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This paper reports the results of a study conducted at a U.S. Naval Base in California. The specific objective was to evaluate sick leave usage patterns and to test seven hypotheses regarding the conditions under which sick leave was used and the types of individuals who used it.

In any given year, it has been estimated that over 300 million work days are lost in Britain due to employee absenteeism. This figure amounts to about 13.5 days lost per employee. Daily absenteeism among blue‐collar workers in many industries runs as high as 17 per cent of the work force with rates often much higher on Mondays and Fridays. These estimates include absenteeism due to illness, as well as other reasons. High rates of absenteeism have been cited as contributing to industrial slumps in some areas of Britain. Productivity losses, loss of good will, extra labour costs to replace the absent employee, overtime costs, and sick pay are all costs associated with absenteeism. Clearly, employee absenteeism is a major area of concern for personnel managers.

We analyse an empirical model of absence from work based upon a variant of the traditional work–leisure model of labour supply. The model is tested with data from the 1993 UK Family Expenditure Survey and a comparison of absenteeism is made across genders. We find substantial differences in the probability of absenteeism across gender and various family situations. We also find that our conclusions concerning gender differences in absenteeism are sensitive to the definition of absenteeism used and that the differences in the determination of these measures may help to explain some of the existing disagreements in the literature.

"Ichino and Moretti (2009) find that menstruation may contribute to gender gaps in absenteeism and earnings, based on evidence that absences of young female Italian bank employees follow a 28-day cycle. We analyze absenteeism of teachers and find no evidence of increased female absenteeism on a 28-day cycle. We also show that the evidence of 28-day cycles in the Italian data is not robust to the correction of coding errors or small changes in specification. We show that five day workweeks can cause misleading group differences in absence hazards at multiples of 7, including 28 days"--National Bureau of Economic Research web site