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Macroeconomic switching

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  • Christopher A. Sims
  • Tao Zha

Abstract

We discuss the results of fitting a 6-variable structural VAR in which we allow for certain types of parameter variation over time. Allowing structural equation variances to change over time is extremely important in improving fit. Allowing the coefficients that define the model?s dynamics to change is less important to improving fit, though models with changing parameters are consistent with the data. We pay special attention to a version of the model that allows the monetary policy rule, but not other parts of the model, to show changing coefficients. Results from this model fit some aspects of conventional wisdom about changes in monetary policy over time, but imply that the changes in policy have been more subtle than dramatic. We construct counterfactual histories for the early 1980?s, suppressing the ?Volcker regime? in monetary policy. We find a steadier decline in inflation and a smaller recession earlier in the period, but slower growth later, than actually occurred.

Suggested Citation

  • Christopher A. Sims & Tao Zha, 2002. "Macroeconomic switching," Proceedings, Federal Reserve Bank of San Francisco, issue Mar.
    • Handle: RePEc:fip:fedfpr:y:2002:i:mar:x:6
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    References listed on IDEAS

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    1. Leeper, Eric M. & Zha, Tao, 2003. "Modest policy interventions," Journal of Monetary Economics, Elsevier, vol. 50(8), pages 1673-1700, November.
    2. Richard Clarida & Jordi Galí & Mark Gertler, 2000. "Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 115(1), pages 147-180.
    3. Timothy Cogley & Thomas J. Sargent, 2002. "Evolving Post-World War II US Inflation Dynamics," NBER Chapters, in: NBER Macroeconomics Annual 2001, Volume 16, pages 331-388, National Bureau of Economic Research, Inc.
    4. Waggoner, Daniel F. & Zha, Tao, 2003. "A Gibbs sampler for structural vector autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 28(2), pages 349-366, November.
    5. 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.
    6. Hanson, Michael S., 2006. "Varying monetary policy regimes: A vector autoregressive investigation," Journal of Economics and Business, Elsevier, vol. 58(5-6), pages 407-427.
    7. Rochelle M. Edge, 2000. "Time-to-build, time-to-plan, habit-persistence, and the liquidity effect," International Finance Discussion Papers 673, Board of Governors of the Federal Reserve System (U.S.).
    8. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    9. Sims, Christopher A & Zha, Tao, 1998. "Bayesian Methods for Dynamic Multivariate Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 949-968, November.
    10. Eric M. Leeper & Tao Zha, 2002. "Empirical analysis of policy interventions," Proceedings, Federal Reserve Bank of San Francisco, issue Mar.
    11. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    12. Chib S. & Jeliazkov I., 2001. "Marginal Likelihood From the Metropolis-Hastings Output," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 270-281, March.
    13. Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388, December.
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