Dynamic evolution and driving factors of new energy development: Fresh evidence from China

Yuling Pan and Feng Dong

Technological Forecasting and Social Change, 2022, vol. 176, issue C

Abstract: New energy is an emerging energy source for alleviating the energy crisis and environmental deterioration. In the case of China's 30 provinces, this study explores the trend in the dynamic evolution and driving factors of new energy development. The following conclusions are obtained: (1) the status of new energy development in China is “strong in the north and weak in the south and strong in the east and weak in the west”. (2) Through dynamic convergence analysis, an absolute convergence in China's new energy development occurs, with the absolute convergence rate continuously increasing. Furthermore, China's new energy development is experiencing a conditional convergence process. (3) According to the generalized Divisia index method, technology primarily drives the early stage of new energy development, whereas economic development drives the later stage. (4) The heterogeneity analysis indicates that the share of new energy technology inputs in regions with lagging levels of new energy development is much lower than that in regions with advanced levels of new energy development, indicating that the lagging regions learn new energy technologies from developed regions.

Keywords: New energy development; Convergence analysis; New energy technology; Generalized Divisia index method (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (19)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0040162522000075
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:176:y:2022:i:c:s0040162522000075

DOI: 10.1016/j.techfore.2022.121475

Access Statistics for this article

Technological Forecasting and Social Change is currently edited by Fred Phillips

More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Catherine Liu ().