The Impact of the Eligibility Threshold of a French Means-Tested Health Insurance Programme on Doctor Visits: A Regression Discontinuity Analysis.
This paper assesses the impact of eligibility for a free means-tested complementary health insurance plan, called Couverture Maladie Universelle Complémentaire (CMUC), on doctor visits. We use information on the selection rule to qualify for the plan to identify the effect of eligibility and adopt a regression discontinuity approach. Our sample consists of low-income individuals enrolled in the Health Insurance Fund and recipients of social benefits from the Family Allowance Fund of an urban area in Northern France. Our findings do not show significant impacts of the CMUC threshold on the number of doctor visits within the full sample. Among the subsample of adults under 30 years old, however, eligible individuals are more likely to see a specialist and have, on average, significantly more specialist visits than non-eligible individuals. This specific impact of the CMUC cut-off point among young adults may be explained by the fact that young adults are less likely to be covered by a complementary health insurance plan when they are not recipients of the CMUC plan. © 2017 The Authors. Health Economics Published by John Wiley & Sons, Ltd.
PSL, Université Paris Dauphine, LEDa-LEGOS, Paris, France.|European Commission, Joint Research Centre, Ispra (VA), Italy.
Sophie
0000-0002-9115-304X
S
Guthmuller
PSL, Université Paris Dauphine, LEDa-LEGOS, Paris, France.|Université de Bordeaux, Inserm U1219 Bordeaux Population Health, Bordeaux, France.
Jérôme
J
Wittwer
D000328:Adult; D004608:Eligibility Determination / Q000191:economics*; D005260:Female; D005602:France; D006293:Health Promotion; D006297:Health Services Accessibility / Q000191:economics*; D006801:Humans; D007348:Insurance, Health / Q000191:economics*; D008297:Male; D009819:Office Visits / Q000191:economics*; D011203:Poverty / Q000191:economics; D012044:Regression Analysis
France; doctor visits; means-tested social programme; public health insurance; regression discontinuity design