Monitoring cointegrating polynomial regressions: Theory and application to the environmental Kuznets curves for carbon and sulfur dioxide emissions

Artikel

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.

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• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Journal: Econometrics ; ISSN: 2225-1146 ; Volume: 9 ; Year: 2021 ; Issue: 1 ; Pages: 1-35 ; Basel: MDPI

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes ; Model Evaluation, Validation, and Selection ; Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth
• Thema: cointegrating polynomial regression ; environmental kuznets curve ; monitoring ; structural change

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Knorre, Fabian ; Wagner, Martin ; Grupe, Maximilian
• Ereignis: Veröffentlichung
• (wer): MDPI
• (wo): Basel
• (wann): 2021

Weitere Informationen

• DOI: doi:10.3390/econometrics9010012
• Handle: http://hdl.handle.net/10419/247602