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In matched-pairs experiments in which one cluster per pair of clusters isassigned to treatment, to estimate treatment effects, researchers often regresstheir outcome on a treatment indicator and pair fixed effects, clusteringstandard errors at the unit-ofrandomization level. We show that even if thetreatment has no effect, a 5%-level t-test based on this regression willwrongly conclude that the treatment has an effect up to 16.5% of the time. Tofix this problem, researchers should instead cluster standard errors at thepair level. Using simulations, we show that similar results apply to clusteredexperiments with small strata.

At What Level Should One Cluster Standard Errors in Paired and Small-Strata Experiments?