Department of Economics, University of Oviedo, Avenida del Cristo, s/n, 33006, Oviedo, Spain.
Eur J Health Econ. 2018 Nov;19(8):1137-1148. doi: 10.1007/s10198-018-0962-6. Epub 2018 Feb 21.
Labour absenteeism may be detrimental to firms and society because of the economic costs, organizational problems and production cuts that it involves. Although involuntary absenteeism due to accident or illness that prevents workers from performing their work is unavoidable, avoidable voluntary absenteeism may also emerge due to asymmetric information given that neither employers nor doctors have perfect information about workers' health status. Assuming that there is heterogeneity in individual's behaviour and thus some workers are more likely to take sick leave than others due to differences in observable and unobservable characteristics, we specify a Finite Mixture Model to analyse sick leave days per year using a sample of employees from the 2014 European Health Survey in Spain. This specification accounts for unobserved heterogeneity in a discrete way assuming that there are two types of workers even though the data do not allow us to identify which group any individual belongs to. Our results reveal that, although health indicators have the greatest impact on the proportional change in days of absenteeism, there is heterogeneity in sick leave decisions and individual and job characteristics have different effect on the absenteeism of each group.
劳动力缺勤可能对企业和社会造成损害，因为这涉及到经济成本、组织问题和生产削减。尽管由于事故或疾病导致工人无法工作而导致的非自愿缺勤是不可避免的，但由于信息不对称，也可能出现可避免的自愿缺勤，因为雇主和医生都没有关于工人健康状况的完美信息。假设个体行为存在异质性，因此由于可观察和不可观察特征的差异，一些工人比其他人更有可能请病假，我们指定了一个有限混合模型，使用西班牙 2014 年欧洲健康调查的员工样本，分析每年的病假天数。这种指定以离散的方式考虑了未观察到的异质性，假设存在两种类型的工人，尽管数据不允许我们确定任何个体属于哪个群体。我们的结果表明，尽管健康指标对缺勤天数的比例变化影响最大，但在病假决策方面存在异质性，个人和工作特征对每个群体的缺勤率有不同的影响。
