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Interpreting rational expectations econometrics via analytic function approach

Author

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  • Fei Tan

    (Department of Economics, Saint Louis University; ICSS, Zhejiang University)

Abstract

An analytic function method is applied to illustrate Geweke's (2010) three econometric interpretations for a generic rational expectations (RE) model. This delivers an explicit characterization of the model's cross-equation restrictions imposed by the RE hypothesis under each interpretation. It is shown that the degree of identification on the deep parameters is positively related to the strength of the underlying econometric interpretation, and observationally equivalent models may arise once the cross-equation restrictions are interpreted in a minimal sense. This offers important insights into the econometric modeling and evaluation of dynamic economic models.

Suggested Citation

  • Fei Tan, 2017. "Interpreting rational expectations econometrics via analytic function approach," Economics Bulletin, AccessEcon, vol. 37(2), pages 1182-1190.
    • Handle: RePEc:ebl:ecbull:eb-17-00218
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    References listed on IDEAS

    as
    1. Pesaran, M. H., 1981. "Identification of rational expectations models," Journal of Econometrics, Elsevier, vol. 16(3), pages 375-398, August.
    2. Thomas Lubik & Frank Schorfheide, 2006. "A Bayesian Look at New Open Economy Macroeconomics," NBER Chapters, in: NBER Macroeconomics Annual 2005, Volume 20, pages 313-382, National Bureau of Economic Research, Inc.
    3. Wallis, Kenneth F, 1980. "Econometric Implications of the Rational Expectations Hypothesis," Econometrica, Econometric Society, vol. 48(1), pages 49-73, January.
    4. Hansen, Lars Peter & Sargent, Thomas J., 1980. "Formulating and estimating dynamic linear rational expectations models," Journal of Economic Dynamics and Control, Elsevier, vol. 2(1), pages 7-46, May.
    5. John Geweke, 2010. "Complete and Incomplete Econometric Models," Economics Books, Princeton University Press, edition 1, number 9218.
    6. Tan, Fei & Walker, Todd B., 2015. "Solving generalized multivariate linear rational expectations models," Journal of Economic Dynamics and Control, Elsevier, vol. 60(C), pages 95-111.
    7. Olivier J. Blanchard, 1982. "Identification in Dynamic Linear Models with Rational Expectations," NBER Technical Working Papers 0024, National Bureau of Economic Research, Inc.
    8. Marco Del Negro & Frank Schorfheide, 2004. "Priors from General Equilibrium Models for VARS," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 45(2), pages 643-673, May.
    9. DeJong, David N & Ingram, Beth Fisher & Whiteman, Charles H, 1996. "A Bayesian Approach to Calibration," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(1), pages 1-9, January.
    10. Ingram, Beth F. & Whiteman, Charles H., 1994. "Supplanting the 'Minnesota' prior: Forecasting macroeconomic time series using real business cycle model priors," Journal of Monetary Economics, Elsevier, vol. 34(3), pages 497-510, December.
    11. Andreas Beyer & Roger E. A. Farmer, 2007. "Testing for Indeterminacy: An Application to U.S. Monetary Policy: Comment," American Economic Review, American Economic Association, vol. 97(1), pages 524-529, March.
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    More about this item

    Keywords

    Rational expectations; econometric interpretation; identification; analytic functions;
    All these keywords.

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

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