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Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College Choice

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Listed:
  • Carneiro, Pedro

    (University College London)

  • Hansen, Karsten T.

    (Northwestern University)

  • Heckman, James J.

    (University of Chicago)

Abstract

This paper uses factor models to identify and estimate distributions of counterfactuals. We extend LISREL frameworks to a dynamic treatment effect setting, extending matching to account for unobserved conditioning variables. Using these models, we can identify all pairwise and joint treatment effects. We apply these methods to a model of schooling and determine the intrinsic uncertainty facing agents at the time they make their decisions about enrollment in school. Reducing uncertainty in returns raises college enrollment. We go beyond the “Veil of Ignorance” in evaluating educational policies and determine who benefits and loses from commonly proposed educational reforms.

Suggested Citation

  • Carneiro, Pedro & Hansen, Karsten T. & Heckman, James J., 2003. "Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College Choice," IZA Discussion Papers 767, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp767
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    References listed on IDEAS

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    More about this item

    Keywords

    factor models; returns to schooling; policy evaluation; counterfactual distributions;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models

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