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Minimum Distance Estimation and Testing of DSGE Models from Structural VARs

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  • Patrick Fève
  • Julien Matheron
  • Jean-Guillaume Sahuc

Abstract

The aim of this paper is to complement the minimum distance estimation-structural vector autoregression approach when the weighting matrix is not optimal. In empirical studies, this choice is motivated by stochastic singularity or collinearity problems associated with the covariance matrix of impulse response functions. Consequently, the asymptotic distribution cannot be used to test the economic model's fit. To circumvent this difficulty, we propose a simple simulation method to construct critical values for the test statistics. An empirical application with US data illustrates the proposed method. Copyright (c) Blackwell Publishing Ltd and the Department of Economics, University of Oxford, 2009.

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Bibliographic Info

Article provided by Department of Economics, University of Oxford in its journal Oxford Bulletin of Economics and Statistics.

Volume (Year): 71 (2009)
Issue (Month): 6 (December)
Pages: 883-894

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Handle: RePEc:bla:obuest:v:71:y:2009:i:6:p:883-894

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References

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  1. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 2005. "Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 1-45, February.
  2. Alastair Hall & Atsushi Inoue & James M. Nason & Barbara Rossi, 2007. "Information criteria for impulse response function matching estimation of DSGE models," Working Paper 2007-10, Federal Reserve Bank of Atlanta.
  3. Jean Boivin & Marc P. Giannoni, 2006. "Has Monetary Policy Become More Effective?," The Review of Economics and Statistics, MIT Press, vol. 88(3), pages 445-462, August.
  4. David Altig & Lawrence J. Christiano & Martin Eichenbaum & Jesper Linde, 2004. "Firm-specific capital, nominal rigidities and the business cycle," Working Paper Series WP-05-01, Federal Reserve Bank of Chicago.
  5. Julio Rotemberg & Michael Woodford, 1997. "An Optimization-Based Econometric Framework for the Evaluation of Monetary Policy," NBER Chapters, in: NBER Macroeconomics Annual 1997, Volume 12, pages 297-361 National Bureau of Economic Research, Inc.
  6. Marc Giannoni & Michael Woodford, 2004. "Optimal Inflation-Targeting Rules," NBER Chapters, in: The Inflation-Targeting Debate, pages 93-172 National Bureau of Economic Research, Inc.
  7. Darné, O. & Ferrara, L., 2009. "Identification of slowdowns and accelerations for the euro area economy," Working papers 239, Banque de France.
  8. Aghion, Ph. & Askenazy, Ph. & Bourlès, R. & Cette, G. & Dromel, N., 2009. "Education, Market Rigidities and Growth," Working papers 229, Banque de France.
  9. Fabio Canova & Luca Sala, 2005. "Back to square one: Identification issues in DSGE models," Economics Working Papers 927, Department of Economics and Business, Universitat Pompeu Fabra, revised Sep 2006.
  10. Sahuc, Jean-Guillaume & Avouyi-Dovi, Sanvi, 2009. "Comportement du banquier central en environnement incertain," Economics Papers from University Paris Dauphine 123456789/5490, Paris Dauphine University.
  11. Basu, Susanto & Fernald, John G, 1997. "Returns to Scale in U.S. Production: Estimates and Implications," Journal of Political Economy, University of Chicago Press, vol. 105(2), pages 249-83, April.
  12. Amato, Jeffery D. & Laubach, Thomas, 2003. "Estimation and control of an optimization-based model with sticky prices and wages," Journal of Economic Dynamics and Control, Elsevier, vol. 27(7), pages 1181-1215, May.
  13. Bardos, Mireille & Moquet, Jeremy & Kendaoui, Ludovic & Jardet, Caroline & Avouyi-Dovi, Sanvi, 2009. "Macro stress testing with a macroeconomic credit risk model : Application to the French manufacturing sector," Economics Papers from University Paris Dauphine 123456789/11161, Paris Dauphine University.
  14. Sbordone, Argia M, 2006. "U.S. Wage and Price Dynamics: A Limited-Information Approach," MPRA Paper 811, University Library of Munich, Germany.
  15. Hall, Peter & Horowitz, Joel L, 1996. "Bootstrap Critical Values for Tests Based on Generalized-Method-of-Moments Estimators," Econometrica, Econometric Society, vol. 64(4), pages 891-916, July.
  16. Jordi Galí & Pau Rabanal, 2004. "Technology Shocks and Aggregate Fluctuations," IMF Working Papers 04/234, International Monetary Fund.
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Cited by:
  1. Carrillo, Julio A., 2012. "How well does sticky information explain the dynamics of inflation, output, and real wages?," Journal of Economic Dynamics and Control, Elsevier, vol. 36(6), pages 830-850.
  2. Kamber, Gunes & Millard, Stephen, 2010. "Using estimated models to assess nominal and real rigidities in the United Kingdom," Bank of England working papers 396, Bank of England.
  3. Franke, Reiner, 2013. "Competitive Moment Matching of a New-Keynesian and an Old-Keynesian Model," Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79988, Verein für Socialpolitik / German Economic Association.
  4. Omotor, Douglason G. & Niringiye, Aggrey, 2011. "Optimum Currency Area and Shock Asymmetry: A Dynamic Analysis of the West African Monetary Zone (WAMZ)," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 71-82, September.
  5. Lewis, Vivien & Poilly, Céline, 2012. "Firm entry, markups and the monetary transmission mechanism," Journal of Monetary Economics, Elsevier, vol. 59(7), pages 670-685.

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