Assessing the development of China's new energy industry

Bin Xu and Boqiang Lin ()

Energy Economics, 2018, vol. 70, issue C, 116-131

Abstract: As the world's largest carbon dioxide (CO2) emitter, China is facing increasing international pressure to reduce emissions. Actively developing new energy has become a fundamental means to solve the dilemma between environmental pollution and energy consumption growth. Thus, more scholars have conducted a wide range of studies on the new energy industry. However, most of the existing studies use traditional linear models to investigate the relationships between new energy industry and its driving forces, ignoring the objective reality that there are many nonlinear relationships in economic variables. In order to overcome the shortcomings of existing research, this paper uses a data-driven nonparametric additive regression model to study the new energy industry. The results show that the nonlinear effect of agricultural development shows an inverted “U-shaped” pattern due to the changes in crop acreage at different stages of development. The nonlinear impact of foreign energy dependence also indicates an inverted “U–shaped” pattern. However, technological progress produces a positive “U–shaped” nonlinear impact on the new energy industry because of the difference in R&D funding and R&D personnel investments. Similarly, the impact of energy consumption structure also shows a positive “U–shaped” pattern, owing to the gradual decline in coal consumption. Therefore, the government should develop differentiated policies at different stages, in order to effectively promote the development of new energy industries.

Keywords: New energy industry; Driving forces; Nonparametric additive regression models (search for similar items in EconPapers)
JEL-codes: C23 K32 O13 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (24)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:70:y:2018:i:c:p:116-131

DOI: 10.1016/j.eneco.2018.01.001

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