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Take your model bowling: forecasting with general equilibrium models

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  • Marco Del Negro
  • Frank Schorfheide

Abstract

During the past two decades, dynamic stochastic general equilibrium (DSGE) models have taken center stage in academic macroeconomics. Nonetheless, these models are still rarely used in policy-making and forecasting. ; This article describes the workings of the DSGE-VAR, a procedure that combines DSGE models and vector autoregressions (VARs). The procedure uses DSGE models as priors to restrict the VAR’s parameters. Since the VAR’s parameters are imprecisely estimated unless a very long time series of data is available, using DSGE priors can improve the VAR’s forecasting performance. Moreover, the Lucas critique implies that DSGE priors can be particularly useful when forecasting the impact of policy changes. ; The authors assess DSGE-VAR’s forecasting performance in terms of three variables that most interest monetary policymakers: real output growth, inflation, and the federal funds rate. Their results show that the DSGE-VAR forecast is superior to that of unrestricted VARs and comparable to that of VARs with Minnesota priors. ; The article also discusses how DSGE-VAR can be used to identify the fundamental shocks that hit the economy and to forecast the impact of changes in the policy rule followed by the monetary authorities. ; Perhaps in the not-too-distant future, practitioners and policymakers will be able to use a full-fledged DSGE model for both forecasting and policy assessment. In the meantime, the authors argue, DSGE-VAR may provide a viable alternative to the models currently used.

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Bibliographic Info

Article provided by Federal Reserve Bank of Atlanta in its journal Economic Review.

Volume (Year): (2003)
Issue (Month): Q4 ()
Pages: 35-50

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Handle: RePEc:fip:fedaer:y:2003:i:q4:p:35-50:n:v.88no.4

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Keywords: Econometric models ; Stochastic analysis ; Economic forecasting;

References

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  1. Marco Del Negro & Frank Schorfheide, 2004. "Priors from General Equilibrium Models for VARS," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 45(2), pages 643-673, 05.
  2. Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1986. "Forecasting and conditional projection using realistic prior distribution," Staff Report, Federal Reserve Bank of Minneapolis 93, Federal Reserve Bank of Minneapolis.
  3. Lawrence J. Christiano & Martin Eichenbaum & Charles Evans, 2001. "Nominal rigidities and the dynamic effects of a shock to monetary policy," Working Paper 0107, Federal Reserve Bank of Cleveland.
  4. Ben S. Bernanke, 1986. "Alternative Explanations of the Money-Income Correlation," NBER Working Papers 1842, National Bureau of Economic Research, Inc.
  5. Ray C. Fair, 1992. "The Cowles Commission Approach, Real Business Cycle Theories, and New Keynesian Economics," NBER Working Papers 3990, National Bureau of Economic Research, Inc.
  6. Flint Brayton & Eileen Mauskopf & David Reifschneider & Peter Tinsley & John Williams, 1997. "The role of expectations in the FRB/US macroeconomic model," Federal Reserve Bulletin, Board of Governors of the Federal Reserve System (U.S.), Board of Governors of the Federal Reserve System (U.S.), issue Apr, pages 227-245.
  7. Brayton, Flint & Levin, Andrew & Lyon, Ralph & Williams, John C., 1997. "The evolution of macro models at the Federal Reserve Board," Carnegie-Rochester Conference Series on Public Policy, Elsevier, Elsevier, vol. 47(1), pages 43-81, December.
  8. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, Econometric Society, vol. 48(1), pages 1-48, January.
  9. Altug, Sumru, 1989. "Time-to-Build and Aggregate Fluctuations: Some New Evidence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 30(4), pages 889-920, November.
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Cited by:
  1. Javier Andrés & Fernando Restoy, 2007. "Macroeconomic modelling in EMU: how relevant is the change in regime?," Banco de Espa�a Working Papers 0718, Banco de Espa�a.
  2. Kirdan Lees & Troy Matheson & Christie Smith, 2007. "Open economy DSGE-VAR forecasting and policy analysis - head to head with the RBNZ published forecasts," Reserve Bank of New Zealand Discussion Paper Series DP2007/01, Reserve Bank of New Zealand.
  3. Muhanji, Stella & Malikane, Christopher & Ojah, Kalu, 2013. "Price and liquidity puzzles of a monetary shock: Evidence from indebted African economies," Economic Modelling, Elsevier, Elsevier, vol. 33(C), pages 620-630.
  4. Tovar, Camilo Ernesto, 2009. "DSGE Models and Central Banks," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy, vol. 3(16), pages 1-31.
  5. Lees, Kirdan & Matheson, Troy & Smith, Christie, 2011. "Open economy forecasting with a DSGE-VAR: Head to head with the RBNZ published forecasts," International Journal of Forecasting, Elsevier, Elsevier, vol. 27(2), pages 512-528, April.
  6. Alvarez-Lois, Pedro & Harrison, Richard & Piscitelli, Laura & Scott, Alasdair, 2008. "On the application and use of DSGE models," Journal of Economic Dynamics and Control, Elsevier, Elsevier, vol. 32(8), pages 2428-2452, August.
  7. Muhanji, Stella & Ojah, Kalu, 2011. "External shocks and persistence of external debt in open vulnerable economies: The case of Africa," Economic Modelling, Elsevier, Elsevier, vol. 28(4), pages 1615-1628, July.
  8. Liu, G. & Gupta, R. & Schaling, E., 2008. "Forecasting the South African Economy: A DSGE-VAR Approach," Discussion Paper, Tilburg University, Center for Economic Research 2008-32, Tilburg University, Center for Economic Research.

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