A regional analysis of the urbanization-energy-economy-emissions nexus in China: based on the environmental Kuznets curve hypothesis

ABSTRACT

The process of urbanization has accelerated in the recent decades, bringing with it an enormous impact on climate change. This paper examines the relationships between urbanization, energy consumption, and economic growth on carbon dioxide emissions in regions of China during the 1997–2019 period. Additionally, the environmental Kuznets curve (EKC) hypothesis is also examined. The cross-sectional dependence test indicates that no cross-sectional dependence is present in the panel data, and six unit root tests show that all variables are integrated on the order of one, I(1). Results of all cointegration tests provide evidence for a long-term equilibrium in the selected time series data. The fully modified ordinary least squares (FMOLS) and the augmented mean group (AMG) estimator indicate that the EKC hypothesis is valid in all regions except Western China. Given its abundant renewable resources, this region can vigorously develop renewable energy and energy storage technology. Moreover, energy consumption can lead to emissions increasing, while it is not certain that urbanization leads to emissions decreasing. Clean technologies for energy and intensive development of urban area should be emphasized. Finally, the results of pairwise Dumitrescu-Hurlin (DH) Panel causality test between each pair of variables are complicated and mixed in different regions.

KEYWORDS:

• Urbanization
• China
• EKC
• emissions
• Dumitrescu-Hurlin causality

JEL CLASSIFICATION:

• R11; Q43; Q57; N55

Acknowledgments

This study was supported by Henan Office of Philosophy and Social Science (No. 2022BJJ074) and Luoyang Normal University (No. 2018-PYJJ-019/2020-PYJJ-006/2020XJGGJS-04).

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

¹ CEADs, 2019. Emission Inventories for 30 Provinces 2019. https://www.ceads.net/user/index.php?id=1188&lang=en (accessed 24 May 2022).

² CESY, 2020. China Energy Statistical Yearbook, 2020. https://data.cnki.net/trade/Yearbook/Single/N2021050066?zcode=Z025 (accessed 24 May 2022).

³ CSY, 2020. China Statistical Yearbook, 2020. http://www.stats.gov.cn/tjsj/ndsj/2020/indexch.htm (accessed 24 May 2022)..

Additional information

Funding

The work was supported by the Luoyang Normal University [2018-PYJJ-019; 2020-PYJJ-006; 2020XJGGJS-04]; Henan Office of Philosophy and Social Science [2022BJJ074].