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

By Pedro Carneiro, Karsten Hansen, James J. Heckman. Social Science Research Network, 2003

666 citations recorded by the source corpus.

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.

Subfields: Economics and Econometrics, Education, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/39d7276f57a7982b61de383ab3af048e8f12faa9

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Citations in the corpus

Endogenous selection or treatment model estimation (2007, background): “Let f̂v(V | X)−1 be nonparametrically estimated as in Theorem 4, define W by equation (22), and define ν = ν(θ), where ν is given by equation (17).”
Inferring Labor Income Risk From Economic Choices: An Indirect Inference Approach (2010, methodology): “(8)Our paper is also in the same spirit as Carneiro et al. (2003) and Cunha et al.”
Field of Study, Earnings, and Self-Selection* (2016, neutral): “See also Carneiro et al. (2003) who show that uncertainty coming from forecast errors seem to have little effect on schooling choices.”
Fifty Years of Mincer Earnings Regressions (2003, methodology): “Methods for extracting heterogeneity from uncertainty are available (Carneiro, Hansen, and Heckman, 2003) but require panel data and cannot be applied to Census cross sections.”
Removing the Veil of Ignorance in Assessing the Distributional Impacts of Social Policies (2002, background): ““The Empirical Content of the Roy Model,” Econometrica, 58(5):1121-1149.”
Comparing IV With Structural Models: What Simple IV Can and Cannot Identify (2010, neutral): “45See e.g. Abbring and Heckman (2007), Carneiro, Hansen, and Heckman (2003), Cunha, Heckman, and Navarro (2007), Cunha, Heckman, and Schennach (2006, revised 2008), and Matzkin (1992, 1993, 2007).”
Disentangling the College Wage Premium: Estimating a Model with Endogenous Education Choices (2006, background): “Carneiro et al. (2003) show that nonpecuniary factors associated with psychic costs, motivations, and the like play a major role in explaining why individuals from low-income families do not attend college even though it is financially profitable to do so.”
PARTIAL IDENTIFICATION OF THE DISTRIBUTION OF TREATMENT EFFECTS AND ITS CONFIDENCE SETS (2009, background): “models, Fan and Wu (2007) studied partial identification and inference for conditional distributions of treatment effects.”
The Specificity of General Human Capital: Evidence from College Major Choice (2015, methodology): “Our framework and identification strategy is related to Carneiro et al. (2003) and Cunha et al.”
Building Bridges Between Structural and Program Evaluation Approaches to Evaluating Policy (2010, critical): “…and Heckman and Vytlacil (2007b), their proposed extension has some unsatisfactory features which can be removed by using an extension of the generalized Roy model to an ordered choice model using the choice framework of Cunha, Heckman, and Navarro (2007) and Carneiro, Hansen, and Heckman (2003).”
Instrumental Variable Estimation of Dynamic Linear Panel Data Models with Defactored Regressors and a Multifactor Error Structure (2019, neutral): “…instance, in a model of wage determination the factor loadings may represent several unmeasured skills, specific to each individual, while the factors may capture the price of these skills, which changes intertemporally in an arbitrary way; see e.g. Carneiro et al. (2003) and Heckman et al. (2006).”
Estimating Marginal Treatment Effects in Heterogeneous Populations (2008, background): “Carneiro et al. (2003a, 2003b) have also used a wider range of instruments, together with other identifying assumptions, and have been able to estimate the full range of returns to education.”