Testing for asymmetric information in insurance markets : a multivariate ordered regression approach

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      <subfield code="a">Testing for asymmetric information in insurance markets</subfield>
      <subfield code="b">: a multivariate ordered regression approach</subfield>
      <subfield code="c">Valentino Dardanoni, Antonio Forcina, Paolo Li Donni</subfield>
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      <subfield code="a">The positive correlation (PC) test is the standard procedure used in the empirical literature to detect the existence of asymmetric information in insurance markets. This article describes a new tool to implement an extension of the PC test based on a new family of regression models, the multivariate ordered logit, designed to study how the joint distribution of two or more ordered response variables depends on exogenous covariates. We present an application of our proposed extension of the PC test to the Medigap health insurance market in the United States. Results reveal that the riskcoverage association is not homogeneous across coverage and risk categories, and depends on individual socioeconomic and risk preference characteristics</subfield>
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      <subfield code="t">The Journal of risk and insurance</subfield>
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      <subfield code="g">01/03/2018 Volumen 85 Número 1 - marzo 2018 , p. 107-125</subfield>
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