What Mean Impacts Miss: Distributional Effects of Welfare Reform Experiments

Labor supply theory predicts systematic heterogeneity in the impact of recent welfare reforms on earnings, transfers, and income. Yet most welfare reform research focuses on mean impacts. We investigate the importance of heterogeneity using random-assignment data from Connecticut’s Jobs First waiver, which features key elements of post-1996 welfare programs. Estimated quantile treatment effects exhibit the substantial heterogeneity predicted by labor supply theory. Thus mean impacts miss a great deal. Looking separately at samples of dropouts and other women does not improve the performance of mean impacts. We conclude that welfare reform’s effects are likely both more varied and more extensive than has been recognized. ∗Correspondence to Hoynes at UC Davis, Department of Economics, 1152 Social Sciences and Humanities Building, One Shields Avenue, Davis, CA 95616-8578, phone (530) 752-3226, fax (530) 752-9382, or [email protected]; Gelbach at [email protected]; or Bitler at [email protected]. Bitler gratefully acknowledges the financial support of the National Institute of Child Health and Human Development and the National Institute on Aging. This work has not been formally reviewed or edited. The views and conclusions are those of the authors and do not necessarily represent those of the RAND Corporation. The data used in this paper are derived from data files made available to researchers by MDRC. The authors remain solely responsible for how the data have been used or interpreted. We are very grateful to MDRC for providing the public access to the experimental data used here. We would also like to thank Dan Bloom, Mary Daly, Jeff Grogger, Richard Hendra, Guido Imbens, Sanders Korenman, Chuck Michalopoulos, Lorien Rice, Susan Simmat, Jeff Smith, Till von Wachter, Arthur van Soest, and Johanna Walter for helpful conversations, as well as seminar participants from Berkeley, Chicago–Harris School, Cornell, Davis, Delaware, GW, the IRP summer workshop, Johns Hopkins, Maryland, Michigan, the NBER, PAA, PPIC, SOLE, the RAND Corporation, and Syracuse.