Evaluating the Differential Effects of Alternative Welfare-to-Work Training Components: A Re-Analysis of the California GAIN Program
In this paper, we explore ways of combining experimental data and non-experimental methods to estimate the differential effects of components of training programs. We show how data from a multi-site experimental evaluation in which subjects are randomly assigned to any treatment versus a control group who receives no treatment can be combined with non-experimental regression-adjustment methods to estimate the differential effects of particular types of treatments. We also devise tests of the validity of using the latter methods. We use these methods and tests to re-analyze data from the MDRC Evaluation of California%u2019s Greater Avenues to Independence (GAIN) program. While not designed to estimate the differential effects of the Labor Force Attachment (LFA) training and Human Capital Development (HCD) training components used in this program, we show how data from this experimental evaluation can be used in conjunction with non-experimental methods to estimate such effects. We present estimates of both the short- and long-term differential effects of these two training components on employment and earnings. We find that while there are short-term positive differential effects of LFA versus HCD, the latter training component is relatively more beneficial in the longer-term.