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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 re- strictions on parameters, appearing as an economic hypothesis, a consequence of economic theory, or an econometric modeling assumption. I propose a new theoret- ical 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, 2013. "Model Equivalence Tests in a Parametric Framework," TSE Working Papers 13-379, Toulouse School of Economics (TSE).
    • Handle: RePEc:tse:wpaper:26789
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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

    JEL classification:

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

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