Confronting model misspecification in macroeconomics

Citations

Cited by:

1. Hansen, Lars Peter & Sargent, Thomas J., 2022. "Structured ambiguity and model misspecification," Journal of Economic Theory, Elsevier, vol. 199(C).
2. Tan, Fei, 2018. "A Frequency-Domain Approach to Dynamic Macroeconomic Models," MPRA Paper 90487, University Library of Munich, Germany.
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. Maik H. Wolters, 2015. "Evaluating Point and Density Forecasts of DSGE Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(1), pages 74-96, January.
   • Wolters, Maik H., 2011. "Forecasting under Model Uncertainty," VfS Annual Conference 2011 (Frankfurt, Main): The Order of the World Economy - Lessons from the Crisis 48723, Verein für Socialpolitik / German Economic Association.
   • Wolters, Maik H., 2013. "Evaluating point and density forecasts of DSGE models," Economics Working Papers 2013-03, Christian-Albrechts-University of Kiel, Department of Economics.
   • Wolters, Maik Hendrik, 2012. "Evaluating point and density forecasts of DSGE models," IMFS Working Paper Series 59, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
   • Wolters, Maik Hendrik, 2012. "Evaluating point and density forecasts of DSGE models," MPRA Paper 36147, University Library of Munich, Germany.
5. Davide Pettenuzzo & Francesco Ravazzolo, 2016. "Optimal Portfolio Choice Under Decision‐Based Model Combinations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1312-1332, November.
   • Davide Pettenuzzo & Francesco Ravazzolo, 2014. "Optimal Portfolio Choice under Decision-Based Model Combinations," Working Papers 80, Brandeis University, Department of Economics and International Business School.
   • Davide Pettenuzzo & Francesco Ravazzolo, 2015. "Optimal Portfolio Choice under Decision-Based Model Combinations," Working Papers No 9/2015, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
   • Davide Pettenuzzo & Francesco Ravazzolo, 2014. "Optimal portfolio choice under decision-based model combinations," Working Paper 2014/15, Norges Bank.
6. Thorsten Drautzburg, 2020. "A narrative approach to a fiscal DSGE model," Quantitative Economics, Econometric Society, vol. 11(2), pages 801-837, May.
   • Thorsten Drautzburg, 2014. "A Narrative Approach to a Fiscal DSGE Model," 2014 Meeting Papers 791, Society for Economic Dynamics.
   • Thorsten Drautzburg, 2016. "A narrative approach to a fiscal DSGE model," Working Papers 16-11, Federal Reserve Bank of Philadelphia.
7. Paccagnini, Alessia, 2017. "Dealing with Misspecification in DSGE Models: A Survey," MPRA Paper 82914, University Library of Munich, Germany.
8. Miranda-Agrippino, Silvia & Ricco, Giovanni, 2018. "Bayesian Vector Autoregressions," The Warwick Economics Research Paper Series (TWERPS) 1159, University of Warwick, Department of Economics.
   • 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.
   • Silvia Miranda Agrippino & Giovanni Ricco, 2018. "Bayesian vector autoregressions," Working Papers hal-03458277, HAL.
   • Silvia Miranda-Agrippino & Giovanni Ricco, 2018. "Bayesian Vector Autoregressions," Discussion Papers 1808, Centre for Macroeconomics (CFM).
   • Silvia Miranda Agrippino & Giovanni Ricco, 2018. "Bayesian vector autoregressions," Sciences Po publications 18, Sciences Po.
   • Silvia Miranda Agrippino & Giovanni Ricco, 2018. "Bayesian vector autoregressions," SciencePo Working papers Main hal-03458277, HAL.
   • Miranda-Agrippino, Silvia & Ricco, Giovanni, 2018. "Bayesian vector autoregressions," Bank of England working papers 756, Bank of England.
   • Silvia Miranda-Agrippino & Giovanni Ricco, 2018. "Bayesian vector autoregressions," Documents de Travail de l'OFCE 2018-18, Observatoire Francais des Conjonctures Economiques (OFCE).
9. 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.
   • Li Li & Yanfei Kang & Feng Li, 2021. "Bayesian forecast combination using time-varying features," Papers 2108.02082, arXiv.org, revised Jun 2022.
10. Fabio Canova & Christian Matthes, 2021. "A Composite Likelihood Approach for Dynamic Structural Models," The Economic Journal, Royal Economic Society, vol. 131(638), pages 2447-2477.
    • Fabio Canova & Christian Matthes, 2018. "A Composite Likelihood Approach for Dynamic Structural Models," Working Paper 18-12, Federal Reserve Bank of Richmond.
    • Canova, Fabio & Matthes, Christian, 2018. "A composite likelihood approach for dynamic structural models," CEPR Discussion Papers 13245, C.E.P.R. Discussion Papers.
    • Fabio Canova & Christian Matthes, 2018. "A composite likelihood approach for dynamic structural models," Working Papers No 10/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
11. Li, Bing & Pei, Pei & Tan, Fei, 2021. "Financial distress and fiscal inflation," Journal of Macroeconomics, Elsevier, vol. 70(C).
12. Gianni Amisano & John Geweke, 2017. "Prediction Using Several Macroeconomic Models," The Review of Economics and Statistics, MIT Press, vol. 99(5), pages 912-925, December.
    • Amisano, Gianni & Geweke, John, 2013. "Prediction using several macroeconomic models," Working Paper Series 1537, European Central Bank.
13. Chen, Yi-Ting & Liu, Chu-An, 2023. "Model averaging for asymptotically optimal combined forecasts," Journal of Econometrics, Elsevier, vol. 235(2), pages 592-607.
    • 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.
14. Baştürk, N. & Borowska, A. & Grassi, S. & Hoogerheide, L. & van Dijk, H.K., 2019. "Forecast density combinations of dynamic models and data driven portfolio strategies," Journal of Econometrics, Elsevier, vol. 210(1), pages 170-186.
    • Nalan Basturk & Agnieszka Borowska & Stefano Grassi & Lennart (L.F.) Hoogerheide & Herman (H.K.) van Dijk, 2018. "Forecast Density Combinations of Dynamic Models and Data Driven Portfolio Strategies," Tinbergen Institute Discussion Papers 18-076/III, Tinbergen Institute.
    • 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.
15. 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.
    • Knüppel, Malte & Krüger, Fabian, 2019. "Forecast uncertainty, disagreement, and the linear pool," Discussion Papers 28/2019, Deutsche Bundesbank.
16. Kilian, Lutz, 2022. "Facts and fiction in oil market modeling," Energy Economics, Elsevier, vol. 110(C).
    • Lutz Kilian, 2019. "Facts and Fiction in Oil Market Modeling," CESifo Working Paper Series 7902, CESifo.
    • Kilian, Lutz, 2019. "Facts and Fiction in Oil Market Modeling," CEPR Discussion Papers 14047, C.E.P.R. Discussion Papers.
    • Kilian, Lutz, 2021. "Facts and fiction in oil market modeling," CFS Working Paper Series 661, Center for Financial Studies (CFS).
    • Lutz Kilian, 2019. "Facts and Fiction in Oil Market Modeling," Working Papers 1907, Federal Reserve Bank of Dallas, revised 21 Dec 2020.
17. Paul Ho & Thomas A. Lubik & Christian Matthes, 2023. "Averaging Impulse Responses Using Prediction Pools," Working Paper 23-04, Federal Reserve Bank of Richmond.
18. Inoue, Atsushi & Kilian, Lutz, 2022. "Joint Bayesian inference about impulse responses in VAR models," Journal of Econometrics, Elsevier, vol. 231(2), pages 457-476.
    • Inoue, Atsushi & Kilian, Lutz, 2020. "Joint Bayesian inference about impulse responses in VAR models," CFS Working Paper Series 650, Center for Financial Studies (CFS).
    • Atsushi Inoue & Lutz Kilian, 2020. "Joint Bayesian Inference about Impulse Responses in VAR Models," Working Papers 2022, Federal Reserve Bank of Dallas.
19. Gergely Akos Ganics, 2017. "Optimal density forecast combinations," Working Papers 1751, Banco de España.
20. Fabio Canova & Christian Matthes, 2021. "Dealing with misspecification in structural macroeconometric models," Quantitative Economics, Econometric Society, vol. 12(2), pages 313-350, May.
    • Canova, Fabio & Matthes, Christian, 2019. "Dealing with misspecification in structural macroeconometric models," CEPR Discussion Papers 13511, C.E.P.R. Discussion Papers.
21. Fernández-Villaverde, J. & Rubio-Ramírez, J.F. & Schorfheide, F., 2016. "Solution and Estimation Methods for DSGE Models," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 527-724, Elsevier.
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    • Jesús Fernández-Villaverde & Juan F. Rubio Ramírez & Frank Schorfheide, 2016. "Solution and Estimation Methods for DSGE Models," NBER Working Papers 21862, National Bureau of Economic Research, Inc.
    • Rubio-Ramírez, Juan Francisco & Schorfheide, Frank & Fernández-Villaverde, Jesús, 2015. "Solution and Estimation Methods for DSGE Models," CEPR Discussion Papers 11032, C.E.P.R. Discussion Papers.
22. Hubrich, Kirstin & Tetlow, Robert J., 2015. "Financial stress and economic dynamics: The transmission of crises," Journal of Monetary Economics, Elsevier, vol. 70(C), pages 100-115.
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    • Hubrich, Kirstin & Tetlow, Robert J., 2014. "Financial stress and economic dynamics: the transmission of crises," Working Paper Series 1728, European Central Bank.
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23. Loretta J. Mester, 2016. "Acknowledging Uncertainty, 10-07-2016; Shadow Open Market Committee Fall Meeting, New York, NY," Speech 77, Federal Reserve Bank of Cleveland.
24. Stona, Filipe & Morais, Igor A.C. & Triches, Divanildo, 2018. "Economic dynamics during periods of financial stress: Evidences from Brazil," International Review of Economics & Finance, Elsevier, vol. 55(C), pages 130-144.
25. Kapetanios, G. & Mitchell, J. & Price, S. & Fawcett, N., 2015. "Generalised density forecast combinations," Journal of Econometrics, Elsevier, vol. 188(1), pages 150-165.
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26. Loria, Francesca & Matthes, Christian & Wang, Mu-Chun, 2022. "Economic theories and macroeconomic reality," Journal of Monetary Economics, Elsevier, vol. 126(C), pages 105-117.
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27. 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.
28. 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.
29. Hasumi, Ryo & Iiboshi, Hirokuni & Matsumae, Tatsuyoshi & Nakamura, Daisuke, 2018. "Does a financial accelerator improve forecasts during financial crises?: Evidence from Japan with Prediction Pool Methods," MPRA Paper 85523, University Library of Munich, Germany.
30. Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2015. "Dynamic predictive density combinations for large data sets in economics and finance," Working Paper 2015/12, Norges Bank.
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32. repec:hal:spmain:info:hdl:2441/27od5pb99881folvtfs8s3k16l is not listed on IDEAS
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