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On Using The Two-Way Cluster-Robust Standard Errors

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arxiv 2301.13775 v1 pith:YHXLW5XE submitted 2023-01-31 econ.EM

classification econ.EM
keywords errorsstandardtwcrtwo-waycluster-robusttheoreticalthousandsarrays
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Thousands of papers have reported two-way cluster-robust (TWCR) standard errors. However, the recent econometrics literature points out the potential non-gaussianity of two-way cluster sample means, and thus invalidity of the inference based on the TWCR standard errors. Fortunately, simulation studies nonetheless show that the gaussianity is rather common than exceptional. This paper provides theoretical support for this encouraging observation. Specifically, we derive a novel central limit theorem for two-way clustered triangular arrays that justifies the use of the TWCR under very mild and interpretable conditions. We, therefore, hope that this paper will provide a theoretical justification for the legitimacy of most, if not all, of the thousands of those empirical papers that have used the TWCR standard errors. We provide a guide in practice as to when a researcher can employ the TWCR standard errors.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Specification Testing for Dyadic Regression Models

    econ.EM 2026-07 conditional novelty 7.0 of 10

    A corrected Gaussian bootstrap makes KS and CvM specification tests for dyadic regression valid in both shared-node and independent-dyad regimes.

  2. Clustering with Potential Multidimensionality: Inference and Practice

    econ.EM 2024-11 conditional novelty 7.0 of 10

    In finite population M-estimation, cluster-robust standard errors are justified by cluster sampling or cluster assignment, and a covariate-adjusted variance estimator can be valid and less conservative than existing t...

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