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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 Author info | Abstract | Publisher info | Download info | Related research | Statistics Carneiro, Pedro () (University of Chicago)
Hansen, Karsten T. (Northwestern University)
Heckman, James J. (University of Chicago, American Bar Foundation and IZA Bonn)
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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.
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Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number
767.
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Length: 66 pages
Date of creation: Apr 2003Date of revision:
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Keywords: policy evaluation returns to schooling factor models counterfactual distributions Other versions of this item:
Find related papers by JEL classification: C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
This paper has been announced in the following NEP Reports :
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