A Stock-Flow Analysis of the Welfare Caseload: Insights from California Economic Conditions

During the 1990s, the welfare caseload peaked and then declined by about half. The decline occurred simultaneously with a robust economic expansion and a series of major welfare reforms. This paper reconsiders the methods used in the previous studies to explain these changes. The authors explicitly model the welfare caseload as the net outcome of past flows onto and off of aid and explore the implications of such a stock-flow perspective for understanding the determinants of the caseload size and its evolution over time. The approach is shown to explain some of the anomalous findings in the literature regarding the effects of economic conditions on the welfare caseload. Then, using administrative data for California, the authors estimate the effect of the changing unemployment rate on the underlying flows and simulate the impact of the caseload stock. They find that approximately 50 percent of the caseload decline in California can be attributed to the declining unemployment rate. These estimates are substantially larger than the 20 to 35 percent estimates that are obtained from more traditional methods.

Evaluating the Differential Effects of Alternative Welfare-to-Work Training Components: A Re-Analysis of the California GAIN Program

helped with the preparation of the data. We also wish to thank Howard Bloom, Jim Riccio, Han

The Long-Term Gains from GAIN: A Re-Analysis of the Impacts of the California GAIN Program

As part of recent reforms of the welfare programs in the U.S., many states and localities have refocused their Welfare-to-Work programs from an emphasis on human capital acquisition (i.e., providing basic education and vocational training) to an emphasis on "work-first," (i.e., moving welfare recipients into unsubsidized employment as quickly as possible). This change in emphasis has been motivated, in part, by results from the experimental evaluation, conducted by the Manpower Demonstration Research Corporation (MDRC), of California's Greater Avenues to Independence (GAIN) programs during the early 1990s. Their evaluation found that, compared to programs in other counties that emphasized skill accumulation, the work-first program in Riverside County had larger effects on employment earnings, and welfare receipt. In addition, the Riverside program was cheaper per recipient than the other programs. This paper reexamines the GAIN program from two complementary perspectives. First, the authors extend the earlier analysis through nine years post-randomization, which is the longest follow-up of any randomized training program, and find that the stronger impacts for Riverside County's work first program tend to shrink, whereas the weaker impacts for the human capital programs in Alameda and Los Angeles Counties tend to remain constant or even grow over time. Second, the authors develop and implement methods to allow the comparison of programs implemented by random assignment in different places despite striking differences in the composition of the participant populations. On a substantive level, the authors' reexamination of the GAIN experiment leads them to conclude that although the work-first programs were more successful than the human capital accumulation programs in the early years, this relative advantage disappears in later years. On a methodological level, the authors' results suggest that, at least in this welfare context, these methods are a promising approach both for the estimation of program effects from non-experimental data and for extrapolating program results from one location to a different location with a different population mix.

Evaluating the Differential Effects of Alternative Welfare-to-Work Training Components: A Reanalysis of the California GAIN Program

We show how data from an evaluation in which subjects are randomly assigned to some treatment versus a control group can be combined with nonexperimental methods to estimate the differential effects of alternative treatments. We propose tests for the validity of these methods. We use these methods and tests to analyze the differential effects of labor force attachment (LFA) versus human capital development (HCD) training components with data from California's Greater Avenues to Independence (GAIN) program. While LFA is more effective than HCD training in the short term, we find that HCD is relatively more effective in the longer term.