Farinha Luz, Vitor and Gottardi, Piero and Moreira, Humberto (2023) Risk Classification in Insurance Markets with Risk and Preference Heterogeneity. The Review of Economic Studies, 90 (6). pp. 3022-3082. DOI https://doi.org/10.1093/restud/rdad017
Farinha Luz, Vitor and Gottardi, Piero and Moreira, Humberto (2023) Risk Classification in Insurance Markets with Risk and Preference Heterogeneity. The Review of Economic Studies, 90 (6). pp. 3022-3082. DOI https://doi.org/10.1093/restud/rdad017
Farinha Luz, Vitor and Gottardi, Piero and Moreira, Humberto (2023) Risk Classification in Insurance Markets with Risk and Preference Heterogeneity. The Review of Economic Studies, 90 (6). pp. 3022-3082. DOI https://doi.org/10.1093/restud/rdad017
Abstract
This paper studies a competitive model of insurance markets in which consumers are privately informed about their risk and risk preferences. We provide a tractable characterization of equilibria, which depend non-trivially on consumers' type distribution, a desirable feature for policy analysis. The use of consumer characteristics for risk classification is modeled as the disclosure of a public informative signal. A novel monotonicity property of signals is shown to be necessary and sufficient for their release to be welfare improving for almost all consumer types. We also study the effect of changes to the risk distribution in the population as the result of demographic changes or policy interventions. We show that an increase in the risk distribution, according to the monotone likelihood ratio ordering of distribution, leads to lower utility for almost all consumer types. In contrast, the effect is ambiguous when considering the first order stochastic dominance ordering.
Item Type: | Article |
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Uncontrolled Keywords: | adverse selection; insurance; risk classification |
Divisions: | Faculty of Social Sciences Faculty of Social Sciences > Economics, Department of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 06 Feb 2023 10:05 |
Last Modified: | 30 Oct 2024 20:57 |
URI: | http://repository.essex.ac.uk/id/eprint/34176 |