EFFICIENT ESTIMATION OF AVERAGE TREATMENT EFFECTS

By Guido W. Imbens. 2003

137 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/5735f3304c4cada42fc2450806af7ecdd544949e

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Citations in the corpus

Does Matching Overcome Lalonde's Critique of Nonexperimental Estimators? (2005, unknown): “The match for each participant i ∈ I1 ∩ SP is constructed as a weighted average 12HIT (1998), Hahn (1998) and Angrist and Hahn (1999) consider whether it is better in terms of efficiency to match on P (X) or on X directly.”
The influence function of semiparametric estimators (2015, methodology): “Hahn (1998) and Hirano, Imbens, and Ridder (2003) applied this approach to derive the influence function of important treatment effect estimators.”
Simultaneous inference for Best Linear Predictor of the Conditional Average Treatment Effect and other structural functions (2017, background): “As for the eﬃciency bounds for the average treatment eﬀect (Hahn (1998), Hirano et al. (2003)), these papers rely on the estimation of the propensity score (or other nuisance parameters) by kernel or series methods, which fail in modern high-dimensional settings.”
Covariate balancing propensity score (2014, background): “This confirms the theoretical result in the literature that the estimated propensity score leads to a more efficient estimator of the average treatment effect (e.g., Hahn, 1998; Hirano et al., 2003).”
Non-Parametric Regression for Binary Dependent Variables (2006, background): “Copas (1995), Hjort and Jones (1996), Loader (1996), Staniswalis (1989), Fan and Gijbels (1996), Eguchi and Copas (1998), Bebchuk and Betensky (2001) and Park et al.”
Assessing the Effect of Race Bias in Post-traffic Stop Outcomes Using Propensity Scores (2006, background): “Although these standard errors ignore uncertainty in the weights, it has been shown that these standard errors are an upper bound for the actual sampling variability of the estimator, and hence, conservative (Hirano et al., 2003; Imbens, 2003).”
Large Dimensional Latent Factor Modeling with Missing Observations and Applications to Causal Inference (2019, unknown): “This observation is aligned with the results for the classical inverse propensity weighted estimator in Hirano, Imbens, and Ridder (2003).”
Beyond The Average Effects: The Distributional Impacts of Export Promotion Programs in Developing Countries (2010, methodology): “strategy proposed by Hirano et al. (2003) consists of a constant, lagged size categories in terms of total sales (three binary variables), lagged (natural logarithm of) total exports, lagged (natural logarithm of) number of products exported, lagged (natural logarithm of) number of countries served,”
Case Selection Techniques in Case Study Research (2008, background): “…have been a major topic in quantitative methodology over the last twentyfive years, first in statistics (Rosenbaum and Rubin 1983; Rosenbaum 2002) and subsequently in econometrics (Hahn 1998; Hirano, Imbens, and Ridder 2003) and political science (Ho, Imai, King and Stewart 2004; Imai forthcoming).”