Essays on stability, functional form and poolability of nonlinear cointegrating regressions

dc.contributor.advisorWagner, Martin
dc.contributor.authorKnorre, Fabian
dc.contributor.refereeLinnemann, Ludger
dc.date.accepted2025-05-12
dc.date.accessioned2025-06-18T06:02:14Z
dc.date.available2025-06-18T06:02:14Z
dc.date.issued2025
dc.description.abstractThis cumulative dissertation develops and examines cointegration regression techniques and their application to nonlinear cointegrating relationships between integrated time series, with a particular focus on the Environmental Kuznets Curve (EKC). The EKC hypothesis postulates an inverted U-shaped relationship between economic development and pollution. Chapter 1 introduces residual-based monitoring procedures for cointegrating polynomial regressions (CPRs) to detect and date structural changes, i.e. whether a relationship may turn into a spurious relationship or whether the parameters of the relationship change. CPRs capture nonlinear dynamics by incorporating integer powers of integrated regressors. Chapter 2 evaluates estimators for nonparametric cointegrating regressions and specification tests for nonlinear cointegrating relationships, comparing their performance through a large scale simulation study. Chapter 3 extends estimators for seemingly unrelated cointegrating polynomial regressions to accommodate common integrated regressors across equations. It provides limiting distributions for these estimators, along with Wald-type hypothesis tests, RESET-type specification tests, and methods for group-wise pooled estimation, enhancing flexibility and precision in modeling complex systems.en
dc.identifier.urihttp://hdl.handle.net/2003/43757
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-25531
dc.language.isoen
dc.subjectNonlinear cointegrationen
dc.subjectCointegrating polynomial regressionen
dc.subjectEnvironmental Kuznets curveen
dc.subject.ddc310
dc.subject.rswkKuznets-Kurvede
dc.subject.rswkPolynomiale Regressionde
dc.subject.rswkKointegrationde
dc.titleEssays on stability, functional form and poolability of nonlinear cointegrating regressionsen
dc.typeText
dc.type.publicationtypePhDThesis
dcterms.accessRightsopen access
eldorado.secondarypublicationfalse

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