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Standard Errors for Panel Data Models with Unknown Clusters

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  • Jushan Bai
  • Sung Hoon Choi
  • Yuan Liao

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.

Suggested Citation

  • Jushan Bai & Sung Hoon Choi & Yuan Liao, 2019. "Standard Errors for Panel Data Models with Unknown Clusters," Papers 1910.07406, arXiv.org, revised May 2020.
    • Handle: RePEc:arx:papers:1910.07406
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    Cited by:

    1. Chen, Hongrui, 2023. "Energy innovations, natural resource abundance, urbanization, and environmental sustainability in the post-covid era. Does environmental regulation matter?," Resources Policy, Elsevier, vol. 85(PB).
    2. Jiti Gao & Bin Peng & Yayi Yan, 2022. "Higher-order Expansions and Inference for Panel Data Models," Papers 2205.00577, arXiv.org, revised Jun 2023.

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