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Le problème des données longitudinales incomplètes : une nouvelle approche


  • Paquet, Marie-France

    (Université d’Ottawa)

  • Bolduc, Denis

    (Université Laval)


In this paper, we suggest to use a Gibbs sampler with data augmentation to estimate models based on incomplete longitudinal data which, in the extreme case where the sample is composed of independent cross-sections, corresponds to a situation that normally calls for pseudo-panel modeling. The idea suggested here can be applied in several contexts: static and dynamic models linear or nonlinear type, discrete choice models, models with endogenous regressors, etc. To present the suggested method, we apply it to a linear model with continuous dependent variable. For comparison purpose, we also use the conventional pseudo-panel approach which is based on averages computed on cohorts. In terms of efficiency, the technique suggested in this work gives better results than the conventional pseudo-panel technique. This conclusion remains valid for any proportion of missing observations in the sample. Dans ce travail, nous suggérons l’utilisation de l’échantillonnage de Gibbs combiné à l’augmentation des données pour estimer des modèles à données longitudinales incomplètes, qui dans le cas extrême où l’échantillon est composé de coupes transversales indépendantes, correspond au cas de modèle de type pseudo-panel. Cette idée peut être appliquée dans plusieurs contextes : modèles statiques ou dynamiques de type linéaires, non linéaires, de choix discrets, avec régresseurs endogènes, etc. Pour présenter la méthode proposée, nous l’appliquons dans le cas d’un modèle linéaire à variable dépendante continue. Comme point de comparaison, nous utilisons les estimations par l’approche conventionnelle dite de pseudo-panel basée sur des moyennes calculées sur des cohortes. La technique proposée dans ce travail donne des résultats supérieurs, en terme d’efficacité, à la technique conventionnelle. Cette conclusion demeure valide quelle que soit la proportion des observations manquantes.

Suggested Citation

  • Paquet, Marie-France & Bolduc, Denis, 2004. "Le problème des données longitudinales incomplètes : une nouvelle approche," L'Actualité Economique, Société Canadienne de Science Economique, vol. 80(2), pages 341-361, Juin-Sept.
  • Handle: RePEc:ris:actuec:v:80:y:2004:i:2:p:341-361

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    References listed on IDEAS

    1. Gordon, Stephen & Bélanger, Gilles, 1996. "Échantillonnage de Gibbs et autres applications économétriques des chaînes markoviennes," L'Actualité Economique, Société Canadienne de Science Economique, vol. 72(1), pages 27-49, mars.
    2. Verbeek, Marno & Nijman, Theo, 1992. "Can Cohort Data Be Treated as Genuine Panel Data?," Empirical Economics, Springer, vol. 17(1), pages 9-23.
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    6. François Gardes & Christian Loisy, 1998. "La pauvreté selon les ménages : une évaluation subjective et indexée sur leur revenu," Économie et Statistique, Programme National Persée, vol. 308(1), pages 95-112.
    7. Baltagi, Badi H., 1995. "Editor's introduction Panel data," Journal of Econometrics, Elsevier, vol. 68(1), pages 1-4, July.
    8. Verbeek, Marno & Nijman, Theo, 1993. "Minimum MSE estimation of a regression model with fixed effects from a series of cross-sections," Journal of Econometrics, Elsevier, vol. 59(1-2), pages 125-136, September.
    9. Alessie, Rob & Devereux, Michael P. & Weber, Guglielmo, 1997. "Intertemporal consumption, durables and liquidity constraints: A cohort analysis," European Economic Review, Elsevier, vol. 41(1), pages 37-59, January.
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