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Regime-dependent impulse response functions in a Markov-switching vector autoregression model

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Author Info

  • Ehrmann , Michael
  • Ellison, Martin
  • Valla, Natacha

Abstract

In this paper we introduce identifying restrictions into a Markov-switching vector autoregression model. We define a separate set of impulse responses for each Markov regime to show how fundamental disturbances affect the variables in the model dependent on the regime. We go to illustrate the use of these regime-dependent impulse response functions in a model of the U.S. economy. The regimes we identify come close to the “old” and “new economy” regimes found in recent research. We provide evidence that oil price shocks are much less contractionary and inflationary than they used to be. We show furthermore that the decoupling of the US economic performance from oil price shocks cannot be explained by “good luck” alone, but that structural changes within the US economy have taken place.

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File URL: http://www.suomenpankki.fi/en/julkaisut/tutkimukset/keskustelualoitteet/Documents/0111.pdf
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Bibliographic Info

Paper provided by Bank of Finland in its series Research Discussion Papers with number 11/2001.

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Length: 27 pages
Date of creation: 03 Aug 2001
Date of revision:
Handle: RePEc:hhs:bofrdp:2001_011

Contact details of provider:
Postal: Bank of Finland, P.O. Box 160, FI-00101 Helsinki, Finland
Web page: http://www.suomenpankki.fi/en/
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Related research

Keywords: vector autoregression; regime switching; shocks; new economy;

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References

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  1. Kevin L. Kliesen, 2001. "Rising oil prices and economic turmoil: must they always go hand in hand?," The Regional Economist, Federal Reserve Bank of St. Louis, issue Jan, pages 4-9.
  2. Krolzig, H.-M. & Toro, J., 1999. "A New Approach to the Analysis of Shocks and the Cycle in a Model of Output and Employment," Economics Working Papers eco99/30, European University Institute.
  3. Ehrmann, M., 2000. "Firm Size and Monetary Policy Transmission - Evidence from German Business Survey Data," Economics Working Papers eco2000/12, European University Institute.
  4. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
  5. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70.
  6. Blanchard, Olivier Jean & Quah, Danny, 1989. "The Dynamic Effects of Aggregate Demand and Supply Disturbances," American Economic Review, American Economic Association, vol. 79(4), pages 655-73, September.
  7. Michael M. Hutchison, 1992. "Structural change and the macroeconomic effects of oil shocks: empirical evidence from the United States and Japan," Pacific Basin Working Paper Series 92-06, Federal Reserve Bank of San Francisco.
  8. Richard Clarida & Jordi Galí & Mark Gertler, 1997. "Monetary policy rules and macroeconomic stability: Evidence and some theory," Economics Working Papers 350, Department of Economics and Business, Universitat Pompeu Fabra, revised May 1999.
  9. Robert G. King & Charles I. Plosser & James H. Stock & Mark W. Watson, 1987. "Stochastic Trends and Economic Fluctuations," NBER Working Papers 2229, National Bureau of Economic Research, Inc.
  10. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
  11. Ellison, Martin & Valla, Natacha, 2000. "Learning, uncertainty and central bank activism in an economy with strategic interactions," Working Paper Series 0028, European Central Bank.
  12. Christopher Sims & Tao Zha, 2002. "Macroeconomic switching," Proceedings, Federal Reserve Bank of San Francisco, issue Mar.
  13. 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 357-84, March.
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