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An Empirical Evaluation of the Implementation of the Bonus-Malus System in the Tunisian Automobile Insurance Ratemaking

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  • Olfa N. Ghali

Abstract

The objective of this study was to empirically assess the impact of the introduction of the Bonus-Malus system on road security in the pricing of car insurance in Tunisia. Results indicate that when we consider the risks altogether, the effect of the reform is not very significant. This is explained by the fact that bad risks, which represent 92.44 percent of the sample, get round the law to change the company. Therefore, the bonus-malus system was not very efficient in reducing the probability of accidents. This shows the need for indicative variables of inflows and outflows in a pricing system where there is no central risk and where individuals can easily change the company and increase their benefits, since they can be placed in a Bonus-Malus category that is less than the one where they were. One of the important conclusions has been that besides the power of the vehicle, three other variables can explain the number of accidents: the brand and the age of the vehicle, the place of residence of the insured and the guarantees to which they are subscribed.

Suggested Citation

  • Olfa N. Ghali, 2001. "An Empirical Evaluation of the Implementation of the Bonus-Malus System in the Tunisian Automobile Insurance Ratemaking," Working Papers 0135, Economic Research Forum, revised 11 2001.
  • Handle: RePEc:erg:wpaper:0135
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    References listed on IDEAS

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    1. Dionne, G & Vanasse, C, 1992. "Automobile Insurance Ratemaking in the Presence of Asymmetrical Information," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(2), pages 149-165, April-Jun.
    2. Dionne, Georges & Gagne, Robert & Vanasse, Charles, 1998. "Inferring technological parameters from incomplete panel data," Journal of Econometrics, Elsevier, vol. 87(2), pages 303-327, September.
    3. Dionne, Georges & Artis, Manuel & Guillen, Montserrat, 1996. "Count data models for a credit scoring system," Journal of Empirical Finance, Elsevier, vol. 3(3), pages 303-325, September.
    4. Boyer, M. & Dionee, G. & Vanasse, C., 1990. "Econometric Models of Accident Distributions," Cahiers de recherche 9001, Universite de Montreal, Departement de sciences economiques.
    5. repec:adr:anecst:y:1986:i:1 is not listed on IDEAS
    6. Richard A. Lambert, 1983. "Long-Term Contracts and Moral Hazard," Bell Journal of Economics, The RAND Corporation, vol. 14(2), pages 441-452, Autumn.
    7. Cameron, A Colin & Trivedi, Pravin K, 1986. "Econometric Models Based on Count Data: Comparisons and Applications of Some Estimators and Tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 1(1), pages 29-53, January.
    8. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 38(2), pages 112-134.
    9. Lechner, Michael, 1995. "Some Specification Tests for Probit Models Estimated on Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(4), pages 475-488, October.
    10. Michael Hoy, 1982. "Categorizing Risks in the Insurance Industry," The Quarterly Journal of Economics, Oxford University Press, vol. 97(2), pages 321-336.
    11. Wilson, Charles, 1977. "A model of insurance markets with incomplete information," Journal of Economic Theory, Elsevier, vol. 16(2), pages 167-207, December.
    12. Hausman, Jerry & Hall, Bronwyn H & Griliches, Zvi, 1984. "Econometric Models for Count Data with an Application to the Patents-R&D Relationship," Econometrica, Econometric Society, vol. 52(4), pages 909-938, July.
    13. Guilkey, David K. & Murphy, James L., 1993. "Estimation and testing in the random effects probit model," Journal of Econometrics, Elsevier, vol. 59(3), pages 301-317, October.
    14. 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.
    15. Amemiya, Takeshi, 1981. "Qualitative Response Models: A Survey," Journal of Economic Literature, American Economic Association, vol. 19(4), pages 1483-1536, December.
    16. Dominique Henriet & Jean-Charles Rochet, 1986. "La logique des systèmes bonus-malus en assurance automobile: une approche théorique," Annals of Economics and Statistics, GENES, issue 1, pages 133-152.
    17. Arthur J. Hosios & Michael Peters, 1989. "Repeated Insurance Contracts with Adverse Selection and Limited Commitment," The Quarterly Journal of Economics, Oxford University Press, vol. 104(2), pages 229-253.
    18. repec:adr:anecst:y:1986:i:1:p:07 is not listed on IDEAS
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