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Nonparametric classes for identification in random coefficients models when regressors have limited variation

Author

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  • Christophe Gaillac

    (TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

  • Eric Gautier

    (TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse)

Abstract
This paper studies point identification of the distribution of the coefficients in some random coefficients models with exogenous regressors when their support is a proper subset, possibly discrete but countable. We exhibit trade-offs between restrictions on the distribution of the random coefficients and the support of the regressors. We consider linear models including those with nonlinear transforms of a baseline regressor, with an infinite number of regressors and deconvolution, the binary choice model, and panel data models such as single-index panel data models and an extension of the Kotlarski lemma.

Suggested Citation

  • Christophe Gaillac & Eric Gautier, 2021. "Nonparametric classes for identification in random coefficients models when regressors have limited variation," Working Papers hal-03231392, HAL.
    • Handle: RePEc:hal:wpaper:hal-03231392
    Note: View the original document on HAL open archive server: https://hal.science/hal-03231392
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    References listed on IDEAS

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    Keywords

    Identification; Random Coefficients; Quasi-analyticity; Deconvolution; Deconvolution AMS 2010 Subject Classification: Primary 62P20; secondary 42A99; 62G07; 62G08;
    All these keywords.

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