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Empirical study on the technical efficiency and total factor productivity of power industry: Evidence from Chinese provinces
Energy Economics, Volume: 128, Start page: 107161
Swansea University Author: Mohammad Abedin
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DOI (Published version): 10.1016/j.eneco.2023.107161
Abstract
With government policy reviews of renewable energy, environmental regulation and climate change, the energy-based power industry has received much attention. To explore the inherent characteristics of technical efficiency and total factor productivity in Chinese power industry, we use DEA-BCC and DE...
| Published in: | Energy Economics |
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| ISSN: | 0140-9883 |
| Published: |
Elsevier BV
2023
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| Online Access: |
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa64936 |
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| Abstract: |
With government policy reviews of renewable energy, environmental regulation and climate change, the energy-based power industry has received much attention. To explore the inherent characteristics of technical efficiency and total factor productivity in Chinese power industry, we use DEA-BCC and DEA-Malmquist models to exam the regional disparities of energy efficiency in 30 provinces based on the Yearbook database from 1998 to 2017. The market technical efficiency and environment technical efficiency were compared from the power generation link, the power network link and the comprehensive performance, respectively. Although the empirical results indicate that the Chinese power industry presents the development pattern of "emphasizing market over environment", the green technology and renewable energy are the waves of future and the practices of environmental regulations have borne some fruit actually. In addition, the power market reform in power industry actually works out but lacks of long-term incentives for continuous progress. The research conclusions can ravel out the complex strong correlation system in power industry and help to make targeted efficiency promotion strategies, which is in line with other energy policy goals. |
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| Keywords: |
energy technical efficiency; total factor productivity; Chinese power industry; DEA model |
| College: |
Faculty of Humanities and Social Sciences |
| Funders: |
This research was funded by National Natural Science Foundation of PR China (grant number 72001191), Key R&D and Promotion Special Project (Soft Science Research) in Henan Province (grant number 232400411184), National Social Science Foundation of China (grant number 20BJL034), Key Project of Henan province higher education (Humanities and Social Sciences) (grant number 21A170020). |
| Start Page: |
107161 |