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

Cyrus Samii and Peter M. Aronow

Statistics & Probability Letters, 2012, vol. 82, issue 2, 365-370

Abstract: 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.

Keywords: Potential outcomes; Randomized experiments; Robust variance estimators (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (14)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:82:y:2012:i:2:p:365-370

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DOI: 10.1016/j.spl.2011.10.024

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