Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/247602 
Year of Publication: 
2021
Citation: 
[Journal:] Econometrics [ISSN:] 2225-1146 [Volume:] 9 [Issue:] 1 [Publisher:] MDPI [Place:] Basel [Year:] 2021 [Pages:] 1-35
Publisher: 
MDPI, Basel
Abstract: 
This paper develops residual-based monitoring procedures for cointegrating polynomial regressions (CPRs), i.e., regression models including deterministic variables and 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 countries since the first oil price shock.
Subjects: 
cointegrating polynomial regression
environmental kuznets curve
monitoring
structural change
JEL: 
C22
C52
Q56
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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