Health Insurance for “Humans”: Information Frictions, Plan Choice, and Consumer Welfare

TLDR

Traditional models of insurance choice assume fully informed rational consumers, yet in practice plan selection is complex and often made without full information. The study aims to identify risk preferences, information frictions, and hassle costs by linking administrative health plan data with consumer survey information. The authors use administrative data on plan choices and claims together with survey data on consumer information to estimate these parameters and analyze counterfactual allocations. The estimated friction measures significantly predict plan choices and alter risk preference estimates, underscoring their importance for welfare analysis. JEL codes: D81, D83, G22, I13.

Abstract

Traditional models of insurance choice are predicated on fully informed and rational consumers protecting themselves from exposure to financial risk. In practice, choosing an insurance plan is a complicated decision often made without full information. In this paper we combine new administrative data on health plan choices and claims with unique survey data on consumer information to identify risk preferences, information frictions, and hassle costs. Our additional friction measures are important predictors of choices and meaningfully impact risk preference estimates. We study the implications of counterfactual insurance allocations to illustrate the importance of distinguishing between these micro-foundations for welfare analysis. (JEL D81, D8 3, G22, I13)