At What Level Should One Cluster Standard Errors in Paired and Small-Strata Experiments?
American Economic Journal: Applied Economics
vol. 16,
no. 1, January 2024
(pp. 193-212)
Abstract
In matched pairs experiments in which one cluster per pair of clusters is assigned to treatment, to estimate treatment effects, researchers often regress their outcome on a treatment indicator and pair fixed effects, clustering standard errors at the unit-of-randomization level. We show that even if the treatment has no effect, a 5 percent–level t-test based on this regression will wrongly conclude that the treatment has an effect up to 16.5 percent of the time. To fix this problem, researchers should instead cluster standard errors at the pair level. Using simulations, we show that similar results apply to clustered experiments with small strata.Citation
de Chaisemartin, Clément, and Jaime Ramirez-Cuellar. 2024. "At What Level Should One Cluster Standard Errors in Paired and Small-Strata Experiments?" American Economic Journal: Applied Economics, 16 (1): 193-212. DOI: 10.1257/app.20210252Additional Materials
JEL Classification
- C21 Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions
- C90 Design of Experiments: General
- G21 Banks; Depository Institutions; Micro Finance Institutions; Mortgages
- O16 Economic Development: Financial Markets; Saving and Capital Investment; Corporate Finance and Governance
- O18 Economic Development: Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure
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