Multivalued Treatments and Decomposition Analysis: An application to the WIA Program

• Departmental Seminar

Date and Location

Wednesday, February 1, 2017, 10:30 AM - 11:50 AM
ARE Library Conference Room, 4101 Social Sciences and Humanities

Abstract

We analyze how different levels of active labor program participation affect participants' labor market outcomes. To do so, we propose two-step semiparametric efficient estimators that can be used to decompose differences in earnings distributions into (i) wage structure effects, arising due to the conditional outcome distributions associated with different levels of participation; and (ii) composition effect, arising due to differences in the distribution of observable characteristics. These counterfactual differences reveal causal relationships under a conditional independence assumption. Moreover, we calculate the semiparametric efficiency bound for the multivalued treatment effects, generalizing previous results for binary treatment effects. We employ these procedures to study the effects of the Workforce Investment Act (WIA), a large US job service program. Our estimation results show that heterogeneity in levels of participation is an important dimension to evaluate the WIA and other social programs in which participation varies. The results of this paper, both theoretically and empirically, provide rigorous assessment of intervention programs and relevant suggestions to improve the performance and cost-effectiveness of these programs.