The Efficiency of Voluntary Risk Classification in Insurance Markets

It has been established that categorical discrimination based on observable characteristics such as gender, age, or ethnicity enhances efficiency. We consider a different form of risk classification when there exists a costless yet imperfectly informative test of risk type, with the test outcome unknown to the agents ex ante. We show that a voluntary risk classification in which agents are given the option to take the test always increases efficiency compared with no risk classification. Moreover, voluntary risk classification also Pareto dominates a regime of compulsory risk classification in which all agents are required to take the test.

This is the peer reviewed version of the following article: [Crocker, K.J., and Zhu, N. (2020). The efficiency of voluntary risk classification in insurance markets. Journal of Risk and Insurance 88, 325–350.], which has been published in final form at https://doi.org/10.1111/jori.12326. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions: https://authorservices.wiley.com/author-resources/Journal-Authors/licensing/self-archiving.html#3.

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Work Title The Efficiency of Voluntary Risk Classification in Insurance Markets
Access
Open Access
Creators
  1. Keith J. Crocker
  2. Nan Zhu
License In Copyright (Rights Reserved)
Work Type Article
Publisher
  1. Wiley
Publication Date September 11, 2020
Publisher Identifier (DOI)
  1. 10.1111/jori.12326
Source
  1. Journal of Risk and Insurance
Deposited January 13, 2022

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