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Cited by 5,037Advanced Causal Inference TechniquesSpatial and Panel Data AnalysisStatistical Methods and Bayesian Inference

The DOI matches its Crossref record; 81 of the 83 references it cites were found in a registry or an index.

A Practitioner’s Guide to Cluster-Robust Inference

Colin Cameron, A., Miller, Douglas L.·2015·Journal of Human Resources
DOI 10.3368/jhr.50.2.317
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Abstract

We consider statistical inference for regression when data are grouped into clusters, with regression model errors independent across clusters but correlated within clusters. Examples include data on individuals with clustering on village or region or other category such as industry, and state-year differences-in-differences studies with clustering on state. In such settings default standard errors can greatly overstate estimator precision. Instead, if the number of clusters is large, statistical inference after OLS should be based on cluster-robust standard errors. We outline the basic method as well as many complications that can arise in practice. These include cluster-specific fixed efects, few clusters, multi-way clustering, and estimators other than OLS.

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Research works printed but not linked: 8

  1. Andrews, Donald W. K. and James H. Stock. 2007. 'Inference with Weak Instruments.' In Advances in Economics and Econometrics, Theory and Applications: Ninth World Congress of the Econometric Society , Vol. III, ed. Richard Blundell, Whitney K. Newey, and T. Persson, 122-173, Cambridge: Cambridge University Press.
  2. Arellano, Manuel 1987. 'Computing Robust Standard Errors for Within-Group Estimators.' Oxford Bulletin of Economics and Statistic 49(4): 431-434.
  3. Baum, Christopher F., Mark E. Schaffer, Steven Stillman. 2007. 'Enhanced Routines for Instrumental Variables/GMM Estimation and Testing.' The Stata Journal 7(4): 465-506.
  4. Hansen, Christian. 2007b. 'Generalized Least Squares Inference in Panel and Multi-level Models with Serial Correlation and Fixed Effects.' Journal of Econometrics 141(2): 597-620.
  5. Kish, Leslie. 1965. Survey Sampling. New York: John Wiley.
  6. Kish, Leslie, and Martin R. Frankel. 1974. 'Inference from Complex Surveys with Discussion.' Journal Royal Statistical Society B 36(1): 1-37.
  7. McCaffrey, Daniel F., Bell, Robert M., and Carsten H. Botts. 2001. 'Generalizations of Bias Reduced Linearization.' Proceedings of the Survey Research Methods Section , American Statistical Association.
  8. Thompson, Samuel. 2006. 'Simple Formulas for Standard Errors that Cluster by Both Firm and Time.' SSRN paper. http://ssrn.com/abstract=914002.

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Metadata

Authors
Colin Cameron, A., & Miller, D. L.
ORCID
Miller, Douglas L.
Venue
Journal of Human Resources
Publisher
University of Wisconsin Press
Published
2015
Volume
50
Issue
2
Pages
317-372
ISSN
  • 0022-166X (ISSN-L)
  • 1548-8004
DOI
10.3368/jhr.50.2.317
OpenAlex
W2118836230
Cited by
5,037
References
83
Citations by year
2026: 992 · 2025: 497 · 2024: 370 · 2023: 385 · 2022: 445 · 2021: 436 · 2020: 425 · 2019: 358 · 2018: 396 · 2017: 344 · 2016: 225 · 2015: 115
FWCI
321.44
Type
journal article
Language
en
Open access
closed
Locations
  • The Journal of Human Resources (publishedVersion)
  • Project Muse (Johns Hopkins University) (submittedVersion)
  • eScholarship (California Digital Library) (submittedVersion)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Spatial and Panel Data Analysis
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
Keywords
cluster-robust standard errors, clustered data, intra-cluster correlation, regression inference, ordinary least squares, estimator precision

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