We highlight three caveats that apply to the tables presented in Part II and one additional caveat that applies to further use of the reweighted CPS database. The first three are the CPS's undercount of the Medicaid population, the overstatement of uninsurance among infants, and the limitations of the Medicaid simulation. The fourth involves limitations on the kinds of data that can be tabulated with the reweighted database.
1. Medicaid Undercount
It is widely known that the Medicaid enrollment in the CPS understates estimates compiled from the states' program administrative statistics. It is much less widely known that this Medicaid undercount has been growing.11 It is very likely that at least some of the children reported as uninsured were actually covered by Medicaid.12 We have not attempted to adjust our estimates in any way for this Medicaid undercount, so a portion (and perhaps a large portion) of those children that we report as eligible for Medicaid but uninsured may have actually been covered by Medicaid.13
2. Uninsured Rates for Infants
Despite their greater access to Medicaid, infants are reported to have higher uninsured rates than children 1 to 5. This is peculiar to the CPS, however, and it is very likely due to a combination of two factors: (1) the uninsured being identified as those who report no insurance (as opposed to reporting that they were uninsured) and (2) insurance coverage being measured for the previous year (Czajka and Lewis 1999). Children born between the end of the reference year and the March survey date cannot in truth be described as having had coverage of any kind the previous year, and parents who answer the questions literally will end up with their newborn infants classified as uninsured. It is not possible to identify infants born after the end of the reference year, and so it is not possible to screen out those who may have been misclassified. Users of the data need to be aware that the rate of uninsurance among infants is overstated.
3. Medicaid Eligibility
The rules governing Medicaid eligibility, which vary by state, are extraordinarily complex. A complete simulation of all the ways that a child can become eligible for Medicaid is impossible--both because of the limitations of survey data and because the full details of eligibility, state by state, are not documented in any accessible form. For this reason, any Medicaid eligibility simulation is going to involve simplifications. It is quite rare, for example, that anyone simulates eligibility under the medically needy provisions, other than indirectly, and we have not done so here. Nor have we incorporated state-specific differences in the calculation and application of disregards. The information required to do so for all of the states is not readily available, and that limits not only our own simulation but those that could be constructed by others--even with substantially more resources.
4. Tabulating the Reweighted Database
The reweighting of the CPS database for state estimation was accomplished by applying a number of controls that, depending on which of the 51 sets of weights is chosen, make the database "look like" a specific state. The controls were chosen because of their relevance to estimating the number of uninsured children by age and poverty level. While it is possible to tabulate any field on the CPS file with the state weights that we have constructed, the state-specificity of the resulting tabulation deteriorates with the declining relevance of children's age, race and Hispanic origin, poverty level, and insurance coverage (insured or not) to the fields being tabulated. In addition, fields that depend on rules that differ across states, such as AFDC participation or Medicaid participation, may be inconsistent with the rules in most other states and, for this reason, should not be tabulated or used to infer eligibility in a simulation algorithm.14