Simulation of Medicaid and SCHIP Eligibility: Implications of Findings From 10 States. Final Report.. IV. Implications for Simulations Based on Household Survey Data


Simulating eligibility for Medicaid and SCHIP involves applying state rules for determining program eligibility to the data collected in a household survey. The data would be sufficient for a step-by-step replication of the eligibility determination process, but this remains only an ideal. With data from SIPP, researchers have achieved a high level of precision in simulating eligibility under the Food Stamp Program (FSP), but the rules for FSP are relatively simple compared with those for other means-tested programs, and they do not vary from state to state.

Medicaid eligibility has proven much more difficult to simulate, for several reasons. The detailed rules are not well documented. They vary from state to state. They require extensive household- and person-level data to replicate. And the kinds of data they require cut across the subject matter specialization of our major national surveys.

It would appear that SCHIP has taken state-to-state variation a step further than Medicaid. Thus, differences between states and even within states (between programs) in how income and resources are counted may prove equally daunting to efforts to simulate SCHIP eligibility. In addition, anti-crowd-out features have imposed new demands on simulation efforts.

In this chapter we outline the features of a generic SCHIP simulation routine. Then we compare the data requirements to the information collected in five national household surveys.