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Welfare Effects of Banning Genetic Information in the Life Insurance Market: The Case of BRCA1/2 Genes

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  • Michael Hoy

    (Department of Economics, University of Guelph)

  • Julia Witt

Abstract

This paper is a contribution to the debate about whether regulations that ban insurance companies from access to individuals’ genetic tests may lead in the near to medium term future to substantial adverse selection costs. We choose the specific possibility of widespread knowledge based on genetic testing for the so-called breast cancer (BRCA1/2) genes. We use a data set including economic, demographic, and relevant family background information to simulate the market for 10-year term life insurance targeted at women aged 35 to 39. Using standard welfare economic analysis for various information and regulatory scenarios concerning genetic test results, we find generally only modest adverse selection costs associated with such a regulatory ban. However, for family background groups which are at high risk for carrying one of the BRCA1/2 genes, the efficiency cost of adverse selection may be significant especially if a large fraction of women within such groups were to obtain genetic test results. These results, therefore, suggest some caution in developing regulations which protect individuals’ genetic privacy.

Suggested Citation

  • Michael Hoy & Julia Witt, 2005. "Welfare Effects of Banning Genetic Information in the Life Insurance Market: The Case of BRCA1/2 Genes," Working Papers 0505, University of Guelph, Department of Economics and Finance.
  • Handle: RePEc:gue:guelph:2005-5
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    References listed on IDEAS

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    Cited by:

    1. Maureen Durnin & Michael Hoy & Michael Ruse, 2012. "Genetic Testing and Insurance: The Complexity of Adverse Selection," Working Papers 1208, University of Guelph, Department of Economics and Finance.
    2. Oster, Emily & Shoulson, Ira & Quaid, Kimberly & Dorsey, E. Ray, 2010. "Genetic adverse selection: Evidence from long-term care insurance and Huntington disease," Journal of Public Economics, Elsevier, vol. 94(11-12), pages 1041-1050, December.
    3. Filipova-Neumann, Lilia & Hoy, Michael, 2014. "Managing genetic tests, surveillance, and preventive medicine under a public health insurance system," Journal of Health Economics, Elsevier, vol. 34(C), pages 31-41.
    4. Georges Dionne & Casey Rothschild, 2014. "Economic Effects of Risk Classification Bans," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 39(2), pages 184-221, September.
    5. Alma Cohen & Peter Siegelman, 2010. "Testing for Adverse Selection in Insurance Markets," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 77(1), pages 39-84, March.
    6. Michael Hoy & Richard Peter & Andreas Richter, 2014. "Take-up for genetic tests and ambiguity," Journal of Risk and Uncertainty, Springer, vol. 48(2), pages 111-133, April.
    7. Finkelstein, Amy & Poterba, James & Rothschild, Casey, 2009. "Redistribution by insurance market regulation: Analyzing a ban on gender-based retirement annuities," Journal of Financial Economics, Elsevier, vol. 91(1), pages 38-58, January.
    8. Karlsson Linnér, Richard & Koellinger, Philipp D., 2022. "Genetic risk scores in life insurance underwriting," Journal of Health Economics, Elsevier, vol. 81(C).
    9. Francesca Barigozzi & Dominique Henriet, 2011. "Genetic Information: Comparing Alternative Regulatory Approaches When Prevention Matters," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 13(1), pages 23-46, February.
    10. Georges Dionne & Casey G. Rothschild, 2011. "Risk Classification in Insurance Contracting," Cahiers de recherche 1137, CIRPEE.
    11. Kesternich, Iris & Schumacher, Heiner, 2009. "On the Use of Information in Repeated Insurance Markets," Discussion Paper Series of SFB/TR 15 Governance and the Efficiency of Economic Systems 280, Free University of Berlin, Humboldt University of Berlin, University of Bonn, University of Mannheim, University of Munich.
    12. Ron Cheung & Cassandra R. Cole & David A. Macpherson & Kathleen A. McCullough & Charles Nyce, 2015. "Demographic Factors and Price Distortions in Insurance," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 18(1), pages 1-28, March.
    13. 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.
    14. Angus Macdonald & Pradip Tapadar, 2010. "Multifactorial Genetic Disorders and Adverse Selection: Epidemiology Meets Economics," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 77(1), pages 155-182, March.
    15. Dionne, Georges & Fombaron, Nathalie & Doherty, Neil, 2012. "Adverse selection in insurance contracting," Working Papers 12-8, HEC Montreal, Canada Research Chair in Risk Management.
    16. Lu Li, 2021. "Opening up the black box: Technological transparency and prevention," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 88(3), pages 665-693, September.
    17. Stefan Felder, 2022. "Decision thresholds with genetic testing," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(6), pages 1071-1078, August.
    18. Michael Hoy & Michael Ruse, 2008. "“No Solution to This Dilemma Exists”: Discrimination, Insurance, and the Human Genome Project," Working Papers 0808, University of Guelph, Department of Economics and Finance.

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