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“They do know what they are doing... at least most of them.†Asymmetric Information in the (private) Disability Insurance

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  • Spindler, Martin

    (Munich Center for the Economics of Aging (MEA))

Abstract

In this paper we analyze asymmetric information in the (private) disability insurance, which has not been analyzed before in the literature, but covers one of the most important risks faced by individuals in modern society, namely the loss of human capital. We show that there is asymmetric information, but the extent depends on the amount of coverage. Moreover, the option of choosing an annual adjustment of the insured sum has strong predictive power both for the occurrence of an accident and the chosen coverage, although it should be irrelevant from the point of theory. This result shows new ways to design contracts and variable selection for risk classification. In contrast to most previous studies, we also explicitly take into consideration unobserved heterogeneity by applying finite mixture models and so called ‘unused’ observables.

Suggested Citation

  • Spindler, Martin, 2013. "“They do know what they are doing... at least most of them.†Asymmetric Information in the (private) Disability Insurance," MEA discussion paper series 201209, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
  • Handle: RePEc:mea:meawpa:201209
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    References listed on IDEAS

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    More about this item

    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • 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

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