Using RD design to understand heterogeneity in health insurance crowd-out

J Health Econ. 2013 May;32(3):599-611. doi: 10.1016/j.jhealeco.2013.03.002. Epub 2013 Mar 21.

Abstract

Crowd-out, the switching from private to public insurance, is often found, but estimates are rarely consistent with prior measurements. Cutler and Gruber (1996) found crowd-out in up to half of the newly eligible children, while Card and Shore-Sheppard (2004) found almost none. This paper exploits many regression discontinuity (RD) designs to estimate heterogeneous effects of public insurance eligibility. Crowd-out and its impact on spending and utilization is documented across the income spectrum, but effects are smaller at higher income levels. These differences vary by state and correspond to changes in the reimbursement rates of public insurance plans.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Child
  • Child, Preschool
  • Eligibility Determination / statistics & numerical data*
  • Female
  • Health Expenditures / statistics & numerical data
  • Humans
  • Income / statistics & numerical data
  • Infant
  • Insurance, Health / economics
  • Insurance, Health / statistics & numerical data*
  • Male
  • Models, Statistical
  • Private Sector / economics
  • Private Sector / statistics & numerical data*
  • Public Sector / economics
  • Public Sector / statistics & numerical data*
  • Regression Analysis
  • Reimbursement Mechanisms
  • United States