On equivalencies between design-based and regression-based variance estimators for randomized experiments

被引：26

作者：

Samii, Cyrus ^{[1
]}

Aronow, Peter M. ^{[2
]}

机构：

[1] NYU, Dept Polit, New York, NY 10012 USA

[2] Yale Univ, Dept Polit Sci, New Haven, CT 06520 USA

来源：

STATISTICS & PROBABILITY LETTERS | 2012年 / 82卷 / 02期

关键词：

Potential outcomes; Randomized experiments; Robust variance estimators; ADJUSTMENTS; BIAS;

D O I：

10.1016/j.spl.2011.10.024

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

This paper demonstrates that the randomization-based "Neyman" and constant-effects estimators for the variance of estimated average treatment effects are equivalent to a variant of the White "heteroskedasticity-robust" estimator and the homoskedastic ordinary least squares (OLS) estimator, respectively. (C) 2011 Elsevier BM. All rights reserved.

引用

页码：365 / 370

页数：6

共 15 条

[1]

Angrist JD, 2009, MOSTLY HARMLESS ECONOMETRICS: AN EMPIRICISTS COMPANION, P1

[2]

[Anonymous], 2002, Springer Series in Statistics

[3]

[Anonymous], CAMBRIDGE HDB EXPT P

[4]

Cochran W.G., 2007, Sampling techniques