Comparisons of the alternative biased estimators for the distributed lag models

dc.authoridGuler, Huseyin/0000-0002-7807-526X
dc.contributor.authorGuler, Huseyin
dc.contributor.authorGultay, Berrin
dc.contributor.authorKaciranlar, Selahattin
dc.date.accessioned2025-01-27T20:55:51Z
dc.date.available2025-01-27T20:55:51Z
dc.date.issued2017
dc.departmentÇanakkale Onsekiz Mart Üniversitesi
dc.description.abstractThe finite distributed lag models include highly correlated variables as well as lagged and unlagged values of the same variables. Some problems are faced for this model when applying the ordinary least squares (OLS) method or econometric models such as Almon and Koyck models. The primary aim of this study is to compare performances of alternative estimators to the OLS estimator defined by combining the Almon estimator with some estimators using Almon (1965) data. A simulation study with different model parameters is performed and the estimators are compared according to the root mean square error (RMSE) and prediction mean square error (PMSE).
dc.identifier.doi10.1080/03610918.2015.1053919
dc.identifier.endpage3318
dc.identifier.issn0361-0918
dc.identifier.issn1532-4141
dc.identifier.issue4
dc.identifier.scopus2-s2.0-85003894397
dc.identifier.scopusqualityQ2
dc.identifier.startpage3306
dc.identifier.urihttps://doi.org/10.1080/03610918.2015.1053919
dc.identifier.urihttps://hdl.handle.net/20.500.12428/26209
dc.identifier.volume46
dc.identifier.wosWOS:000400186200053
dc.identifier.wosqualityQ4
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherTaylor & Francis Inc
dc.relation.ispartofCommunications in Statistics-Simulation and Computation
dc.relation.publicationcategoryinfo:eu-repo/semantics/openAccess
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WoS_20250125
dc.subjectAlmon estimator
dc.subjectFinite distributed lag model
dc.subjectLiu estimator
dc.subjectRidge estimator
dc.titleComparisons of the alternative biased estimators for the distributed lag models
dc.typeArticle

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