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The impact of health on individual retirement plans: self‐reported versus diagnostic measures

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  • Nabanita Datta Gupta
  • Mona Larsen

Abstract

We reassess the impact of health on retirement plans of older workers using a unique survey‐register match‐up which allows comparing the retirement effects of potentially biased survey self‐reports of health to those of unbiased register‐based diagnostic measures. The aim is to investigate whether even for narrowly defined health measures a divergence exists in the impacts of health on retirement between self‐reported health and objective physician‐reported health. Our sample consists of older workers and retirees drawn from a Danish panel survey from 1997 and 2002, merged to longitudinal register data. Estimation of measurement error‐reduced and selection‐corrected pooled OLS and fixed effects models of retirement show that receiving a medical diagnosis is an important determinant of retirement planning for both men and women, in fact more important than economic factors. The type of diagnosis matters, however. For men, the largest reduction in planned retirement age occurs for a diagnosis of lung disease while for women it occurs for musculo‐skeletal disease. Except for cardiovascular disease, diagnosed disease is more influential in men's retirement planning than in women's. Our study provides evidence that men's self‐report of myalgia and back problems and women's self‐report of osteoarthritis possibly yield biased estimates of the impact on planned retirement age, and that this bias ranges between 1.5 and 2 years, suggesting that users of survey data should be wary of applying self‐reports of health conditions with diffuse symptoms to the study of labor market outcomes. On the other hand, self‐reported cardiovascular disease such as high blood pressure does not appear to bias the estimated impact on planned retirement. Copyright © 2009 John Wiley & Sons, Ltd.

Suggested Citation

  • 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, July.
  • Handle: RePEc:wly:hlthec:v:19:y:2010:i:7:p:792-813
    DOI: 10.1002/hec.1523
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    Cited by:

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    3. Даниелян, Владимир, 2016. "Детерминанты Пенсионного Возраста: Обзор Исследований [Determinants of Retirement Age: A Review of Research]," MPRA Paper 73865, University Library of Munich, Germany.
    4. Thomas Barnay & Mohamed Ali Ben Halima & Emmanuel Duguet & Christine Le Clainche & Camille Regaert, 2016. "The effects of breast cancer on individual labour market outcomes: an evaluation from an administrative panel," TEPP Working Paper 2016-05, TEPP.
    5. Thomas Barnay & Emmanuel Duguet & Christine Le Clainche, 2019. "The Effects of Breast Cancer on Individual Labour Market Outcomes: An Evaluation from an Administrative Panel in France," Annals of Economics and Statistics, GENES, issue 136, pages 103-126.
    6. 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.
    7. Bauer, Ann Barbara & Eichenberger, Reiner, 2021. "Worsening workers' health by lowering retirement age: The malign consequences of a benign reform," The Journal of the Economics of Ageing, Elsevier, vol. 18(C).
    8. 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.
    9. Thomas Barnay & Mohamed Ali Ben Halima & Emmanuel Duguet & Joseph Lanfranchi & Christine Le Clainche, 2015. "La survenue du cancer : effets de court et moyen termes sur l'emploi, le chômage et les arrêts maladie," Économie et Statistique, Programme National Persée, vol. 475(1), pages 157-186.
    10. Smed, Sinne & Rønnow, Helene Normann & Tetens, Inge, 2022. "The retirement (food)-consumption puzzle revisited - A panel data study from Denmark," Food Policy, Elsevier, vol. 112(C).
    11. Lauren Hersch Nicholas & Johanna Catherine Maclean, 2019. "The Effect of Medical Marijuana Laws on the Health and Labor Supply of Older Adults: Evidence from the Health and Retirement Study," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 38(2), pages 455-480, March.
    12. Hersch Nicholas, Lauren & Maclean, J. Catherine, 2017. "The Effect of Medical Marijuana Laws on the Labor Supply of Older Adults: Evidence from the Health and Retirement Study," IZA Discussion Papers 10489, Institute of Labor Economics (IZA).
    13. Kim, Hoolda & Mitra, Sophie, 2022. "Dynamics of health and labor income in Korea," The Journal of the Economics of Ageing, Elsevier, vol. 21(C).
    14. Reed Olsen & Subhasree Basu Roy & Hui-Kuan Tseng, 2019. "The Hispanic health paradox for older Americans: an empirical note," International Journal of Health Economics and Management, Springer, vol. 19(1), pages 33-51, March.
    15. Black, Nicole & Johnston, David W. & Suziedelyte, Agne, 2017. "Justification bias in self-reported disability: New evidence from panel data," Journal of Health Economics, Elsevier, vol. 54(C), pages 124-134.
    16. Andree Ehlert & Eva García‐Morán, 2022. "Workers' self‐selection into public sector employment: A tale of absenteeism," Kyklos, Wiley Blackwell, vol. 75(3), pages 394-409, August.
    17. Christensen, Vibeke Tornhøj & Datta Gupta, Nabanita, 2017. "Hearing loss and disability exit: Measurement issues and coping strategies," Economics & Human Biology, Elsevier, vol. 24(C), pages 80-91.
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