Citation
Abstract
This study investigates the environmental Kuznets curve (EKC) for haze in 31 cities and provinces across China using the spatial data for a period of 15 years, from 2000 to 2014. We utilized the geographically weighted regression (GWR) model to consider the spatial non-stationary characteristics of the air quality in a vast territory. This approach allowed us to verify the region-specific characteristics, while the global model estimated the average relationship across the entire nation. Although the EKC for haze was statistically significant in the global models, the results only confirmed the existence of an EKC between the overall air quality and economic performance. Thus, it was difficult to determine the regional differences in an EKC. The results of the GWR model found the spatial variability of each variable and showed significant spatial heterogeneity in the EKC across regions. Although six regions—Beijing, Gansu, Heilongjiang, Jiangxi, Jilin, Liaoning, Shanghai, Tianjin, Xinjiang, and Zhejiang—showed inverted U-shaped EKCs, these were only statistically significant in three big cities—Beijing, Tianjin, and Shanghai. The results demonstrated no EKCs in the other 25 provinces and cities. These results provide strong empirical evidence that there is significant spatial heterogeneity in the EKC of China. Thus, a more regionally specialized air pollution control policy is required to create an effective policy for balanced economic growth in China.
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Official URL or Download Paper: https://www.mdpi.com/2073-4433/13/5/806
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Additional Metadata
Item Type: | Article |
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Divisions: | Faculty of Economics and Management Institute of Tropical Agriculture and Food Security |
DOI Number: | https://doi.org/10.3390/atmos13050806 |
Publisher: | Multidisciplinary Digital Publishing Institute |
Keywords: | China; Environmental Kuznets curve; Geographically weighted regression; Haze; Spatial heterogeneity |
Depositing User: | Ms. Che Wa Zakaria |
Date Deposited: | 16 Jun 2023 20:29 |
Last Modified: | 16 Jun 2023 20:29 |
Altmetrics: | http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.3390/atmos13050806 |
URI: | http://psasir.upm.edu.my/id/eprint/101976 |
Statistic Details: | View Download Statistic |
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