4.7 Article

Research on the improvement of total factor productivity in China's power industry: a perspective of technological heterogeneity

Journal

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
Volume 29, Issue 8, Pages 11854-11864

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s11356-021-16521-7

Keywords

Technological heterogeneity; Total factor productivity of the power industry; Meta-frontier Global Malmquist-Luenberger index; GMM method

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This study examines the dynamic evolution and regional differences of total factor productivity of the power industry in China's 30 provinces from 2003 to 2017, using the Meta-frontier Global Malmquist-Luenberger (MGML) index. The study finds that innovation is the key factor driving TFPPI growth, with different driving factors in each region.
An improvement in total factor productivity of the power industry (TFPPI) is crucial for achieving China's green transformation and high-quality development. Considering the technological heterogeneity of different regions, the Meta-frontier Global Malmquist-Luenberger(MGML) index was constructed to measure TFPPI in China's 30 provinces from 2003 to 2017, and then we investigated the dynamic evolution and regional differences of TFPPI. On this basis, the two-step system GMM method was used to explore the influencing factors of TFPPI. The results showed that: (1) During the survey period, the average annual growth rate of China's TFPPI was 4.2%, and average values of TFPPI in all provinces were greater than 1. The innovation effect was the key to TFPPI growth, while the catch-up effect and leading effect were not significant. (2) TFPPI showed a decreasing trend from the western to eastern and central regions, with average annual growth rates of 5.69%, 3.66%, and 2.89%, respectively, and the driving factors of each region were different. Moreover, the technology gap was narrowing. (3) Both the economic development level and R&D level had a positive impact on TFPPI, whereas the power consumption intensity was negatively correlated with TFPPI. Based on the conclusions of this paper, some effective recommendations were put forward to improve TFPPI.

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