At What Level Should One Cluster Standard Errors in Paired and Small-Strata Experiments?
Clément de Chaisemartin and
Jaime Ramirez-Cuellar
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Jaime Ramirez-Cuellar: Microsoft - Microsoft Research [Cambridge] - Microsoft Research
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Abstract:
In clustered and paired experiments, to estimate treatment effects, researchers often regress their outcome on the treatment and pair fixed effects, clustering standard errors at the unit-ofrandomization level. We show that even if the treatment has no effect, a 5%-level t-test based on this regression will wrongly conclude that the treatment has an effect up to 16.5% of the time, an error rate much larger than the researcher's 5% target. To achieve their targeted error rate, researchers should instead cluster standard errors at the pair level. Using simulations, we show that similar results apply to clustered experiments with small strata.
Keywords: clustered standard errors; clustering; paired experiments; stratified experiments; randomized experiments; RCT (search for similar items in EconPapers)
Date: 2022-09-15
New Economics Papers: this item is included in nep-exp
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Related works:
Journal Article: At What Level Should One Cluster Standard Errors in Paired and Small-Strata Experiments? (2024) 
Working Paper: At What Level Should One Cluster Standard Errors in Paired and Small-Strata Experiments? (2023) 
Working Paper: At What Level Should One Cluster Standard Errors in Paired and Small-Strata Experiments? (2022) 
Working Paper: At What Level Should One Cluster Standard Errors in Paired and Small-Strata Experiments? (2020) 
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Persistent link: https://EconPapers.repec.org/RePEc:hal:spmain:hal-03873897
DOI: 10.2139/ssrn.3520820
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