The Quantitative Significance of the Lucas Critique
Abstract
T. Doan, R. Litterman, and C. Sims have suggested using conditional forecasts to do policy analysis with Bayesian vector autoregression models. Their method seems to violate the Lucas critique, which implies that coefficients of a Bayesian vector autoregression model will change when there is a change in policy rules. In this article, the authors attempt to determine whether the Lucas critique is important quantitatively in a Bayesian vector autoregression macro model that they construct. They find evidence following two candidate policy rule changes of significant coefficient instability and of a deterioration in the performance of the Doan, Litterman, and Sims method.Download Info
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Bibliographic Info
Article provided by American Statistical Association in its journal Journal of Business and Economic Statistics.
Volume (Year): 9 (1991)
Issue (Month): 4 (October)
Pages: 361-87
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Related research
Keywords:Other versions of this item:
- Preston J. Miller & William Roberds, 1987. "The quantitative significance of the Lucas critique," Staff Report 109, Federal Reserve Bank of Minneapolis.
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Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.Cited by:
- Eric M. Leeper & Tao Zha, 2002.
"Modest Policy Interventions,"
NBER Working Papers
9192, National Bureau of Economic Research, Inc.
- Leeper, Eric M. & Zha, Tao, 2003. "Modest policy interventions," Journal of Monetary Economics, Elsevier, vol. 50(8), pages 1673-1700, November.
- Eric M. Leeper & Tao Zha, 2002. "Modest policy interventions," Working Paper 2002-19, Federal Reserve Bank of Atlanta.
- Eric M. Leeper & Tao Zha, 2003. "Modest policy interventions," Working Paper 2003-24, Federal Reserve Bank of Atlanta.
- Eric M. Leeper & Tao Zha, 1999. "Modest policy interventions," Working Paper 99-22, Federal Reserve Bank of Atlanta.
- Preston J. Miller & William Roberds, 1992. "How little we know about deficit policy effects," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Win, pages 2-11.
- Freeman, John R., 1996. "A Computable Equilibrium Model for the Study of Political Economy," Bulletins 7484, University of Minnesota, Economic Development Center.
- Preston J. Miller & Will Roberds, 1989.
"How little we know about budget policy effects,"
Staff Report
120, Federal Reserve Bank of Minneapolis.
- Preston J. Miller & William Roberds, 1989. "How little we know about budget policy effects," Working Paper 89-4, Federal Reserve Bank of Atlanta.
- Daniel F. Waggoner & Tao Zha, 1998.
"Conditional forecasts in dynamic multivariate models,"
Working Paper
98-22, Federal Reserve Bank of Atlanta.
- Daniel F. Waggoner & Tao Zha, 1999. "Conditional Forecasts In Dynamic Multivariate Models," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 639-651, November.
- Pierre-Yves HENIN & Marie PODEVIN, 2002. "Assessing the Effects of Policy Changes: Lesson from the European 1992 Experience," Annales d'Economie et de Statistique, ENSAE, issue 67-68, pages 435-461.
- David E. Runkle, 1989. "The U.S. economy in 1990 and 1991: continued expansion likely," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Fall, pages 19-26.
- Preston J. Miller & Richard M. Todd, 1992. "Real effects of monetary policy in a world economy," Staff Report 154, Federal Reserve Bank of Minneapolis.
- Miller, Preston J. & Todd, Richard M., 1995. "Real effects of monetary policy in a world economy," Journal of Economic Dynamics and Control, Elsevier, vol. 19(1-2), pages 125-153.
- Daniel M. Chin & John F. Geweke & Preston J. Miller, 2000. "Predicting turning points," Staff Report 267, Federal Reserve Bank of Minneapolis.
- Preston J. Miller & David E. Runkle, 1989. "The U.S. economy in 1989 and 1990: walking a fine line," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Win, pages 3-10.
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