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

Recurso electrónico / electronic resource
Registro MARC
Tag12Valor
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003  MAP
005  20180425162234.0
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040  ‎$a‎MAP‎$b‎spa‎$d‎MAP
084  ‎$a‎219
100  ‎$0‎MAPA20180004483‎$a‎Dardanoni, Valentino
24510‎$a‎Testing for asymmetric information in insurance markets‎$b‎: a multivariate ordered regression approach‎$c‎Valentino Dardanoni, Antonio Forcina, Paolo Li Donni
520  ‎$a‎The 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
650 4‎$0‎MAPA20080586294‎$a‎Mercado de seguros
650 4‎$0‎MAPA20080606695‎$a‎Información asimétrica
650 4‎$0‎MAPA20080573867‎$a‎Seguro de salud
650 4‎$0‎MAPA20080567118‎$a‎Reclamaciones
650 4‎$0‎MAPA20080553630‎$a‎Coberturas
650 4‎$0‎MAPA20080590567‎$a‎Empresas de seguros
650 4‎$0‎MAPA20080616007‎$a‎Aplicaciones informáticas
650 4‎$0‎MAPA20080539948‎$a‎Tests
651 1‎$0‎MAPA20080638337‎$a‎Estados Unidos
7001 ‎$0‎MAPA20180005145‎$a‎Forcina, Antonio
7001 ‎$0‎MAPA20180005152‎$a‎Donni, Paolo Li
7730 ‎$w‎MAP20077000727‎$t‎The Journal of risk and insurance‎$d‎Nueva York : The American Risk and Insurance Association, 1964-‎$x‎0022-4367‎$g‎01/03/2018 Volumen 85 Número 1 - marzo 2018 , p. 107-125