Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College Choice
Pedro Carneiro (),
Karsten T. Hansen () and
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Karsten T. Hansen: Northwestern University
No 767, IZA Discussion Papers from Institute of Labor Economics (IZA)
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.
Keywords: factor models; returns to schooling; policy evaluation; counterfactual distributions (search for similar items in EconPapers)
JEL-codes: C31 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-dcm and nep-ltv
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Published in: International Economic Review, 2003, 44 (2), 361-422
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Working Paper: Estimating distributions of treatment effects with an application to the returns to schooling and measurement of the effects of uncertainty on college choice (2003)
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