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Evaluating provincial eco-efficiency in China: an improved network data envelopment analysis model with undesirable
Shiwei Yu1,2, Jie Liu3,4, Longxi Li3,4
1Center for Energy and Environmental Management and Decision-Making, China University of Geosciences, Wuhan, 430074, China. ysw81993@sina.com.
Environmental Science and Pollution Research International
|December 28, 2019
Summary
China
Area of Science:
- Environmental Science
- Economics
- Regional Science
Background:
- China's rapid economic development has raised concerns about its environmental impact and social equity.
- Evaluating eco-efficiency is crucial for sustainable development strategies.
Purpose of the Study:
- To develop an improved matrix-type network data envelopment analysis (NDEA) model to assess the eco-efficiency of China's 30 provinces.
- To analyze the performance of the economy-society-environment cyclic system and identify key drivers of eco-efficiency.
Main Methods:
- An improved matrix-type network data envelopment analysis (NDEA) model was developed, incorporating undesirable outputs.
- A novel relative reduction of the input-based method was proposed for weight allocation across environmental, economic, and social subsystems.
- Data from 2003 to 2016 for China's 30 provinces were analyzed.
Main Results:
- The average eco-efficiency of China's 30 provinces between 2003 and 2016 was generally low, ranging from 0.59 to 0.73.
- Qinghai and Hainan exhibited the highest average eco-efficiencies, while Shaanxi and Xinjiang had the lowest.
- The environmental subsystem showed the highest average efficiency, primarily due to reduced industrial waste emissions, whereas the economic subsystem had the lowest efficiency, attributed to redundant inputs like fixed assets and energy consumption.
Conclusions:
- Eco-efficiency in China requires significant improvement, particularly in the economic subsystem.
- Reducing undesirable outputs (industrial waste) by over 88% and enhancing positive outputs (air quality, education) by at least 61% are necessary for most provinces.
- Low social subsystem efficiency negatively impacted the eco-efficiency of 18 provinces.
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