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Modèles de comptage semi-paramétriques

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  • Christian Gourieroux

    (Crest)

  • Alain Monfort

    (Crest)

Abstract

In this paper, we introduce a new class of models for count endogenous variables, i.e. the additive log-differentiated probability models (ALDP). This class is similar to the semi-parametric proportional hazard models used for duration data, and has some interesting implications in terms of costs or benefits. The asymptotic properties of the maximum likelihood estimators are studied and compared with the properties of the discriminant analysis estimators. We also explain why these models are suitable in the framework of endogenous sampling. Finally we discuss the introduction of heterogeneity. Dans cet article nous définissons une nouvelle classe de modèles pour les variables endogènes entières : les modèles additifs log-différenciés en probabilité (ALDP). Cette classe a des analogies avec les modèles semi-paramétriques de hasard proportionnel pour les modèles de durées et a des interprétations intéressantes en terme de coûts (ou de bénéfices). Les propriétés asymptotiques des estimateurs du maximum de vraisemblance pour ces modèles sont étudiées et comparées à celles des estimateurs de l’analyse discriminante. On propose également des estimateurs adaptés au cas d’échantillons stratifiés de façon exogène ou endogène. Enfin, le cas d’observations hétérogènes est discuté.
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  • Christian Gourieroux & Alain Monfort, 1997. "Modèles de comptage semi-paramétriques," Working Papers 97-34, Center for Research in Economics and Statistics.
    • Handle: RePEc:crs:wpaper:97-34
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    References listed on IDEAS

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