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DSGE model restrictions for structural VAR identification

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Author Info

  • Liu, Philip

    ()
    (International Monetary Fund)

  • Theodoridis, Konstantinos

    ()
    (Bank of England)

Abstract

The identification of reduced-form VAR model had been the subject of numerous debates in the literature. Different sets of identifying assumptions can lead to very different conclusions in the policy debate. This paper proposes a theoretically consistent identification strategy using restrictions implied by a DSGE model. Monte Carlo simulations suggest the proposed identification strategy is successful in recovering the true structural shocks from the data. In the face of misspecified model restrictions, the data tend to push the identified VAR responses away from the misspecified model and closer to the true data generating process.

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Bibliographic Info

Paper provided by Bank of England in its series Bank of England working papers with number 402.

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Length: 36 pages
Date of creation: 28 Oct 2010
Date of revision:
Handle: RePEc:boe:boeewp:0402

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Keywords: VAR identification; model misspecification; DSGE model;

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References

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  1. Alasdair Scott & George Kapetanios & Adrian Pagan, 2005. "Making a match: combining theory and evidence in policy-oriented macroeconomic modelling," Computing in Economics and Finance 2005 462, Society for Computational Economics.
  2. Marco Del Negro & Frank Schorfheide & Frank Smets & Raf Wouters, 2004. "On the fit and forecasting performance of New Keynesian models," Working Paper 2004-37, Federal Reserve Bank of Atlanta.
  3. Banbura, Marta & Giannone, Domenico & Reichlin, Lucrezia, 2007. "Bayesian VARs with Large Panels," CEPR Discussion Papers 6326, C.E.P.R. Discussion Papers.
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  7. Ren�e Fry & Adrian Pagan, 2011. "Sign Restrictions in Structural Vector Autoregressions: A Critical Review," Journal of Economic Literature, American Economic Association, vol. 49(4), pages 938-60, December.
  8. Frank Smets & Raf Wouters, 2003. "An Estimated Dynamic Stochastic General Equilibrium Model of the Euro Area," Journal of the European Economic Association, MIT Press, vol. 1(5), pages 1123-1175, 09.
  9. G. Peersman & R. Straub, 2005. "Technology Shocks and Robust Sign Restrictions in a Euro Area SVAR," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/288, Ghent University, Faculty of Economics and Business Administration.
  10. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2006. "Assessing Structural VARs," NBER Working Papers 12353, National Bureau of Economic Research, Inc.
    • Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2007. "Assessing Structural VARs," NBER Chapters, in: NBER Macroeconomics Annual 2006, Volume 21, pages 1-106 National Bureau of Economic Research, Inc.
  11. Lütkepohl, Helmut & Poskitt, D.S., 1991. "Estimating Orthogonal Impulse Responses via Vector Autoregressive Models," Econometric Theory, Cambridge University Press, vol. 7(04), pages 487-496, December.
  12. Daniel F. Waggoner & Tao Zha, 1999. "Conditional Forecasts In Dynamic Multivariate Models," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 639-651, November.
  13. Jesús Fernández-Villaverde & Juan F. Rubio-Ramirez & Thomas J. Sargent & Mark Watson, 2006. "A,B,C's (and D's)'s for Understanding VARS," Levine's Bibliography 321307000000000646, UCLA Department of Economics.
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Cited by:
  1. Theodoridis, Konstantinos, 2011. "An efficient minimum distance estimator for DSGE models," Bank of England working papers 439, Bank of England.
  2. Tim Robinson, 2013. "Estimating and Identifying Empirical BVAR-DSGE Models for Small Open Economies," RBA Research Discussion Papers rdp2013-06, Reserve Bank of Australia.
  3. Gehrke, Britta & Yao, Fang, 2013. "Sources of International Business Cycles: The Role of Real Supply Shocks Revisited," Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79821, Verein für Socialpolitik / German Economic Association.

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