Did Medicaid/SCHIP Crowd-Out Private Insurance Coverage among U.S. Low-Income Children?: A Multilevel Approach
- Presenter:
Chair: Michael Grossman; Discussant: TBA Mon June 5, 2006 10:45-12:15 Room 309
Authors: Adetokunbo Oluwole (axo129@psu.edu) and Dennis Shea (dgs4@psu.edu)
Rationale: The implementation of the Medicaid/SCHIP, which began shortly after the major welfare reform of 1996, represented a more recent effort to expand health insurance among lower income populations in the U.S. Previous studies have shown that earlier Medicaid expansions significantly increased public program participation and have reduced the number of uninsured individuals. However, empirical evidence indicates that the reduction in the number of uninsured has been offset by declines in private insurance coverage. Because the Medicaid/SCHIP expansions targeted a different population than earlier expansions and took a different form, a detailed study of these more recent efforts is needed.
Objectives: The objective of this paper is to measure the extent of crowd-out of private insurance coverage, among American low-income children, that is attributable to Medicaid/SCHIP expansion.
Methodology: We combine event history analysis and multilevel modeling techniques to analyze data from the 1996 panel of the Survey of Income and Program Participation (SIPP), which covers the period 1996 to 2000. The combined approach will estimate discrete-time logistic regression models. Events to be modeled are the following transitions in insurance coverage: (1) private coverage to Medicaid; (2) private to uninsured; (3) uninsured to private coverage; (4) uninsured to Medicaid; (5) Medicaid to private; and (6) Medicaid to uninsured. In addition to addressing the question of whether or not children have particular types of health insurance coverage, event history analysis also incorporates the timing of such coverage and transitions. Multilevel modeling accounts for cross-state variations in coverage transition rates as well as corrects for within-group correlation and non-constant error terms. State-level data from other sources such as the Area Resource Files, Regional Economic Information Services, and the Centers for Medicare and Medicaid Services will be appended to the SIPP dataset. The sample for the study consists of unmarried children nineteen or younger, and living in families with incomes at or below 300 percent of the federal poverty level (FPL). The analytic sample is expected to comprise about 8,000 low-income children.
Expected Results and Relevance: This study will provide some insight into how health insurance coverage policies might be directed to have maximum positive effect on the targeted (uninsured) population. This is especially important if there is some evidence of crowd-out of private insurance. Preliminary analyses show that the conditional probability of transition from private insurance to Medicaid/SCHIP started to increase shortly after states began to implement their Medicaid/SCHIP expansion programs.
Conclusions: Given the controversial estimates of crowd-out in previous studies, this study’s use of combined techniques of event history and multilevel modeling will provide more accurate and updated estimates using the 1996 panel of the SIPP dataset, which no other study has analyzed. In addition to personal and family characteristics, the models estimated in this study also control for some state- and program-specific factors, which many previous studies failed to account for.
