@inbook{4130774c5e7043bbbe27964a26392b99,
title = "Eefficient estimation of the dose-response function under ignorability using subclassification on the covariates",
abstract = "This chapter studies the large sample properties of a subclassificationbased estimator of the dose-response function under ignorability. Employing standard regularity conditions, it is shown that the estimator is root-n consistent, asymptotically linear, and semiparametric efficient in large samples. A consistent estimator of the standard-error is also developed under the same assumptions. In a Monte Carlo experiment, we investigate the finite sample performance of this simple and intuitive estimator and compare it to others commonly employed in the literature.",
keywords = "Blocking, Missing data, Semiparametric efficiency, Stratification, Subclassification, Treatment effects",
author = "Cattaneo, {Matias D.} and Farrell, {Max H.}",
year = "2011",
doi = "10.1108/S0731-9053(2011)000027A007",
language = "English (US)",
isbn = "9781780525242",
series = "Advances in Econometrics",
pages = "93--127",
editor = "William Greene and David Drukker",
booktitle = "Missing Data Methods",
}