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How Useful Are Estimated DSGE Model Forecasts for Central Bankers?

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  • Edge, Rochelle M
  • Gürkaynak, Refet S.

Abstract

DSGE models are a prominent tool for forecasting at central banks and the competitive forecasting performance of these models relative to alternatives--including official forecasts--has been documented. When evaluating DSGE models on an absolute basis, however, we find that the benchmark estimated medium scale DSGE model forecasts inflation and GDP growth very poorly, although statistical and judgmental forecasts forecast as poorly. Our finding is the DSGE model analogue of the literature documenting the recent poor performance of macroeconomic forecasts relative to simple naive forecasts since the onset of the Great Moderation. While this finding is broadly consistent with the DSGE model we employ--ie, the model itself implies that under strong monetary policy especially inflation deviations should be unpredictable--a 'wrong' model may also have the same implication. We therefore argue that forecasting ability during the Great Moderation is not a good metric to judge models.

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Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 8158.

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Date of creation: Dec 2010
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Handle: RePEc:cpr:ceprdp:8158

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Keywords: DSGE model forecast; forecast comparison; Great Moderation;

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References

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  1. Malin Adolfson & Michael K. Andersson & Jesper Lindé & Mattias Villani & Anders Vredin, 2007. "Modern Forecasting Models in Action: Improving Macroeconomic Analyses at Central Banks," International Journal of Central Banking, International Journal of Central Banking, vol. 3(4), pages 111-144, December.
  2. Kirdan Lees & Troy Matheson & Christie Smith, 2007. "Open Economy Dsge-Var Forecasting And Policy Analysis: Head To Head With The Rbnz Published Forecasts," CAMA Working Papers 2007-05, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  3. Andrew Atkeson & Lee E. Ohanian., 2001. "Are Phillips curves useful for forecasting inflation?," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Win, pages 2-11.
  4. Refet S. Gürkaynak & Brian Sack & Eric Swanson, 2006. "Market-based measures of monetary policy expectations," Working Paper Series 2006-04, Federal Reserve Bank of San Francisco.
  5. D’Agostino, Antonello & Giannone, Domenico & Surico, Paolo, 2006. "(Un)Predictability and macroeconomic stability," Working Paper Series 0605, European Central Bank.
  6. Bharat Trehan, 2009. "Survey measures of expected inflation and the inflation process," Working Paper Series 2009-10, Federal Reserve Bank of San Francisco.
  7. Volker Wieland & Maik Wolters, 2011. "The diversity of forecasts from macroeconomic models of the US economy," Economic Theory, Springer, vol. 47(2), pages 247-292, June.
  8. Rochelle M. Edge & Michael T. Kiley & Jean-Philippe Laforte, 2009. "A comparison of forecast performance between Federal Reserve staff forecasts, simple reduced-form models, and a DSGE model," Finance and Economics Discussion Series 2009-10, Board of Governors of the Federal Reserve System (U.S.).
  9. Jeff Fuhrer & Giovanni Olivei & Geoffrey M. B. Tootell, 2009. "Empirical estimates of changing inflation dynamics," Working Papers 09-4, Federal Reserve Bank of Boston.
  10. Antonello D’ Agostino & Domenico Giannone, 2012. "Comparing Alternative Predictors Based on Large‐Panel Factor Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(2), pages 306-326, 04.
  11. Refet Gürkaynak & Justin Wolfers, 2005. "Macroeconomic Derivatives: An Initial Analysis of Market-Based Macro Forecasts, Uncertainty, and Risk," NBER Chapters, in: NBER International Seminar on Macroeconomics 2005, pages 11-50 National Bureau of Economic Research, Inc.
  12. John P. Judd & Bharat Trehan, 1992. "Money, credit, and M2," FRBSF Economic Letter, Federal Reserve Bank of San Francisco, issue sep4.
  13. Faust, Jon & Wright, Jonathan H., 2009. "Comparing Greenbook and Reduced Form Forecasts Using a Large Realtime Dataset," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 468-479.
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Citations

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Cited by:
  1. Edward Herbst & Frank Schorfheide, 2011. "Evaluating DSGE model forecasts of comovements," Working Papers 11-5, Federal Reserve Bank of Philadelphia.
  2. Ippei Fujiwara & Yasuo Hirose, 2014. "Indeterminacy and Forecastability," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 46(1), pages 243-251, 02.
  3. Wolters, Maik Hendrik, 2012. "Evaluating point and density forecasts of DSGE models," IMFS Working Paper Series 59, Institute for Monetary and Financial Stability (IMFS), Goethe University Frankfurt.
  4. Vasco Cúrdia & Marco Del Negro & Daniel L. Greenwald, 2012. "Rare shocks, great recessions," Staff Reports 585, Federal Reserve Bank of New York.
  5. Jon D. Samuels & Rodrigo Sekkel, 2013. "Forecasting with Many Models: Model Confidence Sets and Forecast Combination," Working Papers 13-11, Bank of Canada.
  6. Marco Del Negro & Frank Schorfheide, 2012. "DSGE model-based forecasting," Staff Reports 554, Federal Reserve Bank of New York.
  7. Knüppel, Malte & Schultefrankenfeld, Guido, 2013. "The Empirical (Ir)Relevance of the Interest Rate Assumption for Central Bank Forecasts," Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 80042, Verein für Socialpolitik / German Economic Association.
  8. Kolasa, Marcin & Rubaszek, Michał, 2014. "Forecasting with DSGE models with financial frictions," Dynare Working Papers 40, CEPREMAP.
  9. Marco Del Negro & Marc Giannoni & Christina Patterson, 2012. "The forward guidance puzzle," Staff Reports 574, Federal Reserve Bank of New York.
  10. Gürkaynak, Refet S. & Kisacikoglu, Burçin & Rossi, Barbara, 2013. "Do DSGE Models Forecast More Accurately Out-of-Sample than VAR Models?," CEPR Discussion Papers 9576, C.E.P.R. Discussion Papers.
  11. Arai, Natsuki, 2014. "Using forecast evaluation to improve the accuracy of the Greenbook forecast," International Journal of Forecasting, Elsevier, vol. 30(1), pages 12-19.
  12. James M. Nason & Gregor W. Smith, 2014. "Measuring the Slowly Evolving Trend in US Inflation with Professional Forecasts," CAMA Working Papers 2014-07, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  13. Bårdsen, Gunnar & den Reijer, Ard & Jonasson, Patrik & Nymoen, Ragnar, 2012. "MOSES: Model for studying the economy of Sweden," Economic Modelling, Elsevier, vol. 29(6), pages 2566-2582.
  14. James M. Nason & Gregor W. Smith, 2013. "Reverse Kalman filtering U.S. inflation with sticky professional forecasts," Working Papers 13-34, Federal Reserve Bank of Philadelphia.
  15. Wolters, Maik H., 2011. "Forecasting under Model Uncertainty," Annual Conference 2011 (Frankfurt, Main): The Order of the World Economy - Lessons from the Crisis 48723, Verein für Socialpolitik / German Economic Association.

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