title: The effects of state policy design features on take-up and crowd-out rates for the State Children's Health Insurance Program.
abstract: We evaluate the effects of state policy design features on SCHIP take-up rates and on the degree to which SCHIP benefits crowd out private benefits. The results indicate overall program take-up rates of approximately 10 percent. However, there is considerable heterogeneity across states, suggesting a potential role of inter-state variation in policy design. We find that several design mechanisms have significant and substantial positive effects on take-up. For example, eliminating asset tests, offering continuous coverage, simplifying the application and renewal processes, and extending benefits to parents all have sizable and positive effects on take-up rates. Mandatory waiting periods, on the other hand, consistently reduce take-up rates. In all, inter-state differences in outreach and anti-crowd-out efforts explain roughly one-quarter of the cross-state variation in take-up rates. Concerning the crowding out of private health insurance benefits, we find that between one-quarter and one-third of the increase in public health insurance coverage for SCHIP-eligible children is offset by a decline in private health coverage. We find little evidence that the policy-induced variation in take-up is associated with a significant degree of crowd out, and no evidence that the negative effect on private coverage caused by state policy choices is any greater than the overall crowding-out effect. This suggests that states are not augmenting take-up rates by enrolling children that are relatively more likely to have private health insurance benefits.
authors.affiliation: Department of Economics, San Diego State University, USA.
authors.forename: Cynthia
authors.initials: C
authors.lastname: Bansak
authors.forename: Steven
authors.initials: S
authors.lastname: Raphael
mesh_terms: D002648:Child; D002662:Child Health Services / Q000706:statistics & numerical data* / Q000639:trends; D003159:Community-Institutional Relations; D004608:Eligibility Determination; D005544:Forecasting; D006291:Health Policy; D006801:Humans; D019458:Insurance Coverage / Q000706:statistics & numerical data* / Q000639:trends; D007348:Insurance, Health / Q000706:statistics & numerical data* / Q000639:trends; D008483:Medical Assistance / Q000706:statistics & numerical data* / Q000639:trends; D017149:Private Sector; D017150:Public Sector; D013219:State Government; D013997:Time Factors; D014481:United States