Full metadata record
DC FieldValueLanguage
dc.contributor.authorStypka, Oliver-
dc.contributor.authorGrabarczyk, Peter-
dc.contributor.authorKawka, Rafael-
dc.contributor.authorWagner, Martin-
dc.date.accessioned2016-11-23T12:59:02Z-
dc.date.available2016-11-23T12:59:02Z-
dc.date.issued2016-
dc.identifier.urihttp://hdl.handle.net/2003/35393-
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-17434-
dc.description.abstractA large part of the empirical environmental Kuznets curve literature uses cointegrating regressions involving a unit root process and its powers as regressors. In this literature the unit root process and its powers are, incorrectly, all treated as integrated processes and modified least squares estimation methods for linear cointegrating regressions are routinely employed. We show that this approach to estimation leads for the Fully Modified OLS estimator surprisingly to the same limiting distribution as obtained for the version of the Fully Modified OLS estimator adapted to the cointegrating polynomial regression setting of Wagner and Hong (2016).en
dc.language.isoende
dc.relation.ispartofseriesDiscussion Paper / SFB823;77, 2016en
dc.subjectcointegrating polynomial regressionen
dc.subjectnonlinearityen
dc.subjectintegrated processen
dc.subjectfully modified OLS estimationen
dc.subjectcointegration testen
dc.subjectenvironmental Kuznets curveen
dc.subject.ddc310-
dc.subject.ddc330-
dc.subject.ddc620-
dc.title“Linear” fully modified OLS estimation of cointegrating polynomial regressionsen
dc.typeTextde
dc.type.publicationtypeworkingPaperde
dcterms.accessRightsopen access-
Appears in Collections:Sonderforschungsbereich (SFB) 823

Files in This Item:
File Description SizeFormat 
NDP_7716_SFB823_Stypka_Grabarczyk.pdfDNB883.79 kBAdobe PDFView/Open


This item is protected by original copyright



This item is protected by original copyright rightsstatements.org