Is the photovoltaic power generation policy effective in China? A quantitative analysis of policy synergy based on text mining

Zhaotian Chong, Qunwei Wang and Lei Wang

Technological Forecasting and Social Change, 2023, vol. 195, issue C

Abstract: To achieve carbon neutrality by 2060, the Chinese government needs to establish effective policies for promoting renewable energy. However, there is a lack of research on the quantitative assessment of policies and policy synergies. Focusing on the photovoltaic power generation policies in China, this study quantitatively examines the degree of synergy of the policies in terms of promulgating departments, goals, and measures. Additionally, this study expands the existing quantitative research on policy content analysis. The results show that changes in the degree of synergy between policy goals and measures tend to be consistent and that China's policies on photovoltaic power generation have gradually shifted to the combined use of different policy measures. Moreover, China relies more on traditional administrative resources and employs strong administrative power approaches, such as macro planning, regulation and supervision, and fiscal policies. Meanwhile, market-oriented approaches, such as financial measures, have not produced strong synergistic effects. Furthermore, the relative lag in policy formulation has resulted in a lack of policy continuity and systematization. Hence, the Chinese government should enhance the synergy between market-oriented and other policy measures, strengthen the structure of the policy system, promote cooperation between policy-promulgating departments, and improve the early warning mechanisms for policies.

Keywords: Photovoltaic power; Text mining; Power generation policy; China (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:195:y:2023:i:c:s0040162523004559

DOI: 10.1016/j.techfore.2023.122770

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