Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/228665 
Year of Publication: 
2020
Series/Report no.: 
IHS Working Paper No. 27
Publisher: 
Institut für Höhere Studien - Institute for Advanced Studies (IHS), Vienna
Abstract: 
This paper develops residual-based monitoring procedures for cointegrating polynomial regressions, i. e. , regression models including deterministic variables, integrated processes as well as integer powers of integrated processes as regressors. The regressors are allowed to be endogenous and the stationary errors are allowed to be serially correlated. We consider five variants of monitoring statistics and develop the results for three modified least squares estimators for the parameters of the CPRs. The simulations show that using the combination of self-normalization and a moving window leads to the best performance. We use the developed monitoring statistics to assess the structural stability of environmental Kuznets curves (EKCs) for both CO2 and SO2 emissions for twelve industrialized country since the first oil price shock.
Subjects: 
Cointegrating Polynomial Regression
Environmental Kuznets Curve
Monitoring
Structural Change
Creative Commons License: 
cc-by Logo
Document Type: 
Working Paper

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