{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,31]],"date-time":"2026-10-31T20:57:29Z","timestamp":1793480249392,"version":"4.5.0"},"reference-count":49,"publisher":"Cambridge University Press (CUP)","issue":"4","license":[{"start":{"date-parts":[[2018,9,4]],"date-time":"2018-09-04T00:00:00Z","timestamp":1536019200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/www.cambridge.org\/core\/terms"},{"start":{"date-parts":[[2018,9,4]],"date-time":"2018-09-04T00:00:00Z","timestamp":1536019200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":["www.cambridge.org"],"crossmark-restriction":true},"short-container-title":["Econom. Theory"],"published-print":{"date-parts":[[2019,8]]},"abstract":"<jats:p>This article considers the problem of inference for nested least squares averaging estimators. We study the asymptotic behavior of the Mallows model averaging estimator (MMA; Hansen, 2007) and the jackknife model averaging estimator (JMA; Hansen and Racine, 2012) under the standard asymptotics with fixed parameters setup. We find that both MMA and JMA estimators asymptotically assign zero weight to the under-fitted models, and MMA and JMA weights of just-fitted and over-fitted models are asymptotically random. Building on the asymptotic behavior of model weights, we derive the asymptotic distributions of MMA and JMA estimators and propose a simulation-based confidence interval for the least squares averaging estimator. Monte Carlo simulations show that the coverage probabilities of proposed confidence intervals achieve the nominal level.<\/jats:p>","DOI":"10.1017\/s0266466618000269","type":"journal-article","created":{"date-parts":[[2018,9,4]],"date-time":"2018-09-04T08:42:36Z","timestamp":1536050556000},"page":"816-841","update-policy":"https:\/\/doi.org\/10.1017\/policypage","source":"Crossref","is-referenced-by-count":64,"title":["INFERENCE AFTER MODEL AVERAGING IN LINEAR REGRESSION MODELS"],"prefix":"10.1017","volume":"35","author":[{"given":"Xinyu","family":"Zhang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chu-An","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"56","published-online":{"date-parts":[[2018,9,4]]},"reference":[{"key":"S0266466618000269_ref44","doi-asserted-by":"publisher","DOI":"10.1198\/016214505000000088"},{"key":"S0266466618000269_ref6","doi-asserted-by":"publisher","DOI":"10.1214\/13-AOS1106"},{"key":"S0266466618000269_ref39","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1111\/j.2517-6161.1996.tb02080.x","article-title":"Regression shrinkage and selection via the lasso","volume":"58","author":"Tibshirani","year":"1996","journal-title":"Journal of the Royal Statistical Society, Series B"},{"key":"S0266466618000269_ref46","doi-asserted-by":"publisher","DOI":"10.1198\/jbes.2011.10075"},{"key":"S0266466618000269_ref36","doi-asserted-by":"publisher","DOI":"10.1214\/074921706000000987"},{"key":"S0266466618000269_ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.jeconom.2014.07.002"},{"key":"S0266466618000269_ref1","doi-asserted-by":"publisher","DOI":"10.1016\/0304-4076(91)90107-O"},{"key":"S0266466618000269_ref41","doi-asserted-by":"publisher","DOI":"10.1016\/j.jeconom.2009.10.030"},{"key":"S0266466618000269_ref30","doi-asserted-by":"publisher","DOI":"10.1111\/ectj.12009"},{"key":"S0266466618000269_ref28","doi-asserted-by":"publisher","DOI":"10.1198\/jasa.2011.tm09478"},{"key":"S0266466618000269_ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.jeconom.2008.08.022"},{"key":"S0266466618000269_ref25","doi-asserted-by":"publisher","DOI":"10.1017\/S0266466608080158"},{"key":"S0266466618000269_ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.jeconom.2009.07.004"},{"key":"S0266466618000269_ref40","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4757-2545-2"},{"key":"S0266466618000269_ref18","doi-asserted-by":"publisher","DOI":"10.1198\/016214507000000473"},{"key":"S0266466618000269_ref27","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1176350486"},{"key":"S0266466618000269_ref31","doi-asserted-by":"publisher","DOI":"10.1080\/07350015.2014.982755"},{"key":"S0266466618000269_ref7","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511790485"},{"key":"S0266466618000269_ref5","doi-asserted-by":"publisher","DOI":"10.1198\/jasa.2011.tm10159"},{"key":"S0266466618000269_ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.jeconom.2016.07.006"},{"key":"S0266466618000269_ref23","doi-asserted-by":"publisher","DOI":"10.1017\/S0266466605050036"},{"key":"S0266466618000269_ref35","doi-asserted-by":"publisher","DOI":"10.1017\/S0266466600004382"},{"key":"S0266466618000269_ref22","doi-asserted-by":"publisher","DOI":"10.1017\/S0266466603191050"},{"key":"S0266466618000269_ref2","doi-asserted-by":"publisher","DOI":"10.1007\/BF00058655"},{"key":"S0266466618000269_ref42","doi-asserted-by":"publisher","DOI":"10.1006\/jmva.1999.1884"},{"key":"S0266466618000269_ref3","doi-asserted-by":"publisher","DOI":"10.2307\/2533961"},{"key":"S0266466618000269_ref43","doi-asserted-by":"publisher","DOI":"10.1198\/016214501753168262"},{"key":"S0266466618000269_ref45","doi-asserted-by":"publisher","DOI":"10.1214\/10-AOS832"},{"key":"S0266466618000269_ref9","doi-asserted-by":"publisher","DOI":"10.1111\/j.1468-0262.2007.00785.x"},{"key":"S0266466618000269_ref24","doi-asserted-by":"publisher","DOI":"10.1214\/009053606000000821"},{"key":"S0266466618000269_ref11","doi-asserted-by":"publisher","DOI":"10.3982\/QE332"},{"key":"S0266466618000269_ref37","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmva.2009.06.010"},{"key":"S0266466618000269_ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.jeconom.2011.06.019"},{"key":"S0266466618000269_ref12","unstructured":"Hansen B.E. 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