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A review of recent theoretical and empirical analyses of asymmetric information in road safety and automobile insurance

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  • Dionne, Georges
  • Michaud, Pierre-Carl
  • Pinquet, Jean

Abstract

Road safety policies and automobile insurance contracts often use incentive mechanisms based on traffic violations and accidents to promote safe driving. Can these mechanisms improve road safety efficiently? Do they reduce asymmetric information between drivers and insurers and regulators? In other words, is there residual asymmetric information in observed distributions of accidents and infractions? We answer these questions in this article by reviewing recent theoretical and empirical results that rest on various data and methodologies. We present recent tests related to the identification of residual asymmetric information in road safety management and in automobile insurance contracting. We also propose a theoretical analysis of the foundations of point-record driver's licenses observed around the world.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:retrec:v:43:y:2013:i:1:p:85-97
    DOI: 10.1016/j.retrec.2012.12.006
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    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. 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.
    2. Dionne, Georges & Harrington, Scott, 2017. "Insurance and Insurance Markets," Working Papers 17-2, HEC Montreal, Canada Research Chair in Risk Management.
    3. Abay, Kibrom A. & Kahsay, Goytom Abraha, 2018. "Long-term effects of alternative deterrence policies: Panel data evidence from traffic punishments in Denmark," Transportation Research Part A: Policy and Practice, Elsevier, vol. 113(C), pages 1-19.
    4. 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.
    5. Dionne, Georges & Desjardins, Denise & Angers, Jean-François, 2021. "Road safety for fleets of vehicles," Working Papers 21-3, HEC Montreal, Canada Research Chair in Risk Management.
    6. Imen Karaa, 2018. "Moral Hazard and Learning in the Tunisian Automobile Insurance Market: New Evidence from Dynamic Data," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 43(3), pages 560-589, July.
    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. Kibrom A. Abay, 2018. "How Effective Are Non‐Monetary Instruments for Safe Driving? Panel Data Evidence on the Effect of the Demerit Point System in Denmark," Scandinavian Journal of Economics, Wiley Blackwell, vol. 120(3), pages 894-924, July.
    9. Georges Dionne & Ying Liu, 2021. "Effects of Insurance Incentives on Road Safety: Evidence from a Natural Experiment in China," Scandinavian Journal of Economics, Wiley Blackwell, vol. 123(2), pages 453-477, April.
    10. Yarmukhamedov, Sherzod, 2013. "Empirical analysis of moral hazard: a study of a vehicle insurance tax reform," Working papers in Transport Economics 2013:14, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
    11. Omid Ghaffarpasand & Mark Burke & Louisa K. Osei & Helen Ursell & Sam Chapman & Francis D. Pope, 2022. "Vehicle Telematics for Safer, Cleaner and More Sustainable Urban Transport: A Review," Sustainability, MDPI, vol. 14(24), pages 1-20, December.

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    More about this item

    Keywords

    Road safety; Point-record driver's license; Asymmetric information; Road safety management; Empirical test;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • L90 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - General
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

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