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Evidence of Asymmetric Information in the Automobile Insurance Market: Dichotomous Versus Multinomial Measurement of Insurance Coverage

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  • Hyojoung Kim
  • Doyoung Kim
  • Subin Im
  • James W. Hardin

Abstract

In the empirical analysis of information asymmetry in automobile insurance markets, prior research used a dichotomous measurement approach that induces excessive bundling in coverage measurements and sample selection biases. To improve on the conditional correlation method for testing information asymmetry, we propose a multinomial measurement approach that constructs coverage categories at ordered multinomial levels. With this approach, we find robust evidence of information asymmetry in both coverage area and coverage amount choices, which we could not find with the dichotomous measurement approach. It thus demonstrates the sensitivity of the empirical findings to the method used to measure insurance coverage. Copyright (c) The Journal of Risk and Insurance, 2009.

Suggested Citation

  • 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.
  • Handle: RePEc:bla:jrinsu:v:76:y:2009:i:2:p:343-366
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    References listed on IDEAS

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    Cited by:

    1. Georges Dionne, 2012. "The Empirical Measure of Information Problems with Emphasis on Insurance Fraud and Dynamic Data," Cahiers de recherche 1233, CIRPEE.
    2. 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.
    3. Hsu, Yung-Ching & Shiu, Yung-Ming & Chou, Pai-Lung & Chen, Yen-Ming J., 2015. "Vehicle insurance and the risk of road traffic accidents," Transportation Research Part A: Policy and Practice, Elsevier, vol. 74(C), pages 201-209.
    4. Paul Kofman & Gregory P. Nini, 2013. "Do Insurance Companies Possess an Informational Monopoly? Empirical Evidence From Auto Insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 80(4), pages 1001-1026, December.
    5. repec:mea:meawpa:12259 is not listed on IDEAS
    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. 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.
    8. Ciprian Matis & Eugenia Matis, 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.
    9. Renate Lange & Jörg Schiller & Petra Steinorth, 2015. "Demand and Selection Effects in Supplemental Health Insurance in Germany," SOEPpapers on Multidisciplinary Panel Data Research 757, DIW Berlin, The German Socio-Economic Panel (SOEP).
    10. Renate Lange & Jörg Schiller & Petra Steinorth, 2017. "Demand and Selection Effects in Supplemental Health Insurance in Germany," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 42(1), pages 5-30, January.
    11. repec:bla:jrinsu:v:84:y:2017:i:4:p:1269-1293 is not listed on IDEAS

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