Monitoring cointegrating polynomial regressions: Theory and application to the environmental Kuznets curves for carbon and sulfur dioxide emissions
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.
Year of publication: |
2021
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Authors: | Knorre, Fabian ; Wagner, Martin ; Grupe, Maximilian |
Published in: |
Econometrics. - Basel : MDPI, ISSN 2225-1146. - Vol. 9.2021, 1, p. 1-35
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Publisher: |
Basel : MDPI |
Subject: | cointegrating polynomial regression | environmental kuznets curve | monitoring | structural change |
Saved in:
freely available
Type of publication: | Article |
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Type of publication (narrower categories): | Article |
Language: | English |
Other identifiers: | 10.3390/econometrics9010012 [DOI] 1755992920 [GVK] hdl:10419/247602 [Handle] |
Classification: | C22 - Time-Series Models ; C52 - Model Evaluation and Testing ; Q56 - Environment and Development; Environment and Trade; Sustainability; Environmental Accounting |
Source: |
Persistent link: https://www.econbiz.de/10012696317