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Economic Effects of Risk Classification Bans

Author

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  • Dionne, Georges

    (HEC Montreal, Canada Research Chair in Risk Management)

  • Rothschild, Casey

    (Wellesley College)

Abstract

Risk classification refers to the use of observable characteristics by insurers to group individuals with similar expected claims, to compute the corresponding premiums, and thereby to reduce asymmetric information. Permitting risk classification may reduce informational asymmetry-induced adverse selection and improve insurance market efficiency. It may also have undesirable equity consequences and undermine the implicit insurance against reclassification risk which legislated restrictions on risk classification could provide. We use a canonical insurance market screening model to survey and to extend the risk classification literature. We provide a unified framework for analyzing the economic consequences of legalized vs. banned risk classification, both in static-information environments and in environments in which additional information can be learned, by either side of the market, through potentially costly tests.

Suggested Citation

  • Dionne, Georges & Rothschild, Casey, 2014. "Economic Effects of Risk Classification Bans," Working Papers 14-4, HEC Montreal, Canada Research Chair in Risk Management.
    • Handle: RePEc:ris:crcrmw:2014_004
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    3. Bernard Salanié, 2017. "Equilibrium in Insurance Markets: An Empiricist’s View," The Geneva Papers on Risk and Insurance Theory, Springer;International Association for the Study of Insurance Economics (The Geneva Association), vol. 42(1), pages 1-14, March.
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    5. David A. Cather, 2020. "Reconsidering insurance discrimination and adverse selection in an era of data analytics," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 45(3), pages 426-456, July.
    6. Hao, MingJie & Macdonald, Angus S. & Tapadar, Pradip & Thomas, R. Guy, 2018. "Insurance loss coverage and demand elasticities," Insurance: Mathematics and Economics, Elsevier, vol. 79(C), pages 15-25.
    7. Ruo Jia & Zenan Wu, 2019. "Insurer commitment and dynamic pricing pattern," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 44(1), pages 87-135, March.
    8. Bardey, David & De Donder, Philippe & Mantilla, César, 2019. "How is the trade-off between adverse selection and discrimination risk affected by genetic testing? Theory and experiment," Journal of Health Economics, Elsevier, vol. 68(C).
    9. Karlsson Linnér, Richard & Koellinger, Philipp D., 2022. "Genetic risk scores in life insurance underwriting," Journal of Health Economics, Elsevier, vol. 81(C).
    10. Martin Eling & Ruo Jia & Yi Yao, 2017. "Between-Group Adverse Selection: Evidence From Group Critical Illness Insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 84(2), pages 771-809, June.
    11. Peter, Richard & Richter, Andreas & Thistle, Paul, 2017. "Endogenous information, adverse selection, and prevention: Implications for genetic testing policy," Journal of Health Economics, Elsevier, vol. 55(C), pages 95-107.
    12. Meyer, Christina, 2022. "Geschlechtsspezifisches Altersvorsorgeverhalten – Untersuchungen mit dem deutschen Taxpayer-Panel," WISTA – Wirtschaft und Statistik, Statistisches Bundesamt (Destatis), Wiesbaden, vol. 74(2), pages 30-41.
    13. M. Martin Boyer & Richard Peter, 2020. "Insurance Fraud in a Rothschild–Stiglitz World," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 87(1), pages 117-142, March.
    14. Gemmo, Irina & Browne, Mark J. & Gründl, Helmut, 2017. "Transparency aversion and insurance market equilibria," ICIR Working Paper Series 25/17, Goethe University Frankfurt, International Center for Insurance Regulation (ICIR).
    15. Martin Eling & Irina Gemmo & Danjela Guxha & Hato Schmeiser, 2024. "Big data, risk classification, and privacy in insurance markets," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 49(1), pages 75-126, March.
    16. Caliendo, Frank N. & Gorry, Aspen & Slavov, Sita, 2020. "Survival ambiguity and welfare," Journal of Economic Behavior & Organization, Elsevier, vol. 170(C), pages 20-42.
    17. Donatella Porrini, 2015. "Risk Classification Efficiency and the Insurance Market Regulation," Risks, MDPI, vol. 3(4), pages 1-10, September.
    18. Levon Barseghyan & Francesca Molinari & Darcy Steeg Morris & Joshua C. Teitelbaum, 2020. "The Cost of Legal Restrictions on Experience Rating," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 17(1), pages 38-70, March.
    19. Ruo Jia & Zenan Wu, 2019. "Insurer commitment and dynamic pricing pattern," The Geneva Papers on Risk and Insurance Theory, Springer;International Association for the Study of Insurance Economics (The Geneva Association), vol. 44(1), pages 87-135, March.
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    More about this item

    Keywords

    Adverse selection; Classification risk; Classification bans; Equity; Efficiency;
    All these keywords.

    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • I13 - Health, Education, and Welfare - - Health - - - Health Insurance, Public and Private
    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • I38 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Government Programs; Provision and Effects of Welfare Programs

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