Multiway empirical likelihood

Harold D. Chiang, Yukitoshi Matsushita and Taisuke Otsu

Journal of Econometrics, 2025, vol. 249, issue PA

Abstract: This paper develops a general methodology to conduct statistical inference for observations indexed by multiple sets of entities. We propose a novel multiway empirical likelihood statistic that converges to a chi-square distribution under the non-degenerate case, where corresponding Hoeffding type decomposition is dominated by linear terms. Our methodology is related to the notion of jackknife empirical likelihood but the leave-out pseudo values are constructed by leaving out columns or rows. We further develop a modified version of our multiway empirical likelihood statistic, which converges to a chi-square distribution regardless of the degeneracy, and discuss its desirable higher-order property in a simplified setup. The proposed methodology is illustrated by several important econometric problems, such as bipartite network, generalized estimating equations, and three-way observations.

Keywords: Multiway clustering; Empirical likelihood; Jackknife; Efron-Stein bias; Two-sample U-statistics (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304407624002069
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:249:y:2025:i:pa:s0304407624002069

DOI: 10.1016/j.jeconom.2024.105861

Access Statistics for this article

Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson

More articles in Journal of Econometrics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().