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Selection bias corrections based on the multinomial logit model: Monte Carlo comparisons

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  • François Bourguignon

    () (PSE - Paris School of Economics, La Banque mondiale - The World Bank - La Banque mondiale - The World Bank, PJSE - Paris-Jourdan Sciences Economiques - ENS Paris - École normale supérieure - Paris - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique)

  • Marc Gurgand

    (PSE - Paris School of Economics, PJSE - Paris-Jourdan Sciences Economiques - ENS Paris - École normale supérieure - Paris - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique, CREST - Centre de Recherche en Économie et Statistique - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - X - École polytechnique - ENSAE ParisTech - École Nationale de la Statistique et de l'Administration Économique)

  • Martin Fournier

    () (GATE - Groupe d'analyse et de théorie économique - UL2 - Université Lumière - Lyon 2 - Ecole Normale Supérieure Lettres et Sciences Humaines - CNRS - Centre National de la Recherche Scientifique)

Abstract

This survey presents the set of methods available in the literature on selection bias correction, when selection is specified as a multinomial logit model. It contrasts the underlying assumptions made by the different methods and shows results from a set of Monte Carlo experiments. We find that, in many cases, the approach initiated by Dubin and MacFadden (1984) as well as the semi-parametric alternative recently proposed by Dahl (2002) are to be preferred to the most commonly used Lee (1983) method. We also find that a restriction imposed in the original Dubin and MacFadden paper can be waived to achieve more robust estimators. Monte Carlo experiments also show that selection bias correction based on the multinomial logit model can provide fairly good correction for the outcome equation, even when the IIA hypothesis is violated.

Suggested Citation

  • François Bourguignon & Marc Gurgand & Martin Fournier, 2007. "Selection bias corrections based on the multinomial logit model: Monte Carlo comparisons," Post-Print halshs-00201372, HAL.
  • Handle: RePEc:hal:journl:halshs-00201372
    DOI: 10.1111/j.1467-6419.2007.00503.x
    Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-00201372
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    Keywords

    Selection bias; Multinomial logit; Monte Carlo;

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