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Adverse Selection in Term Life Insurance Purchasing due to the BRCA1/2 Genetic Test and Elastic Demand

Author

Listed:
  • Krupa S. Viswanathan
  • Jean Lemaire
  • Kate Withers
  • Katrina Armstrong
  • Agnieszka Baumritter
  • John C. Hershey
  • Mark V. Pauly
  • David A. Asch

Abstract

Consumer groups fear that the use of genetic testing information in insurance underwriting might lead to the creation of an underclass of individuals who cannot obtain insurance; thus, these groups want to ban insurance companies from accessing genetic test results. Insurers contend that such a ban might lead to adverse selection that could threaten their financial solvency. To investigate the potential effect of adverse selection in a term life insurance market, a discrete‐time, discrete‐state, Markov chain is used to track the evolution of twelve closed cohorts of women, differentiated by family history of breast and ovarian cancer and age at issue of a 20‐year annually renewable term life insurance policy. The insurance demand behavior of these women is tracked, incorporating elastic demand for insurance. During the 20‐year period, women may get tested for BRCA1/2 mutations. Each year, the insurer calculates the expected premiums and expected future benefit payouts which determine the following year's premium schedule. At the end of each policy year, women can change their life insurance benefit, influenced by their testing status and premium changes. Adverse selection could result from (i) differentiated benefits following test results; (ii) differentiated lapse rates according to test results; and (iii) differentiated reactions to price increases. It is concluded that with realistic estimates of behavioral parameters, adverse selection could be a manageable problem for insurers.

Suggested Citation

  • Krupa S. Viswanathan & Jean Lemaire & Kate Withers & Katrina Armstrong & Agnieszka Baumritter & John C. Hershey & Mark V. Pauly & David A. Asch, 2007. "Adverse Selection in Term Life Insurance Purchasing due to the BRCA1/2 Genetic Test and Elastic Demand," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 74(1), pages 65-86, March.
  • Handle: RePEc:bla:jrinsu:v:74:y:2007:i:1:p:65-86
    DOI: 10.1111/j.1539-6975.2007.00202.x
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    References listed on IDEAS

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    1. B. Douglas Bernheim & Katherine Grace Carman & Jagadeesh Gokhale & Laurence J. Kotlikoff, 2001. "The Mismatch Between Life Insurance Holdings and Financial Vulnerabilities: Evidence from the Survey of Consumer Finances," NBER Working Papers 8544, National Bureau of Economic Research, Inc.
    2. B. Douglas Bernheim & Lorenzo Forni & Jagadeesh Gokhale & Laurence J. Kotlikoff, 2001. "The mismatch between life insurance holdings and financial vulnerabilities: evidence from the Health and Retirement Survey," Working Papers (Old Series) 0109, Federal Reserve Bank of Cleveland.
    3. Mark V. Pauly & Kate H. Withers & Krupa Subramanian-Viswana & Jean Lemaire & John C. Hershey, 2003. "Price Elasticity of Demand for Term Life Insurance and Adverse Selection," NBER Working Papers 9925, National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. 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.
    2. Nadine Gatzert & Gudrun Hoermann & Hato Schmeiser, 2009. "The Impact of the Secondary Market on Life Insurers’ Surrender Profits," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 76(4), pages 887-908, December.
    3. Georges Dionne & Nathalie Fombaron & Wanda Mimra, 2025. "Adverse Selection in Insurance," Springer Books, in: Georges Dionne (ed.), Handbook of Insurance, edition 0, pages 165-221, Springer.
    4. Jir^o Akahori & Yuuki Ida & Maho Nishida & Shuji Tamada, 2020. "The Thermodynamic Approach to Whole-Life Insurance: A Method for Evaluation of Surrender Risk," Papers 2012.09606, arXiv.org.
    5. Timothy F. Harris & Aaron Yelowitz, 2017. "Nudging Life Insurance Holdings In The Workplace," Economic Inquiry, Western Economic Association International, vol. 55(2), pages 951-981, April.
    6. Simeon Schudy & Verena Utikal, 2015. "Does imperfect data privacy stop people from collecting personal health data?," TWI Research Paper Series 98, Thurgauer Wirtschaftsinstitut, Universität Konstanz.
    7. R. Guy Thomas, 2018. "Why Insurers Are Wrong about Adverse Selection," Laws, MDPI, vol. 7(2), pages 1-8, April.
    8. 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.
    9. Simeon Schudy & Verena Utikal, 2018. "Does Imperfect Data Privacy Stop People from Collecting Personal Data?," Games, MDPI, vol. 9(1), pages 1-23, March.
    10. Kenkel Don S. & Wang Hua, 2013. "The Economics of Personalization in Prevention and Public Health," Forum for Health Economics & Policy, De Gruyter, vol. 16(2), pages 53-71, June.
    11. Jason Nassios & James Giesecke, 2022. "Property Tax Reform: Implications for Housing Prices and Economic Productivity," Centre of Policy Studies/IMPACT Centre Working Papers g-330, Victoria University, Centre of Policy Studies/IMPACT Centre.

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