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Adverse Selection, Moral Hazard and the Demand for Medigap Insurance

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The size of adverse selection and moral hazard effects in health insurance markets has important policy implications. For example, if adverse selection effects are small while moral hazard effects are large, conventional remedies for inefficiencies created by adverse selection (e.g., mandatory insurance enrolment) may lead to substantial increases in health care spending. Unfortunately, there is no consensus on the magnitudes of adverse selection vs. moral hazard. This paper sheds new light on this While both adverse selection and moral hazard effects of Medigap have been studied separately, this is the first paper to estimate both in an unified econometric framework. We develop an econometric model of insurance demand and health care expenditure, where adverse selection is measured by sensitivity of insurance demand to expected expenditure. The model allows for correlation between unobserved determinants of expenditure and insurance demand, and for heterogeneity in the size of moral hazard effects. Inference relies on an MCMC algorithm with data augmentation. Our results suggest there is adverse selection into Medigap, but the effect is small. A one standard deviation increase in expenditure risk raises the probability of insurance purchase by 0.037. In contrast, our estimate of the moral hazard effect is much larger. On average, Medigap coverage increases health care expenditure by 32%.

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  • Michael Keane & Olena Stavrunova, 2011. "Adverse Selection, Moral Hazard and the Demand for Medigap Insurance," Working Paper Series 167, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
  • Handle: RePEc:uts:wpaper:167
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    File URL: http://www.finance.uts.edu.au/research/wpapers/wp167.pdf
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    Cited by:

    1. Vincenzo Atella & Alberto Holly & Alessandro Mistretta, 2016. "Disentangling Adverse Selection, Moral Hazard and Supply Induced Demand: An Empirical Analysis of The Demand For Healthcare Services," CEIS Research Paper 389, Tor Vergata University, CEIS, revised 28 Jun 2016.
    2. Woldemichael, Andinet & Gurara, Daniel Zerfu & Shimeles, Abebe, 2016. "Community-Based Health Insurance and Out-of-Pocket Healthcare Spending in Africa: Evidence from Rwanda," IZA Discussion Papers 9922, Institute for the Study of Labor (IZA).
    3. Julie L. Hotchkiss & Anil Rupasingha, 2016. "Wage Determination in Social Occupations: the Role of Individual Social Capital," Working Papers 16-46, Center for Economic Studies, U.S. Census Bureau.
    4. Michael Keane & Olena Stavrunova, 2011. "A smooth mixture of Tobits model for healthcare expenditure," Health Economics, John Wiley & Sons, Ltd., vol. 20(9), pages 1126-1153, September.
    5. repec:taf:oaefxx:v:5:y:2017:i:1:p:1330303 is not listed on IDEAS
    6. Mercy Raquel Orellana Bravo & Juan Andrés Piedra Peña & Luis Santiago Sarmiento Moscoso, 2017. "Evidence About The Moral Hazard In The Ecuadorian Health System," Journal of Smart Economic Growth, , vol. 2(1), pages 109-132, March.
    7. Julie L. Hotchkiss, 2017. "Decennial Census Return Rates: The Role of Social Capital," Working Papers 17-39, Center for Economic Studies, U.S. Census Bureau.
    8. Stephen Kwasi Opoku Duku & Francis Asenso-Boadi & Edward Nketiah-Amponsah & Daniel Kojo Arhinful, 2016. "Utilization of healthcare services and renewal of health insurance membership: evidence of adverse selection in Ghana," Health Economics Review, Springer, vol. 6(1), pages 1-12, December.

    More about this item

    Keywords

    health insurance; adverse selection; moral hazard; health care expenditure;

    JEL classification:

    • I13 - Health, Education, and Welfare - - Health - - - Health Insurance, Public and Private
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions

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