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Asymptotic Theory and Wild Bootstrap Inference with Clustered Errors

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  • Djogbenou, Antoine A.
  • MacKinnon, James G.
  • Orregaard Nielsen, Morten

Abstract

We study asymptotic inference based on cluster-robust variance estimators for regression models with clustered errors, focusing on the wild cluster bootstrap and the ordinary wild bootstrap. We state conditions under which both asymptotic and bootstrap tests and confidence intervals will be asymptotically valid. These conditions put limits on the rates at which the cluster sizes can increase as the number of clusters tends to infinity. To include power in the analysis, we allow the data to be generated under sequences of local alternatives. Under a somewhat stronger set of conditions, we also derive formal Edgeworth expansions for the asymptotic and bootstrap test statistics. Simulation experiments illustrate the theoretical results, and the Edgeworth expansions explain the overrejection of the asymptotic test and shed light on the choice of auxiliary distribution for the wild bootstrap.

Suggested Citation

  • Djogbenou, Antoine A. & MacKinnon, James G. & Orregaard Nielsen, Morten, 2018. "Asymptotic Theory and Wild Bootstrap Inference with Clustered Errors," Queen's Economics Department Working Papers 274725, Queen's University - Department of Economics.
    • Handle: RePEc:ags:quedwp:274725
    DOI: 10.22004/ag.econ.274725
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    Cited by:

    1. James G. MacKinnon & Matthew D. Webb, 2020. "When and How to Deal with Clustered Errors in Regression Models," Working Paper 1421, Economics Department, Queen's University.
    2. Djogbenou, Antoine A. & MacKinnon, James G. & Nielsen, Morten Ørregaard, 2019. "Asymptotic theory and wild bootstrap inference with clustered errors," Journal of Econometrics, Elsevier, vol. 212(2), pages 393-412.
    3. Harold D. Chiang, 2018. "Many Average Partial Effects: with An Application to Text Regression," Papers 1812.09397, arXiv.org, revised Jan 2022.
    4. Wang, Wenjie, 2021. "Wild Bootstrap for Instrumental Variables Regression with Weak Instruments and Few Clusters," MPRA Paper 106227, University Library of Munich, Germany.
    5. Adnan M. S. Fakir & Tushar Bharati, 2021. "Healthy, nudged, and wise: Experimental evidence on the role of cost reminders in healthy decision-making," Economics Discussion / Working Papers 21-13, The University of Western Australia, Department of Economics.

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