{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T21:35:17Z","timestamp":1784842517176,"version":"3.55.0"},"reference-count":35,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2020,10,5]],"date-time":"2020-10-05T00:00:00Z","timestamp":1601856000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,8,12]]},"abstract":"<jats:title>Summary<\/jats:title>\n               <jats:p>This article aims to shed light on inference problems for statistical models under alternative or nonstandard asymptotic frameworks from the perspective of the jackknife empirical likelihood. Examples include small-bandwidth asymptotics for semiparametric inference and goodness-of-fit testing, sparse-network asymptotics, many-covariates asymptotics for regression models, and many-weak-instruments asymptotics for instrumental variable regression. We first establish Wilks\u2019 theorem for the jackknife empirical likelihood statistic in a general semiparametric inference problem under the conventional asymptotics. We then show that the jackknife empirical likelihood statistic may lose asymptotic pivotalness in the above nonstandard asymptotic frameworks, and argue that this phenomenon can be understood in terms of the emergence of Efron &amp; Stein (1981)\u2019s bias of the jackknife variance estimator at first order. Finally, we propose a modification of the jackknife empirical likelihood to recover asymptotic pivotalness under both conventional and nonstandard asymptotics. Our modification works for all of the above examples and provides a unified framework for investigating nonstandard asymptotic problems.<\/jats:p>","DOI":"10.1093\/biomet\/asaa081","type":"journal-article","created":{"date-parts":[[2020,9,21]],"date-time":"2020-09-21T19:22:54Z","timestamp":1600716174000},"page":"661-674","source":"Crossref","is-referenced-by-count":11,"title":["Jackknife empirical likelihood: small bandwidth, sparse network and high-dimensional asymptotics"],"prefix":"10.1093","volume":"108","author":[{"given":"Yukitoshi","family":"Matsushita","sequence":"first","affiliation":[{"name":"Graduate School of Economics, Hitotsubashi University, 2-1 Naka, Kunitachi, Tokyo 186-8601, Japan matsushita.y@r.hit-u.ac.jp"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Taisuke","family":"Otsu","sequence":"additional","affiliation":[{"name":"Department of Economics, London School of Economics, Houghton Street, London WC2A 2AE, U.K. t.otsu@lse.ac.uk"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2020,10,5]]},"reference":[{"key":"2021081218511279500_B1","doi-asserted-by":"crossref","first-page":"299","DOI":"10.3150\/bj\/1145993976","article-title":"Empirical likelihood in some semi-parametric models","volume":"12","author":"Bertail","year":"2006","journal-title":"Bernoulli"},{"key":"2021081218511279500_B2","first-page":"2384","article-title":"Subsampling bootstrap of count features of networks","volume":"42","author":"Bhattacharyya,","year":"2015","journal-title":"Ann. 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