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

Clément de Chaisemartin, Jaime Ramirez-Cuellar

arXiv 1 Jun 2019 · Econometrics · publishedAmerican Economic Journal Applied Economics (2023) · 34 citations (OpenAlex)

arXiv:1906.00288 · PDF · DOI · OpenAlex · Extracted main text

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-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. 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 extraction

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appendix boundary found by appendix_command · 37% of the source is main text. Read the extracted text to check this.

Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Kung-Yee Liang \ Scott L Zeger (1986) Longitudinal Data Analysis Using Generalized Linear Models0.8434375%
2A Colin Cameron \ Douglas L Miller (2015) A Practitioner’s Guide to Cluster-Robust Inference0.7948450%
3Bruno Crépon, Florencia Devoto, Esther Duflo \ William Parienté (2015) Estimating the Impact of Microcredit on Those Who Take it up: Evidence from a Randomized Experiment in Morocco0.7946450%
4Kosuke Imai, Gary King \ Clayton Nall (2009) The Essential Role of Pair Matching in Cluster-Randomized Experiments, with Application to the Mexican Universal Health Insuranc…0.7218338%
5Yuehao Bai (2019) Optimality of Matched-pair Designs in Randomized Controlled Trials0.69351100%
6Yuehao Bai, Joseph P Romano \ Azeem M Shaikh (2021) Inference in Experiments with Matched Pairs0.64811527%
7Susan Athey \ Guido W Imbens (2017) Chapter 3 - The Econometrics of Randomized Experiments0.64422100%
8Bruno Crépon, Florencia Devoto, Esther Duflo \ William Parienté (2015) Replication data for: Estimating the Impact of Microcredit on Those Who Take it up: Evidence from a Randomized Experiment in Mor…0.64422100%
9Alberto Abadie \ Guido W Imbens (2008) Estimation of the Conditional Variance in Paired Experiments0.56711318%
10Alberto Abadie, Susan Athey, Guido W Imbens \ Jeffrey Wooldridge (2017) When Should You Adjust Standard Errors for Clustering?0.5112250%

Showing the top 10 of 40 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Inference in Cluster Randomized Trials with Matched Pairs1.00064
2Inference for Matched Tuples and Fully Blocked Factorial Designs0.73732
3A New Design-Based Variance Estimator for Finely Stratified Experiments0.64422
4ASSESSING INFERENCE METHODS0.40511
5Inference for Two-stage Experiments under Covariate-Adaptive Randomization0.40511
6Inference in Experiments with Matched Pairs and Imperfect Compliance0.40511
7A Primer on the Analysis of Randomized Experiments and a Survey of some Recent Advances0.40511
8Clustering with Potential Multidimensionality: Inference and Practice0.40511