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DSGE Model Restrictions for Structural VAR Identification

  • Philip Liu

    (International Monetary Fund)

  • Konstantinos Theodoridis

    (Bank of England)

The identification of reduced-form VAR models has been the subject of numerous debates in the literature. Different sets of identifying assumptions can lead to very different conclusions regarding the effects of shocks. This paper proposes a theoretically consistent identification strategy using restrictions implied by a DSGE model. Monte Carlo simulations suggest that both quantitative and qualitative restrictions work well together, where they act as complements to each other, in minimizing errors in finding the correct VAR identification. When using 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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Article provided by International Journal of Central Banking in its journal International Journal of Central Banking.

Volume (Year): 8 (2012)
Issue (Month): 4 (December)
Pages: 61-95

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Handle: RePEc:ijc:ijcjou:y:2012:q:4:a:3
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  1. Paustian Matthias, 2007. "Assessing Sign Restrictions," The B.E. Journal of Macroeconomics, De Gruyter, vol. 7(1), pages 1-33, August.
  2. Marco Del Negro & Frank Schorfheide, 2002. "Priors from general equilibrium models for VARs," Working Paper 2002-14, Federal Reserve Bank of Atlanta.
  3. Frank Smets & Raf Wouters, 2002. "An estimated dynamic stochastic general equilibrium model of the euro area," Working Paper Research 35, National Bank of Belgium.
  4. 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.
  5. Jesús Fernández-Villaverde & Juan F. Rubio-Ramirez & Thomas J. Sargent, 2005. "A,B,C's (and D's)'s for Understanding VARS," Levine's Bibliography 172782000000000096, UCLA Department of Economics.
  6. 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.
  7. Daniel F. Waggoner & Tao Zha, 1998. "Conditional forecasts in dynamic multivariate models," Working Paper 98-22, Federal Reserve Bank of Atlanta.
  8. Renee Fry & Adrian Pagan, 2010. "Sign Restrictions in Structural Vector Autoregressions: A Critical Review," CAMA Working Papers 2010-22, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  9. Kenneth L. Judd, 1998. "Numerical Methods in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262100711, June.
  10. Del Negro, Marco & Schorfheide, Frank & Smets, Frank & Wouters, Rafael, 2005. "On the Fit and Forecasting Performance of New Keynesian Models," CEPR Discussion Papers 4848, C.E.P.R. Discussion Papers.
  11. Banbura, Marta & Giannone, Domenico & Reichlin, Lucrezia, 2007. "Bayesian VARs with Large Panels," CEPR Discussion Papers 6326, C.E.P.R. Discussion Papers.
  12. Marta Bańbura, 2008. "Large Bayesian VARs," 2008 Meeting Papers 334, Society for Economic Dynamics.
  13. 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.
  14. 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.
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