Clustering with potential multidimensionality: Inference and practice
Abstract
We show how clustering standard errors in one or more dimensions can be justified in M-estimation when there is sampling or assignment uncertainty. Since existing procedures for variance estimation are either conservative or invalid, we propose a variance estimator that refines a conservative procedure and remains valid. We then interpret environments where clustering is frequently employed in empirical work from our design-based perspective and provide insights on their estimands and inference procedures.
Fields of Study & Subjects
Advanced Clustering Algorithms Research
Publication details
- Journal / source
- Journal of Econometrics
- Publisher
- Elsevier BV
- Volume
- 258
- Pages
- 106321–106321
- Publication date
- 5 September 2026
- Language
- EN