Heterogeneous links among urban concentration, non-renewable energy use intensity, economic development, and environmental emissions across regional development levels

Munir Ahmad; Cem Işık; Gul Jabeen; Tausif Ali; Ilhan Ozturk; Desire Wade Atchike

doi:10.1016/j.scitotenv.2020.144527

Heterogeneous links among urban concentration, non-renewable energy use intensity, economic development, and environmental emissions across regional development levels

Sci Total Environ. 2021 Apr 15:765:144527. doi: 10.1016/j.scitotenv.2020.144527. Epub 2020 Dec 25.

Authors

Munir Ahmad¹, Cem Işık², Gul Jabeen³, Tausif Ali⁴, Ilhan Ozturk⁵, Desire Wade Atchike⁶

Affiliations

¹ School of Economics, Zhejiang University, Hangzhou 310058, China. Electronic address: munirahmad@zju.edu.cn.
² Faculty of Tourism, Anadolu University, Turkey.
³ College of Management, Research Institute of Business Analytics and Supply Chain Management, Shenzhen University, Shenzhen 518060, China; School of Economics and Management, North China Electric Power University, Beijing 102206, China. Electronic address: guljabeen@ncepu.edu.cn.
⁴ College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China.
⁵ Faculty of Economics and Administrative Sciences, Cag University, 33800 Mersin, Turkey; Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan; Department of Finance, Asia University, 500, Lioufeng Rd., Wufeng, Taichung 41354, Taiwan.
⁶ School of Economics and Management, North China Electric Power University, Beijing 102206, China.

PMID: 33412378
DOI: 10.1016/j.scitotenv.2020.144527

Abstract

This study examined the long-run and short-run heterogeneous links among urban concentration, non-renewable energy use intensity, economic development, and environmental emissions index across the regional development levels of 31 Chinese provinces. By employing the augmented mean group method and Dumitrescu-Hurlin causality, the following results are drawn: Firstly, a bidirectional positive linkage was existent between the economic development and urban concentration in both the long-run and short-run across regional development levels. Secondly, a unidirectional positive linkage emerged from non-renewable energy use intensity to environmental emissions index, with the most influential effect in EER China (highest development level). Thirdly, bidirectional mixed linkages prevailed between economic development and non-renewable energy use intensity. Economic development mitigated the non-renewable energy use intensity (inverted U-shaped curve) in the national data set and EER China (highest development level); nevertheless, the linear linkage was observed in IER China (medium development level) and WER China (lowest development level). Fourthly, unidirectional mixed linkages were found from urban concentration to non-renewable energy use intensity and environmental emissions index. Urban concentration demonstrated a U-shaped linkage with non-renewable energy use intensity and environmental emissions index in the national data set and EER China. But it unveiled a linear linkage with both variables in IER China and WER China. Fifthly, economic development showed an environmental Kuznets curve with environmental emissions index in the national data set and EER China. Conversely, it showed a linear linkage with the environmental emissions index in IER China and WER China. In turn, the environmental emissions index linearly hampered the economic development in the national data set as well as regional samples. Finally, the long-run and short-run effects showed homogeneity of the linkages' nature; yet, the degree of effects in the long-run surpassed those in the short-run for all development levels.

Keywords: Chinese economy; Economic development; Environmental Kuznets Curve; Environmental emissions index; Non-renewable energy use intensity; Urban concentration.