Characterizing selection bias using experimental data

James Heckman, Hidehiko Ichimura, Jeffrey Smith, Petra Todd

Research output: Contribution to journalArticlepeer-review

1084 Scopus citations


Semiparametric methods are developed to estimate the bias that arises from using nonexperimental comparison groups to evaluate social programs and to test the identifying assumptions that justify matching, selection models, and the method of difference-in-differences. Using data from an experiment on a prototypical social program and data from nonexperimental comparison groups, we reject the assumptions justifying matching and our extensions of it. The evidence supports the selection bias model and the assumptions that justify a semiparametric version of the method of difference-in-differences. We extend our analysis to consider applications of the methods to ordinary observational data.

Original languageEnglish (US)
Pages (from-to)1017-1098
Number of pages82
Issue number5
StatePublished - Sep 1998


  • Program evaluation
  • Selection bias
  • Semiparametric estimation
  • Training programs

ASJC Scopus subject areas

  • Economics and Econometrics


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