Risk? Event-Based Evidence from the Euro-Area SPF," International Journal of Central Banking, International Journal of Central Banking, vol. 11(4), pages 1-46, December.
    54. 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.
    55. Diego Fresoli, 2022. "Bootstrap VAR forecasts: The effect of model uncertainties," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 279-293, March.
    56. Fawcett, Nicholas & Kapetanios, George & Mitchell, James & Price, Simon, 2014. "Generalised density forecast combinations," Bank of England working papers 492, Bank of England.
    57. Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2017. "Density Forecasts With Midas Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(4), pages 783-801, June.
    58. 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.
    59. Knut Are Aastveit & Francesco Ravazzolo & Herman K. van Dijk, 2018. "Combined Density Nowcasting in an Uncertain Economic Environment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 131-145, January.
    60. Filippo di Mauro & Filippo di Mauro, Fabio Fornari, 2014. "Going granular: The importance of firm-level equity information in anticipating economic activity," EcoMod2014 6809, EcoMod.
    61. 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.
    62. Anthony Garratt & James Mitchell & Shaun P. Vahey & Elizabeth C. Wakerly, 2010. "Real-time Inflation Forecast Densities from Ensemble Phillips Curves," CAMA Working Papers 2010-34, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    63. 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.
    64. 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.
    65. Tomáš Jeřábek & Radka Šperková, 2015. "A Predictive Likelihood Approach to Bayesian Averaging," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 63(4), pages 1269-1276.
    66. Kenneth Sæterhagen Paulsen & Tuva Marie Fastbø & Tobias Ingebrigtsen, 2022. "Aggregate density forecast of models using disaggregate data - A copula approach," Working Paper 2022/5, Norges Bank.
    67. 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.
    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. Anne Opschoor & Dick van Dijk & Michel van der Wel, 2014. "Improving Density Forecasts and Value-at-Risk Estimates by Combining Densities," Tinbergen Institute Discussion Papers 14-090/III, Tinbergen Institute.
    70. Marcus P. A. Cobb, 2020. "Aggregate density forecasting from disaggregate components using Bayesian VARs," Empirical Economics, Springer, vol. 58(1), pages 287-312, January.
    71. Massimiliano Marcellino & Mario Porqueddu & Fabrizio Venditti, 2016. "Short-Term GDP Forecasting With a Mixed-Frequency Dynamic Factor Model With Stochastic Volatility," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 118-127, January.
    72. Taylor, James W., 2020. "Forecast combinations for value at risk and expected shortfall," International Journal of Forecasting, Elsevier, vol. 36(2), pages 428-441.
    73. di Mauro, Filippo & Fornari, Fabio & Mannucci, Dario, 2011. "Stock market firm-level information and real economic activity," Working Paper Series 1366, European Central Bank.
    74. Tony Chernis & Taylor Webley, 2022. "Nowcasting Canadian GDP with Density Combinations," Discussion Papers 2022-12, Bank of Canada.
    75. Dr. James Mitchell, 2009. "Measuring Output Gap Uncertainty," National Institute of Economic and Social Research (NIESR) Discussion Papers 342, National Institute of Economic and Social Research.
    76. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2011. "Combining Predictive Densities using Nonlinear Filtering with Applications to US Economics Data," Tinbergen Institute Discussion Papers 11-172/4, Tinbergen Institute.
    77. Niango Ange Joseph Yapi, 2020. "Exchange rate predictive densities and currency risks: A quantile regression approach," EconomiX Working Papers 2020-16, University of Paris Nanterre, EconomiX.
    78. Dr. James Mitchell, 2009. "Macro Modelling with Many Models," National Institute of Economic and Social Research (NIESR) Discussion Papers 337, National Institute of Economic and Social Research.
    79. Fabian Krüger & Ingmar Nolte, 2011. "Disagreement, Uncertainty and the True Predictive Density," Working Paper Series of the Department of Economics, University of Konstanz 2011-43, Department of Economics, University of Konstanz.
    80. Victor Lopez-Perez, 2016. "Macroeconomic Forecast Uncertainty In The Euro Area," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 11(1), pages 9-41, March.
    81. Garratt, Anthony & Mise, Emi, 2014. "Forecasting exchange rates using panel model and model averaging," Economic Modelling, Elsevier, vol. 37(C), pages 32-40.
    82. Mitchell, James, 2013. "The Recalibrated and Copula Opinion Pools," EMF Research Papers 02, Economic Modelling and Forecasting Group.
    83. Barbara Rossi, 2018. "Identifying and estimating the effects of unconventional monetary policy in the data: How to do It and what have we learned?," Economics Working Papers 1641, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2020.
    84. Manzan, Sebastiano & Zerom, Dawit, 2013. "Are macroeconomic variables useful for forecasting the distribution of U.S. inflation?," International Journal of Forecasting, Elsevier, vol. 29(3), pages 469-478.
    85. Pauwels, Laurent L. & Vasnev, Andrey L., 2016. "A note on the estimation of optimal weights for density forecast combinations," International Journal of Forecasting, Elsevier, vol. 32(2), pages 391-397.
    86. 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.
    87. 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.
    88. Fabio Busetti, 2017. "Quantile Aggregation of Density Forecasts," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(4), pages 495-512, August.
    89. Magnus Reif, 2018. "Macroeconomic Uncertainty and Forecasting Macroeconomic Aggregates," ifo Working Paper Series 265, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    90. Christian Kascha & Francesco Ravazzolo, 2008. "Combining inflation density forecasts," Working Paper 2008/22, Norges Bank.
    91. Lan Bai & Xiafei Li & Yu Wei & Guiwu Wei, 2022. "Does crude oil futures price really help to predict spot oil price? New evidence from density forecasting," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3694-3712, July.
    92. Nima Nonejad, 2021. "Bayesian model averaging and the conditional volatility process: an application to predicting aggregate equity returns by conditioning on economic variables," Quantitative Finance, Taylor & Francis Journals, vol. 21(8), pages 1387-1411, August.
    93. 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.
    94. 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.
    95. Timo Henckel & Shaun Vahey & Liz Wakerly, 2011. "Probabilistic interest rate setting with a shadow board: A description of the pilot project," CAMA Working Papers 2011-27, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    96. Gaglianone, Wagner Piazza & Marins, Jaqueline Terra Moura, 2017. "Evaluation of exchange rate point and density forecasts: An application to Brazil," International Journal of Forecasting, Elsevier, vol. 33(3), pages 707-728.
    97. Karapanagiotidis, Paul, 2012. "Improving Bayesian VAR density forecasts through autoregressive Wishart Stochastic Volatility," MPRA Paper 38885, University Library of Munich, Germany.
    98. Enrique Moral-Benito, 2015. "Model Averaging In Economics: An Overview," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 46-75, February.
    99. Wang, Xiaoqian & Hyndman, Rob J. & Li, Feng & Kang, Yanfei, 2023. "Forecast combinations: An over 50-year review," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1518-1547.
    100. Clark, Todd E. & Doh, Taeyoung, 2014. "Evaluating alternative models of trend inflation," International Journal of Forecasting, Elsevier, vol. 30(3), pages 426-448.
    101. 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.
    102. Liu, Li & Wang, Yudong & Yang, Li, 2018. "Predictability of crude oil prices: An investor perspective," Energy Economics, Elsevier, vol. 75(C), pages 193-205.
    103. Francesco Ravazzolo & Shaun P Vahey, 2010. "Measuring Core Inflation in Australia with Disaggregate Ensembles," RBA Annual Conference Volume (Discontinued), in: Renée Fry & Callum Jones & Christopher Kent (ed.),Inflation in an Era of Relative Price Shocks, Reserve Bank of Australia.
    104. 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.
    105. 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.
    106. 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.
    107. Drachal, Krzysztof, 2021. "Forecasting crude oil real prices with averaging time-varying VAR models," Resources Policy, Elsevier, vol. 74(C).
    108. K=osaku Takanashi & Kenichiro McAlinn, 2019. "Equivariant online predictions of non-stationary time series," Papers 1911.08662, arXiv.org, revised Jun 2023.
    109. McAdam, Peter & Warne, Anders, 2020. "Density forecast combinations: the real-time dimension," Working Paper Series 2378, European Central Bank.

  31. Troy Matheson & James Mitchell & Brian Silverstone, 2007. "Nowcasting and predicting data revisions in real time using qualitative panel survey data," Reserve Bank of New Zealand Discussion Paper Series DP2007/02, Reserve Bank of New Zealand.

    Cited by:

    1. Kirdan Lees, 2009. "Overview of a recent Reserve Bank workshop: nowcasting with model combination," Reserve Bank of New Zealand Bulletin, Reserve Bank of New Zealand, vol. 72, pages 31-33, March.
    2. Bhattacharya, Rudrani & Pandey, Radhika & Veronese, Giovanni, 2011. "Tracking India Growth in Real Time," Working Papers 11/90, National Institute of Public Finance and Policy.

  32. Dr Martin Weale & Dr. James Mitchell, 2007. "The Rationality and Reliability of Expectations Reported by British Households: Micro Evidence from the British Household Panel Survey," National Institute of Economic and Social Research (NIESR) Discussion Papers 287, National Institute of Economic and Social Research.

    Cited by:

    1. Bovi, Maurizio, 2009. "Economic versus psychological forecasting. Evidence from consumer confidence surveys," Journal of Economic Psychology, Elsevier, vol. 30(4), pages 563-574, August.
    2. Péter Gábriel, 2010. "Household inflation expectations and inflation dynamics," MNB Working Papers 2010/12, Magyar Nemzeti Bank (Central Bank of Hungary).
    3. Maurizio Bovi, 2008. "The “Psycho-analysis” of Common People’s Forecast Errors. Evidence from European Consumer Surveys," ISAE Working Papers 95 Classification-JEL C42, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    4. Piotr Białowolski, 2016. "The influence of negative response style on survey-based household inflation expectations," Quality & Quantity: International Journal of Methodology, Springer, vol. 50(2), pages 509-528, March.
    5. David G. Blanchflower & Conall MacCoille, 2009. "The formation of inflation expectations: an empirical analysis for the UK," NBER Working Papers 15388, National Bureau of Economic Research, Inc.
    6. Abubakar Mammadi & Habu Mallam Baba & Sadiq Tukur & Abdul Azeez Adam Muhammad & Umar Abdullahi, 2020. "Measuring Residents Satisfaction Levels of Public Housing in Maiduguri Metropolis of Borno State, Nigeria," Traektoriâ Nauki = Path of Science, Altezoro, s.r.o. & Dialog, vol. 6(3), pages 3001-3020, Macrh.
    7. Magdalena Szyszko, 2017. "Central Banks Inflation Forecast and Expectations. A Comparative Analysis," Prague Economic Papers, Prague University of Economics and Business, vol. 2017(3), pages 286-299.
    8. Brown, Sarah & Harris, Mark N. & Spencer, Christopher & Taylor, Karl, 2020. "Financial Expectations and Household Consumption: Does Middle Inflation Matter?," IZA Discussion Papers 13023, Institute of Labor Economics (IZA).
    9. Magdalena Szyszko & Aleksandra Rutkowska, 2019. "Forward-looking component in consumers’ expectations and inflation forecast targeting: the case of six European economies," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 37(1), pages 77-112.
    10. Sarah Brown & Karl Taylor, 2008. "Expectations, Reservation Wages And Employment: Evidence From British Panel Data," Working Papers 2008007, The University of Sheffield, Department of Economics, revised May 2008.

  33. Dr Martin Weale & Dr. James Mitchell, 2005. "Poverty and Debt," National Institute of Economic and Social Research (NIESR) Discussion Papers 263, National Institute of Economic and Social Research.

    Cited by:

    1. Servaas Deroose (Editor), 2006. "Assessing the factors of resilience of private consumption in the euro area," European Economy - Economic Papers 2008 - 2015 252, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.

  34. Dr Martin Weale & Dr. James Mitchell, 2005. "Uncertainty in UK manufacturing: evidence from qualitative survey data," National Institute of Economic and Social Research (NIESR) Discussion Papers 266, National Institute of Economic and Social Research.

    Cited by:

    1. Oscar Claveria, 2021. "Uncertainty indicators based on expectations of business and consumer surveys," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 48(2), pages 483-505, May.
    2. Kevin Lee & Michael Mahony & Paul Mizen, 2020. "The CBI Suite of Business Surveys," Economic Statistics Centre of Excellence (ESCoE) Technical Reports ESCOE-TR-08, Economic Statistics Centre of Excellence (ESCoE).
    3. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“A geometric approach to proxy economic uncertainty by a metric of disagreement among qualitative expectations”," AQR Working Papers 201803, University of Barcelona, Regional Quantitative Analysis Group, revised Jun 2018.
    4. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Economic Uncertainty: A Geometric Indicator of Discrepancy Among Experts’ Expectations," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 143(1), pages 95-114, May.
    5. Byrne, Joseph P & Spaliara, Marina-Eliza & Serafeim, Tsoukas, 2015. "Firm survival, uncertainty and financial frictions: Is there a financial uncertainty accelerator?," SIRE Discussion Papers 2015-68, Scottish Institute for Research in Economics (SIRE).
    6. Oscar Claveria, 2020. "Measuring and assessing economic uncertainty," IREA Working Papers 202011, University of Barcelona, Research Institute of Applied Economics, revised Jul 2020.
    7. Breitung, Jörg & Schmeling, Maik, 2011. "Quantifying survey expectations: What's wrong with the probability approach?," Hannover Economic Papers (HEP) dp-485, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    8. Oscar Claveria, 2021. "Forecasting with Business and Consumer Survey Data," Forecasting, MDPI, vol. 3(1), pages 1-22, February.
    9. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "A new approach for the quantification of qualitative measures of economic expectations," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(6), pages 2685-2706, November.
    10. Oscar Claveria, 2021. "Disagreement on expectations: firms versus consumers," SN Business & Economics, Springer, vol. 1(12), pages 1-23, December.

  35. James Mitchell, 2005. "Should we be surprised by the unreliability of real-time output gap estimates? Density estimates for the Euro area," Computing in Economics and Finance 2005 52, Society for Computational Economics.

    Cited by:

    1. Cayen, Jean-Philippe & van Norden, Simon, 2004. "The reliability of Canadian output gap estimates," Discussion Paper Series 1: Economic Studies 2004,29, Deutsche Bundesbank.

  36. Dr. James Mitchell, 2004. "Optimal combination of density forecasts," National Institute of Economic and Social Research (NIESR) Discussion Papers 248, National Institute of Economic and Social Research.

    Cited by:

    1. Benjamin Avanzi & Yanfeng Li & Bernard Wong & Alan Xian, 2022. "Ensemble distributional forecasting for insurance loss reserving," Papers 2206.08541, arXiv.org, revised Feb 2024.
    2. Mouratidis, Kostas, 2008. "Evaluating currency crises: A Bayesian Markov switching approach," Journal of Macroeconomics, Elsevier, vol. 30(4), pages 1688-1711, December.
    3. Österholm, Pär, 2006. "Incorporating Judgement in Fan Charts," Working Paper Series 2006:30, Uppsala University, Department of Economics.
    4. Ohnsorge,Franziska Lieselotte & Stocker,Marc & Some,Modeste Y., 2016. "Quantifying uncertainties in global growth forecasts," Policy Research Working Paper Series 7770, The World Bank.

  37. James Mitchell & Michael Massmann, 2004. "Reconsidering the evidence: are Eurozone business cycles converging?," Money Macro and Finance (MMF) Research Group Conference 2003 67, Money Macro and Finance Research Group.

    Cited by:

    1. Michaelides, Panayotis G. & Papageorgiou, Theofanis & Vouldis, Angelos T., 2013. "Business cycles and economic crisis in Greece (1960–2011): A long run equilibrium analysis in the Eurozone," Economic Modelling, Elsevier, vol. 31(C), pages 804-816.
    2. Juliana Ávila Vélez & Álvaro José Pinzón Giraldo, 2015. "¿Están sincronizados los ciclos económicos en Latinoamérica?," Borradores de Economia 864, Banco de la Republica de Colombia.
    3. Dionysios K. Solomos & Dimitrios N. Koumparoulis, 2013. "Financial Sector and Business Cycles Determinants in the EMU: An Empirical Approach (1996-2011)," European Research Studies Journal, European Research Studies Journal, vol. 0(2), pages 34-58.
    4. 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.
    5. Hideaki Hirata & M. Ayhan Kose & Christopher Otrok, 2013. "Regionalization vs. globalization," Working Papers 2013-002, Federal Reserve Bank of St. Louis.
    6. Balli, Faruk & Rana, Faisal, 2015. "Determinants of risk sharing through remittances," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 107-116.
    7. Inklaar, Robert & Jong-A-Pin, Richard & de Haan, Jakob, 2008. "Trade and business cycle synchronization in OECD countries--A re-examination," European Economic Review, Elsevier, vol. 52(4), pages 646-666, May.
    8. Mark Mink & Jan P.A.M. Jacobs & Jakob de Haan, 2007. "Measuring Synchronicity And Co-Movement Of Business Cycles With An Application To The Euro Area," CAMA Working Papers 2007-19, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    9. Bojeşteanu, Elena & Manu, Ana Simona, 2011. "Analiza empirică a sincronizării ciclului de afaceri şi a similarităţii şocurilor între România şi zona euro [Empirical analysis of business cycle synchronization and shock similarity between Roman," MPRA Paper 31295, University Library of Munich, Germany.
    10. U. Michael Bergman, 2004. "How Similar Are European Business Cycles?," EPRU Working Paper Series 04-13, Economic Policy Research Unit (EPRU), University of Copenhagen. Department of Economics, revised Nov 2004.
    11. Crespo-Cuaresma, Jesús & Fernández-Amador, Octavio, 2013. "Business cycle convergence in EMU: A second look at the second moment," Journal of International Money and Finance, Elsevier, vol. 37(C), pages 239-259.
    12. Makoto Muto & Tamotsu Onozaki & Yoshitaka Saiki, 2023. "Regional Synchronization during Economic Contraction: The Case of the U.S. and Japan," Applied Economics, Taylor & Francis Journals, vol. 55(30), pages 3472-3486, June.
    13. Ludmila Fadejeva & Aleksejs Melihovs, 2008. "The Baltic states and Europe: common factors of economic activity," Baltic Journal of Economics, Baltic International Centre for Economic Policy Studies, vol. 8(1), pages 75-96, October.
    14. Angelos VOULDIS & Panayotis MICHAELIDES & John MILIOS, 2008. "Do Technology Shocks affect Output and Profitability over the Business Cycle in Greece (1960-2008)?," EcoMod2008 23800152, EcoMod.
    15. Emilia Gyoerk, 2017. "Economic Costs and Benefits of EMU Membership from the Perspective of a Non-member," Open Economies Review, Springer, vol. 28(5), pages 893-921, November.
    16. Sonia de Lucas Santos & M. Jesús Delgado Rodríguez & Inmaculada Álvarez Ayuso & José Luis Cendejas Bueno, 2011. "Los ciclos económicos internacionales: antecedentes y revisión de la literatura," Cuadernos de Economía - Spanish Journal of Economics and Finance, Asociación Cuadernos de Economía, vol. 34(95), pages 73-84, Agosto.
    17. Ageliki Anagnostou & Ioannis Panteladis & Maria Tsiapa, 2015. "Disentangling different patterns of business cycle synchronicity in the EU regions," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 42(3), pages 615-641, August.
    18. Máximo Camacho & Gabriel Pérez-Quirós & Lorena Saiz, 2004. "Are european business cycles close enough to be just one?," Working Papers 0408, Banco de España.
    19. Faruk Balli & Faisal Rana, 2014. "Determinants of risk sharing through remittances: cross-country evidence," CAMA Working Papers 2014-12, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    20. Michaelides, Panayotis G. & Tsionas, Efthymios G. & Konstantakis, Konstantinos N., 2018. "Debt Crisis in Europe (2001-2015): A Network General Equilibrium GVAR approach," MPRA Paper 89998, University Library of Munich, Germany.
    21. Ionut Jianu, 2020. "Examining the drivers of business cycle divergence between Euro Area and Romania," Papers 2007.11407, arXiv.org.
    22. Gyódi Kristóf & Sobolewski Maciej & Ziembiński Michał, 2017. "What Drives Price Dispersion in the European E-commerce Industry?," Central European Economic Journal, Sciendo, vol. 3(50), pages 53-71, December.
    23. Konstantakis, Konstantinos N. & Michaelides, Panayotis G. & Vouldis, Angelos T., 2016. "Non performing loans (NPLs) in a crisis economy: Long-run equilibrium analysis with a real time VEC model for Greece (2001–2015)," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 149-161.
    24. Konstantakis, Konstantinos N. & Michaelides, Panayotis G., 2017. "Technology and Business Cycles: A Schumpeterian Investigation for the USA," MPRA Paper 80636, University Library of Munich, Germany.
    25. Barbara Berkel, 2006. "The EMU and German Cross-Border Portfolio Flows," MEA discussion paper series 06110, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
    26. Viviana Fernandez & Ali M. Kutan, 2005. "Do Regional Integration Agreements Increase Business-Cycle Convergence? Evidence From APEC and NAFTA," William Davidson Institute Working Papers Series wp765, William Davidson Institute at the University of Michigan.
    27. Bengoechea, Pilar & Camacho, Maximo & Perez-Quiros, Gabriel, 2006. "A useful tool for forecasting the Euro-area business cycle phases," International Journal of Forecasting, Elsevier, vol. 22(4), pages 735-749.
    28. Chen, Xiaoshan & Mills, Terence C., 2009. "Evaluating growth cycle synchronisation in the EU," Economic Modelling, Elsevier, vol. 26(2), pages 342-351, March.
    29. Sybille Lehwald, 2012. "Has the Euro Changed Business Cycle Synchronization? Evidence from the Core and the Periphery," ifo Working Paper Series 122, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    30. Ionuț JIANU, 2020. "Examining the drivers of business cycle divergence between Euro Area and Romania," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(2(623), S), pages 19-32, Summer.
    31. Michaelides, Panayotis G. & Tsionas, Efthymios G. & Konstantakis, Konstantinos N., 2018. "Debt dynamics in Europe: A Network General Equilibrium GVAR approach," Journal of Economic Dynamics and Control, Elsevier, vol. 93(C), pages 175-202.
    32. Marco Percoco, 2016. "Labour Market Institutions: Sensitivity to the Cycle and Impact of the Crisis in European Regions," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 107(3), pages 375-385, July.
    33. Theofanis Papageorgiou & Panayotis G. Michaelides & John G. Milios, 2011. "Technology and economic fluctuations in the US food sector (1958‐2006)," International Journal of Social Economics, Emerald Group Publishing Limited, vol. 38(2), pages 140-164, January.
    34. Jesús Crespo-Cuaresma & Octavio Fernández-Amador, 2010. "Business cycle convergence in EMU: A first look at the second moment," Working Papers 2010-22, Faculty of Economics and Statistics, Universität Innsbruck.
    35. Kovačić, Zlatko & Vilotić, Miloš, 2017. "Assessing European business cycles synchronization," MPRA Paper 79990, University Library of Munich, Germany.
    36. Jakob De Haan & Robert Inklaar & Richard Jong‐A‐Pin, 2008. "Will Business Cycles In The Euro Area Converge? A Critical Survey Of Empirical Research," Journal of Economic Surveys, Wiley Blackwell, vol. 22(2), pages 234-273, April.
    37. Ifrim Mihaela & Ignat Ion, 2009. "The European Business Cycle," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 332-336, May.
    38. Hasan Engin Duran & Alexandra Ferreira-Lopes, 2017. "Determinants of co-movement and of lead and lag behavior of business cycles in the Eurozone," International Review of Applied Economics, Taylor & Francis Journals, vol. 31(2), pages 255-282, March.
    39. Beate Schirwitz & Christian Seiler & Klaus Wohlrabe, 2009. "Regional business cycles in Germany – convergence," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 62(15), pages 23-32, August.
    40. Bergman, Michael, 2004. "How Similar Are European Business Cycles?," Working Papers 2004:9, Lund University, Department of Economics.
    41. Konstantakis, Konstantinos & Michaelides, Panayotis G., 2014. "The Political Economy of Car Sales in Athens, Greece," MPRA Paper 74489, University Library of Munich, Germany.
    42. Periklis Gogas, 2013. "Business cycle synchronisation in the European Union: The effect of the common currency," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2013(1), pages 1-14.
    43. Theophilos Papadimitriou & Periklis Gogas & Georgios-Antonios Sarantitis, 2014. "Convergence of European Business Cycles: A Complex Networks Approach," Working Paper series 35_14, Rimini Centre for Economic Analysis.
    44. Konstantinos Konstantakis & Theofanis Papageorgiou & Panayotis Michaelides & Efthymios Tsionas, 2015. "Economic Fluctuations and Fiscal Policy in Europe: A Political Business Cycles Approach Using Panel Data and Clustering (1996–2013)," Open Economies Review, Springer, vol. 26(5), pages 971-998, November.
    45. André, NYEMBWE & Konstantin, KHOLODILIN, 2005. "North-South Asymmetric Relationships : Does the EMU Business Affect Small African Economies ?," Discussion Papers (ECON - Département des Sciences Economiques) 2005032, Université catholique de Louvain, Département des Sciences Economiques.
    46. Gabriel Moser & Wolfgang Pointner & Gerhard Reitschuler, 2004. "Economic Growth in Denmark, Sweden and the United Kingdom since the Start of Monetary Union," Monetary Policy & the Economy, Oesterreichische Nationalbank (Austrian Central Bank), issue 4, pages 53-66.
    47. Panayotis G. Michaelides & Konstantinos N. Konstantakis, 2015. "Business Cycles and Economic Crisis: The Case of Car Sales in Athens, Greece (2000-2012)," Bulletin of Political Economy, Bulletin of Political Economy, vol. 9(1), pages 69-83, June.
    48. Antje Hildebrandt & Isabella Moder, 2015. "Business cycle synchronization between the Western Balkans and the European Union," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 3, pages 8-25.
    49. Panayotis G. Michaelides & Efthymios G. Tsionas & Angelos T. Vouldis & Konstantinos N. Konstantakis & Panagiotis Patrinos, 2018. "A Semi-Parametric Non-linear Neural Network Filter: Theory and Empirical Evidence," Computational Economics, Springer;Society for Computational Economics, vol. 51(3), pages 637-675, March.
    50. Susanne Bärenthaler-Sieber & Sandra Bilek-Steindl & Christian Glocker, 2013. "Trade Synchronisation During Major Economic Crises," WIFO Working Papers 449, WIFO.
    51. Bovi, M., 2005. "Economic Clubs and European Commitment. Evidence from the International Business Cycles," International Journal of Applied Econometrics and Quantitative Studies, Euro-American Association of Economic Development, vol. 2(2), pages 101-122.
    52. Sergiy Rakhmayil, 2010. "Did Financial Performance Of European Firms Improve And Converge After Introduction Of The Euro?," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 4(2), pages 27-41.
    53. Calcagnini, Giorgio & Travaglini, Giuseppe, 2014. "A time series analysis of labor productivity. Italy versus the European countries and the U.S," Economic Modelling, Elsevier, vol. 36(C), pages 622-628.
    54. Papageorgiou, Theofanis & Michaelides, Panayotis G. & Milios, John, 2009. "Economic Fluctuations, Cyclical Regularities and Technological Change: The U.S. Food Sector (1958–2006)," MPRA Paper 67115, University Library of Munich, Germany.
    55. Kappler Marcus, 2011. "Business Cycle Co-movement and Trade Intensity in the Euro Area: is there a Dynamic Link?," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(2), pages 247-265, April.
    56. Michaelides, Panayotis G. & Papageorgiou, Theofanis, 2012. "On the transmission of economic fluctuations from the USA to EU-15 (1960–2011)," Journal of Economics and Business, Elsevier, vol. 64(6), pages 427-438.
    57. Papageorgiou, Theofanis & Michaelides, Panayotis G. & Milios, John G., 2010. "Business cycles synchronization and clustering in Europe (1960-2009)," Journal of Economics and Business, Elsevier, vol. 62(5), pages 419-470, September.
    58. Demyanyk, Yuliya & Volosovych, Vadym, 2005. "Macroeconomic Asymmetry in the European Union: The Difference Between New and Old Members," CEPR Discussion Papers 4847, C.E.P.R. Discussion Papers.
    59. Papageorgiou, Theofanis & Michaelides, Panayotis G. & Tsionas, Efthymios G., 2016. "Business cycle determinants and fiscal policy: A Panel ARDL approach for EMU," The Journal of Economic Asymmetries, Elsevier, vol. 13(C), pages 57-68.
    60. Konstantakis, Konstantinos & Michaelides, Panayotis G. & Tsionas, Efthymios, 2015. "The Determinants of Economic Fluctuations in Greece: An Empirical Investigation (1995-2014)," MPRA Paper 74459, University Library of Munich, Germany.
    61. Ioanna Konstantakopoulou & Eftymios Tsionas & Tryphon Kollintzas, 2009. "Stylized Facts of Prices and Interest Rates over the Business Cycle," Economics Bulletin, AccessEcon, vol. 29(4), pages 2613-2627.
    62. Jianu, Ionut, 2020. "Examining the drivers of business cycle divergence between Euro Area and Romania," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 27(2), pages 19-32.
    63. Solomos, Dionysios & Papageorgiou, Theofanis & Koumparoulis, Dimitrios, 2012. "Financial Sector and Business Cycles Determinants in the EMU context: An Empirical Approach (1996-2011)," MPRA Paper 43858, University Library of Munich, Germany.
    64. Afflatet, Nicolas, 2014. "European Monetary Policy in the Heterogeneous Currency Area and the Open Question of Convergence," EconStor Preprints 93382, ZBW - Leibniz Information Centre for Economics.
    65. Hui-Ying Sng & Liyu Dou & Pradumna Bickram Rana, 2017. "Catalyst Of Business Cycle Synchronization In East Asia," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 62(03), pages 703-719, June.
    66. Gächter, Martin & Riedl, Aleksandra, 2014. "One money, one cycle? The EMU experience," Journal of Macroeconomics, Elsevier, vol. 42(C), pages 141-155.
    67. Matesanz, David & Ortega, Guillermo J., 2016. "On business cycles synchronization in Europe: A note on network analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 287-296.

  38. Dr Martin Weale & Dr. James Mitchell, 2001. "Quantification of qualitative firm-level survey data," National Institute of Economic and Social Research (NIESR) Discussion Papers 181, National Institute of Economic and Social Research.

    Cited by:

    1. Ulf von Kalckreuth & Emma Murphy, 2005. "Financial constraints and capacity adjustment in the United Kingdom: evidence from a large panel of survey data," Bank of England working papers 260, Bank of England.
    2. Bob McNabb & Karl Taylor, 2002. "Business Cycles and the Role of Confidence: Evidence from Europe," Discussion Papers in Economics 02/3, Division of Economics, School of Business, University of Leicester.
    3. Tatiana Cesaroni, 2011. "The cyclical behavior of the Italian business survey data," Empirical Economics, Springer, vol. 41(3), pages 747-768, December.
    4. Lahiri, Kajal & Zhao, Yongchen, 2015. "Quantifying survey expectations: A critical review and generalization of the Carlson–Parkin method," International Journal of Forecasting, Elsevier, vol. 31(1), pages 51-62.
    5. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“Tracking economic growth by evolving expectations via genetic programming: A two-step approach”," IREA Working Papers 201801, University of Barcelona, Research Institute of Applied Economics, revised Jan 2018.
    6. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "A Data-Driven Approach to Construct Survey-Based Indicators by Means of Evolutionary Algorithms," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 135(1), pages 1-14, January.
    7. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "“Let the data do the talking: Empirical modelling of survey-based expectations by means of genetic programming”," AQR Working Papers 201706, University of Barcelona, Regional Quantitative Analysis Group, revised May 2017.
    8. Lanse Minkler, 2002. "Shirking and Motivation in Firms: Survey Evidence on Worker Attitudes," Working papers 2002-37, University of Connecticut, Department of Economics.
    9. Bruno Giancarlo & Lupi Claudio, 2003. "Forecasting Euro-Area Industrial Production Using (Mostly) Business Surveys Data," ISAE Working Papers 33, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    10. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Evolutionary Computation for Macroeconomic Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 833-849, February.
    11. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Empirical modelling of survey-based expectations for the design of economic indicators in five European regions," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 46(2), pages 205-227, May.
    12. Leandro D�Aurizio & Stefano Iezzi, 2011. "Investment forecasting with business survey data," Temi di discussione (Economic working papers) 832, Bank of Italy, Economic Research and International Relations Area.
    13. Miguel A. Costa-Gomes & Georg Weizsäcker, 2008. "Stated Beliefs and Play in Normal-Form Games," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 75(3), pages 729-762.
    14. Oscar Claveria & Enric Monte & Salvador Torra, 2015. "“Self-organizing map analysis of agents’ expectations. Different patterns of anticipation of the 2008 financial crisis”," AQR Working Papers 201508, University of Barcelona, Regional Quantitative Analysis Group, revised Mar 2015.
    15. Breitung, Jörg & Schmeling, Maik, 2011. "Quantifying survey expectations: What's wrong with the probability approach?," Hannover Economic Papers (HEP) dp-485, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    16. Oscar Claveria, 2021. "Forecasting with Business and Consumer Survey Data," Forecasting, MDPI, vol. 3(1), pages 1-22, February.
    17. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "A new approach for the quantification of qualitative measures of economic expectations," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(6), pages 2685-2706, November.
    18. Tommaso Proietti & Cecilia Frale, 2007. "New proposals for the quantification of qualitative survey data," CEIS Research Paper 98, Tor Vergata University, CEIS.
    19. David Bywaters & Gareth Thomas, 2008. "Output Expectations and Forecasting of UK Manufacturing," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 36(2), pages 125-137, June.
    20. G. Bruno & L. Crosilla & P. Margani, 2019. "Inspecting the Relationship Between Business Confidence and Industrial Production: Evidence on Italian Survey Data," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 15(1), pages 1-24, April.
    21. Ulf von Kalckreuth, 2005. "Financial constraints and real activity: a non-structural approach using UK survey data," BIS Papers chapters, in: Bank for International Settlements (ed.), Investigating the relationship between the financial and real economy, volume 22, pages 64-80, Bank for International Settlements.
    22. Kajal Lahiri & Yongchen Zhao, 2013. "Quantifying Heterogeneous Survey Expectations: The Carlson-Parkin Method Revisited," Discussion Papers 13-08, University at Albany, SUNY, Department of Economics.
    23. Nolte, Ingmar & Pohlmeier, Winfried, 2007. "Using forecasts of forecasters to forecast," International Journal of Forecasting, Elsevier, vol. 23(1), pages 15-28.

Articles

  1. Ana Beatriz Galvão & James Mitchell, 2024. "Communicating Data Uncertainty: Multiwave Experimental Evidence for UK GDP," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 56(1), pages 81-114, February.
    See citations under working paper version above.
  2. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2023. "Reconciled Estimates of Monthly GDP in the United States," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(2), pages 563-577, April.

    Cited by:

    1. Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2024. "Forecasting Growth-at-Risk of the United States: Housing Price versus Housing Sentiment or Attention," Working Papers 202401, University of Pretoria, Department of Economics.

  3. Galvão, Ana Beatriz & Garratt, Anthony & Mitchell, James, 2021. "Does judgment improve macroeconomic density forecasts?," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1247-1260.
    See citations under working paper version above.
  4. Koop, Gary & McIntyre, Stuart & Mitchell, James & Poon, Aubrey, 2021. "Nowcasting ‘True’ Monthly U.S. Gdp During The Pandemic," National Institute Economic Review, National Institute of Economic and Social Research, vol. 256, pages 44-70, April.
    See citations under working paper version above.
  5. Koop, Gary & McIntyre, Stuart & Mitchell, James & Poon, Aubrey, 2020. "Reconciled Estimates And Nowcasts Of Regional Output In The Uk," National Institute Economic Review, National Institute of Economic and Social Research, vol. 253, pages 44-59, August.

    Cited by:

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

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

    Cited by:

    1. Martin Feldkircher & Florian Huber & Michael Pfarrhofer, 2021. "Measuring the effectiveness of US monetary policy during the COVID‐19 recession," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(3), pages 287-297, July.
    2. Robert Lehmann & Sascha Möhrle, 2022. "Forecasting Regional Industrial Production with High-Frequency Electricity Consumption Data," CESifo Working Paper Series 9917, CESifo.
    3. Robert Lehmann & Ida Wikman, 2022. "Quarterly GDP Estimates for the German States," ifo Working Paper Series 370, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    4. Joshua Chan, 2023. "BVARs and Stochastic Volatility," Papers 2310.14438, arXiv.org.
    5. 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.
    6. Michael Beenstock & Daniel Felsenstein, 2021. "A Solution for Absent Spatial Data: The Common Correlated Effects Estimator," International Regional Science Review, , vol. 44(3-4), pages 466-484, May.
    7. Mehmet Balcilar & David Gabauer & Rangan Gupta & Christian Pierdzioch, 2021. "Uncertainty and Forecastability of Regional Output Growth in the United Kingdom: Evidence from Machine Learning," Working Papers 202111, University of Pretoria, Department of Economics.
    8. Li Zhe & Serhat Yüksel & Hasan Dinçer & Shahriyar Mukhtarov & Mayis Azizov, 2021. "The Positive Influences of Renewable Energy Consumption on Financial Development and Economic Growth," SAGE Open, , vol. 11(3), pages 21582440211, August.
    9. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2020. "Regional output growth in the United Kingdom: More timely and higher frequency estimates from 1970," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(2), pages 176-197, March.
    10. Mehmet Balcilar & David Gabauer & Rangan Gupta & Christian Pierdzioch, 2022. "Uncertainty and forecastability of regional output growth in the UK: Evidence from machine learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1049-1064, September.

  7. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2020. "Regional output growth in the United Kingdom: More timely and higher frequency estimates from 1970," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(2), pages 176-197, March.

    Cited by:

    1. Martin Feldkircher & Florian Huber & Michael Pfarrhofer, 2021. "Measuring the effectiveness of US monetary policy during the COVID‐19 recession," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(3), pages 287-297, July.
    2. Robert Lehmann & Sascha Möhrle, 2022. "Forecasting Regional Industrial Production with High-Frequency Electricity Consumption Data," CESifo Working Paper Series 9917, CESifo.
    3. Robert Lehmann & Ida Wikman, 2022. "Quarterly GDP Estimates for the German States," ifo Working Paper Series 370, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    4. Matteo Iacopini & Aubrey Poon & Luca Rossini & Dan Zhu, 2022. "Bayesian Mixed-Frequency Quantile Vector Autoregression: Eliciting tail risks of Monthly US GDP," Papers 2209.01910, arXiv.org.
    5. Robert Lehmann, 2020. "The Forecasting Power of the ifo Business Survey," CESifo Working Paper Series 8291, CESifo.
    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.
    8. Huber, Florian & Koop, Gary & Onorante, Luca & Pfarrhofer, Michael & Schreiner, Josef, 2023. "Nowcasting in a pandemic using non-parametric mixed frequency VARs," Journal of Econometrics, Elsevier, vol. 232(1), pages 52-69.
    9. Joshua Chan, 2023. "BVARs and Stochastic Volatility," Papers 2310.14438, arXiv.org.
    10. Friederike Fourné & Robert Lehmann, 2023. "From Shopping to Statistics: Tracking and Nowcasting Private Consumption Expenditures in Real-Time," CESifo Working Paper Series 10764, CESifo.
    11. 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.
    12. Joshua C. C. Chan, 2022. "Comparing Stochastic Volatility Specifications for Large Bayesian VARs," Papers 2208.13255, arXiv.org.
    13. Haoqi Qian & Zhengyu Shi & Libo Wu, 2021. "Inferring Economic Condition Uncertainty from Electricity Big Data," Papers 2107.11593, arXiv.org, revised May 2023.
    14. Marcellino, Massimiliano & Bai, Yu & Carriero, Andrea & Clark, Todd, 2022. "Macroeconomic Forecasting in a Multi-country Context," CEPR Discussion Papers 16994, C.E.P.R. Discussion Papers.
    15. Bhattacharjee, Arnab & Lisauskaite, Elena & Pabst, Adrian, 2021. "UK regional outlook," National Institute UK Economic Outlook, National Institute of Economic and Social Research, issue 2, pages 42-57.
    16. 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).
    17. Deborah Gefang & Gary Koop & Aubrey Poon, 2020. "Computationally Efficient Inference in Large Bayesian Mixed Frequency VARs," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2020-07, Economic Statistics Centre of Excellence (ESCoE).
    18. Niesr, 2021. "Overview," National Institute UK Economic Outlook, National Institute of Economic and Social Research, issue 2, pages 1-4.
    19. Josh Martin & Rebecca Riley, 2023. "Productivity measurement - Reassessing the production function from micro to macro," Working Papers 033, The Productivity Institute.
    20. Kucuk, Hande & Lenoel, Cyrille & MacQueen, Rory, 2021. "Brisk but not better growth," National Institute UK Economic Outlook, National Institute of Economic and Social Research, issue 2, pages 5-32.
    21. Robert Lehmann, 2023. "READ-GER: Introducing German Real-Time Regional Accounts Data for Revision Analysis and Nowcasting," CESifo Working Paper Series 10315, CESifo.
    22. Chadha, Jagjit S., 2021. "Foreward," National Institute UK Economic Outlook, National Institute of Economic and Social Research, issue 2, pages 1-3.
    23. Mehmet Balcilar & David Gabauer & Rangan Gupta & Christian Pierdzioch, 2021. "Uncertainty and Forecastability of Regional Output Growth in the United Kingdom: Evidence from Machine Learning," Working Papers 202111, University of Pretoria, Department of Economics.
    24. Proietti, Tommaso & Giovannelli, Alessandro & Ricchi, Ottavio & Citton, Ambra & Tegami, Christían & Tinti, Cristina, 2021. "Nowcasting GDP and its components in a data-rich environment: The merits of the indirect approach," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1376-1398.
    25. Kucuk, Hande & Lenoel, Cyrille & MacQueen, Rory, 2021. "UK sectoral output," National Institute UK Economic Outlook, National Institute of Economic and Social Research, issue 2, pages 33-41.
    26. Niesr, 2021. "Appendix," National Institute UK Economic Outlook, National Institute of Economic and Social Research, issue 2, pages 58-66.
    27. Luca Barbaglia & Lorenzo Frattarolo & Niko Hauzenberger & Dominik Hirschbuehl & Florian Huber & Luca Onorante & Michael Pfarrhofer & Luca Tiozzo Pezzoli, 2024. "Nowcasting economic activity in European regions using a mixed-frequency dynamic factor model," Papers 2401.10054, arXiv.org.
    28. Blagov, Boris & Müller, Henrik & Jentsch, Carsten & Schmidt, Torsten, 2021. "The investment narrative: Improving private investment forecasts with media data," Ruhr Economic Papers 921, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    29. Mehmet Balcilar & David Gabauer & Rangan Gupta & Christian Pierdzioch, 2022. "Uncertainty and forecastability of regional output growth in the UK: Evidence from machine learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1049-1064, September.

  8. James Mitchell & Donald Robertson & Stephen Wright, 2019. "R2 Bounds for Predictive Models: What Univariate Properties Tell us About Multivariate Predictability," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(4), pages 681-695, October.
    See citations under working paper version above.
  9. Kapetanios, G. & Mitchell, J. & Price, S. & Fawcett, N., 2015. "Generalised density forecast combinations," Journal of Econometrics, Elsevier, vol. 188(1), pages 150-165.
    See citations under working paper version above.
  10. Gian Luigi Mazzi & James Mitchell & Gaetana Montana, 2014. "Density Nowcasts and Model Combination: Nowcasting Euro-Area GDP Growth over the 2008–09 Recession," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(2), pages 233-256, April.

    Cited by:

    1. Pablo Aguilar & Corinna Ghirelli & Matías Pacce & Alberto Urtasun, 2020. "Can news help measure economic sentiment? An application in COVID-19 times," Working Papers 2027, Banco de España.
    2. 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.
    3. 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.
    4. Tommaso Proietti & Martyna Marczak & Gianluigi Mazzi, 2015. "EuroMInd-D: A Density Estimate of Monthly Gross Domestic Product for the Euro Area," CEIS Research Paper 340, Tor Vergata University, CEIS, revised 10 Apr 2015.
    5. 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.
    6. Matteo Luciani & Lorenzo Ricci, 2014. "Nowcasting Norway," International Journal of Central Banking, International Journal of Central Banking, vol. 10(4), pages 215-248, December.
    7. Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2017. "Density Forecasts With Midas Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(4), pages 783-801, June.
    8. 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.
    9. 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.
    10. Grant Allan & Gary Koop & Stuart McIntyre & Paul Smith, 2019. "Nowcasting Using Mixed Frequency Methods: An Application to the Scottish Economy," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(1), pages 12-45, September.
    11. 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.
    12. Clark, Todd E. & Doh, Taeyoung, 2014. "Evaluating alternative models of trend inflation," International Journal of Forecasting, Elsevier, vol. 30(3), pages 426-448.
    13. Liu, Li & Wang, Yudong & Yang, Li, 2018. "Predictability of crude oil prices: An investor perspective," Energy Economics, Elsevier, vol. 75(C), pages 193-205.
    14. Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2019. "Density Forecasting," BEMPS - Bozen Economics & Management Paper Series BEMPS59, Faculty of Economics and Management at the Free University of Bozen.

  11. Garratt, Anthony & Mitchell, James & Vahey, Shaun P., 2014. "Measuring output gap nowcast uncertainty," International Journal of Forecasting, Elsevier, vol. 30(2), pages 268-279.
    See citations under working paper version above.
  12. Kapetanios, George & Mitchell, James & Shin, Yongcheol, 2014. "A nonlinear panel data model of cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 179(2), pages 134-157.
    See citations under working paper version above.
  13. James Mitchell & Richard J. Smith & Martin R. Weale, 2013. "Efficient Aggregation Of Panel Qualitative Survey Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(4), pages 580-603, June.
    See citations under working paper version above.
  14. Mitchell, James & Solomou, Solomos & Weale, Martin, 2012. "Monthly GDP estimates for inter-war Britain," Explorations in Economic History, Elsevier, vol. 49(4), pages 543-556.
    See citations under working paper version above.
  15. Silvia Lui & James Mitchell & Martin Weale, 2011. "Qualitative business surveys: signal or noise?," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 174(2), pages 327-348, April.
    See citations under working paper version above.
  16. Lui, Silvia & Mitchell, James & Weale, Martin, 2011. "The utility of expectational data: Firm-level evidence using matched qualitative-quantitative UK surveys," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1128-1146, October.
    See citations under working paper version above.
  17. 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.
    See citations under working paper version above.
  18. James Mitchell & Nigel Pain & Rebecca Riley, 2011. "The drivers of international migration to the UK: A panel‐based Bayesian model averaging approach," Economic Journal, Royal Economic Society, vol. 121(557), pages 1398-1444, December.

    Cited by:

    1. James Rockey & Jonathan Temple, 2015. "Growth Econometrics for Agnostics and True Believers," Bristol Economics Discussion Papers 15/656, School of Economics, University of Bristol, UK.
    2. Protte, Benjamin, 2012. "How does Economic Integration Change Personal Income Taxation? Evidence from a new Index of Potential Labor Mobility," Working Papers 12-20, University of Mannheim, Department of Economics.
    3. Christie Smith & Christoph Thoenissen, 2018. "Migration and Business Cycle Dynamics," Reserve Bank of New Zealand Discussion Paper Series DP2018/07, Reserve Bank of New Zealand.
    4. Mariam Camarero & Laura Montolio & Cecilio Tamarit, 2019. "Determinants of German outward FDI: variable selection using Bayesian statistical," Working Papers 1906, Department of Applied Economics II, Universidad de Valencia.
    5. Silvia Angeloni & Francesco Maria Spano, 2018. "Asylum Seekers in Europe: Issues and Solutions," Journal of International Migration and Integration, Springer, vol. 19(2), pages 473-495, May.
    6. Smith, Christie & Thoenissen, Christoph, 2019. "Skilled migration and business cycle dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 109(C).
    7. Camarero, Mariam & Montolio, Laura & Tamarit, Cecilio, 2019. "What drives German foreign direct investment? New evidence using Bayesian statistical techniques," Economic Modelling, Elsevier, vol. 83(C), pages 326-345.
    8. Mariam Camarero & Laura Montolio & Cecilio Tamarit, 2019. "Alternative Estimators For The Fdi Gravity Model: An Application To German Outward Fdi," Working Papers 1907, Department of Applied Economics II, Universidad de Valencia.
    9. Enrique Moral-Benito, 2015. "Model Averaging In Economics: An Overview," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 46-75, February.
    10. Mathias Czaika & Hein De Haas, 2013. "The Effectiveness of Immigration Policies," Population and Development Review, The Population Council, Inc., vol. 39(3), pages 487-508, September.
    11. Yufei Lin & Yingxia Pu & Xinyi Zhao & Guangqing Chi & Cui Ye, 2023. "The Spatiotemporal Elasticity of Age Structure in China’s Interprovincial Migration System," Sustainability, MDPI, vol. 15(10), pages 1-18, May.

  19. James Mitchell & Kenneth F. Wallis, 2011. "Evaluating density forecasts: forecast combinations, model mixtures, calibration and sharpness," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(6), pages 1023-1040, September.

    Cited by:

    1. Li, Li & Kang, Yanfei & Li, Feng, 2023. "Bayesian forecast combination using time-varying features," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1287-1302.
    2. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2020. "The contribution of intraday jumps to forecasting the density of returns," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-02505861, HAL.
    3. Jonas Dovern & Hans Manner, 2018. "Order Invariant Tests for Proper Calibration of Multivariate Density Forecasts," CESifo Working Paper Series 7023, CESifo.
    4. Harvey, A. & Palumbo, D., 2019. "Score-Driven Models for Realized Volatility," Cambridge Working Papers in Economics 1950, Faculty of Economics, University of Cambridge.
    5. Emilio Zanetti Chini, 2018. "Forecaster’s utility and forecasts coherence," CREATES Research Papers 2018-01, Department of Economics and Business Economics, Aarhus University.
    6. Carola Conces Binder & Rodrigo Sekkel, 2023. "Central Bank Forecasting: A Survey," Staff Working Papers 23-18, Bank of Canada.
    7. 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.).
    8. 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.
    9. Gian Luigi Mazzi & James Mitchell & Gaetana Montana, 2014. "Density Nowcasts and Model Combination: Nowcasting Euro-Area GDP Growth over the 2008–09 Recession," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(2), pages 233-256, April.
    10. João Henrique G. Mazzeu & Gloria González-Rivera & Esther Ruiz & Helena Veiga, 2020. "A bootstrap approach for generalized Autocontour testing Implications for VIX forecast densities," Econometric Reviews, Taylor & Francis Journals, vol. 39(10), pages 971-990, November.
    11. Francesco Ravazzolo & Shaun P. Vahey, 2010. "Forecast densities for economic aggregates from disaggregate ensembles," Working Paper 2010/02, Norges Bank.
    12. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2020. "The contribution of intraday jumps to forecasting the density of returns," Post-Print halshs-02505861, HAL.
    13. Malte Knüppel & Guido Schultefrankenfeld, 2017. "Interest rate assumptions and predictive accuracy of central bank forecasts," Empirical Economics, Springer, vol. 53(1), pages 195-215, August.
    14. Barbara Rossi & Tatevik Sekhposyan, 2013. "Evaluating predictive densities of U.S. output growth and inflation in a large macroeconomic data set," Economics Working Papers 1370, Department of Economics and Business, Universitat Pompeu Fabra.
    15. Hanan Naser, 2015. "Estimating and forecasting Bahrain quarterly GDP growth using simple regression and factor-based methods," Empirical Economics, Springer, vol. 49(2), pages 449-479, September.
    16. Tamás Kiss & Hoang Nguyen & Pär Österholm, 2021. "Modelling Returns in US Housing Prices—You’re the One for Me, Fat Tails," JRFM, MDPI, vol. 14(11), pages 1-17, October.
    17. Andrew B. Martinez, 2020. "Forecast Accuracy Matters for Hurricane Damages," Working Papers 2020-003, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    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. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024.
    20. Matteo Mogliani & Anna Simoni, 2020. "Bayesian MIDAS penalized regressions: Estimation, selection, and prediction," Post-Print hal-03089878, HAL.
    21. Ana Beatriz Galvão & James Mitchell, 2023. "Real‐Time Perceptions of Historical GDP Data Uncertainty," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 457-481, June.
    22. Andres, P. & Harvey, A., 2012. "The Dyanamic Location/Scale Model: with applications to intra-day financial data," Cambridge Working Papers in Economics 1240, Faculty of Economics, University of Cambridge.
    23. Raffaella Giacomini & Barbara Rossi, 2014. "Forecasting in Nonstationary Environments: What Works and What Doesn't in Reduced-Form and Structural Models," Working Papers 819, Barcelona School of Economics.
    24. Kenneth C. Lichtendahl & Yael Grushka-Cockayne & Robert L. Winkler, 2013. "Is It Better to Average Probabilities or Quantiles?," Management Science, INFORMS, vol. 59(7), pages 1594-1611, July.
    25. Andres, Philipp, 2014. "Maximum likelihood estimates for positive valued dynamic score models; The DySco package," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 34-42.
    26. Boriss Siliverstovs, 2013. "Do business tendency surveys help in forecasting employment?: A real-time evidence for Switzerland," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2013(2), pages 129-151.
    27. Rodríguez, Gabriel, 2017. "Modeling Latin-American stock and Forex markets volatility: Empirical application of a model with random level shifts and genuine long memory," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 393-420.
    28. Justyna Wróblewska & Anna Pajor, 2019. "One-period joint forecasts of Polish inflation, unemployment and interest rate using Bayesian VEC-MSF models," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 11(1), pages 23-45, March.
    29. 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).
    30. Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2015. "Bayesian nonparametric calibration and combination of predictive distributions," Working Paper 2015/03, Norges Bank.
    31. Kolasa, Marcin & Rubaszek, Michał, 2014. "Forecasting with DSGE models with financial frictions," Dynare Working Papers 40, CEPREMAP.
    32. Mansoor Maitah & Daniel Toth & Elena Kuzmenko & Karel r dl & Helena Rezbov & Petra nov, 2016. "Forecast of Employment in Switzerland: The Macroeconomic View," International Journal of Economics and Financial Issues, Econjournals, vol. 6(1), pages 132-138.
    33. Galvao, Ana Beatriz, 2016. "Data Revisions and DSGE Models," EMF Research Papers 11, Economic Modelling and Forecasting Group.
    34. James Mitchell & Aubrey Poon & Dan Zhu, 2022. "Constructing Density Forecasts from Quantile Regressions: Multimodality in Macro-Financial Dynamics," Working Papers 22-12R, Federal Reserve Bank of Cleveland, revised 11 Apr 2023.
    35. Andres Trujillo-Barrera & Philip Garcia & Mindy L Mallory, 2018. "Short-term price density forecasts in the lean hog futures market," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 45(1), pages 121-142.
    36. Nalban, Valeriu, 2018. "Forecasting with DSGE models: What frictions are important?," Economic Modelling, Elsevier, vol. 68(C), pages 190-204.
    37. Ito, Ryoko, 2013. "Modeling Dynamic Diurnal Patterns in High-Frequency Financial Data," Cambridge Working Papers in Economics 1315, Faculty of Economics, University of Cambridge.
    38. Garratt, Anthony & Mitchell, James & Vahey, Shaun P., 2014. "Measuring output gap nowcast uncertainty," International Journal of Forecasting, Elsevier, vol. 30(2), pages 268-279.
    39. Gergely Akos Ganics, 2017. "Optimal density forecast combinations," Working Papers 1751, Banco de España.
    40. Andrea Carriero & Galvao, Ana Beatriz & Kapetanios, George, 2016. "A comprehensive evaluation of macroeconomic forecasting methods," EMF Research Papers 10, Economic Modelling and Forecasting Group.
    41. Piergiorgio Alessandri & Haroon Mumtaz, 2017. "Financial conditions and density forecasts for US output and inflation," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 24, pages 66-78, March.
    42. Malte Knüppel, 2015. "Evaluating the Calibration of Multi-Step-Ahead Density Forecasts Using Raw Moments," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 270-281, April.
    43. Kenny, Geoff & Kostka, Thomas & Masera, Federico, 2014. "Density characteristics and density forecast performance: a panel analysis," Working Paper Series 1679, European Central Bank.
    44. Marc-Oliver Pohle, 2020. "The Murphy Decomposition and the Calibration-Resolution Principle: A New Perspective on Forecast Evaluation," Papers 2005.01835, arXiv.org.
    45. 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.
    46. Geoff Kenny & Thomas Kostka & Federico Masera, 2015. "Can Macroeconomists Forecast Risk? Event-Based Evidence from the Euro-Area SPF," International Journal of Central Banking, International Journal of Central Banking, vol. 11(4), pages 1-46, December.
    47. 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.
    48. Chorro, Christophe & Ielpo, Florian & Sévi, Benoît, 2020. "The contribution of intraday jumps to forecasting the density of returns," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    49. Taylor, James W., 2020. "A strategic predictive distribution for tests of probabilistic calibration," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1380-1388.
    50. 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.
    51. Wojciech CHAREMZA & Carlos DÍAZ & Svetlana MAKAROVA, 2019. "Conditional Term Structure of Inflation Forecast Uncertainty: The Copula Approach," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 5-18, March.
    52. Marcus P. A. Cobb, 2020. "Aggregate density forecasting from disaggregate components using Bayesian VARs," Empirical Economics, Springer, vol. 58(1), pages 287-312, January.
    53. Zeyyad Mandalinci, 2015. "Forecasting Inflation in Emerging Markets: An Evaluation of Alternative Models," CReMFi Discussion Papers 3, CReMFi, School of Economics and Finance, QMUL.
    54. Rafal Weron, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," HSC Research Reports HSC/14/07, Hugo Steinhaus Center, Wroclaw University of Technology.
    55. Tsyplakov, Alexander, 2014. "Theoretical guidelines for a partially informed forecast examiner," MPRA Paper 55017, University Library of Munich, Germany.
    56. Tsyplakov, Alexander, 2013. "Evaluation of Probabilistic Forecasts: Proper Scoring Rules and Moments," MPRA Paper 45186, University Library of Munich, Germany.
    57. Dovern, Jonas & Manner, Hans, 2016. "Order Invariant Evaluation of Multivariate Density Forecasts," Working Papers 0608, University of Heidelberg, Department of Economics.
    58. 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.
    59. Mitchell, James, 2013. "The Recalibrated and Copula Opinion Pools," EMF Research Papers 02, Economic Modelling and Forecasting Group.
    60. Manzan, Sebastiano & Zerom, Dawit, 2013. "Are macroeconomic variables useful for forecasting the distribution of U.S. inflation?," International Journal of Forecasting, Elsevier, vol. 29(3), pages 469-478.
    61. Kolassa, Stephan, 2016. "Evaluating predictive count data distributions in retail sales forecasting," International Journal of Forecasting, Elsevier, vol. 32(3), pages 788-803.
    62. 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.
    63. 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.
    64. Jorge Fornero & Andrés Gatty, 2020. "Back testing fan charts of activity and inflation: the Chilean case," Working Papers Central Bank of Chile 881, Central Bank of Chile.
    65. Tsyplakov, Alexander, 2012. "Assessment of probabilistic forecasts: Proper scoring rules and moments," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 27(3), pages 115-132.
    66. Djennad, Abdelmajid & Rigby, Robert & Stasinopoulos, Dimitrios & Voudouris, Vlasios & Eilers, Paul, 2015. "Beyond location and dispersion models: The Generalized Structural Time Series Model with Applications," MPRA Paper 62807, University Library of Munich, Germany.
    67. Liu, Li & Wang, Yudong & Yang, Li, 2018. "Predictability of crude oil prices: An investor perspective," Energy Economics, Elsevier, vol. 75(C), pages 193-205.
    68. Cobb, Marcus P A, 2017. "Aggregate Density Forecasting from Disaggregate Components Using Large VARs," MPRA Paper 76849, University Library of Munich, Germany.
    69. Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2019. "Density Forecasting," BEMPS - Bozen Economics & Management Paper Series BEMPS59, Faculty of Economics and Management at the Free University of Bozen.

  20. Garratt, Anthony & Mitchell, James & Vahey, Shaun P. & Wakerly, Elizabeth C., 2011. "Real-time inflation forecast densities from ensemble Phillips curves," The North American Journal of Economics and Finance, Elsevier, vol. 22(1), pages 77-87, January.
    See citations under working paper version above.
  21. Troy D. Matheson & James Mitchell & Brian Silverstone, 2010. "Nowcasting and predicting data revisions using panel survey data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(3), pages 313-330.

    Cited by:

    1. Dr Silvia Lui & Dr Martin Weale & Dr. James Mitchell, 2009. "The utility of expectational data: Firm-level evidence using matched qualitative-quantitative UK surveys," National Institute of Economic and Social Research (NIESR) Discussion Papers 343, National Institute of Economic and Social Research.
    2. Fornaro, Paolo, 2016. "Predicting Finnish economic activity using firm-level data," International Journal of Forecasting, Elsevier, vol. 32(1), pages 10-19.
    3. Sayag, Doron & Ben-hur, Dano & Pfeffermann, Danny, 2022. "Reducing revisions in hedonic house price indices by the use of nowcasts," International Journal of Forecasting, Elsevier, vol. 38(1), pages 253-266.
    4. Paolo Fornaro & Henri Luomaranta, 2020. "Nowcasting Finnish real economic activity: a machine learning approach," Empirical Economics, Springer, vol. 58(1), pages 55-71, January.
    5. Boysen-Hogrefe, Jens & Neuwirth, Stefan, 2012. "The impact of seasonal and price adjustments on the predictability of German GDP revisions," Kiel Working Papers 1753, Kiel Institute for the World Economy (IfW Kiel).
    6. Guizzardi, Andrea & Stacchini, Annalisa, 2015. "Real-time forecasting regional tourism with business sentiment surveys," Tourism Management, Elsevier, vol. 47(C), pages 213-223.
    7. Chrystalleni Aristidou & Kevin Lee & Kalvinder Shields, 2015. "Real-Time Data should be used in Forecasting Output Growth and Recessionary Events in the US," Discussion Papers 2015/13, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).
    8. Kjetil Martinsen & Francesco Ravazzolo & Fredrik Wulfsberg, 2011. "Forecasting macroeconomic variables using disaggregate survey data," Working Paper 2011/04, Norges Bank.

  22. Anne Sofie Jore & James Mitchell & Shaun P. Vahey, 2010. "Combining forecast densities from VARs with uncertain instabilities," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 621-634.
    See citations under working paper version above.
  23. Holmes, Mark J. & Mitchell, James & Silverstone, Brian, 2009. "Architects as Nowcasters of Housing Construction," National Institute Economic Review, National Institute of Economic and Social Research, vol. 210, pages 111-122, October.

    Cited by:

    1. Gustavo Adolfo HERNANDEZ DIAZ & Margarita MARÍN JARAMILLO, 2016. "Pronóstico del Consumo Privado: Usando datos de alta frecuencia para el pronóstico de variables de baja frecuencia," Archivos de Economía 14828, Departamento Nacional de Planeación.

  24. Mitchell, James, 2009. "Where are we now? The UK Recession and Nowcasting GDP Growth Using Statistical Models," National Institute Economic Review, National Institute of Economic and Social Research, vol. 209, pages 60-69, July.

    Cited by:

    1. P�r Österholm, 2014. "Survey data and short-term forecasts of Swedish GDP growth," Applied Economics Letters, Taylor & Francis Journals, vol. 21(2), pages 135-139, January.
    2. Giannone, Domenico & Reichlin, Lucrezia & Bańbura, Marta, 2010. "Nowcasting," Working Paper Series 1275, European Central Bank.
    3. Roberto Golinelli & Giuseppe Parigi, 2013. "Tracking world trade and GDP in real time," Temi di discussione (Economic working papers) 920, Bank of Italy, Economic Research and International Relations Area.
    4. Bengt Assarsson & Pär Österholm, 2015. "Do Swedish Consumer Confidence Indicators Do What They Are Intended to Do?," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot GmbH, Berlin, vol. 61(4), pages 391-404.
    5. Anesti, Nikoleta & Galvao, Ana Beatriz & Miranda-Agrippino, Silvia, 2018. "Uncertain kingdom: nowcasting GDP and its revisions," LSE Research Online Documents on Economics 90382, London School of Economics and Political Science, LSE Library.
    6. Steven Trypsteen, 2014. "The Importance of a Time-Varying Variance and Cross-Country Interactions in Forecast Models," Discussion Papers 2014/15, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).
    7. Billstam, Maria & Frändén, Kristina & Samuelsson, Johan & Österholm, Pär, 2016. "Quasi-Real-Time Data of the Economic Tendency Survey," Working Papers 143, National Institute of Economic Research.
    8. Nikoleta Anesti & Ana Beatriz Galvão & Silvia Miranda‐Agrippino, 2022. "Uncertain Kingdom: Nowcasting Gross Domestic Product and its revisions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 42-62, January.
    9. Ana Beatriz Galvão & Marta Lopresto, 2020. "Real-time Probabilistic Nowcasts of UK Quarterly GDP Growth using a Mixed-Frequency Bottom-up Approach," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2020-06, Economic Statistics Centre of Excellence (ESCoE).
    10. Stratford, Kate, 2013. "Nowcasting world GDP and trade using global indicators," Bank of England Quarterly Bulletin, Bank of England, vol. 53(3), pages 233-242.
    11. Christopher Adam & David Cobham, 2009. "Using Real-Time Output Gaps To Examine Past And Future Policy Choices," National Institute Economic Review, National Institute of Economic and Social Research, vol. 210(1), pages 98-110, October.
    12. Jennifer Castle & David Hendry & Oleg Kitov, 2013. "Forecasting and Nowcasting Macroeconomic Variables: A Methodological Overview," Economics Series Working Papers 674, University of Oxford, Department of Economics.
    13. Smith Paul, 2016. "Nowcasting UK GDP during the depression," Working Papers 1606, University of Strathclyde Business School, Department of Economics.

  25. Ehsan Khoman & James Mitchell & Martin Weale, 2008. "Incidence‐based estimates of life expectancy of the healthy for the UK: coherence between transition probabilities and aggregate life‐tables," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(1), pages 203-222, January.

    Cited by:

    1. William Lim & Gaurav Khemka & David Pitt & Bridget Browne, 2019. "A method for calculating the implied no-recovery three-state transition matrix using observable population mortality incidence and disability prevalence rates among the elderly," Journal of Population Research, Springer, vol. 36(3), pages 245-282, September.
    2. Dr Silvia Lui & Dr Martin Weale, 2012. "Education and its Effects on Survival, Income and Health of those aged Sixty-five and over in the United Kingdom," National Institute of Economic and Social Research (NIESR) Discussion Papers 393, National Institute of Economic and Social Research.
    3. Dorsett, Richard & Lui, Silvia & Weale, Martin, 2014. "Education and its effects on income and mortality of men aged sixty-five and over in Great Britain," Labour Economics, Elsevier, vol. 27(C), pages 71-82.

  26. Mitchell, James & Mouratidis, Kostas & Weale, Martin, 2007. "Uncertainty in UK manufacturing: Evidence from qualitative survey data," Economics Letters, Elsevier, vol. 94(2), pages 245-252, February.
    See citations under working paper version above.
  27. Hall, Stephen G. & Mitchell, James, 2007. "Combining density forecasts," International Journal of Forecasting, Elsevier, vol. 23(1), pages 1-13.

    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. Hautsch, Nikolaus & Voigt, Stefan, 2017. "Large-scale portfolio allocation under transaction costs and model uncertainty," CFS Working Paper Series 582, Center for Financial Studies (CFS).
    3. Li, Li & Kang, Yanfei & Li, Feng, 2023. "Bayesian forecast combination using time-varying features," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1287-1302.
    4. 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.
    5. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    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. Michal Franta & Jozef Barunik & Roman Horvath & Katerina Smidkova, 2011. "Are Bayesian Fan Charts Useful for Central Banks? Uncertainty, Forecasting, and Financial Stability Stress Tests," Working Papers 2011/10, Czech National Bank.
    8. Pauwels, Laurent & Radchenko, Peter & Vasnev, Andrey, 2019. "Higher Moment Constraints for Predictive Density Combinations," Working Papers BAWP-2019-01, University of Sydney Business School, Discipline of Business Analytics.
    9. 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.
    10. 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.
    11. Gian Luigi Mazzi & James Mitchell & Gaetana Montana, 2014. "Density Nowcasts and Model Combination: Nowcasting Euro-Area GDP Growth over the 2008–09 Recession," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(2), pages 233-256, April.
    12. Berg, Tim O. & Henzel, Steffen R., 2015. "Point and density forecasts for the euro area using Bayesian VARs," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1067-1095.
    13. Timmermann, Allan & Pettenuzzo, Davide, 2016. "Forecasting Macroeconomic Variables under Model Instability," CEPR Discussion Papers 11355, C.E.P.R. Discussion Papers.
    14. Deak, S. & Levine, P. & Mirza, A. & Pearlman, J., 2019. "Designing Robust Monetary Policy Using Prediction Pools," Working Papers 19/11, Department of Economics, City University London.
    15. Roberto Casarin & Fabrizio Leisen & German Molina & Enrique Ter Horst, 2014. "A Bayesian Beta Markov Random Field calibration of the term structure of implied risk neutral densities," Working Papers 2014:22, Department of Economics, University of Venice "Ca' Foscari".
    16. Pauwels, Laurent & Vasnev, Andrey, 2013. "Forecast combination for U.S. recessions with real-time data," Working Papers 02/2013, University of Sydney Business School, Discipline of Business Analytics.
    17. Buncic, Daniel, 2009. "Understanding forecast failure in ESTAR models of real exchange rates," MPRA Paper 13121, University Library of Munich, Germany.
    18. Davide Pettenuzzo & Francesco Ravazzolo, 2014. "Optimal portfolio choice under decision-based model combinations," Working Paper 2014/15, Norges Bank.
    19. Kenny, Geoff & Morgan, Julian, 2011. "Some lessons from the financial crisis for the economic analysis," Occasional Paper Series 130, European Central Bank.
    20. Kolassa, Stephan, 2011. "Combining exponential smoothing forecasts using Akaike weights," International Journal of Forecasting, Elsevier, vol. 27(2), pages 238-251, April.
    21. Richard K. Crump & Miro Everaert & Domenico Giannone & Sean Hundtofte, 2018. "Changing Risk-Return Profiles," Staff Reports 850, Federal Reserve Bank of New York.
    22. Marco J. Lombardi & Francesco Ravazzolo, 2012. "Oil price density forecasts: exploring the linkages with stock markets," Working Paper 2012/24, Norges Bank.
    23. Qian, Wei & Rolling, Craig A. & Cheng, Gang & Yang, Yuhong, 2022. "Combining forecasts for universally optimal performance," International Journal of Forecasting, Elsevier, vol. 38(1), pages 193-208.
    24. Hilde C. Bjørnland & Karsten Gerdrup & Anne Sofie Jore & Christie Smith & Leif Anders Thorsrud, 2012. "Does Forecast Combination Improve Norges Bank Inflation Forecasts?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(2), pages 163-179, April.
    25. 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.
    26. He, Yaoyao & Cao, Chaojin & Wang, Shuo & Fu, Hong, 2022. "Nonparametric probabilistic load forecasting based on quantile combination in electrical power systems," Applied Energy, Elsevier, vol. 322(C).
    27. Čapek, Jan & Crespo Cuaresma, Jesús & Hauzenberger, Niko & Reichel, Vlastimil, 2023. "Macroeconomic forecasting in the euro area using predictive combinations of DSGE models," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1820-1838.
    28. John Geweke & Gianni Amisano, 2008. "Optimal Prediction Pools," Working Paper series 22_08, Rimini Centre for Economic Analysis.
    29. Ruben Loaiza‐Maya & Gael M. Martin & David T. Frazier, 2021. "Focused Bayesian prediction," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 517-543, August.
    30. Benjamin Avanzi & Yanfeng Li & Bernard Wong & Alan Xian, 2022. "Ensemble distributional forecasting for insurance loss reserving," Papers 2206.08541, arXiv.org, revised Feb 2024.
    31. Paulo Mauricio Sánchez Beltrán & Luis Fernando Melo Velandia, 2013. "Combinación de brechas del producto colombiano," Borradores de Economia 10973, Banco de la Republica.
    32. Miranda-Agrippino, Silvia & Ricco, Giovanni, 2018. "Bayesian vector autoregressions," LSE Research Online Documents on Economics 87393, London School of Economics and Political Science, LSE Library.
    33. 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.
    34. Timmermann, Allan & Pettenuzzo, Davide & Gargano, Antonio, 2014. "Bond Return Predictability: Economic Value and Links to the Macroeconomy," CEPR Discussion Papers 10104, C.E.P.R. Discussion Papers.
    35. Wagner Piazza Gaglianone & Luiz Renato Lima, 2014. "Constructing Optimal Density Forecasts From Point Forecast Combinations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(5), pages 736-757, August.
    36. Hugo Gerard & Kristoffer Nimark, 2008. "Combining Multivariate Density Forecasts Using Predictive Criteria," RBA Research Discussion Papers rdp2008-02, Reserve Bank of Australia.
    37. Tamás Kiss & Hoang Nguyen & Pär Österholm, 2021. "Modelling Returns in US Housing Prices—You’re the One for Me, Fat Tails," JRFM, MDPI, vol. 14(11), pages 1-17, October.
    38. Lombardi, Marco J. & Ravazzolo, Francesco, 2016. "On the correlation between commodity and equity returns: Implications for portfolio allocation," Journal of Commodity Markets, Elsevier, vol. 2(1), pages 45-57.
    39. Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2019. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Working Paper 2019/2, Norges Bank.
    40. Cristina Conflitti & Christine De Mol & Domenico Giannone, 2012. "Optimal Combination of Survey Forecasts," Working Papers ECARES ECARES 2012-023, ULB -- Universite Libre de Bruxelles.
    41. Michael S. O’Doherty & N. E. Savin & Ashish Tiwari, 2016. "Evaluating Hedge Funds with Pooled Benchmarks," Management Science, INFORMS, vol. 62(1), pages 69-89, January.
    42. Allayioti, Anastasia & Venditti, Fabrizio, 2024. "The role of comovement and time-varying dynamics in forecasting commodity prices," Working Paper Series 2901, European Central Bank.
    43. Mehmet Balcilar & Nico Katzke & Rangan Gupta, 2015. "Do Precious Metal Prices Help in Forecasting South African Inflation?," Working Papers 03/2015, Stellenbosch University, Department of Economics.
    44. 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.
    45. Yi-Ting Chen & Chu-An Liu, 2021. "Model Averaging for Asymptotically Optimal Combined Forecasts," IEAS Working Paper : academic research 21-A002, Institute of Economics, Academia Sinica, Taipei, Taiwan.
    46. Jean-Guillaume Sahuc & Matteo Mogliani & Laurent Ferrara, 2022. "High-frequency monitoring of growth at risk," Post-Print hal-03361425, HAL.
    47. Marco Del Negro & Raiden B. Hasegawa & Frank Schorfheide, 2014. "Dynamic Prediction Pools: An Investigation of Financial Frictions and Forecasting Performance," PIER Working Paper Archive 14-034, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    48. Cang, Shuang & Yu, Hongnian, 2014. "A combination selection algorithm on forecasting," European Journal of Operational Research, Elsevier, vol. 234(1), pages 127-139.
    49. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2011. "Combining Predictive Densities using Bayesian Filtering with Applications to US Economics Data," Tinbergen Institute Discussion Papers 11-003/4, Tinbergen Institute.
    50. 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.
    51. 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.
    52. 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.
    53. Ardia, David & Lennart, Hoogerheide & Nienke, Corré, 2011. "Stock index returns’ density prediction using GARCH models: Frequentist or Bayesian estimation?," MPRA Paper 28259, University Library of Munich, Germany.
    54. 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.
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    45. Murdipi, Rafiqa & Law, Siong Hook, 2016. "Dynamic Linkages between Price Indices and Inflation in Malaysia," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 50(1), pages 41-52.
    46. Filippo Altissimo & Riccardo Cristadoro & Mario Forni & Marco Lippi & Giovanni Veronese, 2010. "New Eurocoin: Tracking Economic Growth in Real Time," The Review of Economics and Statistics, MIT Press, vol. 92(4), pages 1024-1034, November.
    47. Cristea, R. G., 2020. "Can Alternative Data Improve the Accuracy of Dynamic Factor Model Nowcasts?," Cambridge Working Papers in Economics 20108, Faculty of Economics, University of Cambridge.
    48. Weale, Martin & Wieladek, Tomasz, 2022. "Financial effects of QE and conventional monetary policy compared," Journal of International Money and Finance, Elsevier, vol. 127(C).
    49. Chevapatrakul, Thanaset & Kim, Tae-Hwan & Mizen, Paul, 2012. "Monetary information and monetary policy decisions: Evidence from the euroarea and the UK," Journal of Macroeconomics, Elsevier, vol. 34(2), pages 326-341.
    50. Sorić, Petar & Lolić, Ivana & Claveria, Oscar & Monte, Enric & Torra, Salvador, 2019. "Unemployment expectations: A socio-demographic analysis of the effect of news," Labour Economics, Elsevier, vol. 60(C), pages 64-74.
    51. Ana Beatriz Galvão & Marta Lopresto, 2020. "Real-time Probabilistic Nowcasts of UK Quarterly GDP Growth using a Mixed-Frequency Bottom-up Approach," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2020-06, Economic Statistics Centre of Excellence (ESCoE).
    52. Daniel Roash & Tanya Suhoy, 2019. "Sentiment Indicators Based on a Short Business Tendency Survey," Bank of Israel Working Papers 2019.11, Bank of Israel.
    53. Henning Hesse & Boris Hofmann & James Weber, 2017. "The macroeconomic effects of asset purchases revisited," BIS Working Papers 680, Bank for International Settlements.
    54. Tae-Hwan Kima & Paul Mizena & Alan Thanaset, 2007. "Predicting Directional Changes in Interest Rates: Gains from Using Information from Monetary Indicators," Discussion Papers 07/07, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).
    55. Conefrey, Thomas & Walsh, Graeme, 2018. "A Monthly Indicator of Economic Activity for Ireland," Economic Letters 14/EL/18, Central Bank of Ireland.
    56. Luis Frank, 2019. "Desagregación temporal de series económicas con programación lineal," Ensayos de Política Económica, Departamento de Investigación Francisco Valsecchi, Facultad de Ciencias Económicas, Pontificia Universidad Católica Argentina., vol. 3(1), pages 59-82, Octubre.
    57. Proietti, Tommaso & Giovannelli, Alessandro & Ricchi, Ottavio & Citton, Ambra & Tegami, Christían & Tinti, Cristina, 2021. "Nowcasting GDP and its components in a data-rich environment: The merits of the indirect approach," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1376-1398.
    58. Juergen Amann & Paul Middleditch, 2017. "Growth in a time of austerity: evidence from the UK," Scottish Journal of Political Economy, Scottish Economic Society, vol. 64(4), pages 349-375, September.
    59. Yasutomo Murasawa, 2016. "The Beveridge–Nelson decomposition of mixed-frequency series," Empirical Economics, Springer, vol. 51(4), pages 1415-1441, December.
    60. Luke Mosley & Idris A. Eckley & Alex Gibberd, 2022. "Sparse temporal disaggregation," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 2203-2233, October.
    61. Naveen Srinivasan & Vidya Mahambare & M. Ramachandran, 2006. "UK monetary policy under inflation forecast targeting: is behaviour consistent with symmetric preferences?," Oxford Economic Papers, Oxford University Press, vol. 58(4), pages 706-721, October.
    62. Jennifer Castle & David Hendry & Oleg Kitov, 2013. "Forecasting and Nowcasting Macroeconomic Variables: A Methodological Overview," Economics Series Working Papers 674, University of Oxford, Department of Economics.
    63. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2020. "Regional output growth in the United Kingdom: More timely and higher frequency estimates from 1970," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(2), pages 176-197, March.
    64. Churm, Rohan & Joyce, Michael & Kapetanios, George & Theodoridis, Konstantinos, 2021. "Unconventional monetary policies and the macroeconomy: The impact of the UK's QE2 and funding for lending scheme," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 721-736.
    65. Gilhooly, Robert & Weale, Martin & Wieladek, Tomasz, 2012. "Disaggregating the international business cycle," Discussion Papers 37, Monetary Policy Committee Unit, Bank of England.
    66. Bahaj, Saleem, 2020. "Sovereign spreads in the Euro area: Cross border transmission and macroeconomic implications," Journal of Monetary Economics, Elsevier, vol. 110(C), pages 116-135.
    67. Luke Mosley & Idris Eckley & Alex Gibberd, 2021. "Sparse Temporal Disaggregation," Papers 2108.05783, arXiv.org, revised Oct 2022.
    68. Boero, Gianna & Smith, Jeremy & Wallis, Kenneth F., 2008. "Evaluating a three-dimensional panel of point forecasts: The Bank of England Survey of External Forecasters," International Journal of Forecasting, Elsevier, vol. 24(3), pages 354-367.
    69. Paul Labonne, 2020. "Capturing GDP nowcast uncertainty in real time," Papers 2012.02601, arXiv.org, revised Oct 2021.
    70. Filippo Lechthaler & Lisa Leinert, 2019. "Moody oil: What is driving the crude oil price?," Empirical Economics, Springer, vol. 57(5), pages 1547-1578, November.

  29. James Mitchell & Richard J. Smith & Martin R. Weale, 2005. "Forecasting Manufacturing Output Growth Using Firm‐Level Survey Data," Manchester School, University of Manchester, vol. 73(4), pages 479-499, July.

    Cited by:

    1. Dr Silvia Lui & Dr Martin Weale & Dr. James Mitchell, 2009. "The utility of expectational data: Firm-level evidence using matched qualitative-quantitative UK surveys," National Institute of Economic and Social Research (NIESR) Discussion Papers 343, National Institute of Economic and Social Research.
    2. Driver, Ciaran & Muñoz-Bugarin, Jair, 2019. "Financial constraints on investment: Effects of firm size and the financial crisis," Research in International Business and Finance, Elsevier, vol. 47(C), pages 441-457.
    3. Lahiri, Kajal & Zhao, Yongchen, 2015. "Quantifying survey expectations: A critical review and generalization of the Carlson–Parkin method," International Journal of Forecasting, Elsevier, vol. 31(1), pages 51-62.
    4. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“Tracking economic growth by evolving expectations via genetic programming: A two-step approach”," IREA Working Papers 201801, University of Barcelona, Research Institute of Applied Economics, revised Jan 2018.
    5. James Mitchell & Richard J. Smith & Martin R. Weale, 2013. "Efficient Aggregation Of Panel Qualitative Survey Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(4), pages 580-603, June.
    6. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "A Data-Driven Approach to Construct Survey-Based Indicators by Means of Evolutionary Algorithms," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 135(1), pages 1-14, January.
    7. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "“Let the data do the talking: Empirical modelling of survey-based expectations by means of genetic programming”," AQR Working Papers 201706, University of Barcelona, Regional Quantitative Analysis Group, revised May 2017.
    8. Troy D. Matheson & James Mitchell & Brian Silverstone, 2010. "Nowcasting and predicting data revisions using panel survey data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(3), pages 313-330.
    9. Ciaran Driver, 2019. "Trade liberalization and South African manufacturing: Looking back with data," WIDER Working Paper Series wp-2019-30, World Institute for Development Economic Research (UNU-WIDER).
    10. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Evolutionary Computation for Macroeconomic Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 833-849, February.
    11. Troy Matheson & James Mitchell & Brian Silverstone, 2007. "Nowcasting and predicting data revisions in real time using qualitative panel survey data," Reserve Bank of New Zealand Discussion Paper Series DP2007/02, Reserve Bank of New Zealand.
    12. Sorić, Petar & Lolić, Ivana & Claveria, Oscar & Monte, Enric & Torra, Salvador, 2019. "Unemployment expectations: A socio-demographic analysis of the effect of news," Labour Economics, Elsevier, vol. 60(C), pages 64-74.
    13. Oscar Claveria & Enric Monte & Salvador Torra, 2015. "“Self-organizing map analysis of agents’ expectations. Different patterns of anticipation of the 2008 financial crisis”," AQR Working Papers 201508, University of Barcelona, Regional Quantitative Analysis Group, revised Mar 2015.
    14. Breitung, Jörg & Schmeling, Maik, 2011. "Quantifying survey expectations: What's wrong with the probability approach?," Hannover Economic Papers (HEP) dp-485, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    15. Guizzardi, Andrea & Stacchini, Annalisa, 2015. "Real-time forecasting regional tourism with business sentiment surveys," Tourism Management, Elsevier, vol. 47(C), pages 213-223.
    16. David Bywaters & Gareth Thomas, 2008. "Output Expectations and Forecasting of UK Manufacturing," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 36(2), pages 125-137, June.
    17. Maurizio Bovi, 2006. "Consumers Sentiment and Cognitive Macroeconometrics Paradoxes and Explanations," ISAE Working Papers 66, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    18. François Hild, 2006. "Un nouvel indicateur synthétique prenant en compte la dynamique des réponses individuelles à l'enquête Industrie," Économie et Statistique, Programme National Persée, vol. 395(1), pages 65-89.
    19. Olivier Biau & Hélène Erkel-Rousse & Nicolas Ferrari, 2006. "Réponses individuelles aux enquêtes de conjoncture et prévision de la production manufacturière," Économie et Statistique, Programme National Persée, vol. 395(1), pages 91-116.
    20. Kajal Lahiri & Yongchen Zhao, 2013. "Quantifying Heterogeneous Survey Expectations: The Carlson-Parkin Method Revisited," Discussion Papers 13-08, University at Albany, SUNY, Department of Economics.

  30. Michael Massmann & James Mitchell, 2005. "Reconsidering the Evidence: Are Euro Area Business Cycles Converging?," Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2004(3), pages 275-307.

    Cited by:

    1. Erdenebat Bataa & Denise R. Osborn & Marianne Sensier & Dick van Dijk, 2009. "Changes in International Business Cycle Affiliations," Centre for Growth and Business Cycle Research Discussion Paper Series 132, Economics, The University of Manchester.
    2. Hideaki Hirata & M. Ayhan Kose & Christopher Otrok, 2013. "Regionalization vs. globalization," Working Papers 2013-002, Federal Reserve Bank of St. Louis.
    3. Caleiro, António, 2011. "Acerca da importância da sincronização do ciclo económico português no contexto europeu [Why and how must Portugal be synchronized with the European Union?]," MPRA Paper 34993, University Library of Munich, Germany.
    4. Klaus Weyerstrass & Bas Aarle & Marcus Kappler & Atilim Seymen, 2011. "Business Cycle Synchronisation with(in) the Euro Area: in Search of a ‘Euro Effect’," Open Economies Review, Springer, vol. 22(3), pages 427-446, July.
    5. Torben Klarl, 2019. "The response of CO2 emissions to the business cycle: New evidence for the U.S," Bremen Papers on Economics & Innovation 1902, University of Bremen, Faculty of Business Studies and Economics.
    6. Klarl, Torben, 2020. "The response of CO2 emissions to the business cycle: New evidence for the U.S," Energy Economics, Elsevier, vol. 85(C).
    7. Luc Dresse & Christophe Van Nieuwenhuyze, 2008. "Do survey indicators let us see the business cycle ? A frequency decomposition," Working Paper Research 131, National Bank of Belgium.
    8. Holtemöller, Oliver (Ed.) & Rahn, Jörg (Ed.) & Stierle, Michael H. (Ed.), 2009. "Characteristics of Business Cycles: Have they Changed?," IWH-Sonderhefte 5/2009, Halle Institute for Economic Research (IWH).
    9. Marco Rubilar-González & Gabriel Pino, 2018. "Are Euro-Area expectations about recession phases effective to anticipate consequences of economic crises?," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 9(2), pages 141-161, June.
    10. Arčabić, Vladimir & Škrinjarić, Tihana, 2021. "Sharing is caring: Spillovers and synchronization of business cycles in the European Union," Economic Modelling, Elsevier, vol. 96(C), pages 25-39.
    11. Iulia Siedschlag, 2008. "Macroeconomic Differentials and Adjustment in the Euro Area," SUERF Studies, SUERF - The European Money and Finance Forum, number 2008/3 edited by Morten Balling, May.
    12. Jakob De Haan & Robert Inklaar & Richard Jong‐A‐Pin, 2008. "Will Business Cycles In The Euro Area Converge? A Critical Survey Of Empirical Research," Journal of Economic Surveys, Wiley Blackwell, vol. 22(2), pages 234-273, April.
    13. Gandjon Fankem, Gislain Stéphane & Fouda Mbesa, Lucien Cédric, 2023. "Business cycle synchronization and African monetary union: A wavelet analysis," Journal of Macroeconomics, Elsevier, vol. 77(C).
    14. Konstantakopoulou, Ioanna & Tsionas, Efthymios G., 2014. "Half a century of empirical evidence of business cycles in OECD countries," Journal of Policy Modeling, Elsevier, vol. 36(2), pages 389-409.
    15. Fernandez, Viviana, 2006. "Does domestic cooperation lead to business-cycle convergence and financial linkages?," The Quarterly Review of Economics and Finance, Elsevier, vol. 46(3), pages 369-396, July.
    16. Nenad Stanisic, 2013. "Convergence between the business cycles of Central and Eastern European countries and the Euro area," Baltic Journal of Economics, Baltic International Centre for Economic Policy Studies, vol. 13(1), pages 63-74, July.
    17. Esser, Andreas, 2014. "A Wavelet Approach to Synchronization of Output Cycles," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100545, Verein für Socialpolitik / German Economic Association.
    18. Ioanna Konstantakopoulou & Eftymios Tsionas & Tryphon Kollintzas, 2009. "Stylized Facts of Prices and Interest Rates over the Business Cycle," Economics Bulletin, AccessEcon, vol. 29(4), pages 2613-2627.
    19. Barrett, Alan & Bergin, Adele & FitzGerald, John & Traistaru-Siedschlag, Iulia, 2006. "Economic Assessment of the Euro Area: Forecasts and Policy Analysis, Autumn Report 2006," Research Series, Economic and Social Research Institute (ESRI), number sustat22, June.

  31. Mitchell, James, 2005. "The National Institute Density Forecasts of Inflation," National Institute Economic Review, National Institute of Economic and Social Research, vol. 193, pages 60-69, July.

    Cited by:

    1. Gian Luigi Mazzi & James Mitchell & Gaetana Montana, 2014. "Density Nowcasts and Model Combination: Nowcasting Euro-Area GDP Growth over the 2008–09 Recession," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(2), pages 233-256, April.
    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. Hall, Stephen G. & Mitchell, James, 2007. "Combining density forecasts," International Journal of Forecasting, Elsevier, vol. 23(1), pages 1-13.

  32. James Mitchell & Stephen G. Hall, 2005. "Evaluating, Comparing and Combining Density Forecasts Using the KLIC with an Application to the Bank of England and NIESR ‘Fan’ Charts of Inflation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 995-1033, December.

    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. Leopoldo Catania & Nima Nonejad, 2016. "Density Forecasts and the Leverage Effect: Some Evidence from Observation and Parameter-Driven Volatility Models," Papers 1605.00230, arXiv.org, revised Nov 2016.
    3. 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.
    4. Enzo D'Innocenzo & André Lucas & Anne Opschoor & Xingmin Zhang, 2024. "Heterogeneity and dynamics in network models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 150-173, January.
    5. Michael Clements, 2016. "Are Macroeconomic Density Forecasts Informative?," ICMA Centre Discussion Papers in Finance icma-dp2016-02, Henley Business School, University of Reading.
    6. Horatio Cuesdeanu & Jens Carsten Jackwerth, 2018. "The pricing kernel puzzle in forward looking data," Review of Derivatives Research, Springer, vol. 21(3), pages 253-276, October.
    7. Wang, Yudong & Liu, Li & Wu, Chongfeng, 2020. "Forecasting commodity prices out-of-sample: Can technical indicators help?," International Journal of Forecasting, Elsevier, vol. 36(2), pages 666-683.
    8. Gian Luigi Mazzi & James Mitchell & Gaetana Montana, 2014. "Density Nowcasts and Model Combination: Nowcasting Euro-Area GDP Growth over the 2008–09 Recession," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(2), pages 233-256, April.
    9. Berg, Tim O. & Henzel, Steffen R., 2015. "Point and density forecasts for the euro area using Bayesian VARs," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1067-1095.
    10. Michal Franta & David Havrlant & Marek Rusnák, 2016. "Forecasting Czech GDP Using Mixed-Frequency Data Models," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(2), pages 165-185, December.
    11. Anne Opschoor & André Lucas, 2019. "Time-varying tail behavior for realized kernels," Tinbergen Institute Discussion Papers 19-051/IV, Tinbergen Institute.
    12. Buncic, Daniel, 2009. "Understanding forecast failure in ESTAR models of real exchange rates," MPRA Paper 13121, University Library of Munich, Germany.
    13. Davide Pettenuzzo & Francesco Ravazzolo, 2014. "Optimal portfolio choice under decision-based model combinations," Working Paper 2014/15, Norges Bank.
    14. Francesco Ravazzolo & Shaun P. Vahey, 2010. "Forecast densities for economic aggregates from disaggregate ensembles," Working Paper 2010/02, Norges Bank.
    15. 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.
    16. Carlos Diaz Vela, 2016. "Extracting the Information Shocks from the Bank of England Inflation Density Forecasts," Discussion Papers in Economics 16/13, Division of Economics, School of Business, University of Leicester.
    17. Marco J. Lombardi & Francesco Ravazzolo, 2012. "Oil price density forecasts: exploring the linkages with stock markets," Working Paper 2012/24, Norges Bank.
    18. Matei Demetrescu & Mu-Chun Wang, 2014. "Incorporating Asymmetric Preferences into Fan Charts and Path Forecasts," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(2), pages 287-297, April.
    19. Dovern, Jonas & Glas, Alexander & Kenny, Geoff, 2023. "Testing for differences in survey-based density expectations: a compositional data approach," Working Paper Series 2791, European Central Bank.
    20. Paulo Mauricio Sánchez Beltrán & Luis Fernando Melo Velandia, 2013. "Combinación de brechas del producto colombiano," Borradores de Economia 10973, Banco de la Republica.
    21. Knüppel, Malte & Schultefrankenfeld, Guido, 2011. "How informative are central bank assessments of macroeconomic risks?," Discussion Paper Series 1: Economic Studies 2011,13, Deutsche Bundesbank.
    22. Xin Sheng & Rangan Gupta & Afees A. Salisu & Elie Bouri, 2021. "OPEC News and Exchange Rate Forecasting Using Dynamic Bayesian Learning," Working Papers 202101, University of Pretoria, Department of Economics.
    23. Lombardi, Marco J. & Ravazzolo, Francesco, 2016. "On the correlation between commodity and equity returns: Implications for portfolio allocation," Journal of Commodity Markets, Elsevier, vol. 2(1), pages 45-57.
    24. Ana Beatriz Galvão & James Mitchell, 2019. "Measuring Data Uncertainty: An Application using the Bank of England's "Fan Charts" for Historical GDP Growth," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2019-08, Economic Statistics Centre of Excellence (ESCoE).
    25. Knüppel, Malte & Schultefrankenfeld, Guido, 2018. "Assessing the uncertainty in central banks' inflation outlooks," Discussion Papers 56/2018, Deutsche Bundesbank.
    26. Allayioti, Anastasia & Venditti, Fabrizio, 2024. "The role of comovement and time-varying dynamics in forecasting commodity prices," Working Paper Series 2901, European Central Bank.
    27. Mehmet Balcilar & Nico Katzke & Rangan Gupta, 2015. "Do Precious Metal Prices Help in Forecasting South African Inflation?," Working Papers 03/2015, Stellenbosch University, Department of Economics.
    28. Barbara Rossi, 2019. "Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them," Economics Working Papers 1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
    29. Lennart Hoogerheide & Richard Kleijn & Francesco Ravazzolo & Herman K. Van Dijk & Marno Verbeek, 2010. "Forecast accuracy and economic gains from Bayesian model averaging using time-varying weights," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 251-269.
    30. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2011. "Combining Predictive Densities using Bayesian Filtering with Applications to US Economics Data," Tinbergen Institute Discussion Papers 11-003/4, Tinbergen Institute.
    31. 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.
    32. Ana Beatriz Galvão & James Mitchell, 2023. "Real‐Time Perceptions of Historical GDP Data Uncertainty," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 457-481, June.
    33. Ardia, David & Lennart, Hoogerheide & Nienke, Corré, 2011. "Stock index returns’ density prediction using GARCH models: Frequentist or Bayesian estimation?," MPRA Paper 28259, University Library of Munich, Germany.
    34. Götz, T.B. & Hecq, A.W. & Urbain, J.R.Y.J., 2014. "Combining distributions of real-time forecasts: An application to U.S. growth," Research Memorandum 027, Maastricht University, Graduate School of Business and Economics (GSBE).
    35. Diks, Cees & Panchenko, Valentyn & van Dijk, Dick, 2010. "Out-of-sample comparison of copula specifications in multivariate density forecasts," Journal of Economic Dynamics and Control, Elsevier, vol. 34(9), pages 1596-1609, September.
    36. Hoogerheide, Lennart F. & Ardia, David & Corré, Nienke, 2012. "Density prediction of stock index returns using GARCH models: Frequentist or Bayesian estimation?," Economics Letters, Elsevier, vol. 116(3), pages 322-325.
    37. Tommaso Proietti & Martyna Marczak & Gianluigi Mazzi, 2015. "EuroMInd-D: A Density Estimate of Monthly Gross Domestic Product for the Euro Area," CEIS Research Paper 340, Tor Vergata University, CEIS, revised 10 Apr 2015.
    38. Li, Zhao-Chen & Xie, Chi & Zeng, Zhi-Jian & Wang, Gang-Jin & Zhang, Ting, 2023. "Forecasting global stock market volatilities in an uncertain world," International Review of Financial Analysis, Elsevier, vol. 85(C).
    39. M. Mogliani & T. Ferrière, 2016. "Rationality of announcements, business cycle asymmetry, and predictability of revisions. The case of French GDP," Working papers 600, Banque de France.
    40. Boriss Siliverstovs, 2013. "Do business tendency surveys help in forecasting employment?: A real-time evidence for Switzerland," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2013(2), pages 129-151.
    41. Rodríguez, Gabriel, 2017. "Modeling Latin-American stock and Forex markets volatility: Empirical application of a model with random level shifts and genuine long memory," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 393-420.
    42. 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).
    43. Kolasa, Marcin & Rubaszek, Michał, 2014. "Forecasting with DSGE models with financial frictions," Dynare Working Papers 40, CEPREMAP.
    44. Cees Diks & Valentyn Panchenko & Oleg Sokolinskiy, & Dick van Dijk, 2013. "Comparing the Accuracy of Copula-Based Multivariate Density Forecasts in Selected Regions of Support," Tinbergen Institute Discussion Papers 13-061/III, Tinbergen Institute.
    45. Mouratidis, Kostas, 2008. "Evaluating currency crises: A Bayesian Markov switching approach," Journal of Macroeconomics, Elsevier, vol. 30(4), pages 1688-1711, December.
    46. Cees Diks & Valentyn Panchenko & Dick van Dijk, 2008. "Partial Likelihood-Based Scoring Rules for Evaluating Density Forecasts in Tails," Discussion Papers 2008-10, School of Economics, The University of New South Wales.
    47. Andres Trujillo-Barrera & Philip Garcia & Mindy L Mallory, 2018. "Short-term price density forecasts in the lean hog futures market," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 45(1), pages 121-142.
    48. Zdeněk Zmeškal & Dana Dluhošová & Karolina Lisztwanová & Antonín Pončík & Iveta Ratmanová, 2023. "Distribution Prediction of Decomposed Relative EVA Measure with Levy-Driven Mean-Reversion Processes: The Case of an Automotive Sector of a Small Open Economy," Forecasting, MDPI, vol. 5(2), pages 1-19, May.
    49. 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.
    50. David Bolder & Yuliya Romanyuk, 2008. "Combining Canadian Interest-Rate Forecasts," Staff Working Papers 08-34, Bank of Canada.
    51. 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.
    52. Österholm, Pär, 2006. "Incorporating Judgement in Fan Charts," Working Paper Series 2006:30, Uppsala University, Department of Economics.
    53. Jie Cheng, 2023. "Modelling and forecasting risk dependence and portfolio VaR for cryptocurrencies," Empirical Economics, Springer, vol. 65(2), pages 899-924, August.
    54. 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.
    55. Anne Opschoor & André Lucas & István Barra & Dick van Dijk, 2021. "Closed-Form Multi-Factor Copula Models With Observation-Driven Dynamic Factor Loadings," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(4), pages 1066-1079, October.
    56. Garratt, Anthony & Mitchell, James & Vahey, Shaun P., 2014. "Measuring output gap nowcast uncertainty," International Journal of Forecasting, Elsevier, vol. 30(2), pages 268-279.
    57. Andrew Martinez, 2017. "Testing for Differences in Path Forecast Accuracy: Forecast-Error Dynamics Matter," Working Papers (Old Series) 1717, Federal Reserve Bank of Cleveland.
    58. Lux, Thomas, 2012. "Estimation of an agent-based model of investor sentiment formation in financial markets," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1284-1302.
    59. Diks, Cees & Fang, Hao, 2020. "Comparing density forecasts in a risk management context," International Journal of Forecasting, Elsevier, vol. 36(2), pages 531-551.
    60. Michael Stanley Smith & Thomas S. Shively, 2018. "Econometric Modeling of Regional Electricity Spot Prices in the Australian Market," Papers 1804.08218, arXiv.org.
    61. Malte Knüppel, 2015. "Evaluating the Calibration of Multi-Step-Ahead Density Forecasts Using Raw Moments," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 270-281, April.
    62. Roberto Casarin & Giulia Mantoan & Francesco Ravazzolo, 2016. "Bayesian Calibration of Generalized Pools of Predictive Distributions," Econometrics, MDPI, vol. 4(1), pages 1-24, March.
    63. Marc-Oliver Pohle, 2020. "The Murphy Decomposition and the Calibration-Resolution Principle: A New Perspective on Forecast Evaluation," Papers 2005.01835, arXiv.org.
    64. Roberto Casarin & Fausto Corradin & Francesco Ravazzolo & Domenico Sartore, 2018. "A scoring rule for factor and autoregressive models under misspecification," Working Papers 2018:18, Department of Economics, University of Venice "Ca' Foscari".
    65. Meng, Fanyi & Liu, Li, 2019. "Analyzing the economic sources of oil price volatility: An out-of-sample perspective," Energy, Elsevier, vol. 177(C), pages 476-486.
    66. Meade, Nigel, 2010. "Oil prices -- Brownian motion or mean reversion? A study using a one year ahead density forecast criterion," Energy Economics, Elsevier, vol. 32(6), pages 1485-1498, November.
    67. Paulo M. Sánchez & Luis Fernando Melo, 2013. "Combinación de brechas del producto colombiano," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República, vol. 31(72), pages 74-82, December.
    68. Andre Lucas & Anne Opschoor & Luca Rossini, 2021. "Tail Heterogeneity for Dynamic Covariance Matrices: the F-Riesz Distribution," Tinbergen Institute Discussion Papers 21-010/III, Tinbergen Institute, revised 11 Jul 2023.
    69. Hall, Stephen G. & Mitchell, James, 2007. "Combining density forecasts," International Journal of Forecasting, Elsevier, vol. 23(1), pages 1-13.
    70. Salisu, Afees A. & Tchankam, Jean Paul, 2022. "US Stock return predictability with high dimensional models," Finance Research Letters, Elsevier, vol. 45(C).
    71. Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2017. "Density Forecasts With Midas Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(4), pages 783-801, June.
    72. Knut Are Aastveit & Francesco Ravazzolo & Herman K. van Dijk, 2018. "Combined Density Nowcasting in an Uncertain Economic Environment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 131-145, January.
    73. 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.
    74. Michal Franta & Jozef Baruník & Roman Horváth & Katerina Smídková, 2014. "Are Bayesian Fan Charts Useful? The Effect of Zero Lower Bound and Evaluation of Financial Stability Stress Tests," International Journal of Central Banking, International Journal of Central Banking, vol. 10(1), pages 159-188, March.
    75. Cees Diks & Valentyn Panchenko & Dick van Dijk, 2011. "Likelihood-based scoring rules for comparing density forecasts in tails," Post-Print hal-00834423, HAL.
    76. Wang, Yudong & Liu, Li & Ma, Feng & Wu, Chongfeng, 2016. "What the investors need to know about forecasting oil futures return volatility," Energy Economics, Elsevier, vol. 57(C), pages 128-139.
    77. Opschoor, Anne & Lucas, André, 2023. "Time-varying variance and skewness in realized volatility measures," International Journal of Forecasting, Elsevier, vol. 39(2), pages 827-840.
    78. 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.
    79. 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).
    80. Guidolin, Massimo & Ravazzolo, Francesco & Tortora, Andrea Donato, 2013. "Alternative econometric implementations of multi-factor models of the U.S. financial markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 53(2), pages 87-111.
    81. Anne Opschoor & Dick van Dijk & Michel van der Wel, 2014. "Improving Density Forecasts and Value-at-Risk Estimates by Combining Densities," Tinbergen Institute Discussion Papers 14-090/III, Tinbergen Institute.
    82. Marcus P. A. Cobb, 2020. "Aggregate density forecasting from disaggregate components using Bayesian VARs," Empirical Economics, Springer, vol. 58(1), pages 287-312, January.
    83. Diks, Cees & Panchenko, Valentyn & Sokolinskiy, Oleg & van Dijk, Dick, 2014. "Comparing the accuracy of multivariate density forecasts in selected regions of the copula support," Journal of Economic Dynamics and Control, Elsevier, vol. 48(C), pages 79-94.
    84. Tony Chernis & Taylor Webley, 2022. "Nowcasting Canadian GDP with Density Combinations," Discussion Papers 2022-12, Bank of Canada.
    85. Roberto Leon-Gonzalez & Blessings Majoni, 2023. "Exact Likelihood for Inverse Gamma Stochastic Volatility Models," Working Paper series 23-11, Rimini Centre for Economic Analysis.
    86. Ricardo Crisostomo & Lorena Couso, 2018. "Financial density forecasts: A comprehensive comparison of risk-neutral and historical schemes," Papers 1801.08007, arXiv.org, revised May 2018.
    87. Thomas Lux & Jaba Ghonghadze, 2011. "Modeling the Dynamics of EU Economic Sentiment Indicators: An Interaction-Based Approach," Post-Print hal-00711445, HAL.
    88. Dr. James Mitchell, 2009. "Measuring Output Gap Uncertainty," National Institute of Economic and Social Research (NIESR) Discussion Papers 342, National Institute of Economic and Social Research.
    89. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2011. "Combining Predictive Densities using Nonlinear Filtering with Applications to US Economics Data," Tinbergen Institute Discussion Papers 11-172/4, Tinbergen Institute.
    90. Dr. James Mitchell, 2009. "Macro Modelling with Many Models," National Institute of Economic and Social Research (NIESR) Discussion Papers 337, National Institute of Economic and Social Research.
    91. Fabio Busetti & Michele Caivano & Lisa Rodano, 2015. "On the conditional distribution of euro area inflation forecast," Temi di discussione (Economic working papers) 1027, Bank of Italy, Economic Research and International Relations Area.
    92. Gelain, Paolo & Iskrev, Nikolay & J. Lansing, Kevin & Mendicino, Caterina, 2019. "Inflation dynamics and adaptive expectations in an estimated DSGE model," Journal of Macroeconomics, Elsevier, vol. 59(C), pages 258-277.
    93. Brentnall, Adam R. & Crowder, Martin J. & Hand, David J., 2010. "Predictive-sequential forecasting system development for cash machine stocking," International Journal of Forecasting, Elsevier, vol. 26(4), pages 764-776, October.
    94. Yang, Dazhi & van der Meer, Dennis, 2021. "Post-processing in solar forecasting: Ten overarching thinking tools," Renewable and Sustainable Energy Reviews, Elsevier, vol. 140(C).
    95. 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.
    96. Casarin, Roberto & Grassi, Stefano & Ravazzolo, Francesco & van Dijk, Herman K., 2023. "A flexible predictive density combination for large financial data sets in regular and crisis periods," Journal of Econometrics, Elsevier, vol. 237(2).
    97. 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.
    98. Victor Lopez-Perez, 2016. "Macroeconomic Forecast Uncertainty In The Euro Area," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 11(1), pages 9-41, March.
    99. Garratt, Anthony & Mise, Emi, 2014. "Forecasting exchange rates using panel model and model averaging," Economic Modelling, Elsevier, vol. 37(C), pages 32-40.
    100. Mitchell, James, 2013. "The Recalibrated and Copula Opinion Pools," EMF Research Papers 02, Economic Modelling and Forecasting Group.
    101. N. Meade & J. E. Beasley & C. J. Adcock, 2019. "Quantitative portfolio selection: using density forecasting to find consistent portfolios," Papers 1908.08442, arXiv.org, revised Jun 2020.
    102. 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.
    103. Tae-Hwy Lee & Yong Bao & Burak Saltoğlu, 2007. "Comparing density forecast models Previous versions of this paper have been circulated with the title, 'A Test for Density Forecast Comparison with Applications to Risk Management' since October 2003;," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(3), pages 203-225.
    104. Roberto Casarin & Stefano Grassi & Francesco Ravazzollo & Herman K. van Dijk, 2019. "Forecast Density Combinations with Dynamic Learning for Large Data Sets in Economics and Finance," Tinbergen Institute Discussion Papers 19-025/III, Tinbergen Institute.
    105. Fabio Busetti, 2017. "Quantile Aggregation of Density Forecasts," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(4), pages 495-512, August.
    106. Christian Kascha & Francesco Ravazzolo, 2008. "Combining inflation density forecasts," Working Paper 2008/22, Norges Bank.
    107. Herman O. Stekler, 2008. "What Do We Know About G-7 Macro Forecasts?," Working Papers 2008-009, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    108. Ilmari Juutilainen & Juha Roning, 2010. "How to compare interpretatively different models for the conditional variance function," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(6), pages 983-997.
    109. 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.
    110. Lukasz Gatarek & Lennart Hoogerheide & Koen Hooning & Herman K. van Dijk, 2013. "Censored Posterior and Predictive Likelihood in Left-Tail Prediction for Accurate Value at Risk Estimation," Tinbergen Institute Discussion Papers 13-060/III, Tinbergen Institute, revised 06 Mar 2014.
    111. Timo Henckel & Shaun Vahey & Liz Wakerly, 2011. "Probabilistic interest rate setting with a shadow board: A description of the pilot project," CAMA Working Papers 2011-27, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    112. Liu, Li & Wang, Yudong & Yang, Li, 2018. "Predictability of crude oil prices: An investor perspective," Energy Economics, Elsevier, vol. 75(C), pages 193-205.
    113. Francesco Ravazzolo & Shaun P Vahey, 2010. "Measuring Core Inflation in Australia with Disaggregate Ensembles," RBA Annual Conference Volume (Discontinued), in: Renée Fry & Callum Jones & Christopher Kent (ed.),Inflation in an Era of Relative Price Shocks, Reserve Bank of Australia.
    114. 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.
    115. 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.
    116. Cobb, Marcus P A, 2017. "Aggregate Density Forecasting from Disaggregate Components Using Large VARs," MPRA Paper 76849, University Library of Munich, Germany.
    117. Li Liu & Zhiyuan Pan & Yudong Wang, 2021. "What can we learn from the return predictability over the business cycle?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 108-131, January.
    118. Tsuchiya, Yoichi, 2022. "Evaluating the European Central Bank’s uncertainty forecasts," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 321-330.
    119. Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2019. "Density Forecasting," BEMPS - Bozen Economics & Management Paper Series BEMPS59, Faculty of Economics and Management at the Free University of Bozen.
    120. Huurman, Christian & Ravazzolo, Francesco & Zhou, Chen, 2012. "The power of weather," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3793-3807.

  33. Massmann, Michael & Mitchell, James & Weale, Martin, 2003. "Business Cycles and Turning Points: A Survey of Statistical Techniques," National Institute Economic Review, National Institute of Economic and Social Research, vol. 183, pages 90-106, January.

    Cited by:

    1. Hahn, Elke & Zekaite, Zivile & de Bondt, Gabe, 2018. "ALICE: A new inflation monitoring tool," Working Paper Series 2175, European Central Bank.
    2. Mark J. Holmes & Brian Silverstone, 2010. "Business confidence and cyclical turning points: a Markov-switching approach," Applied Economics Letters, Taylor & Francis Journals, vol. 17(3), pages 229-233, February.
    3. Maurizio Bovi, 2003. "Nonparametric Analysis Of The International Business Cycles," ISAE Working Papers 37, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    4. Klaus Wohlrabe, 2011. "Konstruktion von Indikatoren zur Analyse der wirtschaftlichen Aktivität in den Dienstleistungsbereichen," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 55.
    5. Massmann, Michael & Mitchell, James, 2003. "Reconsidering the evidence: Are Eurozone business cycles converging," ZEI Working Papers B 05-2003, University of Bonn, ZEI - Center for European Integration Studies.
    6. González, Andrés & Teräsvirta, Timo, 2006. "Modelling autoregressive processes with a shifting mean," SSE/EFI Working Paper Series in Economics and Finance 637, Stockholm School of Economics, revised 22 May 2007.
    7. Francis W. Ahking, 2015. "Measuring U.S. Business Cycles: A Comparison of Two Methods and Two Indicators of Economic Activities (With Appendix A)," Working papers 2015-06, University of Connecticut, Department of Economics.
    8. Marco Rubilar-González & Gabriel Pino, 2018. "Are Euro-Area expectations about recession phases effective to anticipate consequences of economic crises?," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 9(2), pages 141-161, June.
    9. Kovačić, Zlatko & Vilotić, Miloš, 2017. "Assessing European business cycles synchronization," MPRA Paper 79990, University Library of Munich, Germany.
    10. Francis W. Ahking, 2013. "Measuring U.S. Business Cycles: A Comparison of Two Methods and Two Indicators of Economic Activities," Working papers 2013-10, University of Connecticut, Department of Economics.
    11. Lourdes Acedo Montoya & Jakob de Haan, 2007. "Regional Business Cycle Synchronization in Europe," Bruges European Economic Research Papers 11, European Economic Studies Department, College of Europe.
    12. Sèna Kimm Gnangnon, 2012. "An analysis of duration dependence of government revenue expansions and contractions in Developing Countries," Working Papers halshs-00722083, HAL.
    13. Beate Schirwitz & Christian Seiler & Klaus Wohlrabe, 2009. "Regional business cycles in Germany - the dating problem," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 62(14), pages 24-31, July.

  34. Massmann, Michael & Mitchell, James, 2002. "Have UK and Eurozone Business Cycles Become More Correlated?," National Institute Economic Review, National Institute of Economic and Social Research, vol. 182, pages 58-71, October.

    Cited by:

    1. Anthony Garratt & Donald Robertson & Stephen Wright, 2005. "Permanent vs Transitory Components and Economic Fundamentals," Birkbeck Working Papers in Economics and Finance 0501, Birkbeck, Department of Economics, Mathematics & Statistics.
    2. Narayan, Paresh Kumar, 2008. "Understanding the importance of permanent and transitory shocks at business cycle horizons for the UK," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(12), pages 2879-2888.
    3. Massmann, Michael & Mitchell, James, 2003. "Reconsidering the evidence: Are Eurozone business cycles converging," ZEI Working Papers B 05-2003, University of Bonn, ZEI - Center for European Integration Studies.
    4. Holtemöller, Oliver (Ed.) & Rahn, Jörg (Ed.) & Stierle, Michael H. (Ed.), 2009. "Characteristics of Business Cycles: Have they Changed?," IWH-Sonderhefte 5/2009, Halle Institute for Economic Research (IWH).
    5. Gabriel Moser & Wolfgang Pointner & Gerhard Reitschuler, 2004. "Economic Growth in Denmark, Sweden and the United Kingdom since the Start of Monetary Union," Monetary Policy & the Economy, Oesterreichische Nationalbank (Austrian Central Bank), issue 4, pages 53-66.
    6. Fiona Atkins, 2005. "Financial Crises and Money Demand in Jamaica," Birkbeck Working Papers in Economics and Finance 0512, Birkbeck, Department of Economics, Mathematics & Statistics.
    7. Anthony Garratt & Donald Robertson & Stephen Wright, 2004. "Inside the black box: permanent vs transitory components and economic fundamentals," Money Macro and Finance (MMF) Research Group Conference 2003 35, Money Macro and Finance Research Group.
    8. Willie Lahari, 2011. "Assessing Business Cycle Synchronisation - Prospects for a Pacific Islands Currency Union," Working Papers 1110, University of Otago, Department of Economics, revised Oct 2011.
    9. Julien Garnier, 2004. "UK in or UK Out? A Common Cycle Analysis Between the UK and the Euro Zone," Working Papers 2004-17, CEPII research center.

  35. James Mitchell & Richard J. Smith & Martin R. Weale, 2002. "Quantification of Qualitative Firm-Level Survey Data," Economic Journal, Royal Economic Society, vol. 112(478), pages 117-135, March.
    See citations under working paper version above.
  36. Mitchell, James, 2002. "The use of non-normal distributions in quantifying qualitative survey data on expectations," Economics Letters, Elsevier, vol. 76(1), pages 101-107, June.

    Cited by:

    1. Ullrich, Katrin, 2007. "Inflation Expectations of Experts and ECB Communication," ZEW Discussion Papers 07-054, ZEW - Leibniz Centre for European Economic Research.
    2. Tatiana Cesaroni, 2011. "The cyclical behavior of the Italian business survey data," Empirical Economics, Springer, vol. 41(3), pages 747-768, December.
    3. Ece Oral, 2016. "Measuring Consumer Inflation Expectations in Turkey," Eastern European Business and Economics Journal, Eastern European Business and Economics Studies Centre, vol. 2(1), pages 43-74.
    4. Lahiri, Kajal & Zhao, Yongchen, 2015. "Quantifying survey expectations: A critical review and generalization of the Carlson–Parkin method," International Journal of Forecasting, Elsevier, vol. 31(1), pages 51-62.
    5. Sarah M. Lein & Thomas Maag, 2008. "The Formation of Inflation Perceptions - Some Empirical Facts for European Countries," KOF Working papers 08-204, KOF Swiss Economic Institute, ETH Zurich.
    6. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“Tracking economic growth by evolving expectations via genetic programming: A two-step approach”," IREA Working Papers 201801, University of Barcelona, Research Institute of Applied Economics, revised Jan 2018.
    7. James Mitchell & Richard J. Smith & Martin R. Weale, 2013. "Efficient Aggregation Of Panel Qualitative Survey Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(4), pages 580-603, June.
    8. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "A Data-Driven Approach to Construct Survey-Based Indicators by Means of Evolutionary Algorithms," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 135(1), pages 1-14, January.
    9. Ece Oral, 2013. "Consumer Inflation Expectations in Turkey," IFC Working Papers 10, Bank for International Settlements.
    10. Kjellberg, David, 2006. "Measuring Expectations," Working Paper Series 2006:9, Uppsala University, Department of Economics.
    11. Lyziak, Tomasz, 2011. "Non-positive scaling factor in probability quantification methods: deriving consumer inflation perceptions and expectations in the whole euro area and Ireland," MPRA Paper 28900, University Library of Munich, Germany.
    12. Ray Barrell, 1999. "Employment Security and European Labour Demand: A Panel Study Across 16 Industries," National Institute of Economic and Social Research (NIESR) Discussion Papers 148, National Institute of Economic and Social Research.
    13. Dr Martin Weale & Dr. James Mitchell, 2005. "Forecasting manufacturing output growth using firm-level survey data," National Institute of Economic and Social Research (NIESR) Discussion Papers 251, National Institute of Economic and Social Research.
    14. Oscar Claveria & Enric Monte & Salvador Torra, 2015. "“Self-organizing map analysis of agents’ expectations. Different patterns of anticipation of the 2008 financial crisis”," AQR Working Papers 201508, University of Barcelona, Regional Quantitative Analysis Group, revised Mar 2015.
    15. Breitung, Jörg & Schmeling, Maik, 2011. "Quantifying survey expectations: What's wrong with the probability approach?," Hannover Economic Papers (HEP) dp-485, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    16. Oscar Claveria, 2021. "Forecasting with Business and Consumer Survey Data," Forecasting, MDPI, vol. 3(1), pages 1-22, February.
    17. Friedrich Heinemann & Katrin Ullrich, 2006. "The Impact of EMU on Inflation Expectations," Open Economies Review, Springer, vol. 17(2), pages 175-195, April.
    18. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "A new approach for the quantification of qualitative measures of economic expectations," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(6), pages 2685-2706, November.
    19. O Claveria & E Pons & J Surinach, 2006. "Quantification of Expectations. Are They Useful for Forecasting Inflation?," Economic Issues Journal Articles, Economic Issues, vol. 11(2), pages 19-38, September.
    20. Kajal Lahiri & Yongchen Zhao, 2013. "Quantifying Heterogeneous Survey Expectations: The Carlson-Parkin Method Revisited," Discussion Papers 13-08, University at Albany, SUNY, Department of Economics.

Chapters

  1. James Mitchell & Aubrey Poon & Gian Luigi Mazzi, 2022. "Nowcasting Euro Area GDP Growth Using Bayesian Quantile Regression," Advances in Econometrics, in: Essays in Honor of M. Hashem Pesaran: Prediction and Macro Modeling, volume 43, pages 51-72, Emerald Group Publishing Limited.

    Cited by:

    1. 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.

  2. Stephen G. Hall & James Mitchell, 2009. "Recent Developments in Density Forecasting," Palgrave Macmillan Books, in: Terence C. Mills & Kerry Patterson (ed.), Palgrave Handbook of Econometrics, chapter 5, pages 199-239, Palgrave Macmillan.

    Cited by:

    1. Michael Clements, 2016. "Are Macroeconomic Density Forecasts Informative?," ICMA Centre Discussion Papers in Finance icma-dp2016-02, Henley Business School, University of Reading.
    2. Dr Silvia Lui & Dr Martin Weale & Dr. James Mitchell, 2009. "The utility of expectational data: Firm-level evidence using matched qualitative-quantitative UK surveys," National Institute of Economic and Social Research (NIESR) Discussion Papers 343, National Institute of Economic and Social Research.
    3. Clements, Michael P., 2014. "Probability distributions or point predictions? Survey forecasts of US output growth and inflation," International Journal of Forecasting, Elsevier, vol. 30(1), pages 99-117.
    4. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    5. 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.
    6. 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.
    7. 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.
    8. Fabio Busetti, 2017. "Quantile Aggregation of Density Forecasts," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(4), pages 495-512, August.

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