This analysis has several limitations that must be considered in evaluating the results and in conceiving future analyses that build on the current results. First, as shown in Appendix SA2
, the SIPP offers lower estimates of medical expenditures when compared with the more specialized Medical Expenditure Panel Survey (MEPS). Fortunately, differences between the two datasets appear relatively stable over time. The SIPP remains an appropriate dataset for the current analyses because it allows for good identification of income and labor force participation, and because it has family premium payments for all types of health coverage. Future research might replicate these results using the MEPS.
Second, income eligibility thresholds are only one dimension of SCHIP policy. Expanded income eligibility may also proxy for related policies, such as expanded outreach or streamlined administrative processes conducive to enrollment. As noted by Dubay and colleagues (2007)
, SCHIP expansion was accompanied by a variety of measures designed to streamline Medicaid enrollment. We suspect that there are multiple avenues of SCHIP outreach and enrollment. Income-eligible uninsured children who utilize medical services may receive help to enroll by professionals associated with medical providers. Parents of children who utilize medical services also face especially strong incentives to navigate the process of SCHIP enrollment. See Appendix SA2
for a more detailed discussion of this.
Third, we would have liked to consider model variations with child fixed effects. Unfortunately, the annualized form of the medical expenditures data makes this impossible, because it does not allow enough observations within individuals for such an analysis.
Fourth, an analysis such as ours may be sensitive to specification and sample selection. Because of this, we estimated a variety of regression specifications to address the robustness of our findings. As discussed in Appendix SA2
, these regressions did not alter our main result.
Fifth, reduced out-of-pocket and premium expenditures provide only a simple metric to capture a much more complex set of economic benefits and costs that come from shifts in insurance coverage. For example, we do not capture some important benefits, such as the impact on wages or reduced costs to employers that stem from reduced private coverage.
Finally, the present analysis does not unpack the insurance status of other household members, including both siblings and parents. For example, parents may enroll their children onto SCHIP and keep employer-based dependent coverage. Alternatively, parents may choose to go uninsured while their children are enrolled on public coverage. Still other parents, once they have enrolled children on public health insurance, may choose to shift their own coverage from private to public sources. We believe that understanding the broader dynamics of family health insurance changes among families with children who transition will require a complicated analysis that goes beyond the scope of the current study. However, we hope to address these questions in future work.
With due allowance for study limitations, our paper suggests several insights for policy and practice. Between 1998 and 2003, public health insurance was expanded to include higher income groups than in previous years. Rates of private health insurance coverage for these moderate-income groups were somewhat higher, leading to greater possibilities of private-to-public transitions (Congressional Budget Office 2007
Given the limitations in robustly identifying transitions that constitute crowd-out in nationally representative datasets, we focus instead on the broader population of children making the transition from private-to-public health coverage. A key contribution of our study is to develop the first descriptive, nationally representative understanding of who makes these transitions, and to estimate what the effects of such a transition might be for affected families. Our statistical modeling suggests that children in families who transition from private to public health coverage are a relatively vulnerable group. They are more likely to be nonwhite, low income (although well-above poverty), and are more likely to be in relatively poor health. It is worth noting that the characteristics of children in transitioning families change somewhat during our study period. For example, the mean family income of this group rises gradually from about 190 percent of poverty in the late 1990s, to above 210 percent of poverty in 2002 and 2003.
Our instrumental variable results suggest that private-to-public transitions may provide large financial benefits to affected families through reduced medical expenses. We estimate such a transition is associated with a reduction in family premium costs of U.S.$1,300 for 1998–2003 of U.S.$1,300, and a reduction in child out-of-pocket costs of U.S.$166 for the period 2001–2003.
To put our point estimates in perspective, we compared them to two measures: (1) the difference in employer premiums for single versus family coverage, using the MEPS (Insurance Component). For the period 1998–2003, this figure, adjusted to year-2000 dollars, ranges from U.S.$1,055 in 1998 to U.S.$1,569 in 2003. (2) Medicaid payments per capita for children, made available by the Kaiser Commission on Medicaid and the Uninsured for the years 2000–2003. This ranged from an inflation-adjusted U.S.$1,227 in 2000 to U.S.$1,373 in 2003. These benchmarks are consistent with our point estimates and with the likely causal pathways for changes in family coverage sources discussed above.
For a family of three with a U.S.$27,000 income in 2003, our estimated reduction in medical costs is roughly comparable to the value of the federal Earned Income Tax Credit. However, rather than targeting families according to earned income, this transfer disproportionately targets families with high medical expenditures relative to their income. For the marginally affected transition family, SCHIP bears some analogy to Medicaid's medically needy eligibility program in reaching individuals with high medical expenses.
These findings have policy implications. During the SCHIP reauthorization debate, policy makers pointed out that many lower-income children who were already eligible were not enrolled in state SCHIP programs, and many of these children remained uninsured (Congressional Budget Office 2007
). This caused some concern that states had been too quick to expand coverage to higher-income families before uninsured children in lower-income families were covered (The Kaiser Commission on Medicaid and the Uninsured 2007
). Several studies, however, highlight the financial burdens faced by middle-income families bearing substantial medical expenses associated with care for a child in poor health. For this small but vulnerable population of families, SCHIP may provide important and well-targeted social benefits (e.g., Shattuck and Parish 2008
). Our findings suggest that transitions from private-to-public health insurance result in a substantial cash transfer, and such a transfer may serve important social goals, especially when the transfers reach low- and middle-income families with sick children.
This analysis starts the process of assessing how well the health care needs of children are being met in an increasingly mixed public–private system. It further leads to many more questions worthy of further research. To what extent are these private-to-public transitions temporary versus long-term? To what extent do children make transitions in the other direction, from public-to-private coverage, and what are the characteristics of this group?
Perhaps most important, further research should look at outcomes related to the actual experience of care. Do children who transition from private-to-public coverage experience any noticeable effects on service utilization, such as changes in the prevalence of primary care visits or dental care visits? What about changes in the nonmedical consumption of transitioning families (Leininger et al. 2010)? These questions are not only important for understanding the situation of children but will also likely inform changing policy for the broader nonelderly population, for which the health care system of the future holds much greater integration of public and private coverage.