The impact of health changes on labor supply: evidence from merged data on individual objective medical diagnosis codes and early retirement behavior

Health Econ. 2012 Jun;21 Suppl 1:56-100. doi: 10.1002/hec.2811.

Abstract

The justification bias in the estimated impact of health shocks on retirement is mitigated by using objective health measures from a large, register-based longitudinal data set including medical diagnosis codes, along with labor market status, financial, and socio-economic variables. The duration until retirement is modeled using single and competing risk specifications, observed and unobserved heterogeneity, and flexible baseline hazards. Wealth is used as a proxy for elapsed duration to mitigate the potential selection bias stemming from conditioning on initial participation. The competing risk specification distinguishes complete multiperiod routes to retirement, such as unemployment followed by early retirement. A result on comparison of coefficients across all states is offered. The empirical results indicate a strong impact of health changes on retirement and hence a large potential for public policy measures intended to retain older workers longer in the labor force. Disability responds more to health shocks than early retirement, especially to diseases of the circulatory, respiratory, and musculoskeletal systems, as well as mental and behavioral disorders. Some unemployment spells followed by early retirement appear voluntary and spurred by life style diseases.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Age Factors
  • Aged
  • Clinical Coding*
  • Data Interpretation, Statistical
  • Denmark
  • Female
  • Health Status*
  • Humans
  • International Classification of Diseases
  • Male
  • Middle Aged
  • Models, Econometric
  • Old Age Assistance / statistics & numerical data
  • Retirement / economics*
  • Retirement / statistics & numerical data*
  • Sex Factors
  • Sick Leave / economics*
  • Sick Leave / statistics & numerical data*
  • Socioeconomic Factors