IDEAS home Printed from https://ideas.repec.org/a/pes/ierequ/v6y2011i3p117-134.html
   My bibliography  Save this article

An Analysis Of Spanish Accidents In Automobile Insurance: The Use Of The Probit Model And Theoretical Potential Of Other Econometric Tools

Author

Listed:
  • Jose Antonio Ordaz

    (Universidad Pablo de Olavide, Spain)

  • Maria del Carmen Melgar

    (Universidad Pablo de Olavide, Spain)

  • M. Kazim Khan

    (Kent State University in Ohio, United States)

Abstract

Automobile insurance is one of the main pillars of the entire insurance industry in the developed economies. Knowing as much as possible about the factors related to the accidents is an essential issue for the insurance companies so that they may improve their levels of efficiency. Therefore, in this paper we focus on studying the most relevant variables that help explain the registration of claims in the automobile insurance sector. For this purpose, we fit a probit model specification using a database from a Spanish insurance company. Our research points out the significance of certain variables, such as the policyholders’ driving experience, their region of residence as well as their levels of insurance coverage, towards the likelihood of registering an insurance claim. However, probit analysis represents only one of the multiple perspectives which we can consider to examine the question of accidents and their reporting. Very briefly, we also discuss the utility of zero-inflated count data models to study the number of accidents declared by policyholders. Finally, we point out the possibilities that thinned models could offer for this type of research.

Suggested Citation

  • 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.
    • Handle: RePEc:pes:ierequ:v:6:y:2011:i:3:p:117-134
    DOI: 10.12775/EQUIL2011.024
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.12775/EQUIL2011.024
    Download Restriction: no
    File URL: https://libkey.io/10.12775/EQUIL2011.024?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. 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.
    3. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 112-134.
    4. 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.
    5. 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.
    6. 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.
    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.
    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. Marian Reiff & Erik Šoltés & Silvia Komara & Tatiana Šoltésová & Silvia Zelinová, 2022. "Segmentation and estimation of claim severity in motor third-party liability insurance through contrast analysis," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 17(3), pages 803-842, 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. 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.
    2. 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.
    3. 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.
    4. Jean Pinquet & Georges Dionne & Charles Vanasse & Mathieu Maurice, 2007. "Point-record incentives, asymmetric information and dynamic data," Working Papers hal-00243056, HAL.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. Dionne, Georges & Fombaron, Nathalie & Doherty, Neil, 2012. "Adverse selection in insurance contracting," Working Papers 12-8, HEC Montreal, Canada Research Chair in Risk Management.
    10. 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.
    11. Przemysław Jeziorski & Elena Krasnokutskaya & Olivia Ceccarini, 2019. "Skimming from the Bottom: Empirical Evidence of Adverse Selection When Poaching Customers," Marketing Science, INFORMS, vol. 38(4), pages 543-566, July.
    12. Feng Gao & Michael R. Powers & Jun Wang, 2017. "Decomposing Asymmetric Information in China's Automobile Insurance Market," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 84(4), pages 1269-1293, December.
    13. 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.
    14. Dionne, Georges & Vanasse, Charles, 1997. "Une évaluation empirique de la nouvelle tarification de l’assurance automobile (1992) au Québec," L'Actualité Economique, Société Canadienne de Science Economique, vol. 73(1), pages 47-80, mars-juin.
    15. Hanming Fang & Michael P. Keane & Dan Silverman, 2008. "Sources of Advantageous Selection: Evidence from the Medigap Insurance Market," Journal of Political Economy, University of Chicago Press, vol. 116(2), pages 303-350, April.
    16. 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.
    17. Georges Dionne & Pierre-Carl Michaud & Maki Dahchour, 2013. "Separating Moral Hazard From Adverse Selection And Learning In Automobile Insurance: Longitudinal Evidence From France," Journal of the European Economic Association, European Economic Association, vol. 11(4), pages 897-917, August.
    18. Hanming Fang & Zenan Wu, 2018. "Multidimensional private information, market structure, and insurance markets," RAND Journal of Economics, RAND Corporation, vol. 49(3), pages 751-787, September.
    19. 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.
    20. Alois Geyer & Daniela Kremslehner & Alexander Muermann, 2020. "Asymmetric Information in Automobile Insurance: Evidence From Driving Behavior," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 87(4), pages 969-995, December.

    More about this item

    Keywords

    Automobile insurance; claims; probit model; zero-inflated models; thinned models;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

    Statistics

    Access and download statistics

    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:6:y:2011:i:3:p:117-134. 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.