Abstract
This article studies the effect of alcohol consumption on the probability of long-term sickness-related absenteeism for women. Using Swedish matched survey and register data, we apply sample selection models to correct for nonrandom sampling into paid employment. There are three main findings of the study. First, diverging from the most prevalent consumption group (long-term light drinkers) is associated with an increased probability of long-term sickness, ranging from 10% for long-term heavy drinkers to 18% for former drinkers. Second, controlling for former consumption errors (especially former drinker and former abstainer errors) and sample selection into employment are important for unbiased, consistent estimations. Third, by predicting the effect of changes in consumption on long-term sickness-related absence, we find that alcohol only explains a small part of the overall picture of long-term sickness-related absenteeism. Notwithstanding this fact, long-term sickness-related absenteeism due to alcohol adds up to substantial productivity loss for society. Our conclusion is that the commonly found U-shaped relationship between current alcohol consumption and labour market outcomes remains for women, after controlling for past consumption and selection effects. A change in consumption level increases probability of long-term sickness-related absence, compared to individuals with constant consumption levels.
Acknowledgements
Financial support from the Swedish Council for Working Life and Social Research (dnr 2006–1660) is gratefully acknowledged.
Conflict of Interest
The authors declare that they have no competing interests.
Notes
1From here on only ‘absence’.
2 Theoretical secondary school is in preparation for university studies as opposed to practical secondary school that is more focused on professional education.
3 The reason for this is unknown. One hypothesis is that men's life situation affects their alcohol consumption to a smaller extent then women's, and vice versa.
4This could be estimated by taking into account age effects on the probability of absence and age-adjusted average number of days absent, plus income.