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Are "deep" parameters stable? the Lucas critique as an empirical hypothesis

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Author Info
Arturo Estrella
Jeffrey C. Fuhrer

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Abstract

For years, the problems associated with the Lucas critique have loomed over empirical macroeconomics. Since the publication of the classic Lucas (1976) critique, researchers have endeavored to specify models that capture the underlying dynamic decision-making behavior of consumers and firms who require forecasts of future events. By uncovering "deep" structural parameters that characterize these fundamental behaviors, and by explicitly modeling expectations, it is argued one can capture the dependence of agents' behavior on the functions describing policy. However, relatively little effort has been devoted to testing the empirical importance of this critique. Can one find specifications that are policy-invariant? 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, we attempt to test the robustness of optimizing versus non-optimizing models to changes in the monetary policy regime. In this paper we present evidence that shows that some forward-looking models from the recent literature may be less stable that their better-fitting backward-looking counterparts.

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Paper provided by Federal Reserve Bank of Boston in its series Working Papers with number 99-4.

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Date of creation: 1999
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Handle: RePEc:fip:fedbwp:99-4

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Keywords: Monetary policy ; Econometrics ; Macroeconomics ; Forecasting;

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  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. [Downloadable!] (restricted)
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  3. Andrews, Donald W K & Fair, Ray C, 1988. "Inference in Nonlinear Econometric Models with Structural Change," Review of Economic Studies, Blackwell Publishing, vol. 55(4), pages 615-39, October. [Downloadable!] (restricted)
  4. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July. [Downloadable!] (restricted)
  5. Ghysels, E. & Guay, A. & Hall, A., 1995. "Predictive Tests for Structural Change with Unknown Breakpoint," Cahiers de recherche 9524, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
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  6. 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.). [Downloadable!]
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  7. 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 103-116 National Bureau of Economic Research, Inc. [Downloadable!]
  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. [Downloadable!] (restricted)
  9. Anderson, Gary & Moore, George, 1985. "A linear algebraic procedure for solving linear perfect foresight models," Economics Letters, Elsevier, vol. 17(3), pages 247-252. [Downloadable!] (restricted)
  10. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-56, July. [Downloadable!] (restricted)
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