SCHIP premiums, enrollment, and expenditures: a two state, competing risk analysis.
Faced with state budget troubles, policymakers may introduce or increase State Children's Health Insurance Program (SCHIP) premiums for children in the highest program income eligibility categories. In this paper we compare the responses of SCHIP recipients in a state (Kentucky) that introduced SCHIP premiums for the first time at the end of 2003 with the responses of recipients in a state (Georgia) that increased existing SCHIP premiums in mid-2004. We start with a theoretical examination of how these different policies create different changes to family budget constraints and produce somewhat different financial incentives for recipients. Next we empirically model the impact of these policies using a competing risk approach to differentiate exits due to transfers to other eligibility categories of public coverage from exiting the public health insurance system. In both states we find a short-run increase in the likelihood that children transfer to lower- income eligibility/lower-premium categories of SCHIP. We also find a short-run increase in the rate at which children transfer from SCHIP to Medicaid in Kentucky, which is consistent with our theoretical model. These findings have important financial implications for state budgets, as the matching rates and premium levels are different for different eligibility categories of public coverage.
Marton
James
J
Department of Economics, Andrew Young School of Policy Studies and Georgia Health Policy Center, Georgia State University, Atlanta, GA 30302, USA. marton@gsu.edu
Ketsche
Patricia G
PG
Zhou
Mei
M
D000293:Adolescent; D002017:Budgets; D002648:Child; D002662:Child Health Services / Q000191:economics* / Q000706:statistics & numerical data; D002675:Child, Preschool; D036262:Empirical Research; D005260:Female; D005845:Georgia; D005102:Health Expenditures / Q000706:statistics & numerical data*; D006291:Health Policy; D006801:Humans; D007223:Infant; D019458:Insurance Coverage / Q000191:economics* / Q000706:statistics & numerical data; D007348:Insurance, Health / Q000191:economics* / Q000706:statistics & numerical data; D007629:Kentucky; D008297:Male; D008484:Medicaid / Q000191:economics / Q000706:statistics & numerical data; D008962:Models, Theoretical; D018570:Risk Assessment; D013221:State Health Plans / Q000191:economics* / Q000706:statistics & numerical data; D014481:United States