Most stringent test of null of cointegration: A Monte Carlo comparison

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dc.authorid0000-0002-5131-577X
dc.contributor.authorKhan, Asad ul Islam
dc.contributor.authorKhan, Asad ul Islam
dc.contributor.authorKhan, Asad ul Islam
dc.contributor.authorKhan, Waqar Muhammad
dc.contributor.authorHussan, Mehmood
dc.contributor.otherYönetim Bilimleri Fakültesi, İktisat Bölümü
dc.contributor.otherYönetim Bilimleri Fakültesi, İktisat Bölümü
dc.date.accessioned2020-01-20T08:42:05Z
dc.date.available2020-01-20T08:42:05Z
dc.date.issued2022
dc.departmentİHÜ, Yönetim Bilimleri Fakültesi, İktisat Bölümü
dc.description.abstractTo test for the existence of long run relationship, a variety of null of cointegration tests have been developed in literature. This study is aimed at comparing these tests on basis of size and power using stringency criterion: a robust technique for comparison of tests as it provides with a single number representing the maximum difference between a test’s power and maximum possible power in the entire parameter space. It is found that in general, asymptotic critical values tends to produce size distortion and size of test is controlled when simulated critical values are used. The simple LM test based on KPSS statistic is the most stringent test at all sample sizes for all three specifications of deterministic component, as it has the maximum difference approaching to zero and lesser than 20% for the entire parameter space.
dc.identifier.citationKhan, A. I., Khan, W. M. ve Hussan, M. (2022). Most stringent test of null of cointegration: a Monte Carlo comparison, Communications in Statistics- Simulation and Computation
dc.identifier.doi10.1080/03610918.2019.1691229
dc.identifier.endpage19
dc.identifier.issn0361-0918
dc.identifier.issn1532-4141
dc.identifier.scopus2-s2.0-85075195959
dc.identifier.scopusqualityQ3
dc.identifier.startpage1
dc.identifier.urihttps://doi.org/10.1080/03610918.2019.1691229
dc.identifier.urihttps://hdl.handle.net/20.500.12154/1033
dc.identifier.wosWOS:000497211300001
dc.identifier.wosqualityQ4
dc.indekslendigikaynakScopus
dc.indekslendigikaynakWeb of Science
dc.institutionauthorKhan, Asad ul Islam
dc.language.isoen
dc.publisherTaylor & Francis
dc.relation.ihupublicationcategory117
dc.relation.ispartofComunications in Statistics - Simulation and Computation
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectComparison
dc.subjectCointegration Tests
dc.subjectPower
dc.subjectSize
dc.subjectStringency
dc.titleMost stringent test of null of cointegration: A Monte Carlo comparison
dc.typeArticle
dspace.entity.typePublication
relation.isAuthorOfPublication5d56d061-267c-4b33-8b78-b50e651ee5aa
relation.isAuthorOfPublication.latestForDiscovery5d56d061-267c-4b33-8b78-b50e651ee5aa
relation.isOrgUnitOfPublication9d1809d1-3541-41aa-94ed-639736b7e16f
relation.isOrgUnitOfPublication.latestForDiscovery9d1809d1-3541-41aa-94ed-639736b7e16f

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