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Four Essays in Econometrics

Author

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  • Laurent Davezies

    (Sciences Po)

Abstract

Cette thèse se compose de quatre travaux indépendants. Le premier concerne les modèles partiellement identifiés, c'est-à-dire des modèles dans lesquels la valeur du paramètre d’intérêt ne peut pas être déduite de la distribution des données et des hypothèses du modèle. Dans certaines situations, aucune ou au contraire plusieurs valeurs du paramètre d’intérêt sont compatibles avec les données et les hypothèses du modèle. Ce travail démontre entre autre que si l’ensemble des distributions de probabilités compatibles avec le modèle est convexe, alors les parties extrêmes de ce convexe caractérise l’ensemble des distributions compatibles avec le modèle. Le deuxième travail propose une méthode basée sur une condition d’exclusion pour corriger de l’attrition endogène dans les panels. Nous appliquons cette méthode pour estimer les transitions sur le marché du travail à partir de l’enquête emploi française. Le troisième travail propose une méthode simple pour estimer un modèle logistique avec effets fixes et dépendance d’état tel qu’étudié par Honoré et Kiriazidou. Il propose également un nouvel estimateur des écarts-types qui semble avoir de meilleures propriétés à distance finie. Le quatrième travail est une évaluation sur les collèges de la politique éducative des Réseaux-Ambition-Réussite lancée en 2006. Nous exploitons une discontinuité dans la sélection des collèges pour comparer entre eux certains collèges « identiques » avant la mise en place de la politique. Les résultats de cette évaluation laissent place à peu d’optimisme concernant l’efficacité de cette politique.

Suggested Citation

  • Laurent Davezies, 2013. "Four Essays in Econometrics," Sciences Po publications info:hdl:2441/6o65lgig8d0, Sciences Po.
  • Handle: RePEc:spo:wpmain:info:hdl:2441/6o65lgig8d0qcro9p14826c84
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    References listed on IDEAS

    as
    1. van der Klaauw, Wilbert, 2008. "Breaking the link between poverty and low student achievement: An evaluation of Title I," Journal of Econometrics, Elsevier, vol. 142(2), pages 731-756, February.
    2. repec:hal:wpspec:info:hdl:2441/6o65lgig8d0qcro9p14826c84 is not listed on IDEAS
    3. Wooldridge, Jeffrey M., 2007. "Inverse probability weighted estimation for general missing data problems," Journal of Econometrics, Elsevier, vol. 141(2), pages 1281-1301, December.
    4. Gong Tang, 2003. "Analysis of multivariate missing data with nonignorable nonresponse," Biometrika, Biometrika Trust, vol. 90(4), pages 747-764, December.
    Full references (including those not matched with items on IDEAS)

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