IDEAS home Printed from https://ideas.repec.org/a/pes/ierequ/v5y2010i2p181-194.html
   My bibliography  Save this article

The Utility Of Zero-Inflated Models In The Estimation Of The Number Of Accidents In The Automobile Insurance Industry

Author

Listed:
  • Maria del Carmen Melgar

    (Universidad Pablo de Olavide)

  • Jose Antonio Ordaz

    (Universidad Pablo de Olavide)

Abstract

The main purpose of the present paper is to provide an econometric model which estimates the number of automobile accidents that policyholders declare to their insurance companies, pointing out those variables that are significant in this process. Our empirical analysis is based on the data supplied by a private insurance company that operates in Spain, and on the zero-inflated count data models as methodology. We find a positive association between the levels of coverage and the accident rates, suggesting the existence of problems related to adverse selection and moral hazard. This result is one of the most important conclusions of our work and confirms the theoretical aspects pointed up by other empirical studies in the literature. Additionally, estimating the number of policyholders that suffered any accident but not declared, and how many these non-declared accidents are, could be very useful information for insurers to evaluate their risk planning. Our model attempts to reach this target as well.

Suggested Citation

  • Maria del Carmen Melgar & Jose Antonio Ordaz, 2010. "The Utility Of Zero-Inflated Models In The Estimation Of The Number Of Accidents In The Automobile Insurance Industry," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 5(2), pages 181-194, December.
    • Handle: RePEc:pes:ierequ:v:5:y:2010:i:2:p:181-194
    DOI: 10.12775/EQUIL.2010.034
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.12775/EQUIL.2010.034
    Download Restriction: no
    File URL: https://libkey.io/10.12775/EQUIL.2010.034?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Puelz, Robert & Snow, Arthur, 1994. "Evidence on Adverse Selection: Equilibrium Signaling and Cross-Subsidization in the Insurance Market," Journal of Political Economy, University of Chicago Press, vol. 102(2), pages 236-257, April.
    2. G. Dionne & C. Gouriéroux & C. Vanasse, 1998. "Evidence of adverse selection in automobile insurance markets," THEMA Working Papers 98-22, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    3. 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.
    4. Boyer, Marcel & Dionne, Georges, 1989. "An Empirical Analysis of Moral Hazard and Experience Rating," The Review of Economics and Statistics, MIT Press, vol. 71(1), pages 128-134, February.
    5. Chiappori, Pierre-Andre & Salanie, Bernard, 1997. "Empirical contract theory: The case of insurance data," European Economic Review, Elsevier, vol. 41(3-5), pages 943-950, April.
    6. Didier Richaudeau, 1999. "Automobile Insurance Contracts and Risk of Accident: An Empirical Test Using French Individual Data," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 24(1), pages 97-114, June.
    7. Alma Cohen, 2005. "Asymmetric Information and Learning: Evidence from the Automobile Insurance Market," The Review of Economics and Statistics, MIT Press, vol. 87(2), pages 197-207, May.
    8. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-333, March.
    9. Pierre-Andre Chiappori & Bernard Salanie, 2000. "Testing for Asymmetric Information in Insurance Markets," Journal of Political Economy, University of Chicago Press, vol. 108(1), pages 56-78, February.
    10. Martin Ridout & John Hinde & Clarice G. B. Demétrio, 2001. "A Score Test for Testing a Zero‐Inflated Poisson Regression Model Against Zero‐Inflated Negative Binomial Alternatives," Biometrics, The International Biometric Society, vol. 57(1), pages 219-223, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jose Antonio Ordaz & Maria del Carmen Melgar & M. Kazim Khan, 2011. "An Analysis Of Spanish Accidents In Automobile Insurance: The Use Of The Probit Model And Theoretical Potential Of Other Econometric Tools," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 6(3), pages 117-134, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hyojoung Kim & Doyoung Kim & Subin Im & James W. Hardin, 2009. "Evidence of Asymmetric Information in the Automobile Insurance Market: Dichotomous Versus Multinomial Measurement of Insurance Coverage," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 76(2), pages 343-366, June.
    2. Jose Antonio Ordaz & Maria del Carmen Melgar & M. Kazim Khan, 2010. "Use and Extension of Count Data Models in the Determination of Relevant Factors for Claims in the Automobile Insurance Sector," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 119-138.
    3. Pierre-André Chiappori & Bernard Salanié, 2002. "Testing Contract Theory : A Survey of Some Recent Work," Working Papers 2002-11, Center for Research in Economics and Statistics.
    4. Dionne, Georges & Michaud, Pierre-Carl & Pinquet, Jean, 2013. "A review of recent theoretical and empirical analyses of asymmetric information in road safety and automobile insurance," Research in Transportation Economics, Elsevier, vol. 43(1), pages 85-97.
    5. Alma Cohen & Peter Siegelman, 2010. "Testing for Adverse Selection in Insurance Markets," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 77(1), pages 39-84, March.
    6. Dionne, Georges & Fombaron, Nathalie & Doherty, Neil, 2012. "Adverse selection in insurance contracting," Working Papers 12-8, HEC Montreal, Canada Research Chair in Risk Management.
    7. Dionne, Georges, 2012. "The empirical measure of information problems with emphasis on insurance fraud and dynamic data," Working Papers 12-10, HEC Montreal, Canada Research Chair in Risk Management.
    8. Dionne, G. & Doherty, N., 1991. "Adverse Selection In Insurance Markets: A Selective Survey," Cahiers de recherche 9105, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    9. Dionne, Georges, 1998. "La mesure empirique des problèmes d’information," L'Actualité Economique, Société Canadienne de Science Economique, vol. 74(4), pages 585-606, décembre.
    10. Dahchour, Maki & Dionne, Georges, 2002. "Pricing of Automobile Insurance Under Asymmetric Information: a Study on Panel Data," Working Papers 01-6, HEC Montreal, Canada Research Chair in Risk Management.
    11. María Del Carmen Melgar & José Antonio Ordaz & Flor María Guerrero, 2006. "Une étude économétrique du nombre d'accidents dans le secteur de l'assurance automobile," Brussels Economic Review, ULB -- Universite Libre de Bruxelles, vol. 49(2), pages 169-183.
    12. GÓMEZ GARCÍA, J.Mª & PELÁEZ FERMOSO, F.J. & y GARCÍA GONZÁLEZ, A., 2005. "Repercusiones del envejecimiento demográfico sobre el sistema público de pensiones en Castilla y León," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 23, pages 235-253, Abril.
    13. Jose Antonio Ordaz & Maria del Carmen Melgar & M. Kazim Khan, 2011. "An Analysis Of Spanish Accidents In Automobile Insurance: The Use Of The Probit Model And Theoretical Potential Of Other Econometric Tools," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 6(3), pages 117-134, September.
    14. Jean Pinquet & Georges Dionne & Charles Vanasse & Mathieu Maurice, 2007. "Point-record incentives, asymmetric information and dynamic data," Working Papers hal-00243056, HAL.
    15. repec:mea:meawpa:12259 is not listed on IDEAS
    16. Shi, Peng & Valdez, Emiliano A., 2011. "A copula approach to test asymmetric information with applications to predictive modeling," Insurance: Mathematics and Economics, Elsevier, vol. 49(2), pages 226-239, September.
    17. Ciprian MatiÅŸ & Eugenia MatiÅŸ, 2013. "Asymmetric Information In Insurance Field: Some General Considerations," Annales Universitatis Apulensis Series Oeconomica, Faculty of Sciences, "1 Decembrie 1918" University, Alba Iulia, vol. 1(15), pages 1-17.
    18. Martin Spindler & Joachim Winter & Steffen Hagmayer, 2014. "Asymmetric Information in the Market for Automobile Insurance: Evidence From Germany," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 81(4), pages 781-801, December.
    19. Martin Eling & Ruo Jia & Yi Yao, 2017. "Between-Group Adverse Selection: Evidence From Group Critical Illness Insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 84(2), pages 771-809, June.
    20. Dionne, Georges, 2000. "The Empirical Measure of Information Problems with Emphasis on Insurance Fraud," Working Papers 00-4, HEC Montreal, Canada Research Chair in Risk Management.
    21. Bo Qu & Li Wei & Ping Wei, 2018. "An Empirical Investigation of Asymmetric Information in China’s Automobile Insurance Market," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 43(3), pages 520-538, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pes:ierequ:v:5:y:2010:i:2:p:181-194. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Adam P. Balcerzak (email available below). General contact details of provider: https://edirc.repec.org/data/ibgtopl.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.