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Are 'Deep' Parameters Stable? The Lucas Critique as an Empirical Hypothesis

  • Jeff Fuhrer

    ()

    (Federal Reserve Bank of Boston)

  • Arturo Estrella

    ()

    (Federal Reserve Bank of New York)

For years, the problems associated with the Lucas critique have loomed over empirical macroeconomics. However, relatively little effort has been devoted to testing the empirical importance of this critique. This paper develops a set of tests for small macroeconometric models, especially those used for monetary policy analysis, and implements them on a set of models used extensively in the literature. In particular, I attempt to test the robustness of optimizing versus non-optimizing models to changes in the monetary policy regime.

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Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 1999 with number 621.

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Date of creation: 01 Mar 1999
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Handle: RePEc:sce:scecf9:621
Contact details of provider: Postal: CEF99, Boston College, Department of Economics, Chestnut Hill MA 02467 USA
Fax: +1-617-552-2308
Web page: http://fmwww.bc.edu/CEF99/

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  1. Anderson, Gary & Moore, George, 1985. "A linear algebraic procedure for solving linear perfect foresight models," Economics Letters, Elsevier, vol. 17(3), pages 247-252.
  2. Ghysels, Eric & Hall, Alastair, 1990. "A Test for Structural Stability of Euler Conditions Parameters Estimated via the Generalized Method of Moments Estimator," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 31(2), pages 355-64, May.
  3. Neil R. Ericsson & David F. Hendry & Grayham E. Mizon, 1998. "Exogeneity, cointegration, and economic policy analysis," International Finance Discussion Papers 616, Board of Governors of the Federal Reserve System (U.S.).
  4. Alogoskoufis, George S & Smith, Ron, 1991. "The Phillips Curve, the Persistence of Inflation, and the Lucas Critique: Evidence from Exchange-Rate Regimes," American Economic Review, American Economic Association, vol. 81(5), pages 1254-75, December.
  5. E.K. Berndt & B.H. Hall & R.E. Hall, 1974. "Estimation and Inference in Nonlinear Structural Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 4, pages 653-665 National Bureau of Economic Research, Inc.
  6. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 33(1), pages 125-132.
  7. Ghysels, E. & Guay, A. & Hall, A., 1995. "Predictive Tests for Structural Change with Unknown Breakpoint," Cahiers de recherche 9524, Centre interuniversitaire de recherche en ├ęconomie quantitative, CIREQ.
  8. Oliner, Stephen D. & Rudebusch, Glenn D. & Sichel, Daniel, 1996. "The Lucas critique revisited assessing the stability of empirical Euler equations for investment," Journal of Econometrics, Elsevier, vol. 70(1), pages 291-316, January.
  9. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
  10. Andrews, Donald W K & Fair, Ray C, 1988. "Inference in Nonlinear Econometric Models with Structural Change," Review of Economic Studies, Wiley Blackwell, vol. 55(4), pages 615-39, October.
  11. Donald W.K. Andrews, 1990. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Cowles Foundation Discussion Papers 943, Cowles Foundation for Research in Economics, Yale University.
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