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Model equivalence tests in a parametric framework

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  • Lavergne, Pascal

Abstract

In empirical research, one commonly aims to obtain evidence in favor of restrictions on parameters, appearing as an economic hypothesis, a consequence of economic theory, or an econometric modeling assumption. I propose a new theoretical framework based on the Kullback–Leibler information to assess the approximate validity of multivariate restrictions in parametric models. I construct tests that are locally asymptotically maximin and locally asymptotically uniformly most powerful invariant. The tests are applied to three different empirical problems.

Suggested Citation

  • Lavergne, Pascal, 2014. "Model equivalence tests in a parametric framework," Journal of Econometrics, Elsevier, vol. 178(P3), pages 414-425.
    • Handle: RePEc:eee:econom:v:178:y:2014:i:p3:p:414-425
    DOI: 10.1016/j.jeconom.2013.05.007
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    1. Manuel A. Domínguez & Ignacio N. Lobato, 2004. "Consistent Estimation of Models Defined by Conditional Moment Restrictions," Econometrica, Econometric Society, vol. 72(5), pages 1601-1615, September.
    2. Sin, Chor-Yiu & White, Halbert, 1996. "Information criteria for selecting possibly misspecified parametric models," Journal of Econometrics, Elsevier, vol. 71(1-2), pages 207-225.
    3. Andrews, Donald W K, 1994. "The Large Sample Correspondence between Classical Hypothesis Tests and Bayesian Posterior Odds Tests," Econometrica, Econometric Society, vol. 62(5), pages 1207-1232, September.
    4. Robert G. King & Ross Levine, 1993. "Finance and Growth: Schumpeter Might Be Right," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 108(3), pages 717-737.
    5. White,Halbert, 1996. "Estimation, Inference and Specification Analysis," Cambridge Books, Cambridge University Press, number 9780521574464, January.
    6. Nelson, Forrest D & Savin, N E, 1990. "The Danger of Extrapolating Asymptotic Local Power," Econometrica, Econometric Society, vol. 58(4), pages 977-981, July.
    7. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-333, March.
    8. N. Gregory Mankiw & David Romer & David N. Weil, 1992. "A Contribution to the Empirics of Economic Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(2), pages 407-437.
    9. McCloskey, Donald N, 1985. "The Loss Function Has Been Mislaid: The Rhetoric of Significance Tests," American Economic Review, American Economic Association, vol. 75(2), pages 201-205, May.
    10. Gordon Anderson & Richard Blundell, 1983. "Testing Restrictions in a Flexible Dynamic Demand System: An Application to Consumers' Expenditure in Canada," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 50(3), pages 397-410.
    11. Freedman, David A., 2007. "How Can the Score Test Be Inconsistent?," The American Statistician, American Statistical Association, vol. 61, pages 291-295, November.
    12. Andrews, Donald W K, 1989. "Power in Econometric Applications," Econometrica, Econometric Society, vol. 57(5), pages 1059-1090, September.
    13. Gregory, Allan W & Veall, Michael R, 1985. "Formulating Wald Tests of Nonlinear Restrictions," Econometrica, Econometric Society, vol. 53(6), pages 1465-1468, November.
    14. Lillard, Lee A & Aigner, Dennis J, 1984. "Time-of-Day Electricity Consumption Response to Temperature and the Ownership of Air Conditioning Appliances," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(1), pages 40-53, January.
    15. Leamer, Edward E, 1988. "Things That Bother Me," The Economic Record, The Economic Society of Australia, vol. 64(187), pages 331-335, December.
    16. Liu, Zhenjuan & Stengos, Thanasis, 1999. "Non-linearities in Cross-Country Growth Regressions: A Semiparametric Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(5), pages 527-538, Sept.-Oct.
    17. Sawa, Takamitsu, 1978. "Information Criteria for Discriminating among Alternative Regression Models," Econometrica, Econometric Society, vol. 46(6), pages 1273-1291, November.
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    Cited by:

    1. Lavergne, Pascal, 2015. "Assessing the Approximate Validity of Moment Restrictions," TSE Working Papers 15-562, Toulouse School of Economics (TSE), revised May 2020.
    2. Antoine, Bertille & Renault, Eric, 2020. "Testing identification strength," Journal of Econometrics, Elsevier, vol. 218(2), pages 271-293.
    3. Jae H. Kim & Andrew P. Robinson, 2019. "Interval-Based Hypothesis Testing and Its Applications to Economics and Finance," Econometrics, MDPI, vol. 7(2), pages 1-22, May.

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    More about this item

    Keywords

    Hypothesis testing; Parametric methods;

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

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