On Equivalencies Between Design-Based and Regression-Based Variance Estimators for Randomized Experiments
نویسندگان
چکیده
This paper demonstrates that the randomization-based “Neyman” and constanteffects estimators for the variance of estimated average treatment effects are equivalent to a variant of White’s “heteroskedasticity-robust” estimator and the homoskedastic ordinary least squares (OLS) estimator, respectively.
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