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Forecasting in nonstationary environments: What works and what doesn't in reduced-form and structural models

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Abstract

This review provides an overview of forecasting methods that can help researchers forecast in the presence of non-stationarities caused by instabilities. The emphasis of the review is both theoretical and applied, and provides several examples of interest to economists. We show that modeling instabilities can help, but it depends on how they are modeled. We also show how to robustify a model against instabilities.

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  • Raffaella Giacomini & Barbara Rossi, 2014. "Forecasting in nonstationary environments: What works and what doesn't in reduced-form and structural models," Economics Working Papers 1476, Department of Economics and Business, Universitat Pompeu Fabra.
  • Handle: RePEc:upf:upfgen:1476
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    1. Billio, Monica & Casarin, Roberto & Ravazzolo, Francesco & van Dijk, Herman K., 2013. "Time-varying combinations of predictive densities using nonlinear filtering," Journal of Econometrics, Elsevier, vol. 177(2), pages 213-232.
    2. Bates, Brandon J. & Plagborg-Møller, Mikkel & Stock, James H. & Watson, Mark W., 2013. "Consistent factor estimation in dynamic factor models with structural instability," Journal of Econometrics, Elsevier, vol. 177(2), pages 289-304.
    3. Richard Clarida & Jordi Galí & Mark Gertler, 2000. "Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 115(1), pages 147-180.
    4. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    5. Berkowitz, Jeremy, 2001. "Testing Density Forecasts, with Applications to Risk Management," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(4), pages 465-474, October.
    6. 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.
    7. Timothy Cogley & Argia M. Sbordone, 2006. "Trend inflation and inflation persistence in the New Keynesian Phillips curve," Staff Reports 270, Federal Reserve Bank of New York.
    8. Cosmin L. Ilut & Martin Schneider, 2014. "Ambiguous Business Cycles," American Economic Review, American Economic Association, vol. 104(8), pages 2368-2399, August.
    9. Carlo Altavilla & Raffaella Giacomini & Giuseppe Ragusa, 2017. "Anchoring the yield curve using survey expectations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(6), pages 1055-1068, September.
    10. Breitung, Jörg & Eickmeier, Sandra, 2011. "Testing for structural breaks in dynamic factor models," Journal of Econometrics, Elsevier, vol. 163(1), pages 71-84, July.
    11. Marcellino, Massimiliano & Eickmeier, Sandra & Lemke, Wolfgang, 2011. "Classical time-varying FAVAR models - Estimation, forecasting and structural analysis," CEPR Discussion Papers 8321, C.E.P.R. Discussion Papers.
    12. Rossi, Barbara & Sekhposyan, Tatevik, 2014. "Evaluating predictive densities of US output growth and inflation in a large macroeconomic data set," International Journal of Forecasting, Elsevier, vol. 30(3), pages 662-682.
    13. Pesaran, M. Hashem & Timmermann, Allan, 2002. "Market timing and return prediction under model instability," Journal of Empirical Finance, Elsevier, vol. 9(5), pages 495-510, December.
    14. Inoue, Atsushi, 2001. "Testing For Distributional Change In Time Series," Econometric Theory, Cambridge University Press, vol. 17(1), pages 156-187, February.
    15. Raffaella Giacomini & Barbara Rossi, 2016. "Model Comparisons In Unstable Environments," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 57(2), pages 369-392, May.
    16. Jan J. J. Groen & Richard Paap & Francesco Ravazzolo, 2013. "Real-Time Inflation Forecasting in a Changing World," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(1), pages 29-44, January.
    17. Anindya Banerjee & Massimiliano Marcellino & Igor Masten, 2008. "Forecasting Macroeconomic Variables Using Diffusion Indexes in Short Samples with Structural Change," Working Papers 334, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    18. Jonathan H. Wright, 2009. "Forecasting US inflation by Bayesian model averaging," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(2), pages 131-144.
    19. Serena Ng & Jonathan H. Wright, 2013. "Facts and Challenges from the Great Recession for Forecasting and Macroeconomic Modeling," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1120-1154, December.
    20. Stock, James H. & Watson, Mark W., 2006. "Forecasting with Many Predictors," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 10, pages 515-554, Elsevier.
    21. Timothy Cogley & Thomas J. Sargent, 2005. "Drift and Volatilities: Monetary Policies and Outcomes in the Post WWII U.S," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 262-302, April.
    22. Francesco Bianchi, 2013. "Regime Switches, Agents' Beliefs, and Post-World War II U.S. Macroeconomic Dynamics," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 80(2), pages 463-490.
    23. Antonello D'Agostino & Luca Gambetti & Domenico Giannone, 2013. "Macroeconomic forecasting and structural change," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(1), pages 82-101, January.
    24. Olivier Coibion & Yuriy Gorodnichenko, 2012. "What Can Survey Forecasts Tell Us about Information Rigidities?," Journal of Political Economy, University of Chicago Press, vol. 120(1), pages 116-159.
    25. Andrew Foerster & Juan F. Rubio-Ramirez & Daniel F. Waggoner & Tao Zha, 2013. "Perturbation methods for Markov-switching DSGE models," FRB Atlanta Working Paper 2013-01, Federal Reserve Bank of Atlanta.
    26. Gary M. Koop, 2013. "Forecasting with Medium and Large Bayesian VARS," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(2), pages 177-203, March.
    27. Dimitris Korobilis, 2013. "Assessing the Transmission of Monetary Policy Using Time-varying Parameter Dynamic Factor Models-super-," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(2), pages 157-179, April.
    28. Amisano, Gianni & Giacomini, Raffaella, 2007. "Comparing Density Forecasts via Weighted Likelihood Ratio Tests," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 177-190, April.
    29. Giraitis, Liudas & Kapetanios, George & Price, Simon, 2013. "Adaptive forecasting in the presence of recent and ongoing structural change," Journal of Econometrics, Elsevier, vol. 177(2), pages 153-170.
    30. Raffaella Giacomini & Barbara Rossi, 2009. "Detecting and Predicting Forecast Breakdowns," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 76(2), pages 669-705.
    31. Rossi, Barbara & Sekhposyan, Tatevik, 2013. "Conditional predictive density evaluation in the presence of instabilities," Journal of Econometrics, Elsevier, vol. 177(2), pages 199-212.
    32. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
    33. Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2015. "Prior Selection for Vector Autoregressions," The Review of Economics and Statistics, MIT Press, vol. 97(2), pages 436-451, May.
    34. Raffaella Giacomini, 2015. "Economic theory and forecasting: lessons from the literature," Econometrics Journal, Royal Economic Society, vol. 18(2), pages 22-41, June.
    35. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    36. Barbara Rossi & Atsushi Inoue, 2012. "Out-of-Sample Forecast Tests Robust to the Choice of Window Size," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(3), pages 432-453, April.
    37. Raffaella Giacomini & Barbara Rossi, 2006. "How Stable is the Forecasting Performance of the Yield Curve for Output Growth?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(s1), pages 783-795, December.
    38. Robertson, John C & Tallman, Ellis W & Whiteman, Charles H, 2005. "Forecasting Using Relative Entropy," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 383-401, June.
    39. Troy Davig & Eric M. Leeper, 2007. "Generalizing the Taylor Principle," American Economic Review, American Economic Association, vol. 97(3), pages 607-635, June.
    40. Frank Smets & Rafael Wouters, 2007. "Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach," American Economic Review, American Economic Association, vol. 97(3), pages 586-606, June.
    41. Wieland, Volker & Cwik, Tobias & Müller, Gernot J. & Schmidt, Sebastian & Wolters, Maik, 2012. "A new comparative approach to macroeconomic modeling and policy analysis," Journal of Economic Behavior & Organization, Elsevier, vol. 83(3), pages 523-541.
    42. Graham Elliott & Ulrich K. Muller, 2006. "Efficient Tests for General Persistent Time Variation in Regression Coefficients," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 73(4), pages 907-940.
    43. Andrews, Donald W K & Ploberger, Werner, 1994. "Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative," Econometrica, Econometric Society, vol. 62(6), pages 1383-1414, November.
    44. Todd E. Clark, 2011. "Real-Time Density Forecasts From Bayesian Vector Autoregressions With Stochastic Volatility," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(3), pages 327-341, July.
    45. James H. Stock & Mark W. Watson, 2003. "Has the Business Cycle Changed and Why?," NBER Chapters, in: NBER Macroeconomics Annual 2002, Volume 17, pages 159-230, National Bureau of Economic Research, Inc.
    46. Diebold, Francis X. & Li, Canlin, 2006. "Forecasting the term structure of government bond yields," Journal of Econometrics, Elsevier, vol. 130(2), pages 337-364, February.
    47. De Mol, Christine & Giannone, Domenico & Reichlin, Lucrezia, 2008. "Forecasting using a large number of predictors: Is Bayesian shrinkage a valid alternative to principal components?," Journal of Econometrics, Elsevier, vol. 146(2), pages 318-328, October.
    48. Ploberger, Werner & Kramer, Walter, 1992. "The CUSUM Test with OLS Residuals," Econometrica, Econometric Society, vol. 60(2), pages 271-285, March.
    49. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2000. "The Generalized Dynamic-Factor Model: Identification And Estimation," The Review of Economics and Statistics, MIT Press, vol. 82(4), pages 540-554, November.
    50. Stock, James H & Watson, Mark W, 1996. "Evidence on Structural Instability in Macroeconomic Time Series Relations," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(1), pages 11-30, January.
    51. Giorgio E. Primiceri, 2005. "Time Varying Structural Vector Autoregressions and Monetary Policy," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 821-852.
    52. Giacomini, Raffaella & Ragusa, Giuseppe, 2014. "Theory-coherent forecasting," Journal of Econometrics, Elsevier, vol. 182(1), pages 145-155.
    53. M. Hashem Pesaran & Davide Pettenuzzo & Allan Timmermann, 2006. "Forecasting Time Series Subject to Multiple Structural Breaks," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 73(4), pages 1057-1084.
    54. Koop, Gary & Korobilis, Dimitris, 2013. "Large time-varying parameter VARs," Journal of Econometrics, Elsevier, vol. 177(2), pages 185-198.
    55. Pesaran, M. Hashem & Timmermann, Allan, 2007. "Selection of estimation window in the presence of breaks," Journal of Econometrics, Elsevier, vol. 137(1), pages 134-161, March.
    56. G. Elliott & C. Granger & A. Timmermann (ed.), 2006. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 1, number 1.
    57. Chauvet, Marcelle & Potter, Simon, 2013. "Forecasting Output," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 141-194, Elsevier.
    58. Andrew Foerster & Juan F. Rubio‐Ramírez & Daniel F. Waggoner & Tao Zha, 2016. "Perturbation methods for Markov‐switching dynamic stochastic general equilibrium models," Quantitative Economics, Econometric Society, vol. 7(2), pages 637-669, July.
    59. Fabio Canova & Filippo Ferroni, 2011. "Multiple filtering devices for the estimation of cyclical DSGE models," Quantitative Economics, Econometric Society, vol. 2(1), pages 73-98, March.
    60. repec:hal:journl:peer-00834423 is not listed on IDEAS
    61. Malin Adolfson & Jesper Linde & Mattias Villani, 2007. "Forecasting Performance of an Open Economy DSGE Model," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 289-328.
    62. Marta Bańbura, 2008. "Large Bayesian VARs," 2008 Meeting Papers 334, Society for Economic Dynamics.
    63. Barbara Rossi & Tatevik Sekhposyan, 2016. "Forecast Rationality Tests in the Presence of Instabilities, with Applications to Federal Reserve and Survey Forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(3), pages 507-532, April.
    64. Andrade, P. & Ghysels, E. & Idier, J., 2012. "Tails of Inflation Forecasts and Tales of Monetary Policy," Working papers 407, Banque de France.
    65. Pesaran, M. Hashem & Pick, Andreas & Pranovich, Mikhail, 2013. "Optimal forecasts in the presence of structural breaks," Journal of Econometrics, Elsevier, vol. 177(2), pages 134-152.
    66. Atsushi Inoue, "undated". "Testing Change in Time Series," Computing in Economics and Finance 1997 7, Society for Computational Economics.
    67. 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.
    68. Francesca Monti, 2010. "Combining Judgment and Models," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(8), pages 1641-1662, December.
    69. Diebold, Francis X & Gunther, Todd A & Tay, Anthony S, 1998. "Evaluating Density Forecasts with Applications to Financial Risk Management," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 863-883, November.
    70. 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.
    71. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    72. Roger E. A. Farmer & Daniel F. Waggoner & Tao Zha, 2009. "Indeterminacy in a forward‐looking regime switching model," International Journal of Economic Theory, The International Society for Economic Theory, vol. 5(1), pages 69-84, March.
    73. Corradi, Valentina & Swanson, Norman R., 2006. "Predictive Density Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 5, pages 197-284, Elsevier.
    74. 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.
    75. Diks, Cees & Panchenko, Valentyn & van Dijk, Dick, 2011. "Likelihood-based scoring rules for comparing density forecasts in tails," Journal of Econometrics, Elsevier, vol. 163(2), pages 215-230, August.
    76. Rossi, Barbara & Sekhposyan, Tatevik, 2010. "Have economic models' forecasting performance for US output growth and inflation changed over time, and when?," International Journal of Forecasting, Elsevier, vol. 26(4), pages 808-835, October.
    77. Raffaella Giacomini & Barbara Rossi, 2010. "Forecast comparisons in unstable environments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 595-620.
    78. Atsushi Inoue & Barbara Rossi, 2011. "Identifying the Sources of Instabilities in Macroeconomic Fluctuations," The Review of Economics and Statistics, MIT Press, vol. 93(4), pages 1186-1204, November.
    79. Chang-Jin Kim & Charles R. Nelson, 1999. "Has The U.S. Economy Become More Stable? A Bayesian Approach Based On A Markov-Switching Model Of The Business Cycle," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 608-616, November.
    80. G. Elliott & C. Granger & A. Timmermann (ed.), 2013. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 2, number 2.
    81. 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.
    82. Rochelle M. Edge & Refet S. Gurkaynak, 2010. "How Useful Are Estimated DSGE Model Forecasts for Central Bankers?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 41(2 (Fall)), pages 209-259.
    83. Mark W. Watson & James H. Stock, 2004. "Combination forecasts of output growth in a seven-country data set," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(6), pages 405-430.
    84. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
    85. Ploberger, Werner & Kramer, Walter & Kontrus, Karl, 1989. "A new test for structural stability in the linear regression model," Journal of Econometrics, Elsevier, vol. 40(2), pages 307-318, February.
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    3. Cardani, Roberta & Paccagnini, Alessia & Villa, Stefania, 2019. "Forecasting with instabilities: An application to DSGE models with financial frictions," Journal of Macroeconomics, Elsevier, vol. 61(C), pages 1-1.
    4. Alessandro Casini, 2021. "Theory of Evolutionary Spectra for Heteroskedasticity and Autocorrelation Robust Inference in Possibly Misspecified and Nonstationary Models," Papers 2103.02981, arXiv.org.
    5. Graham Elliott & Allan Timmermann, 2016. "Forecasting in Economics and Finance," Annual Review of Economics, Annual Reviews, vol. 8(1), pages 81-110, October.
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    7. Alessandro Casini & Pierre Perron, 2018. "Structural Breaks in Time Series," Papers 1805.03807, arXiv.org.

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    More about this item

    Keywords

    Forecasting; instabilities; structural breaks.;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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