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Poisson Models with Employer-Employee Unobserved Heterogeneity: An Application to Absence Data

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Abstract

We propose a parametric model based on the Poisson distribution that permits to take into account both unobserved worker and workplace heterogeneity as long as both effects are nested. By assuming that workplace and worker unobserved heterogeneity components follow a gamma and a Dirichlet distribution respectively, we obtain a closed form for the unconditional density function. We estimate the model to obtain the determinants of absenteeism using linked employer-employee Canadian data from the Workplace and Employee Survey (2003). Coefficient estimates are interpreted in the framework of the typical labor-leisure model. We show that omitting unobserved heterogeneity on either side of the employement relationship leads to notable biases in the estimated coefficients. In particular, the impact of wages on absences is underestimated in simpler models.

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  • Jean-François Angers & Denise Desjardins & Georges Dionne & Benoit Dostie & François Guertin, 2007. "Poisson Models with Employer-Employee Unobserved Heterogeneity: An Application to Absence Data," Cahiers de recherche 07-02, HEC Montréal, Institut d'économie appliquée.
  • Handle: RePEc:iea:carech:0702
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    1. Angers, Jean-François & Desjardins, Denise & Dionne, Georges & Guertin, François, 2006. "Vehicle and Fleet Random Effects in a Model of Insurance Rating for Fleets of Vehicles," ASTIN Bulletin, Cambridge University Press, vol. 36(1), pages 25-77, May.
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    More about this item

    Keywords

    Absenteeism; Linked Employer-Employee Data; Employer- Employee Unobserved Heterogeneity; Count Data Models; Dirichlet Distribution;
    All these keywords.

    JEL classification:

    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply
    • J29 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Other
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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