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An Insurance Market Simulation With Both Adverse and Advantageous Selection
Author(s) -
Chen Leon,
Jaiprakash Puneet
Publication year - 2017
Publication title -
risk management and insurance review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.386
H-Index - 16
eISSN - 1540-6296
pISSN - 1098-1616
DOI - 10.1111/rmir.12070
Subject(s) - adverse selection , risk aversion (psychology) , actuarial science , selection (genetic algorithm) , game theory , economics , expected utility hypothesis , microeconomics , computer science , financial economics , artificial intelligence
Abstract The theory of adverse selection predicts that high‐risk individuals are more likely to buy insurance than low‐risk individuals if asymmetric information regarding individuals’ risk type is present in the market. The theory of advantageous selection predicts the opposite—a negative relationship between insurance coverage and risk type can be obtained when hidden knowledge in other dimensions (e.g., the degree of risk aversion) is present in addition to the risk type. Using the heterogeneity of insurance buyers in either risk type or risk aversion, we first introduce a classroom‐based insurance market simulation game to show that adverse selection and advantageous selection can coexist. We then explain the underlying concepts using two methods: a mathematical framework based on expected utility theory and an empirical framework based on the results of the game itself. The game is easy to implement, reinforces textbook concepts by providing students a hands‐on experience, and supplements current textbooks by bringing their content up to date with current research.