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dc.contributor.authorBEKIROS, Stelios D.
dc.contributor.authorSJÖ, Bo
dc.contributor.authorSWEENEY, Richard J.
dc.date.accessioned2018-12-06T13:55:34Z
dc.date.available2018-12-06T13:55:34Z
dc.date.issued2018
dc.identifier.citationJournal of economic surveys, 2018, Vol. 32, No. 4, pp. 1045-1073
dc.identifier.issn0950-0804
dc.identifier.issn1467-6419en
dc.identifier.urihttps://hdl.handle.net/1814/59967
dc.descriptionFirst published: 08 March 2018en
dc.description.abstractIn cross-section studies, if the dependent variable is I(0) but the regressor is I(1), the true slope must be zero in the resulting unbalanced regression. A spuriously significant relationship may be found in large cross-sections, however, if the integrated regressor is related to a stationary variable that enters the DGP but is omitted from the regression. The solution is to search for the related stationary variable, in some cases the first difference of the integrated regressor, in other cases, a categorical variable that can take on limited number of values which depend on the integrated variable. We present an extensive survey, new developments, and applications particularly in finance.
dc.description.sponsorshipEU Horizon 2020 research and innovation programme under the MS-C grant [656136]
dc.language.isoen
dc.publisherWileyen
dc.relation.ispartofJournal of economic surveys
dc.subjectCategorical variables
dc.subjectStock appreciation
dc.subjectSurvey
dc.subjectUnbalanced regressions
dc.subjectUnit roots
dc.subjectUnit-root testsen
dc.subjectPanel-dataen
dc.subjectCointegrationen
dc.subjectEarningsen
dc.subjectReturnsen
dc.titlePitfalls in cross-section studies with integrated regressors : a survey and new developments
dc.typeArticleen
dc.identifier.doi10.1111/joes.12246
dc.identifier.volume32
dc.identifier.startpage1045
dc.identifier.endpage1073
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dc.identifier.issue4


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