Under network interference, linear and kernel regression adjustments achieve the smallest asymptotic variance in their classes, and the paper provides consistent variance estimators.
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Causal Inference under Interference: Regression Adjustment and Optimality
Under network interference, linear and kernel regression adjustments achieve the smallest asymptotic variance in their classes, and the paper provides consistent variance estimators.