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How Important Is Health Inequality for Lifetime Earnings Inequality?

Author

Listed:
  • Roozbeh Hosseini

    (University of Georgia)

  • Kai Zhao

    (University of Connecticut)

  • Karen Kopecky

    (Federal Reserve Bank of Atlanta)

Abstract

Health and earnings are positively correlated due to several reasons. First, individuals who are in poor health are significantly less likely to work than healthy individuals. Second, conditional on working, individuals in poor health work fewer hours on average. Third, individuals in poor health on average earn lower wages. We document these facts using an objective measure of health called a frailty index which we construct for PSID respondents. The frailty index measures the fraction of observable health deficits an individual has. In previous work, we documented that health, as measured by the frailty index, deteriorates more rapidly and has a larger increase in dispersion with age than self-reported health. It is also more persistent over the life-cycle. These facts put together suggest that health inequality over the life cycle may be an important driver of lifetime earnings inequality. To assess this claim we develop a model of the joint dynamics of health and earnings over the life cycle. Individuals in the model face health, productivity and employment risk, and optimally choose labor supply on both the intensive and extensive margins. Agents are partially insured against these risks through government-run disability insurance, means-tested social insurance, and social security programs. They face a dynamic process for frailty (health) that is estimated using the PSID data. The model is estimated using a method of moments. Targeted moments are constructed off distributions of wages, hours, and employment rates by frailty and age. These distributions are obtained from an auxiliary simulation model that is estimated using PSID data. We find that health inequality can account for a significant share of the variation in lifetime earnings among 70 year-olds. Most of this effect is due to that unhealthy individuals exit the labor force at much younger ages than healthy ones. We find that health inequality has a larger impact on earnings inequality than previous literature for two reason. One, our model is the first in this literature that allows health to impact earnings through all three margins: participation, hours, and wages (productivity). Two, previous literature measured health using self-reported health status, and thus understated the extent to which health deteriorates with age for some individuals and the increase in health dispersion with age.

Suggested Citation

  • Roozbeh Hosseini & Kai Zhao & Karen Kopecky, 2019. "How Important Is Health Inequality for Lifetime Earnings Inequality?," 2019 Meeting Papers 1383, Society for Economic Dynamics.
  • Handle: RePEc:red:sed019:1383
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    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. How Important Is Health Inequality for Lifetime Earnings Inequality?
      by Christian Zimmermann in NEP-DGE blog on 2021-01-07 18:34:35

    Citations

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    Cited by:

    1. Ashantha Ranasinghe & Xuejuan Su, 2023. "When social assistance meets market power: A mixed duopoly view of health insurance in the United States," Economic Inquiry, Western Economic Association International, vol. 61(4), pages 851-869, October.
    2. Tianxu Chen, 2019. "Can Health Savings Account Reduce Health Spending?: Evidence from China," Working papers 2019-08, University of Connecticut, Department of Economics.
    3. Elena Capatina & Michael P. Keane, 2023. "Health Shocks, Health Insurance, Human Capital, and the Dynamics of Earnings and Health," Opportunity and Inclusive Growth Institute Working Papers 080, Federal Reserve Bank of Minneapolis.
    4. Jeremy Greenwood & Nezih Guner & Karen A. Kopecky, 2022. "The Downward Spiral," NBER Working Papers 29764, National Bureau of Economic Research, Inc.
    5. Ghimire, Umesh, 2022. "The Impact of Health on Wealth: Empirical Evidence," MPRA Paper 113850, University Library of Munich, Germany.
    6. Michael Keane & Elena Capatina & Shiko Maruyama, 2019. "Health Shocks and the Evolution of Earnings over the Life-Cycle," Discussion Papers 2018-14a, School of Economics, The University of New South Wales.
    7. Diego Daruich & Raquel Fernández, 2024. "Universal Basic Income: A Dynamic Assessment," American Economic Review, American Economic Association, vol. 114(1), pages 38-88, January.
    8. FUKAI Taiyo & ICHIMURA Hidehiko & KITAO Sagiri & MIKOSHIBA Minamo, 2021. "Medical Expenditures over the Life Cycle: Persistent Risks and Insurance," Discussion papers 21073, Research Institute of Economy, Trade and Industry (RIETI).
    9. Richard Blundell & Jack Britton & Monica Costa Dias & Eric French & Weijian Zou, 2022. "The Dynamic Effects of Health on the Employment of Older Workers: Impacts by Gender, Country, and Race," Working Papers wp451, University of Michigan, Michigan Retirement Research Center.
    10. Chaoran Chen & Zhigang Feng & Jiaying Gu, 2022. "Health, Health Insurance, and Inequality," Working Papers tecipa-730, University of Toronto, Department of Economics.
    11. You Du & Weige Huang, 2023. "Portfolio Allocation with Medical Expenditure Risk-A Life Cycle Model and Machine Learning Analysis," Journal of Regional Economics, Anser Press, vol. 2(1), pages 53-68, October.
    12. Ayşe İmrohoroğlu & Kai Zhao, 2022. "Homelessness," Working papers 2022-17, University of Connecticut, Department of Economics.
    13. White, Matthew N., 2023. "Self-reported health status and latent health dynamics," Journal of Health Economics, Elsevier, vol. 88(C).
    14. Ross Abram & Margherita Borella & Mariacristina De Nardi & Rory McGee & Nicolò Russo, 2024. "Health Inequality and Economic Disparities by Race, Ethnicity, and Gender," Opportunity and Inclusive Growth Institute Working Papers 099, Federal Reserve Bank of Minneapolis.
    15. Soojin Kim & Serena Rhee, 2022. "Understanding the Aggregate Effects of Disability Insurance," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 46, pages 328-364, October.

    More about this item

    JEL classification:

    • D52 - Microeconomics - - General Equilibrium and Disequilibrium - - - Incomplete Markets
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • H53 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Welfare Programs
    • I13 - Health, Education, and Welfare - - Health - - - Health Insurance, Public and Private
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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