Environmental information disclosure and green energy efficiency: A spatial econometric analysis of 113 prefecture-level cities in China

被引:16
作者
Du, Lei [1 ]
Wang, Fuwei [1 ]
Tian, Minghua [1 ]
机构
[1] Beijing Forestry Univ, Sch Econ & Management, Beijing, Peoples R China
关键词
environmental information disclosure; green energy efficiency; super-efficiency SBM model with undesirable outputs; spatial Durbin model; prefecture-level cities; PANEL-DATA;
D O I
10.3389/fenvs.2022.966580
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
As one of the means of informal environmental regulation, environmental information disclosure has an essential impact on improving green energy efficiency. This paper selects the panel data of 113 environmental information disclosure cities in China from 2008 to 2018 and uses the Super-efficiency SBM model with undesirable outputs to measure green energy efficiency. Based on the measurement results, this paper empirically studies the impact of environmental information disclosure on green energy efficiency and its spatial spillover effect using the spatial Durbin model. The main conclusions are as follows: 1) From 2008 to 2018, the average green energy efficiency of 113 environmental information disclosure cities in China was 0.6676, and the regional distribution showed the characteristics of "high in the East and low in the west. " 2) Both environmental information disclosure and green energy efficiency have significant spatial correlation and show the characteristics of "high-high " and "low-low " agglomeration in spatial distribution. 3) Environmental information disclosure can significantly improve green energy efficiency in the region and surrounding areas. After the robustness test and endogenous test, the conclusion is still robust. 4) The impact of environmental information disclosure on green energy efficiency in the eastern region is significantly more significant than in the central and western regions. This paper provides a theoretical reference for the government to formulate corresponding environmental policies to promote green energy efficiency and promote green and sustainable economic development.
引用
收藏
页数:19
相关论文
共 46 条
[1]   SPATIAL STATISTICAL-ANALYSIS AND GEOGRAPHIC INFORMATION-SYSTEMS [J].
ANSELIN, L ;
GETIS, A .
ANNALS OF REGIONAL SCIENCE, 1992, 26 (01) :19-33
[2]   SOME TESTS OF SPECIFICATION FOR PANEL DATA - MONTE-CARLO EVIDENCE AND AN APPLICATION TO EMPLOYMENT EQUATIONS [J].
ARELLANO, M ;
BOND, S .
REVIEW OF ECONOMIC STUDIES, 1991, 58 (02) :277-297
[3]   Initial conditions and moment restrictions in dynamic panel data models [J].
Blundell, R ;
Bond, S .
JOURNAL OF ECONOMETRICS, 1998, 87 (01) :115-143
[4]   Does environmental information disclosure improve energy efficiency? [J].
Bu, Caiqi ;
Zhang, Kaixia ;
Shi, Daqian ;
Wang, Shuyu .
ENERGY POLICY, 2022, 164
[5]   The impact of environmental regulation, shadow economy, and corruption on environmental quality: Theory and empirical evidence from China [J].
Chen, Heyin ;
Hao, Yu ;
Li, Jingwei ;
Song, Xiaojie .
JOURNAL OF CLEANER PRODUCTION, 2018, 195 :200-214
[6]   Understanding the green total factor energy efficiency gap between regional manufacturingdinsight from infrastructure development [J].
Chen, Yu ;
Lin, Boqiang .
ENERGY, 2021, 237
[7]   Environmental regulation and green energy efficiency: an analysis of spatial Durbin model from 30 provinces in China [J].
Du, Lei ;
Tian, Minghua ;
Cheng, Junguo ;
Chen, Wanzhe ;
Zhao, Zeyu .
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2022, 29 (44) :67046-67062
[8]  
Elhorst JP, 2014, SPRINGERBR REG SCI, P37, DOI 10.1007/978-3-642-40340-8_3
[9]   How does environmental information disclosure affect economic development and haze pollution in Chinese cities? The mediating role of green technology innovation [J].
Feng, Yanchao ;
Wang, Xiaohong ;
Liang, Zhou .
SCIENCE OF THE TOTAL ENVIRONMENT, 2021, 775
[10]   Effects of environmental regulation and FDI on urban innovation in China: A spatial Durbin econometric analysis [J].
Feng, Yanchao ;
Wang, Xiaohong ;
Du, Wenchao ;
Wu, Hongyu ;
Wang, Jintao .
JOURNAL OF CLEANER PRODUCTION, 2019, 235 :210-224