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Evaluating point and density forecasts of DSGE models

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  • Wolters, Maik Hendrik

Abstract

This paper investigates the accuracy of point and density forecasts of four DSGE models for inflation, output growth and the federal funds rate. Model parameters are estimated and forecasts are derived successively from historical U.S. data vintages synchronized with the Fed’s Greenbook projections. Point forecasts of some models are of similar accuracy as the forecasts of nonstructural large dataset methods. Despite their common underlying New Keynesian modeling philosophy, forecasts of different DSGE models turn out to be quite distinct. Weighted forecasts are more precise than forecasts from individual models. The accuracy of a simple average of DSGE model forecasts is comparable to Greenbook projections for medium term horizons. Comparing density forecasts of DSGE models with the actual distribution of observations shows that the models overestimate uncertainty around point forecasts.

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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 36147.

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Date of creation: 23 Jan 2012
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Handle: RePEc:pra:mprapa:36147

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Keywords: DSGE models; forecasting; model uncertainty; forecast combination; density forecasts; real-time data; Greenbook;

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Cited by:
  1. Barbara Rossi & Tatevik Sekhposyan, 2014. "Alternative Tests for Correct Specification of Conditional Predictive Densities," Working Papers 758, Barcelona Graduate School of Economics.
  2. Edward Herbst & Frank Schorfheide, 2011. "Evaluating DSGE model forecasts of comovements," Working Papers 11-5, Federal Reserve Bank of Philadelphia.
  3. Henzel, Steffen R. & Mayr, Johannes, 2013. "The mechanics of VAR forecast pooling—A DSGE model based Monte Carlo study," The North American Journal of Economics and Finance, Elsevier, vol. 24(C), pages 1-24.
  4. Michael Dotsey, 2013. "DSGE models and their use in monetary policy," Business Review, Federal Reserve Bank of Philadelphia, issue Q2, pages 10-16.
  5. Marco Del Negro & Frank Schorfheide, 2012. "DSGE model-based forecasting," Staff Reports 554, Federal Reserve Bank of New York.
  6. Wickens, Michael R., 2012. "How Useful are DSGE Macroeconomic Models for Forecasting?," CEPR Discussion Papers 9049, C.E.P.R. Discussion Papers.
  7. Polito, Vito & Wickens, Mike, 2012. "A model-based indicator of the fiscal stance," European Economic Review, Elsevier, vol. 56(3), pages 526-551.
  8. Inske Pirschel & Maik Wolters, 2014. "Forecasting German Key Macroeconomic Variables Using Large Dataset Methods," Kiel Working Papers 1925, Kiel Institute for the World Economy.
  9. Kolasa, Marcin & Rubaszek, Michał, 2014. "Forecasting with DSGE models with financial frictions," Dynare Working Papers 40, CEPREMAP.

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