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Insurance and Individual Incentives in Adaptive Contexts

W. Kip Viscusi

Abstract

Opportunities for individual learning in multi-period insurance contexts introduce fundamental economic aspects not present in conventional static models. Using a two-period model in which there are two states (accident and no accident), it is shown that more precise prior probability assessments lead to increased insurance coverage and reduced self-protection. These dynamic adverse incentive problems can be diminished by merit rating, which has a backwards influence on earlier actions. Self-protection and insurance purchases in the initial period respond in opposite fashion to changes in insurance pricesin the second period, the interest rate, and parameters of the prior probability assessment.