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Life Cycle Responses to Health Insurance Status

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  • Florian PELGRIN

    (EDHEC Business School)

  • Pascal ST-AMOUR

    (University of Lausanne and Swiss Finance Institute)

Abstract

Health insurance status can change over the life cycle for exogenous reasons (e.g. Medicare for the elders, PPACA for younger agents, termination of coverage at retirement in employer-provided plans). Durability of the health capital, endogenous mortality and morbidity, as well as backward induction suggests that these changes should affect the dynamic life cycle beyond the period at which they occur. The purpose of this paper is to study these lifetime effects on the optimal allocation (consumption, leisure, health expenditures), status (health, wealth and survival rates), and welfare. We analyse the impact of young (resp. old) insurance status conditional on old (resp. young) coverage through the structural estimation of a dynamic model with endogenous death and sickness risks. Our results show that young insurees are healthier, wealthier, consume more health care yet are less exposed to OOP risks, and substitute less (more) leisure before (after) retirement. Old insurees show similar patterns, except for lower precautionary wealth balances. Compulsory health insurance is unambiguously optimal for elders, and for young agents, except early in the life cycle. We draw other implications for public policy such as Medicare and PPACA.

Suggested Citation

  • Florian PELGRIN & Pascal ST-AMOUR, 2014. "Life Cycle Responses to Health Insurance Status," Swiss Finance Institute Research Paper Series 14-31, Swiss Finance Institute, revised Jun 2015.
    • Handle: RePEc:chf:rpseri:rp1431
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    3. Mladenovic, Svetlana Sokolov & Milovancevic, Milos & Mladenovic, Igor & Petrovic, Jelena & Milovanovic, Dragan & Petković, Biljana & Resic, Sead & Barjaktarović, Miljana, 2020. "Identification of the important variables for prediction of individual medical costs billed by health insurance," Technology in Society, Elsevier, vol. 62(C).
    4. Ólafsdóttir, Thorhildur & Ásgeirsdóttir, Tinna Laufey & Norton, Edward C., 2020. "Valuing pain using the subjective well-being method," Economics & Human Biology, Elsevier, vol. 37(C).
    5. Bolin, Kristian & Caputo, Michael R., 2020. "Consumption and investment demand when health evolves stochastically," Journal of Economic Dynamics and Control, Elsevier, vol. 114(C).
    6. Chen, Chang-Chih & Chang, Chia-Chien & Sun, Edward W. & Yu, Min-Teh, 2022. "Optimal decision of dynamic wealth allocation with life insurance for mitigating health risk under market incompleteness," European Journal of Operational Research, Elsevier, vol. 300(2), pages 727-742.
    7. Marlon Azinovic & Luca Gaegauf & Simon Scheidegger, 2022. "Deep Equilibrium Nets," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(4), pages 1471-1525, November.
    8. Raquel Fonseca & Pierre-Carl Michaud & Titus Galama & Arie Kapteyn, 2021. "Accounting for the Rise of Health Spending and Longevity," Journal of the European Economic Association, European Economic Association, vol. 19(1), pages 536-579.
    9. Chaoran Chen & Zhigang Feng & Jiaying Gu, 2022. "Health, Health Insurance, and Inequality," Working Papers tecipa-730, University of Toronto, Department of Economics.
    10. Julien Hugonnier & Florian Pelgrin & Pascal St‐Amour, 2020. "Closing down the shop: Optimal health and wealth dynamics near the end of life," Health Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 138-153, February.
    11. Blundell, R. & French, E. & Tetlow, G., 2016. "Retirement Incentives and Labor Supply," Handbook of the Economics of Population Aging, in: Piggott, John & Woodland, Alan (ed.), Handbook of the Economics of Population Aging, edition 1, volume 1, chapter 0, pages 457-566, Elsevier.
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    More about this item

    Keywords

    Household Finance; Endogenous Morbidity and Mortality Risks; Demand for Health; Medicare and Patient Protection and Affordable Care Act; Simulated Moments Estimation;
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    JEL classification:

    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • I13 - Health, Education, and Welfare - - Health - - - Health Insurance, Public and Private

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