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INSURANCE LOSS COVERAGE UNDER RESTRICTED RISK CLASSIFICATION: THE CASE OF ISO-ELASTIC DEMAND

Published online by Cambridge University Press:  16 February 2016

MingJie Hao ,
Angus S. Macdonald ,
Pradip Tapadar  and
R. Guy Thomas
MingJie Hao
Affiliation:
School of Mathematics, Statistics and Actuarial Science, University of Kent, Canterbury, CT2 7NF, UK E-Mail: [email protected]
Angus S. Macdonald
Affiliation:
Department of Actuarial Mathematics and Statistics, and the Maxwell Institute for Mathematical Sciences, Heriot-Watt University, Edinburgh EH14 4AS, UK E-Mail: [email protected]
Pradip Tapadar*
Affiliation:
School of Mathematics, Statistics and Actuarial Science, University of Kent, Canterbury, CT2 7NF, UK
R. Guy Thomas
Affiliation:
School of Mathematics, Statistics and Actuarial Science, University of Kent, Canterbury, CT2 7NF, UK E-mail: [email protected]
*
E-Mail: [email protected]
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Abstract

This paper investigates equilibrium in an insurance market where risk classification is restricted. Insurance demand is characterised by an iso-elastic function with a single elasticity parameter. We characterise the equilibrium by three quantities: equilibrium premium; level of adverse selection (in the economist's sense); and “loss coverage”, defined as the expected population losses compensated by insurance. We consider both equal elasticities for high and low risk-groups, and then different elasticities. In the equal elasticities case, adverse selection is always higher under pooling than under risk-differentiated premiums, while loss coverage first increases and then decreases with demand elasticity. We argue that loss coverage represents the efficacy of insurance for the whole population; and therefore that if demand elasticity is sufficiently low, adverse selection is not always a bad thing.

Keywords

Adverse selectionloss coveragerisk classificationequilibrium premiumiso-elastic demand
Type
Research Article
Information
ASTIN Bulletin: The Journal of the IAA , Volume 46 , Issue 2 , May 2016 , pp. 265 - 291
Copyright
Copyright © Astin Bulletin 2016 

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References

Blumberg, L., Nichold, L. and Banthin, J. (2001) Worker decisions to purchase health insurance. International Journal of Health Care Finance and Economics, 1, 305–325Google Scholar
Buchmueller, T.C. and Ohri, S. (2006) Health insurance take-up by the near-elderly. Health Services Research, 41, 2054–2073Google Scholar
Butler, J.R.G. (1999) Estimating elasticities of demand for private health insurance in Australia. Working Paper, 43, National Centre for Epidemiology and Population Health, CanberraGoogle Scholar
Cardon, J.H. and Hendel, I. (2001) Asymmetric information in health insurance: Evidence from the National Medical Expenditure Survey. Rand Journal of Economics, 32, 408–427Google Scholar
Chernew, M., Frick, K. and McLaughlin, C. (1997) The demand for health insurance coverage by low-income workers: Can reduced premiums achieve full coverage?. Health Services Research, 32, 453–470Google Scholar
Chiappori, P.-A. and Salanie, B. (2000) Testing for asymmetric information in insurance markets. Journal of Political Economy, 108, 56–78CrossRefGoogle Scholar
Cohen, A. and Siegelman, P. (2010) Testing for adverse selection in insurance markets. Journal of Risk and Insurance, 77, 39–84Google Scholar
De Jong, P. and Ferris, S. (2006) Adverse selection spirals. ASTIN Bulletin, 36, 589–628CrossRefGoogle Scholar
Dionne, G. and Rothschild, C.G. (2014) Economic effects of risk classification bans. Geneva Risk and Insurance Review, 39, 184–221Google Scholar
Finkelstein, A. and McGarry, K. (2006) Multiple dimensions of private information: Evidence from the long-term care insurance market. American Economic Review, 96, 938–958CrossRefGoogle ScholarPubMed
Finkelstein, A. and Poterba, J. (2004) Adverse selection in insurance markets: Policyholder evidence from the UK annuity market. Journal of Political Economy, 112, 183–208CrossRefGoogle Scholar
Hoy, M. (2006) Risk classification and social welfare. Geneva Papers on Risk and Insurance, 31, 245–269Google Scholar
Hoy, M. and Polborn, M. (2000) The value of genetic information in the life insurance market. Journal of Public Economics, 78, 235–252CrossRefGoogle Scholar
Macdonald, A.S. and Tapadar, P. (2010) Multifactorial disorders and adverse selection: epidemiology meets economics. Journal of Risk and Insurance, 77, 155–182Google Scholar
Pauly, M.V., Withers, K.H., Viswanathan, K.S., Lemaire, J., Hershey, J.C., Armstrong, K. and Asch, D.A. (2003) Price elasticity of demand for term life insurance and adverse selection. NBER Working Paper, 9925, http://www.nber.org/papers/w9925. Accessed on February 5, (2016).Google Scholar
Thomas, R.G. (2008) Loss coverage as a public policy objective for risk classification schemes. Journal of Risk and Insurance, 75, 997–1018Google Scholar
Thomas, R.G. (2009) Demand elasticity, risk classification and loss coverage: When can community rating work?. ASTIN Bulletin, 39, 403–428Google Scholar
Viswanathan, K.S., Lemaire, J. K., Withers, K., Armstrong, K., Baumritter, A., Hershey, J., Pauly, M. and Asch, D.A. (2007) Adverse selection in term life insurance purchasing due to the BRCA 1/2 Genetic Test and elastic demand. Journal of Risk and Insurance, 74, 65–86Google Scholar