Estimating treatment effects for discrete outcomes when responses to treatment vary: an application to Norwegian vocational rehabilitation programs

By A. Aakvik, James J. Heckman, E. Vytlacil. 2005

282 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/605b7bf54af945ecfd403315fe415981ace063f9

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Citations in the corpus

Who Benefits from Universal Child Care? Estimating Marginal Returns to Early Child Care Attendance (2018, unknown): “A produces the following outcome equation as a function of the observed regressors X and the propensity 16 The existing literature typically invokes the stronger assumption of full independence between (X, R, T, ~Z), and (U0, U1, UD) (e.g., Aakvik et al. 2005; Carneiro et al. 2011, 2017).”
PARTIAL IDENTIFICATION OF THE DISTRIBUTION OF TREATMENT EFFECTS AND ITS CONFIDENCE SETS (2009, background): “…between the potential outcomes such that distributions of the treatment effects are point identified, see, for example, Heckman et al. (1997), Biddle, Boden, and Reville (2003), Carneiro, Hansen, and Heckman (2003), Aakvik, Heckman, and Vytlacil (2005), and Abbring and Heckman (2007), among others.”
SHARP BOUNDS ON THE DISTRIBUTION OF TREATMENT EFFECTS AND THEIR STATISTICAL INFERENCE (2009, background): “…between the potential outcomes such that their joint distribution and the distribution of the treatment effects are identified; see, e.g., Heckman et al. (1997), Biddle, Boden, and Reville (2003), Carneiro, Hansen, and Heckman (2003), and Aakvik, Heckman, and Vytlacil (2005), among others.”
Community Colleges and Upward Mobility (2019, background): “53 (53)See Aakvik et al. (2005), Walters (2017), Kline and Walters (2016), and Cornelissen et al.”
1. The Scientific Model of Causality (2005, methodology): “¼ 0Þð1 DÞ ¼ 0ðXÞ þ ½ 1ðXÞ 0ðXÞ þ K1ðPðX ;ZÞÞ K0ðPðX ;ZÞÞ D þ K0ðPðX ;ZÞÞ: 84See Aakvik et al. (2005); Carneiro et al. (2003); and Cunha et al. (2005a, 2005b) for a generalization of matching that allows for selection on unobservables by imposing a factor structure on the errors and estimating the…”
From Late to MTE: Alternative Methods for the Evaluation of Policy Interventions (2016, background): “…of the outcome in X and a constant shape of the MTE across X (except for a varying intercept) leads to the following outcome equation: 22 Full independence between (X, 𝑍) and (U0, U1UD) is for example invoked in Aakvik, Heckman, and Vytlacil 2005; Carneiro et al., 2011; and Carneiro et al., 2015.”
Understanding Instrumental Variables in Models with Essential Heterogeneity (2006, unknown): “See Aakvik et al. (2005); Carneiro et al. (2003); Cunha et al. (2005); ? for discussions of the identification of distributions of β.”
Earnings Functions, Rates of Return and Treatment Effects: The Mincer Equation and Beyond (2005, unknown): “This line of research starts from the analysis of Heckman (1990), Heckman and Smith (1998), Aakvik, Heckman, and Vytlacil (2005), Carneiro, Hansen, and Heckman (2001, 2003) and Cunha, Heckman, and Navarro (2005a,c,d).”
Using matching, instrumental variables and control functions to estimate economic choice models (2004, background): “We write V = µV (Z,UV ) D =1 ( V> 0), ( 1 )”
Estimating distributions of potential outcomes using local instrumental variables with an application to changes in college enrollment and wage inequality (2009, methodology): “Heckman, Urzua, and Vytlacil (2006) further extended the method of local instrumental variables and Aakvik, Heckman, and Vytlacil (2005) used factor structures for the analysis of the latent variable framework of Heckman and Vytlacil (1999, 2001, 2005).”