Learning and Risk Management Decisions

Abstract

Due to the lack of descriptive information about the effectiveness of risk management activities, decision-makers often have to rely on (their own) prior experience with these investments. Thus, we propose a novel, feedback-based approach to examine risk management decisions. We simulate individuals’ decisions over 50 time periods and analyze how distributional properties of different risk management instruments influence subjects’ propensity to invest in self-insurance or self-protection. Our results show that subjects act more risk averse over time because self-insurance take-up rates increase when learners gain more experience. Individuals’ risk management decisions are price-sensitive but we find only limited evidence for a complementary relationship between both risk management options. Our findings provide an alternative explanation for the low demand for risk management investments against low probability risks and can be used to predict developments in new insurance markets with inexperienced policyholders.