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Propriétés en échantillon fini des tests robustes à l'hétéroscédasticité de forme inconnue

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  • Emmanuel Flachaire

    (EUREQUA - Equipe Universitaire de Recherche en Economie Quantitative - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

Abstract

Dans la pratique, la plupart des statistiques de test ont une distribution de probabilité de forme inconnue. Généralement, on utilise leur loi asymptotique comme approximation de la vraie loi. Mais, si l'échantillon dont on dispose n'est pas de taille suffisante cette approximation peut être de mauvaise qualité et les tests basés dessus largement biaisés. Les méthodes du bootstrap permettent d'obtenir une approximation de la vraie loi de la statistique en général plus précise que laloi asymptotique. Elles peuvent également servir àapproximer la loi d'une statistique qu'on ne peut pas calculer analytiquement. Dans cet article, nous présentons une méthodologie générale du bootstrap dans le contexte des modèles de régression.

Suggested Citation

  • Emmanuel Flachaire, 2005. "Propriétés en échantillon fini des tests robustes à l'hétéroscédasticité de forme inconnue," Post-Print halshs-00175905, HAL.
    • Handle: RePEc:hal:journl:halshs-00175905
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00175905
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    References listed on IDEAS

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    1. Davidson, Russell & Flachaire, Emmanuel, 2008. "The wild bootstrap, tamed at last," Journal of Econometrics, Elsevier, vol. 146(1), pages 162-169, September.
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    Keywords

    bootstrap; modèles de régression;

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