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Temporal Pattern in Number of Staff on Sick Leave: The Effect of Downsizing
Göran Kauermann and Renate Ortlieb
Journal of the Royal Statistical Society. Series C (Applied Statistics)
Vol. 53, No. 2 (2004), pp. 355-367
Stable URL: http://www.jstor.org/stable/3592546
Page Count: 13
You can always find the topics here!Topics: Workplace absenteeism, Layoffs, Modeling, Maximum likelihood estimation, Business structures, Data smoothing, Statism, Employment termination, Statistical models, Employees
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The pattern of absenteeism in the downsizing process of companies is a topic in focus in economics and social science. A general question is whether employees who are frequently absent are more likely to be selected to be laid off or in contrast whether employees to be dismissed are more likely to be absent for the remaining time of their working contract. We pursue an empirical and microeconomic investigation of these theses. We analyse longitudinal data that were collected in a German company over several years. We fit a semiparametric transition model based on a mixture Poisson distribution for the days of absenteeism per month. Prediction intervals are considered and the primary focus is on the period of downsizing. The data reveal clear evidence for the hypothesis that employees who are to be laid off are more frequently absent before leaving the company. Interestingly, though, no clear evidence is seen that employees being selected to leave the company are those with a bad absenteeism profile.
Journal of the Royal Statistical Society. Series C (Applied Statistics) © 2004 Royal Statistical Society