Fetching the paper…

Reading the bibliography…

2016

Program Evaluation with Right-Censored Data

Sant'Anna, Pedro H. C.

Original
PDF
Post on X

Understand

In a unified framework, we provide estimators and confidence bands for a variety of treatment effects when the outcome of interest, typically a duration, is subjected to right censoring.

Our methodology accommodates average, distributional, and quantile treatment effects under different identifying assumptions including unconfoundedness, local treatment effects, and nonlinear differences-in-differences.
The proposed estimators are easy to implement, have close-form representation, are fully data-driven upon estimation of nuisance parameters, and do not rely on parametric distributional assumptions, shape restrictions, or on restricting the potential treatment effect heterogeneity across different subpopulations.
These treatment effects results are obtained as a consequence of more general results on two-step Kaplan-Meier estimators that are of independent interest: we provide conditions for applying (i) uniform law of large numbers, (ii) functional central limit theorems, and (iii) we prove the validity of the ordinary nonparametric bootstrap in a two-step estimation procedure where the outcome of interest may be randomly censored.

Program Evaluation with Right-Censored Data · Around

Built on

——— (1994): “The bias of Kaplan-Meier integrals,”
1994
Earlier work this paper cites.
——— (1995): “The central limit theorem under random censorship,”
1995
Earlier work this paper cites.
——— (1997): “Nonparametric model checks for regression,”
1997
Earlier work this paper cites.

Similar

——— (1999): “Nonlinear censored regression,”
1999
Cited alongside, same era.
——— (2003): “Semiparametric instrumental variable estimation of treatment response models,”
2003
Cited alongside, same era.
——— (2004): “Kaplan-Meier Integrals,” in
2004
Cited alongside, same era.
——— (2015b): “Treatment Effects With Censoring and Endogeneity,”
Cited in the paper.
——— (1996b): “Multivariate regression estimation local polynomial fitting for time series,”
Cited in the paper.
——— (1996a): “Distributional convergence under random censorship when covariables are present,”
Cited in the paper.
——— (1996b): “The jackknife estimate of variance of a Kaplan-Meier integral,”
Cited in the paper.

Then

——— (2007): “Econometric evaluation of social programs, part I: Causal models, structural models and econometric policy evaluation,”
2007
Later among the works it cites.
——— (2007): “Empirical processes indexed by estimated functions,” in
2007
Later among the works it cites.
——— (2010): “Is ignorance bliss: Fixed vs. random censoring,” in
2010
Later among the works it cites.

Beyond the bibliography

alphaXiv searches the wider corpus for related work and actual follow-ups.

Open on alphaXiv

alphaXiv is searching for related work…