Estimation for the multi-way error components model with ill-conditioned panel data
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, Jaejun | - |
dc.contributor.author | Cheon, Sooyoung | - |
dc.date.accessioned | 2021-09-03T09:05:36Z | - |
dc.date.available | 2021-09-03T09:05:36Z | - |
dc.date.created | 2021-06-16 | - |
dc.date.issued | 2017-03 | - |
dc.identifier.issn | 1226-3192 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/84319 | - |
dc.description.abstract | I Iota Iota-posed problems resulting from limited, partial or incomplete sample information have occurred frequently in econometric practice. The traditional methods of information recovery may cause the estimates highly unstable with low precision, known as ill-conditioned problems. In this paper, we propose a dual generalized maximum entropy estimator for the multi-way error components model with ill-conditioned panel data, based on an unconstrained dual Lagrange multiplier method. The numerical results for the panel data regression model with highly correlated and endogeneous covariates are in favor of our dual generalized maximum entropy estimation method in terms of quality of estimates. (C) 2016 The Korean Statistical Society. Published by Elsevier B.V. All rights reserved. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | SPRINGER HEIDELBERG | - |
dc.subject | RECOVERING INFORMATION | - |
dc.subject | SAMPLE PROPERTIES | - |
dc.title | Estimation for the multi-way error components model with ill-conditioned panel data | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Cheon, Sooyoung | - |
dc.identifier.doi | 10.1016/j.jkss.2016.05.008 | - |
dc.identifier.scopusid | 2-s2.0-85008388713 | - |
dc.identifier.wosid | 000395229600003 | - |
dc.identifier.bibliographicCitation | JOURNAL OF THE KOREAN STATISTICAL SOCIETY, v.46, no.1, pp.28 - 44 | - |
dc.relation.isPartOf | JOURNAL OF THE KOREAN STATISTICAL SOCIETY | - |
dc.citation.title | JOURNAL OF THE KOREAN STATISTICAL SOCIETY | - |
dc.citation.volume | 46 | - |
dc.citation.number | 1 | - |
dc.citation.startPage | 28 | - |
dc.citation.endPage | 44 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.identifier.kciid | ART002240719 | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.description.journalRegisteredClass | kci | - |
dc.relation.journalResearchArea | Mathematics | - |
dc.relation.journalWebOfScienceCategory | Statistics & Probability | - |
dc.subject.keywordPlus | RECOVERING INFORMATION | - |
dc.subject.keywordPlus | SAMPLE PROPERTIES | - |
dc.subject.keywordAuthor | Collinearity | - |
dc.subject.keywordAuthor | Dual generalized maximum entropy | - |
dc.subject.keywordAuthor | Endogeneity | - |
dc.subject.keywordAuthor | Error components model | - |
dc.subject.keywordAuthor | Ill-conditioned problems | - |
dc.subject.keywordAuthor | Panel data | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(02841) 서울특별시 성북구 안암로 14502-3290-1114
COPYRIGHT © 2021 Korea University. All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.