DP434 Worker Absenteeism: An Analysis Using Microdata
|Author(s):||Tim Barmby, Chris D Orme, John Treble|
|Publication Date:||August 1990|
|Keyword(s):||Absenteeism, Dynamic Stochastic Programming, Sequential Logit, Sick-pay, Weibull Hazard|
|JEL(s):||212, 229, 824|
|Programme Areas:||Human Resources|
|Link to this Page:||cepr.org/active/publications/discussion_papers/dp.php?dpno=434|
This paper presents preliminary findings of a study of worker absenteeism. Our main purpose is to identify the various factors that influence the rate of absence for individual workers and to quantify their impact. Candidates for inclusion are measurable factors relating either to the structure of the terms and conditions of work (including the sick-pay scheme and disciplinary system); or personal characteristics of the workers themselves. The firm studied operates an experience-rated sick-pay scheme and the results reported in the paper concentrate on the analysis of a data set constructed from their payroll and attendance records. Under the scheme, workers' entitlement to sick pay in the current calendar year is determined by their record of absence over the previous two years. This is achieved by assigning the workers to three groups: good attenders (A), average attenders (B) and poor attenders (C). A worker's group is determined by the number of absence `points' accumulated during the previous two years. Points are given for any absence that is not deemed acceptable. (Acceptable absences are mostly medically certified.) We find that for the most part, the firm's sick-pay scheme works most effectively on the duration of absence, and not its incidence. The incidence of absence appears to be determined mostly by personal characteristics (especially sex and marital status). We interpret this to mean that workers do not consider their entitlement to sick pay when commencing an absence, but that they do consider it when deciding to return to work.