Determinants of AFDC Caseload Growth. F. RESEARCH IMPLICATIONS


This study demonstrates both the promise and limitations of the pooled time-series approach to studying AFDC caseload participation, other state-level measures of program participation, welfare, and health. We have obtained what we believe to be the most accurate estimates of the effects of labor market factors on AFDC participation of any study to date,(11) and have also obtained strong findings for program parameters.

At the same time, however, we have not been able to reliably estimate the effects of several state-level factors that are believed to be important determinants of AFDC participation. While we obtained strong results for non-marital births and marriages, we do not know the extent to which these variables capture the effects of growth in female-headed households, which we could not measure satisfactorily at the state level. Other determinants to consider further are other characteristics of families, access to health care insurance, the value of Medicaid, wages in low-skill jobs and other aspects of local labor markets not captured in the current model, other aspects of immigration, and parameters of other programs (e.g., UI). Further progress in this area will require development of better measures of state-level variables.

Recent caseload declines and devolution have substantially heightened interest in measuring and understanding the determinants of the welfare and health of vulnerable populations at the state level as well as of program participation. The pooled time-series approach to modeling these variables at the state level may prove to be a useful tool in helping researchers and policymakers determine whether changes in such variables are due to state program changes or to environmental factors that are beyond the control of the states. The promise of this tool will be substantially enhanced if better measures of key state-level factors are developed--both prospectively, as welfare reform and other changes occur, and retrospectively, as is necessary to estimate and understand the impacts of these factors on the measures of interest.

The value of this tool will also depend, however, on the extent to which states vary in their approaches to welfare reform. While the AFDC program varied substantially across states during the sample period, it was still reasonable to say that there were 51 variants of the same program and to analyze them together. Reforms may be so radical and varied as to make such a statement unreasonable in the future. Over time, pre-devolution caseload behavior will become less and less relevant to post-devolution caseload behavior.(12)