Estimating the Tradeoff between Risk Protection and Moral Hazard with a Nonlinear Budget Set Model of Health Insurance

51 Pages Posted: 25 May 2012

See all articles by Amanda Kowalski

Amanda Kowalski

University of Michigan at Ann Arbor - Department of Economics

Date Written: May 2012

Abstract

Insurance induces a well-known tradeoff between the welfare gains from risk protection and the welfare losses from moral hazard. Empirical work traditionally estimates each side of the tradeoff separately, potentially yielding mutually inconsistent results. I develop a nonlinear budget set model of health insurance that allows for the calculation of both sides of the tradeoff simultaneously, allowing for a relationship between moral hazard and risk protection. An important feature of this model is that it considers nonlinearities in the consumer budget set that arise from deductibles, coinsurance rates, and stoplosses that alter moral hazard as well as risk protection relative to no insurance. I illustrate the properties of my model by estimating it using data on employer sponsored health insurance from a large firm. Within my empirical context, the average deadweight losses from moral hazard substantially outweigh the average welfare gains from risk protection. However, the welfare impact of moral hazard and risk protection are both small relative to transfers from the government through the tax preference for employer sponsored health insurance and transfers from some agents to other agents through a common premium.

Suggested Citation

Kowalski, Amanda, Estimating the Tradeoff between Risk Protection and Moral Hazard with a Nonlinear Budget Set Model of Health Insurance (May 2012). NBER Working Paper No. w18108, Available at SSRN: https://ssrn.com/abstract=2066405

Amanda Kowalski (Contact Author)

University of Michigan at Ann Arbor - Department of Economics ( email )

Ann Arbor, MI
United States

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
8
Abstract Views
334
PlumX Metrics