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Influence mechanism of electricity price distortion on industrial green transformation: A spatial analysis of Chinese regions

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  • Razzaq, Asif
  • Sharif, Arshian
  • Yang, Xiaodong
  • Dogan, Eyup

Abstract

Electricity price distortion (DIS) can significantly affect industrial green transformation (IGT), influencing the pace and direction of sustainable economic growth. Understanding this link is essential for crafting effective green energy policies. Initially, this study evaluates the direct and heterogeneous effects of DIS on IGT and then investigates the indirect influence channels using a sample of 30 Chinese provincial-level administrative regions from 2006 to 2019. Spatial analysis techniques (standard deviation ellipse and geographically and temporally weighted regression methods) are applied to explore the spatial and temporal dependence and non-stationary association between DIS and IGT. The outcomes suggest that DIS significantly reduces IGT in the eastern region through R&D input intensity and energy mix, while insignificant in the central and western regions. The adverse effect of DIS is more substantial at higher quantiles of IGT. The individual spatial heterogeneity characteristics reveal that the gravity centre of IGT is located in the southeast of the geometric centre of China, displays a southwest-northeast-southeast directional migration, and distributed at the junction of Henan and Hubei. Manifestly, the ellipse and azimuth of IGT vary significantly between 0.862°-32.854°. The IGT level steadily progresses from discrete to concentrated, reflected by the ellipse's long and short semi-axes. These regions are mainly concentrated in the eastern and northwestern areas, with the most significant inhibitory effects in Fujian, Anhui, Shaanxi, Zhejiang, and Yunnan. These findings offer valuable policy implications.

Suggested Citation

  • Razzaq, Asif & Sharif, Arshian & Yang, Xiaodong & Dogan, Eyup, 2024. "Influence mechanism of electricity price distortion on industrial green transformation: A spatial analysis of Chinese regions," Energy Economics, Elsevier, vol. 130(C).
    • Handle: RePEc:eee:eneeco:v:130:y:2024:i:c:s0140988324000161
    DOI: 10.1016/j.eneco.2024.107308
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