We use administrative data from Missouri to examine the sensitivity of earnings impact estimates for a job training program based on alternative nonexperimental methods. We consider regression adjustment, Mahalanobis distance matching, and various methods using propensity-score matching, examining both cross-sectional estimates and difference-in-difference estimates. Specification tests suggest that the difference-in-difference estimator may provide a better measure of program impact. We find that propensity-score matching is most effective, but the detailed implementation is not of critical importance. Our analyses demonstrate that existing data can be used to obtain useful estimates of program impact.

We explore the effects of temporary help employment on welfare recipients' subsequent employment and welfare dynamics. We find that any employment—in temporary help services or other sectors—yields substantial benefits compared to no employment. Although welfare recipients who go to work for temporary help service firms have lower initial wages than those with jobs in other sectors, they experience faster subsequent wage growth. Two years later, they are no less likely to be employed, their wages are close to those of other workers, and they are only slightly more likely to remain on welfare.