The New Palgrave Dictionary of Economics

2018 Edition
| Editors: Macmillan Publishers Ltd

Structural Vector Autoregressions

  • Jesús Fernández-Villaverde
  • Juan F. Rubio-Ramírez
Reference work entry


Structural vector autoregressions (SVARs) are a multivariate, linear representation of a vector of observables on its own lags. SVARs are used by economists to recover economic shocks from observables by imposing a minimum of assumptions compatible with a large class of models. This article reviews the relation of SVARs to dynamic stochastic general equilibrium models, discusses the normalization, identification, and estimation of SVARs, and concludes with an assessment of the advantages and drawbacks of SVARs.


Bootstrap Dynamic stochastic general equilibrium models Estimation Identification Markov chain Monte Carlo methods Neoclassical growth theory Normalization Reduced-Form representation Sims, C. A. Structural vector autoregressions Vector autoregressions 

JEL Classifications

D4 D10 
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  1. Blanchard, O.J., and D. Quah. 1989. The dynamic effects of aggregate demand and supply disturbances. American Economic Review 79: 655–673.Google Scholar
  2. Blanchard, O.J., and R. Perotti. 2002. An empirical characterization of the dynamic effects of changes in government spending and taxes on output. Quarterly Journal of Economics 117: 1329–1368.CrossRefGoogle Scholar
  3. Chari, V.V., P.J. Kehoe, and E.R. McGrattan. 2005. A critique of structural VARs using real business cycle theory. Working Paper No. 631, Federal Reserve Bank of Minneapolis.Google Scholar
  4. Christiano, L.J., M. Eichenbaum, and R. Vigfusson. 2007. Assessing structural VARs. In NBER macroeconomics annual 2006, ed. D. Acemoglu, K. Rogoff, and M. Woodford, Vol. 21. Cambridge, MA: MIT.Google Scholar
  5. Fernández-Villaverde, J., J.F. Rubio-Ramírez, and T.J. Sargent. 2005. A,B,C’s (and D’s) for understanding VARs. Technical Working Paper No. 308. Cambridge, MA: NBER.Google Scholar
  6. Galí, J. 1999. Technology, employment, and the business cycle: Do technology shocks explain aggregate fluctuations? American Economic Review 89: 249–271.CrossRefGoogle Scholar
  7. Sims, C.A. 1980. Macroeconomics and reality. Econometrica 48: 1–48.CrossRefGoogle Scholar
  8. Sims, C.A., and T. Zha. 2006a. Does monetary policy generate recessions? Macroeconomic Dynamics 10: 231–272.CrossRefGoogle Scholar
  9. Sims, C.A., and T. Zha. 2006b. Were there regime switches in U.S. monetary policy? American Economic Review 96: 54–81.CrossRefGoogle Scholar
  10. Uhlig, H. 2005. What are the effects of monetary policy on output? Results from an agnostic identification procedure. Journal of Monetary Economics 52: 381–419.CrossRefGoogle Scholar
  11. Waggoner, D.F., and T. Zha. 2003. Likelihood preserving normalization in multiple equation models. Journal of Econometrics 114: 329–347.CrossRefGoogle Scholar

Copyright information

© Macmillan Publishers Ltd. 2018

Authors and Affiliations

  • Jesús Fernández-Villaverde
    • 1
  • Juan F. Rubio-Ramírez
    • 1
  1. 1.