How efficient is the environmental pollution control in China?

被引:7
作者
Guo, Ke [1 ]
Li, Zhengyang [2 ]
Cao, Yuequn [1 ]
Yang, Yuling [3 ]
机构
[1] Chongqing Univ, Sch Publ Policy & Adm, Chongqing 400044, Peoples R China
[2] Dongbei Univ Finance & Econ, Sch Finance, Dalian 116012, Peoples R China
[3] Zhejiang Dev & Planning Inst, Hangzhou 310030, Peoples R China
关键词
Pollution control efficiency; Capital input; Three -stage global DEA; Efficiency change decomposition; WATER TREATMENT PLANTS; ECO-EFFICIENCY; AIR-POLLUTION; IMPACT; INNOVATION; GROWTH;
D O I
10.1016/j.psep.2023.02.064
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Currently, China is at a critical stage of economic transformation and pollution control. The environmental pollution control efficiency (PCE) deserves more in-depth study. This paper adopts a three-stage global data envelopment analysis (DEA) model and a global Malmquist index model to measure the PCE and the sources of its changes in China from 1991 to 2019. Study shows that: (1) the overall level of PCE has remained low over the past 29 years, and it has a slowly fluctuating upward trend, with an average annual growth rate of only 0.92 %; (2) the lower pure technical efficiency hinders the effectiveness of environmental pollution control, which is mainly affected by the slow technological progress; and (3) at the provincial level, the overall efficiency of Shanghai and Guangxi has long been above 0.9, while the efficiency of other provinces has been below 0.9 for quite a long time. At the regional level, the Yangtze River Delta is the most effective area, while the Yellow River Basin is the most ineffective area. In consideration of this, we provide specific strategies for improving PCE of each province, from three aspects of increasing the capital input, optimizing the scale structure, and upgrading technology level.
引用
收藏
页码:998 / 1009
页数:12
相关论文
共 48 条
[1]  
[Anonymous], 2009, MEASURING CAPITAL OE, V2nd, DOI DOI 10.1787/9789264068476-EN
[2]  
Baldwin J., 2005, Estimating depreciation rates for the productivity accounts
[3]   A metafrontier production function for estimation of technical efficiencies and technology gaps for firms operating under different technologies [J].
Battese, GE ;
Rao, DSP ;
O'Donnell, CJ .
JOURNAL OF PRODUCTIVITY ANALYSIS, 2004, 21 (01) :91-103
[4]   Air pollution, environmental perceptions, and citizen satisfaction: A mediation analysis [J].
Chen, Longjin ;
Zhang, Junling ;
You, Yu .
ENVIRONMENTAL RESEARCH, 2020, 184
[5]   Effects of population and affluence on CO2 emissions [J].
Dietz, T ;
Rosa, EA .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 1997, 94 (01) :175-179
[6]   Measuring and explaining eco-efficiencies of wastewater treatment plants in China: An uncertainty analysis perspective [J].
Dong, Xin ;
Zhang, Xinyi ;
Zeng, Siyu .
WATER RESEARCH, 2017, 112 :195-207
[7]   Journey for green development transformation of China's metal industry: A spatial econometric analysis [J].
Feng, Chao ;
Wang, Miao .
JOURNAL OF CLEANER PRODUCTION, 2019, 225 :1105-1117
[8]   Evaluating the efficiency of industrial environmental regulation in China:A three-stage data envelopment analysis approach [J].
Feng, Mei ;
Li, Xinyi .
JOURNAL OF CLEANER PRODUCTION, 2020, 242 (242)
[9]   Comprehensive evaluation of benefits from environmental investment: take China as an example [J].
Feng, Qiang ;
Sun, Tao .
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2020, 27 (13) :15292-15304
[10]   Accounting for environmental effects and statistical noise in data envelopment analysis [J].
Fried, HO ;
Lovell, CAK ;
Schmidt, SS ;
Yaisawarng, S .
JOURNAL OF PRODUCTIVITY ANALYSIS, 2002, 17 (1-2) :157-174