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The role of beliefs in inference for rational expectations models

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  • Lehmann, Bruce N.
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    Abstract

    This paper discusses inference for rational expectations models estimated via minimum distance methods by characterizing the probability beliefs regarding the data generating process (DGP) that are compatible with given moment conditions. The null hypothesis is taken to be rational expectations and the alternative hypothesis to be distorted beliefs. This distorted beliefs alternative is analyzed from the perspective of a hypothetical semiparametric Bayesian who believes the model and uses it to learn about the DGP. This interpretation provides a different perspective on estimates, test statistics, and confidence regions in large samples, particularly regarding the economic significance of rejections in rational expectations models. A suggestive application to the equity premium puzzle is examined.

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    Bibliographic Info

    Article provided by Elsevier in its journal Journal of Econometrics.

    Volume (Year): 150 (2009)
    Issue (Month): 2 (June)
    Pages: 322-331

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    Handle: RePEc:eee:econom:v:150:y:2009:i:2:p:322-331

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    Web page: http://www.elsevier.com/locate/jeconom

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    1. Susanne M. Schennach, 2005. "Bayesian exponentially tilted empirical likelihood," Biometrika, Biometrika Trust, vol. 92(1), pages 31-46, March.
    2. Chamberlain, Gary, 1987. "Asymptotic efficiency in estimation with conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 34(3), pages 305-334, March.
    3. Robert J. Barro, 2005. "Rare Events and the Equity Premium," NBER Working Papers 11310, National Bureau of Economic Research, Inc.
    4. Lars Peter Hansen, 2007. "Beliefs, Doubts and Learning: Valuing Macroeconomic Risk," American Economic Review, American Economic Association, vol. 97(2), pages 1-30, May.
    5. Yuichi Kitamura, 2006. "Empirical Likelihood Methods in Econometrics: Theory and Practice," Cowles Foundation Discussion Papers 1569, Cowles Foundation for Research in Economics, Yale University.
    6. Back, Kerry & Brown, David P, 1993. "Implied Probabilities in GMM Estimators," Econometrica, Econometric Society, vol. 61(4), pages 971-75, July.
    7. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
    8. Song Xi Chen & Hengjian Cui, 2006. "On Bartlett correction of empirical likelihood in the presence of nuisance parameters," Biometrika, Biometrika Trust, vol. 93(1), pages 215-220, March.
    9. Rietz, Thomas A., 1988. "The equity risk premium a solution," Journal of Monetary Economics, Elsevier, vol. 22(1), pages 117-131, July.
    10. Yuichi Kitamura, 2006. "Empirical Likelihood Methods in Econometrics: Theory and Practice," Levine's Bibliography 321307000000000307, UCLA Department of Economics.
    11. Nicole A. Lazar, 2003. "Bayesian empirical likelihood," Biometrika, Biometrika Trust, vol. 90(2), pages 319-326, June.
    12. Back, Kerry & Brown, David P., 1992. "GMM, maximum likelihood, and nonparametric efficiency," Economics Letters, Elsevier, vol. 39(1), pages 23-28, May.
    13. Kim, Jae-Young, 2002. "Limited information likelihood and Bayesian analysis," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 175-193, March.
    14. Lucas, Robert E, Jr, 1980. "Methods and Problems in Business Cycle Theory," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 12(4), pages 696-715, November.
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    Cited by:
    1. Chong, Lucy Lee-Yun & Puah, Chin-Hong & Md Isa, Abu Hassan, 2012. "Theory of rational expectations hypothesis: banks and other financial institutions in Malaysia," MPRA Paper 36657, University Library of Munich, Germany.

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