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Risk Classification Efficiency and the Insurance Market Regulation

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  • Donatella Porrini

    (Dipartimento di Scienze dell'Economia, Università del Salento, Ecotekne, Via per Monteroni, Lecce 73100, Italy)

Abstract

Given that the insurance market is characterized by asymmetric information, its efficiency has traditionally been based to a large extent on risk classification. In certain regulations, however, we can find restrictions on these differentiations, primarily the ban on those considered to be “discriminatory”. In 2011, following the European Union Directive 2004/113/EC, the European Court of Justice concluded that any gender-based discrimination was prohibited, meaning that gender equality in the European Union had to be ensured from 21 December 2012. Another restriction was imposed by EU and national competition regulation on the exchange of information considered as anti-competitive behavior. This paper aims to contribute to the recent policy debate in the EU, evaluating the negative economic consequences of these regulatory restrictions in terms of market efficiency.

Suggested Citation

  • Donatella Porrini, 2015. "Risk Classification Efficiency and the Insurance Market Regulation," Risks, MDPI, vol. 3(4), pages 1-10, September.
  • Handle: RePEc:gam:jrisks:v:3:y:2015:i:4:p:445-454:d:56474
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    References listed on IDEAS

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    1. Thomas Buchmueller & John Dinardo, 2002. "Did Community Rating Induce an Adverse Selection Death Spiral? Evidence from New York, Pennsylvania, and Connecticut," American Economic Review, American Economic Association, vol. 92(1), pages 280-294, March.
    2. Liran Einav & Amy Finkelstein & Jonathan Levin, 2010. "Beyond Testing: Empirical Models of Insurance Markets," Annual Review of Economics, Annual Reviews, vol. 2(1), pages 311-336, September.
    3. Kai-Uwe Kühn, 2001. "Fighting collusion by regulating communication between firms," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 16(32), pages 168-204.
    4. R Guy Thomas, 2007. "Some Novel Perspectives on Risk Classification," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 32(1), pages 105-132, January.
    5. Dionne, Georges & Gouriéroux, Christian & Vanasse, Charles, 1998. "Evidence of adverse selection in automobile insurance markets," Working Papers 98-9, HEC Montreal, Canada Research Chair in Risk Management.
    6. Crocker, Keith J & Snow, Arthur, 1986. "The Efficiency Effects of Categorical Discrimination in the Insurance Industry," Journal of Political Economy, University of Chicago Press, vol. 94(2), pages 321-344, April.
    7. Schwarze, Reimund & Wein, Thomas, 2005. "Is the market classification of risk always efficient? Evidence from German third party motor insurance," German Risk and Insurance Review (GRIR), University of Cologne, Department of Risk Management and Insurance, vol. 1(4), pages 173-202.
    8. Donatella Porrini, 2004. "Information Exchange as Collusive Behaviour: Evidence from an Antitrust Intervention in the Italian Insurance Market," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 29(2), pages 219-233, April.
    9. Padilla, A. Jorge & Pagano, Marco, 2000. "Sharing default information as a borrower discipline device," European Economic Review, Elsevier, vol. 44(10), pages 1951-1980, December.
    10. Georges Dionne & Christian Gourieroux & Charles Vanasse, 2001. "Testing for Evidence of Adverse Selection in the Automobile Insurance Market: A Comment," Journal of Political Economy, University of Chicago Press, vol. 109(2), pages 444-473, April.
    11. 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.
    12. Mary Kelly & Norma Nielson, 2006. "Age as a Variable in Insurance Pricing and Risk Classification," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 31(2), pages 212-232, April.
    13. Michael Hoy, 1982. "Categorizing Risks in the Insurance Industry," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 97(2), pages 321-336.
    14. Dahlby, B. G., 1983. "Adverse selection and statistical discrimination : An analysis of Canadian automobile insurance," Journal of Public Economics, Elsevier, vol. 20(1), pages 121-130, February.
    15. Donatella Porrini, 2012. "Insurance Regulation," Chapters, in: Roger J. Van den Bergh & Alessio M. Pacces (ed.), Regulation and Economics, chapter 12, Edward Elgar Publishing.
    16. George A. Akerlof, 1970. "The Market for "Lemons": Quality Uncertainty and the Market Mechanism," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 84(3), pages 488-500.
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    Cited by:

    1. 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.
    2. Mihail Busu & Cristian Busu, 2021. "Detecting Bid-Rigging in Public Procurement. A Cluster Analysis Approach," Administrative Sciences, MDPI, vol. 11(1), pages 1-14, February.
    3. Francesco Masi & Donatella Porrini, 2021. "Cultural Heritage and natural disasters: the insurance choice of the Italian Cathedrals," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 45(3), pages 409-433, September.
    4. Donatella Porrini & Giulio Fusco & Cosimo Magazzino, 2020. "Black boxes and market efficiency: the effect on premiums in the Italian motor-vehicle insurance market," European Journal of Law and Economics, Springer, vol. 49(3), pages 455-472, June.
    5. Alfiero, Simona & Battisti, Enrico & Ηadjielias, Elias, 2022. "Black box technology, usage-based insurance, and prediction of purchase behavior: Evidence from the auto insurance sector," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    6. Alexander Tsyganov & Nadezda Kirillova, 2018. "Regional Aspect of the Russian Insurance Market," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(4), pages 1270-1281.
    7. Aleksandr Kuklin & Maria Pecherkina & Alexander Tyrsin & Alfiya Surina, 2017. "Methodological Tools for the Detection of Risks to the Welfare of the Individuals and the Territory of Residence," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(4), pages 1030-1043.

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