Stationary bootstrapping for semiparametric panel unit root tests
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Hwang, Eunju | - |
dc.contributor.author | Shin, Dong Wan | - |
dc.date.available | 2020-02-28T09:46:58Z | - |
dc.date.created | 2020-02-06 | - |
dc.date.issued | 2015-03 | - |
dc.identifier.issn | 0167-9473 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/10714 | - |
dc.description.abstract | For panels of possible cross-sectional and serial dependency, stationary bootstrapping is applied to construct unit root tests that are valid regardless of the nuisance parameters of such dependency. The tests are semiparametric in that no model structure is imposed on the serial correlation and the cross-sectional correlation. The statistics are Wald tests and t-bar type tests based on the OLSE (ordinary least squares estimator). Residual-based and difference-based stationary bootstrapping are applied to obtain valid critical values of the tests. Both ordinary and recursive mean adjustments are considered. Large sample validity of the bootstrap tests is established for a large time series dimension. A Monte-Carlo simulation compares the proposed tests, yielding some promising tests, i.e., the t-bar type tests based on difference-based bootstrapping and recursive adjustment. (C) 2014 Elsevier B.V. All rights reserved. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | ELSEVIER SCIENCE BV | - |
dc.relation.isPartOf | COMPUTATIONAL STATISTICS & DATA ANALYSIS | - |
dc.subject | CROSS-SECTIONAL DEPENDENCY | - |
dc.subject | AUTOREGRESSIVE TIME-SERIES | - |
dc.title | Stationary bootstrapping for semiparametric panel unit root tests | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.description.journalClass | 1 | - |
dc.identifier.wosid | 000347759700002 | - |
dc.identifier.doi | 10.1016/j.csda.2014.09.004 | - |
dc.identifier.bibliographicCitation | COMPUTATIONAL STATISTICS & DATA ANALYSIS, v.83, pp.14 - 25 | - |
dc.identifier.scopusid | 2-s2.0-84908377308 | - |
dc.citation.endPage | 25 | - |
dc.citation.startPage | 14 | - |
dc.citation.title | COMPUTATIONAL STATISTICS & DATA ANALYSIS | - |
dc.citation.volume | 83 | - |
dc.contributor.affiliatedAuthor | Hwang, Eunju | - |
dc.contributor.affiliatedAuthor | Shin, Dong Wan | - |
dc.type.docType | Article | - |
dc.subject.keywordAuthor | Cross-sectional dependence | - |
dc.subject.keywordAuthor | Difference-based bootstrapping | - |
dc.subject.keywordAuthor | Recursive mean adjustment | - |
dc.subject.keywordAuthor | Residual-based bootstrapping | - |
dc.subject.keywordPlus | CROSS-SECTIONAL DEPENDENCY | - |
dc.subject.keywordPlus | AUTOREGRESSIVE TIME-SERIES | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Mathematics | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Interdisciplinary Applications | - |
dc.relation.journalWebOfScienceCategory | Statistics & Probability | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
1342, Seongnam-daero, Sujeong-gu, Seongnam-si, Gyeonggi-do, Republic of Korea(13120)031-750-5114
COPYRIGHT 2020 Gachon 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.