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Statistical Tests of the Demand for Insurance: An “All or Nothing” Decision

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  • Anne Corcos
  • François Pannequin
  • Claude Montmarquette

Abstract

Several theoretical models and empirical results stress an unexpected all-or-nothing insurance behavior. Using experimental data of Corcos et al. (2017), who developed an extended version of Mossin’s traditional theoretical demand for insurance and provided non-parametric tests, this paper presents descriptive statistical analyses and econometric tests studying whether these experimental data comply with the all-or-nothing hypothesis. Our findings support this assumption for both risk averters and risk lovers. When this all-or-nothing behavior fails to meet Expected Utility predictions, it highlights a lack of responsiveness of individuals to insurance prices. When facing a more-than-actuarial insurance price, risk averters keep buying full insurance rather than partial insurance. A zero fixed cost holds risk lovers in the insurance market where they choose full instead of waive insurance. The bimodal nature of decisions might create an opportunity for the authority for driving people to enter the insurance market where they then buy full insurance.

Suggested Citation

  • Anne Corcos & François Pannequin & Claude Montmarquette, 2017. "Statistical Tests of the Demand for Insurance: An “All or Nothing” Decision," CIRANO Working Papers 2017s-07, CIRANO.
  • Handle: RePEc:cir:cirwor:2017s-07
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    File URL: https://cirano.qc.ca/files/publications/2017s-07.pdf
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    References listed on IDEAS

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    More about this item

    Keywords

    demand for insurance; experimental study; all or nothing decision parametric tests;
    All these keywords.

    JEL classification:

    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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