*Names in bold indicate Presenter
This paper examines the effects of public premium levels on insurance coverage of children, using Medical Expenditure Panel Survey (MEPS) household survey data from 1996 to 2010 and detailed information on state-by-state CHIP/Medicaid Waiver program eligibility rules and premium levels from 1996 to 2010. The sample consists of children ages 18 or younger with family incomes above 100% of the Federal Poverty Level (FPL) who also meet the eligibility requirements for Medicaid or CHIP coverage. The sample has 51,701 observations, and approximately 35% of them are eligible with premiums. Children with family income below 100% of FPL are excluded because they automatically qualify for Medicaid without premiums. We use AHRQ’s KIDSIM model to simulate eligibility for Medicaid and CHIP and child-specific public premiums. The KIDSIM model uses not only the state-specific income thresholds for the programs but also detailed income disregards, asset limits, family composition rules, and immigration rules (Hudson & Selden, 2007). . Following Kenney et al. (2007), we impute cost of private coverage (private premium) based on the work status and firm size of child’s parents by using MEPS Insurance Component (IC) information on average family contribution toward family coverage by state, firm size, and year. We employ multinomial logit models with insurance coverage types (public, private, or uninsured) as the dependent variable. Independent variables include public premiums, private premiums, state program characteristics such as joint Medicaid/CHIP application, face-to-face interview, paper documentation of income, and waiting period, and a large number of child, parent, and family characteristics. We also use state fixed effects to account for time-invariant differences across the states and year effects to account for overall trends The effect of public premiums on enrollment are identified by cross-state variations in premiums at a given time, within-state variation in premiums over time and also by differences in the effective premium per child by family size and family income relative to poverty.