Estimating the influence of health as a risk factor on unemployment: a survival analysis of employment durations for workers surveyed in the German Socio-Economic Panel (1984-1990)

Soc Sci Med. 1996 Jun;42(12):1651-9. doi: 10.1016/0277-9536(95)00329-0.


In this paper we examine the link between unemployment and health. The negative health selection hypothesis, which proposes that poor health poses an unemployment risk, is tested using data from the German Socio-Economic Panel (GSOEP). The statistical influence of health related variables on the duration of employment for a cohort of workers is estimated. Results from the Cox proportional hazards regression model show gender and nationality specific negative selection. In the event of a long or chronic illness female workers are at a higher risk of unemployment than male workers. Whereas chronic illness raises the probability of unemployment among foreign workers, there is no statistical evidence for this for German workers. The paper, thus, shows that health factors determining unemployment affect different types of workers in different ways. Consequently, results from aggregate studies may be misleading. A second result of the paper is that, irrespective of gender and nationality, there is strong evidence for lagged state dependence on previous spells of unemployment, i.e. individuals who had experienced unemployment previously were more at risk of renewed unemployment than those without such spells. These findings do not only confirm the selection hypothesis, but also illustrate how labour market risks are closely associated with attributes of social inequality and how this could result in the accumulation of risks for those who are socially or politically vulnerable in the labour market.

MeSH terms

  • Adolescent
  • Adult
  • Cohort Studies
  • Emigration and Immigration / statistics & numerical data
  • Europe / ethnology
  • Female
  • Germany
  • Health Status*
  • Humans
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Proportional Hazards Models
  • Risk Factors
  • Sex Factors
  • Socioeconomic Factors
  • Survival Analysis
  • Turkey / ethnology
  • Unemployment / statistics & numerical data*