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Inference for VARs Identified with Sign Restrictions

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  • Hyungsik Roger Moon
  • Frank Schorfheide
  • Eleonora Granziera
  • Mihye Lee

Abstract

There is a fast growing literature that partially identifies structural vector autoregressions (SVARs) by imposing sign restrictions on the responses of a subset of the endogenous variables to a particular structural shock (sign-restricted SVARs). To date, the methods that have been used are only justified from a Bayesian perspective. This paper develops methods of constructing error bands for impulse response functions of sign-restricted SVARs that are valid from a frequentist perspective. We also provide a comparison of frequentist and Bayesian error bands in the context of an empirical application - the former can be twice as wide as the latter.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 17140.

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Date of creation: Jun 2011
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Handle: RePEc:nbr:nberwo:17140
Note: EFG ME
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Find related papers by JEL classification:
  • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
  • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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  1. Juan F. Rubio-Ramírez & Daniel F. Waggoner & Tao Zha, 2010. "Structural Vector Autoregressions: Theory of Identification and Algorithms for Inference," Review of Economic Studies, Oxford University Press, vol. 77(2), pages 665-696.
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  5. Andrew Mountford & Harald Uhlig, 2005. "What are the Effects of Fiscal Policy Shocks?," SFB 649 Discussion Papers SFB649DP2005-039, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  6. Andrews, Donald W.K. & Guggenberger, Patrik, 2009. "Validity Of Subsampling And “Plug-In Asymptotic” Inference For Parameters Defined By Moment Inequalities," Econometric Theory, Cambridge University Press, vol. 25(03), pages 669-709, June.
  7. Peersman, Gert, 2003. "What Caused the Early Millennium Slowdown? Evidence Based on Vector Autoregressions," CEPR Discussion Papers 4087, C.E.P.R. Discussion Papers.
  8. Jean Boivin & Marc P. Giannoni, 2003. "Has Monetary Policy Become More Effective?," NBER Working Papers 9459, National Bureau of Economic Research, Inc.
  9. Evi Pappa, 2009. "The Effects Of Fiscal Shocks On Employment And The Real Wage," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 50(1), pages 217-244, 02.
  10. Gert Peersman & Christiane Baumeister, 2009. "Time-Varying Effects of Oil Supply Shocks on the US Economy," 2009 Meeting Papers 171, Society for Economic Dynamics.
  11. Lutz Kilian & Daniel P. Murphy, 2012. "Why Agnostic Sign Restrictions Are Not Enough: Understanding The Dynamics Of Oil Market Var Models," Journal of the European Economic Association, European Economic Association, vol. 10(5), pages 1166-1188, October.
  12. Stefano Neri & Luca Dedola, 2004. "Are technology shocks contractionary? A Bayesian VAR analysis with priors on impulses responses," 2004 Meeting Papers 406, Society for Economic Dynamics.
  13. Jon Faust, 1998. "The robustness of identified VAR conclusions about money," International Finance Discussion Papers 610, Board of Governors of the Federal Reserve System (U.S.).
  14. Phillips, Peter C. B., 1998. "Impulse response and forecast error variance asymptotics in nonstationary VARs," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 21-56.
  15. Victor Chernozhukov & Han Hong & Elie Tamer, 2007. "Estimation and Confidence Regions for Parameter Sets in Econometric Models," Econometrica, Econometric Society, vol. 75(5), pages 1243-1284, 09.
  16. Barry Z. Cynamon & Donald H. Dutkowsky & Barry E. Jones, 2006. "Redefining the Monetary Agggregates: A Clean Sweep," Eastern Economic Journal, Eastern Economic Association, vol. 32(4), pages 661-672, Fall.
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