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Standard Errors for Panel Data Models with Unknown Clusters

Jushan Bai, Sung Hoon Choi, Yuan Liao

arXiv 16 Oct 2019 · Econometrics · publishedJournal of Econometrics (2020) · 16 citations (OpenAlex)

arXiv:1910.07406 · PDF · DOI · OpenAlex · Extracted main text

Abstract

This paper develops a new standard-error estimator for linear panel data models. The proposed estimator is robust to heteroskedasticity, serial correlation, and cross-sectional correlation of unknown forms. The serial correlation is controlled by the Newey-West method. To control for cross-sectional correlations, we propose to use the thresholding method, without assuming the clusters to be known. We establish the consistency of the proposed estimator. Monte Carlo simulations show the method works well. An empirical application is considered.

Citation extraction

25
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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
1Newey and West (1987) A simple, positive semi-definite, heteroskedasticity and autocorrelationconsistent covariance matrix0.87452100%
2Arellano (1987) Computing Robust Standard Errors for Within-groups Estimators0.84333100%
3Newey and West (1994) Automatic lag selection in covariance matrix estimation0.84333100%
4Bickel and Levina (2008) Covariance regularization by thresholding0.81142100%
5Hansen (2007) Asymptotic properties of a robust variance matrix estimator for panel data when T is large0.81142100%
6Wolfers (2006) Did unilateral divorce laws raise divorce rates? A reconciliation and new results0.69361100%
7Andrews (1991) Heteroskedasticity and autocorrelation consistent covariance matrix estimation0.64422100%
8Cameron and Miller (2015) A practitioner’s guide to cluster-robust inference0.64422100%
9Friedberg (1998) Did unilateral divorce raise divorce rates? Evidence from panel data0.51121100%
10Abadie, Athey, Imbens, and Wooldridge (2017) When should you adjust standard errors for clustering?0.40511100%

Showing the top 10 of 25 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
11 Panel Data with Unknown Clusters1.000125
2Feasible Generalized Least Squares for Panel Data with Cross-sectional and Serial Correlations1.00054
3Heterogeneous Grouping Structures in Panel Data0.40511
4Inferential Theory for Pricing Errors with Latent Factors and Firm Characteristics0.00011