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Reconsidering the environmental Kuznets curve, pollution haven, and pollution halo hypotheses with carbon efficiency in China: A dynamic ARDL simulations approach
Given a new perspective on the environmental hypothesis, this paper systematically investigates the validity of the environmental Kuznets curve (EKC), pollution haven, and pollution halo hypotheses using carbon efficiency as the dependent variable. Applying the dynamic autoregressive distributed lag...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10147903/ https://www.ncbi.nlm.nih.gov/pubmed/37118402 http://dx.doi.org/10.1007/s11356-023-26671-5 |
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author | Ozkan, Oktay Coban, Mustafa Necati Iortile, Iormom Bruce Usman, Ojonugwa |
author_facet | Ozkan, Oktay Coban, Mustafa Necati Iortile, Iormom Bruce Usman, Ojonugwa |
author_sort | Ozkan, Oktay |
collection | PubMed |
description | Given a new perspective on the environmental hypothesis, this paper systematically investigates the validity of the environmental Kuznets curve (EKC), pollution haven, and pollution halo hypotheses using carbon efficiency as the dependent variable. Applying the dynamic autoregressive distributed lag simulations based on the annual time series data over the period 1990–2019, the study found that real GDP per capita has negative effects on China’s environmental quality both in the short and long run, whereas the square of real GDP per capita has positive impacts. This validates the EKC hypothesis for China. Furthermore, foreign direct investment has negative effects on environmental quality in China, implying that the case of China exemplifies the pollution haven hypothesis and not the pollution halo hypothesis. The empirical results also demonstrate that energy efficiency and trade openness improve China’s environmental quality both in the short run and long run. These findings, therefore, provide insights into achieving the ambitious climate goals in China by 2050. |
format | Online Article Text |
id | pubmed-10147903 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-101479032023-05-01 Reconsidering the environmental Kuznets curve, pollution haven, and pollution halo hypotheses with carbon efficiency in China: A dynamic ARDL simulations approach Ozkan, Oktay Coban, Mustafa Necati Iortile, Iormom Bruce Usman, Ojonugwa Environ Sci Pollut Res Int Research Article Given a new perspective on the environmental hypothesis, this paper systematically investigates the validity of the environmental Kuznets curve (EKC), pollution haven, and pollution halo hypotheses using carbon efficiency as the dependent variable. Applying the dynamic autoregressive distributed lag simulations based on the annual time series data over the period 1990–2019, the study found that real GDP per capita has negative effects on China’s environmental quality both in the short and long run, whereas the square of real GDP per capita has positive impacts. This validates the EKC hypothesis for China. Furthermore, foreign direct investment has negative effects on environmental quality in China, implying that the case of China exemplifies the pollution haven hypothesis and not the pollution halo hypothesis. The empirical results also demonstrate that energy efficiency and trade openness improve China’s environmental quality both in the short run and long run. These findings, therefore, provide insights into achieving the ambitious climate goals in China by 2050. Springer Berlin Heidelberg 2023-04-29 2023 /pmc/articles/PMC10147903/ /pubmed/37118402 http://dx.doi.org/10.1007/s11356-023-26671-5 Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Research Article Ozkan, Oktay Coban, Mustafa Necati Iortile, Iormom Bruce Usman, Ojonugwa Reconsidering the environmental Kuznets curve, pollution haven, and pollution halo hypotheses with carbon efficiency in China: A dynamic ARDL simulations approach |
title | Reconsidering the environmental Kuznets curve, pollution haven, and pollution halo hypotheses with carbon efficiency in China: A dynamic ARDL simulations approach |
title_full | Reconsidering the environmental Kuznets curve, pollution haven, and pollution halo hypotheses with carbon efficiency in China: A dynamic ARDL simulations approach |
title_fullStr | Reconsidering the environmental Kuznets curve, pollution haven, and pollution halo hypotheses with carbon efficiency in China: A dynamic ARDL simulations approach |
title_full_unstemmed | Reconsidering the environmental Kuznets curve, pollution haven, and pollution halo hypotheses with carbon efficiency in China: A dynamic ARDL simulations approach |
title_short | Reconsidering the environmental Kuznets curve, pollution haven, and pollution halo hypotheses with carbon efficiency in China: A dynamic ARDL simulations approach |
title_sort | reconsidering the environmental kuznets curve, pollution haven, and pollution halo hypotheses with carbon efficiency in china: a dynamic ardl simulations approach |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10147903/ https://www.ncbi.nlm.nih.gov/pubmed/37118402 http://dx.doi.org/10.1007/s11356-023-26671-5 |
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