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The Impact Of Health Changes On Labor Supply: Evidence From Merged Data On Individual Objective Medical Diagnosis Codes And Early Retirement Behavior

Author

Listed:
  • Bruce Hollingsworth
  • Anthony Scott
  • Bent Jesper Christensen
  • Malene Kallestrup‐Lamb

Abstract

People quit the labor force for many different reasons, voluntarily or not, through various arrangements such as unemployment benefits, disability benefits or specially designed early retirement schemes. This paper complements the existing literature by considering a large, register-based sample including objective medical diagnosis codes. We estimate detailed hazard models of duration until retirement, controlling for unobserved heterogeneity and nonparametric baseline hazards, as well as observed heterogeneity through time-varying explanatory variables. These include diagnosis codes, along with a host of demographic, labor market and financial regressors. The panel structure of the data allows following individuals year by year from the age of 50 and precisely measure changes in objectively measured health and other regressors, as well as labor market status. We consider 12 broad, mutually exclusive and exhaustive categories of health diagnoses defined by aggregation across ICD codes. The use of objective medical diagnosis codes should eliminate the justification bias due to self-reports of health, and the large sample size obtained by using register rather than survey data should mitigate the e¤ect of any remaining mismeasurement of true work incapacity. Together, these improvements should help distinguish empirically important effects of health and economic variables on retirement. We distinguish a number of alternative exit routes, in particular, disability, early retirement, unemployment, and others (including out of the labor force and welfare). We estimate both single risk models, lumping all retirement states, and competing risk specifications, including all separate exit routes. Throughout, females are included in the estimations, and we present separate results by gender. We find sizeable differences in retirement behavior across marital status, gender, labor market attachment, occupation, income, and in particular health. We find that the disability reti
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Suggested Citation

  • Bruce Hollingsworth & Anthony Scott & Bent Jesper Christensen & Malene Kallestrup‐Lamb, 2012. "The Impact Of Health Changes On Labor Supply: Evidence From Merged Data On Individual Objective Medical Diagnosis Codes And Early Retirement Behavior," Health Economics, John Wiley & Sons, Ltd., vol. 21, pages 56-100, June.
  • Handle: RePEc:wly:hlthec:v:21:y:2012:i::p:56-100
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    References listed on IDEAS

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    1. Hugo Benítez-Silva & Moshe Buchinsky & Hiu Man Chan & Sofia Cheidvasser & John Rust, 2004. "How large is the bias in self-reported disability?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(6), pages 649-670.
    2. Nabanita Datta Gupta & Mona Larsen, 2010. "The impact of health on individual retirement plans: self-reported versus diagnostic measures," Health Economics, John Wiley & Sons, Ltd., vol. 19(7), pages 792-813.
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    Cited by:

    1. Malene Kallestrup-Lamb, 2011. "The Role of the Spouse in Early Retirement Decisions for Older Workers," CREATES Research Papers 2011-38, Department of Economics and Business Economics, Aarhus University.
    2. Malene Kallestrup-Lamb & Anders Bredahl Kock & Johannes Tang Kristensen, 2016. "Lassoing the Determinants of Retirement," Econometric Reviews, Taylor & Francis Journals, vol. 35(8-10), pages 1522-1561, December.
    3. Boman, Anders, 2015. "Spending time together? Effects on the retirement decision from partner’s labour market status," Working Papers in Economics 618, University of Gothenburg, Department of Economics.
    4. Eric Delattre & Richard Moussa & Mareva Sabatier, 2015. "Health condition and job status interactions: Econometric evidence of causality from a French longitudinal survey," THEMA Working Papers 2015-19, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    5. Gerke, Oke & Lauridsen, Jørgen T., 2013. "Determinants of early retirement in Denmark. An empirical investigation using SHARE data," Discussion Papers of Business and Economics 4/2013, University of Southern Denmark, Department of Business and Economics.

    More about this item

    JEL classification:

    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • J26 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Retirement; Retirement Policies
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies

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