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

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Author Info
Jean-François Angers
Denise Desjardins
Georges Dionne () (HEC Montréal)
Benoit Dostie () (IEA, HEC Montréal)
François Guertin

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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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File URL: http://www2.hec.ca/iea/cahiers/2007/iea0702_bdostie.pdf
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Publisher Info
Paper provided by HEC Montréal, Institut d'économie appliquée in its series Cahiers de recherche with number 07-02.

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Length: 29 pages
Date of creation: Apr 2007
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Handle: RePEc:iea:carech:0702

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Postal: Institut d'économie appliquée HEC Montréal 3000, Chemin de la Côte-Sainte-Catherine Montréal, Québec H3T 2A7
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Related research
Keywords: Absenteeism; Linked Employer-Employee Data; Employer- Employee Unobserved Heterogeneity; Count Data Models; Dirichlet Distribution;

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Find related papers by 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

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This page was last updated on 2009-11-26.


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