EconPapers    
Economics at your fingertips  
 

Program Evaluation with Right-Censored Data

Pedro Sant'Anna ()

Papers from arXiv.org

Abstract: 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.

Date: 2016-04
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
http://arxiv.org/pdf/1604.02642 Latest version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1604.02642

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().

 
Page updated 2020-10-09
Handle: RePEc:arx:papers:1604.02642