Training, wages, and sample selection: Estimating sharp bounds on treatment effects

Research output: Contribution to journalArticlepeer-review

338 Scopus citations

Abstract

This paper empirically assesses the wage effects of the Job Corps program, one of the largest federally funded job training programs in the U.S. Even with the aid of a randomized experiment, the impact of a training program on wages is difficult to study because of sample selection, a pervasive problem in applied microeconometric research. Wage rates are only observed for those who are employed, and employment status itself may be affected by the training program. This paper develops an intuitive trimming procedure for bounding average treatment effects in the presence of sample selection. In contrast to existing methods, the procedure requires neither exclusion restrictions nor a bounded support for the outcome of interest. Identification results, estimators, and their asymptotic distribution are presented. The bounds suggest that the program raised wages, consistent with the notion that the Job Corps raises earnings by increasing human capital, rather than solely through encouraging work. The estimator is generally applicable to typical treatment evaluation problems in which there is nonrandom sample selection/attrition.

Original languageEnglish (US)
Pages (from-to)1071-1102
Number of pages32
JournalReview of Economic Studies
Volume76
Issue number3
DOIs
StatePublished - 2009

All Science Journal Classification (ASJC) codes

  • Economics and Econometrics

Fingerprint Dive into the research topics of 'Training, wages, and sample selection: Estimating sharp bounds on treatment effects'. Together they form a unique fingerprint.

Cite this