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Hétérogénéité - 1. Etude des biais d'estimation dans le cas linéaire

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  • Christian Gouriéroux
  • Irina Peaucelle

Abstract

In the case of panel data, the introduced explanatory variables are often not sufficient for describing all the individual caracteristics and it may be useful to consider relations with individual varying coefficients. When this heterogeneity is even partially omitted, the estimated parameters may or not have some interpretations in terms of the associated disaggregated parameters. In this paper we analyse the existence and the importance of heterogeneity biases for linear models.

Suggested Citation

  • Christian Gouriéroux & Irina Peaucelle, 1990. "Hétérogénéité - 1. Etude des biais d'estimation dans le cas linéaire," Annals of Economics and Statistics, GENES, issue 17, pages 163-183.
    • Handle: RePEc:adr:anecst:y:1990:i:17:p:163-183
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    File URL: http://www.jstor.org/stable/20075777
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    Cited by:

    1. Guillaume Horny, 2009. "Inference in mixed proportional hazard models with K random effects," Statistical Papers, Springer, vol. 50(3), pages 481-499, June.
    2. François Legendre, 1992. "La distribution des rendements d'échelle dans l'industrie. Une illustration à partir d'un panel de plus de 700 entreprises françaises," Revue Économique, Programme National Persée, vol. 43(1), pages 71-100.

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