Hostname: page-component-cd9895bd7-jkksz Total loading time: 0 Render date: 2024-12-23T09:20:51.325Z Has data issue: false hasContentIssue false
  • English
  • Français

Empirical tests for ex post moral hazard in a market for automobile insurance

Published online by Cambridge University Press:  03 November 2021

David Rowell ,
Son Nghiem  and
Luke B. Connelly
David Rowell*
Affiliation:
Centre for the Business and Economics of Health (CBEH), The University of Queensland, 4067 Brisbane, Australia
Son Nghiem
Affiliation:
Centre for Applied Health Economics and School of Medicine and Dentistry, Griffith University, 4111 Brisbane, Australia
Luke B. Connelly
Affiliation:
Centre for the Business and Economics of Health (CBEH), The University of Queensland, 4067 Brisbane, Australia Department of Sociology and Business Law, The University of Bologna, 40126 Bologna BO, Italy
*
*Corresponding author: E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Ex post moral hazard arises when the insured has an unobservable influence on the size of a loss after its occurrence. In automobile (property) insurance, ex post moral hazard could increase in the scope of the repairs and/or the value of the repairs. Both vehicle owners and auto repairers could gain from increasing the scope of repairs, while auto repairers would gain from an increase in the value of repairs. An analysis of 994 Australian road traffic crashes found that ex post moral hazard increased the value of repairs by 46.8 per cent of which 9 percentage points was explained by an increase in the scope of the repairs, which was defined as an increased from 2 to 2.4 parts per auto repair.

Keywords

Ex post moral hazardAutomobile insuranceRoad traffic crash repairs
Type
Original Research Paper
Information
Annals of Actuarial Science , Volume 16 , Issue 2 , July 2022 , pp. 243 - 260
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of Institute and Faculty of Actuaries

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abbring, J., Chiappori, P.A., & Zavadil, T. (2007). Better safe than sorry? Ex ante and ex post moral hazard in dynamic insurance data. Tinbergen Institute Discussion Paper No. 08-075/3 Center Discussion Paper No. 2008–77.Google Scholar
Abbring, J.H., Chiappori, P.A., & Pinquet, J. (2003). Moral hazard and dynamic insurance data. Journal of the European Economic Association, 1, 767–820.CrossRefGoogle Scholar
Arrow, K.J. (1963). Uncertainty and the welfare economics of medical care. The American Economic Review, LIII, 941–973.Google Scholar
Artís, M., Ayuso, M., & Guillén, M. (1999). Modelling different types of automobile insurance fraud behaviour in the Spanish market. Insurance: Mathematics and Economics, 24, 67–81.Google Scholar
Artís, M., Ayuso, M., & Guillen, M. (2002). Detection of automobile insurance fraud with discrete choice models and misclassified claims. The Journal of Risk and Insurance, 69, 325–340.CrossRefGoogle Scholar
Australian Bureau of Statistics. (2004). 2004 Year book Australia (ABS cat. no. 1301.0).Google Scholar
Australian Bureau of Statistics. (2006). Population by age and sex, Australian States and Territories (ABS cat. no. 3201.0).Google Scholar
Bednall, D., & Shaw, M. (2002). Response rates in Australian market research: area differences in consumer response. In ANZMAC 2002 Conference Proceedings.Google Scholar
Belhadji, E.B., Dionne, G., & Tarkhani, F. (2000). A model for the detection of insurance fraud. The Geneva Papers on Risk and Insurance, 25, 517–538.CrossRefGoogle Scholar
Bureau of Transport Economics. (2000). Road crash costs in Australia (BTE Report 102). Bureau of Transport Economics, Canberra.Google Scholar
Caron, L., & Dionne, G. (1999). Insurance fraud estimation: more evidence from Qubec automobile insurance industry. In G. Dionne & C. Laberge-Nadeau (Eds.), Automobile insurance: Road Safety, New Drivers, Risks, Insurance Fraud and Regulation (pp. 175–182). Boston: Kluwer Academic Publishers.Google Scholar
Chiappori, P.A. (2000). Econometric models of insurance under asymmetric information. In G. Dionne (Ed.), Handbook of Insurance (pp. 365–393). Boston: Kluwer Academic Publishers.CrossRefGoogle Scholar
Chiappori, P.A., & Salanié, B. (2000). Testing for asymmetric information in insurance markets. The Journal of Political Economy, 108, 56–78.CrossRefGoogle Scholar
Cummins, J., & Tennyson, S. (1996). Moral hazard in insurance claiming: evidence from automobile insurance. Journal of Risk and Uncertainty, 12, 29–50.CrossRefGoogle Scholar
Dionne, G. (2013). The empirical measure of information problems with emphasis on insurance fraud and dynamic data. In G. Dionne (Ed.), Handbook of Insurance, 2 edition. New York: Springer, Chapter 15.CrossRefGoogle Scholar
Dionne, G., Michaud, P.C., & Dahchour, M. (2013). Separating moral hazard from adverse selection and learning in automobile insurance: longitudinal evidence from France. Journal of the European Economic Association, 11, 897–917.CrossRefGoogle Scholar
Einav, L., & Finkelstein, A. (2018). Moral hazard in health insurance: what we know and how we know it. Journal of the European Economic Association, 16, 957–982.CrossRefGoogle Scholar
Halvorsen, R., & Palmquist, R. (1980). The interpretation of dummy variables in semilogarithmic equations. The American Economic Review, 70, 474–475.Google Scholar
IMRAS. (2000). The Smash Repair Market: Shaping Up for the New Millennium Volume 2 Accidents/Insurers. IMRAS Consulting Pty. Ltd, Sydney.Google Scholar
Israel, M. (2004). Do We Drive More Safely When Accidents Are More Expensive? Identifying Moral Hazard from Experience Rating Schemes (Mimeo). Kellogg School of Management, Northwestern University, Evanston, IL.Google Scholar
Macedo, A.M., Cardoso, C.V., Neto, J.S.M., & da Costa Bras Cunha, C.A. (2020). Car insurance fraud: the role of vehicle repair workshops. International Journal of Law, Crime and Justice, 65, 100456.Google Scholar
Manning, W.G., & Marquis, M.S. (1996). Health insurance: the tradeoff between risk pooling and moral hazard. Journal of Health Economics, 15, 609–639.CrossRefGoogle ScholarPubMed
Nyman, J.A. (1999). The economics of moral hazard revisited. Journal of Health Economics, 18, 811–824.CrossRefGoogle ScholarPubMed
Pauly, M.V. (1968). The economics of moral hazard: comment. The American Economic Review, 58, 531–537.Google Scholar
Picard, P. (2013). Economic analysis of insurance fraud. In G. Dionne (Ed.), Handbook of Insurance, 2 edition (pp. 349–395). Springer, New York. Chapter 13.CrossRefGoogle Scholar
Productivity Commission. (2005). Smash repair and insurance (Report no. 34). The Productivity Commission, Canberra.Google Scholar
Puelz, R., & Snow, A. (1997). Optimal incentive contracting with ex ante and ex post moral hazard: theory and evidence. Journal of Risk and Uncertainty, 14, 169–188.CrossRefGoogle Scholar
Robinson, C., & Zheng, B. (2010). Moral hazard, insurance claims, and repeated insurance contracts. Canadian Journal of Economics, 43, 967–991.CrossRefGoogle Scholar
Rowell, D. (2011). Moral hazard: empirical evidence in the Australian market for automobile insurance. Ph.D. thesis. School of Economics, The University of Queensland.Google Scholar
Rowell, D., Nghiem, H.S., & Connelly, L. (2017). Two tests for ex ante moral hazard in a market for automobile insurance. Journal of Risk and Insurance, 84, 1103–1126.CrossRefGoogle Scholar
RTA Road User Research. (2002). New South Wales driver and vehicle statistics 2001 (RTA/Pub. 02.055). Technical Report. NSW Road Traffic Authority. Sydney.Google Scholar
Shapiro, S., & Wilk, M. (1965). An analysis of variance test for normality (complete samples). Biometrika, 52, 59–611.CrossRefGoogle Scholar
Slutsky, E. (1915). Sulla teoria del bilancio del consumatore. Giornale degli Economisti e Rivista di Statistica 51 (July), pp.1 to 26 Translated. as On the Theory of the Budget of the Consumer in Readings in Price Theory, K.E. Boulding & G.J. Stigler (Eds.). London: Allen & Unwin, 1953, pp. 26–56.Google Scholar
Subelj, L., Furlan, S., & Bajec, M. (2011). An expert system for detecting automobile insurance fraud using social network analysis. Expert Systems with Applications, 38, 1039–1052.CrossRefGoogle Scholar
Tracy, P.E., & Fox, J.A. (1989). A field experiment on insurance fraud in auto body repair. Criminology, 27, 589–603.CrossRefGoogle Scholar
Weisburd, S. (2015). Identifying moral hazard in car insurance contracts. The Review of Economics and Statistics, 97, 301–313.CrossRefGoogle Scholar
Wooldridge, J.M. (2000). Introductory Econometrics: A Modern Approach. Mason, OH: South-Western College Publishing.Google Scholar
Zweifel, P., & Breyer, F. (1997). Health Economics. New York: Oxford University Press.Google Scholar