Randomization and Social Policy Evaluation

37 Pages Posted: 27 Jun 2007

See all articles by James J. Heckman

James J. Heckman

University of Chicago - Department of Economics; National Bureau of Economic Research (NBER); American Bar Foundation; Institute for the Study of Labor (IZA); CESifo (Center for Economic Studies and Ifo Institute)

Date Written: July 1991

Abstract

This paper considers the recent case for randomized social experimentation and contrasts it with older cases for social experimentation. The recent case eschews behavioral models, assumes that certain mean differences in outcomes are the parameters of interest to evaluators and assumes that randomization does not disrupt the social program being analyzed. Conditions under which program disruption effects are of no consequence are presented. Even in the absence of randomization bias, ideal experimental data cannot estimate median (other quantile) differences between treated and untreated persons without invoking supplementary statistical assumptions. The recent case for randomized experimentation does not address the choice of the appropriate stage in a multistage program at which randomization should be conducted. Evidence on randomization bias is presented.

Suggested Citation

Heckman, James J., Randomization and Social Policy Evaluation (July 1991). NBER Working Paper No. t0107. Available at SSRN: https://ssrn.com/abstract=995151

James J. Heckman (Contact Author)

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