雇主-雇员未观察异质性的泊松模型:缺勤数据的应用

J. Angers, D. Desjardins, G. Dionne, B. Dostie, F. Guertin
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引用次数: 1

摘要

我们提出了一个基于泊松分布的参数模型,允许考虑未观察到的工人和工作场所的异质性,只要这两种效应都是嵌套的。假设工作场所和工人未观察到的异质性成分分别遵循gamma和Dirichlet分布,我们得到了无条件密度函数的封闭形式。我们使用来自工作场所和雇员调查(2003)的关联雇主-雇员加拿大数据来估计模型以获得缺勤的决定因素。系数估计是在典型劳动-闲暇模型的框架下解释的。我们表明,忽略雇佣关系两侧未观察到的异质性会导致估计系数出现显著偏差。特别是,在更简单的模型中,工资对缺勤的影响被低估了。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Poisson Models with Employer-Employee Unobserved Heterogeneity: An Application to Absence Data
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 employment 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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