Do We Need Experimental Data To Evaluate the Impact of Manpower Training On Earnings?

Published

Journal Article

This article assesses several recent studies in the manpower training evaluation literature claiming that (1) nonexperimental methods of program evaluation produce unreliable estimates of program impacts and (2) randomized experiments are necessary to produce reliable ones. We present a more optimistic statement about the value of nonexperimental methods in analyzing the effects of training programs on earnings. Previous empirical demonstrations of the sensitivity of estimates of program impact to alternative non experimental procedures either do not test the validity of the testable assumptions that justify the nonexperimental procedures or else disregard the inference from such tests. We reanalyze data from the National Supported Work Demonstration experiment (NSW) utilized by LaLonde and Fraker and Maynard and reexamine the performance of nonexperimental estimates of the net impact of the NSW program on the posttraining earnings of young high school dropouts and adult women. Using several simple strategies for testing the appropriateness of alternative formulations of such estimators, we show that a number of the nonexperimental estimators used in these studies can be rejected. Although we eliminate a number of nonexperimental estimators by such tests, we are able to find estimators that are not rejected by these tests. Estimators not rejected by such tests yield net impact estimates that lead to the same inference about the impact of the program as the experimental estimates. The empirical results from our limited study provide tangible evidence that the recent denunciation of nonexperimental methods forevaluating manpower training effects is premature. © 1987, Sage Publications. All rights reserved.

Full Text

Duke Authors

Cited Authors

  • Heckman, JJ; Hotz, VJ; Dabos, M

Published Date

  • January 1, 1987

Published In

Volume / Issue

  • 11 / 4

Start / End Page

  • 395 - 427

Electronic International Standard Serial Number (EISSN)

  • 1552-3926

International Standard Serial Number (ISSN)

  • 0193-841X

Digital Object Identifier (DOI)

  • 10.1177/0193841X8701100402

Citation Source

  • Scopus