EconBase
← All papers

Wild Bootstrap Inference for Linear Regressions with Many Covariates

Wenze Li

arXiv 26 Jun 2025 · Econometrics

arXiv:2506.20972 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We propose a simple modification to the wild bootstrap procedure and establish its asymptotic validity for linear regression models with many covariates and heteroskedastic errors. Monte Carlo simulations show that the modified wild bootstrap has excellent finite sample performance compared with alternative methods that are based on standard normal critical values, especially when the sample size is small and/or the number of controls is of the same order of magnitude as the sample size.

Citation extraction

35
references
67
in-text mentions
35
distinct cited
0
self-citations
3,207
main-text words

appendix boundary found by appendix_command · 60% of the source is main text. Read the extracted text to check this.

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
1Cattaneo, M. D., M. Jansson, and W. K. Newey (2018) b): Inference in linear regression models with many covariates and heteroscedasticity0.90912675%
2Jochmans, K (2022) Heteroscedasticity-robust inference in linear regression models with many covariates0.83319958%
3Davidson, R. and J. G. MacKinnon (2010) Davidson-Mackinnon(2010)Wild bootstrap tests for IV regression0.64422100%
4Wang, W. and M. Kaffo (2016) Bootstrap inference for instrumental variable models with many weak instruments0.64422100%
5van der Vaart, A. and J. Wellner (1996) Weak Convergence and Empirical Processes: With Applications to Statistics0.5112250%
6Cameron, A. C., J. B. Gelbach, and D. L. Miller (2008) Cameron(2008)Bootstrap-based improvements for inference with clustered errors0.40511100%
7Dov\`, M.-S., A. B. Kock, and S. Mavroeidis (2024) A Ridge-Regularized Jackknifed Anderson-Rubin Test0.40511100%
8Davidson, R. and E. Flachaire (2008) Davidson-Flachaire(2008)The wild bootstrap, tamed at last0.40511100%
9Davidson, R. and J. G. MacKinnon (2008) Davidson-Mackinnon(2008)Bootstrap inference in a linear equation estimated by instrumental variables0.40511100%
10Davidson, R. and J. G. MacKinnon (2014) Davidson-Mackinnon(2014b)Bootstrap confidence sets with weak instruments0.40511100%

Showing the top 10 of 35 scored citations.