Econometrica

Journal Of The Econometric Society

An International Society for the Advancement of Economic
Theory in its Relation to Statistics and Mathematics

Edited by: Guido W. Imbens • Print ISSN: 0012-9682 • Online ISSN: 1468-0262

Econometrica: Sep, 2021, Volume 89, Issue 5

Bootstrap with Cluster-Dependence in Two or More Dimensions

https://doi.org/10.3982/ECTA15383
p. 2143-2188

Konrad Menzel

We propose a bootstrap procedure for data that may exhibit cluster‐dependence in two or more dimensions. The asymptotic distribution of the sample mean or other statistics may be non‐Gaussian if observations are dependent but uncorrelated within clusters. We show that there exists no procedure for estimating the limiting distribution of the sample mean under two‐way clustering that achieves uniform consistency. However, we propose bootstrap procedures that achieve adaptivity with respect to different uniformity criteria. Important cases and extensions discussed in the paper include regression inference, U‐ and V‐statistics, subgraph counts for network data, and non‐exhaustive samples of matched data.


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Supplemental Material

Supplement to "Bootstrap with Cluster-Dependence in Two or More Dimensions"

This zip file contains the replication files for the manuscript.

Supplement to "Bootstrap with Cluster-Dependence in Two or More Dimensions"

This appendix contains extensions of the results in Menzel (2021) as well as an asymptotic theory for alternative inference procedures under multi-way clustering.