Evolving Trends and Influencing Factors of the Rural Green Development Level in Chongqing

Kangwen Zhu, Dan Song, Lanxin Zhang, Yong He, Sheng Zhang, Yaqun Liu () and Xiaosong Tian ()
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Kangwen Zhu: School of Smart City, Chongqing Jiaotong University, Chongqing 400074, China
Dan Song: Chongqing Academy of Eco-Environmental Sciences (Southwest Branch of Chinese Academy of Environmental Sciences), Chongqing 401147, China
Lanxin Zhang: College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
Yong He: School of Smart City, Chongqing Jiaotong University, Chongqing 400074, China
Sheng Zhang: Chongqing Academy of Eco-Environmental Sciences (Southwest Branch of Chinese Academy of Environmental Sciences), Chongqing 401147, China
Yaqun Liu: Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Xiaosong Tian: School of Resources and Safety Engineering, Chongqing Vocational Institute of Engineering, Chongqing 402260, China

Land, 2023, vol. 12, issue 7, 1-17

Abstract: Rural green development is a concrete practice of rural revitalization. Currently, research on quantitative evaluation methods for rural green development levels are not well developed. In this study, an evaluation model of the rural green development level in Chongqing City, China was developed based on the parameters of ecology, living, and production. An entropy weight method, Theil index, optimal scale regression model, and GIS were used to analyze the spatio-temporal characteristics, trends, and influencing factors of the rural green development level from 2018 to 2020 in Chongqing City. The results showed that: (1) the overall “ecology, living, and production” dimensions and the comprehensive index of the development level in the city were generally increasing, and the proportion of counties at a high-level increased from 23.68% in 2018 to 81.58% in 2020; (2) the Theil index of the city in was 0.0185, 0.0121, and 0.0114 in 2018, 2019, and 2020 respectively, indicating that the differences in development level among regions decreased as the development level increased; (3) the level of rural green development showed a clear upwards trend, and the proportion of counties with low-speed growth, medium-speed growth, and high-speed growth from 2018 to 2020 was 5.26%, 81.58%, and 13.16%, respectively; and (4) the optimal scale regression analysis showed that the factors with greater impacts on the rural green development level are social security and employment expenditure level of government finance, health expenditure level of government finance, with their contributions is 40.3% and 26%, respectively. The results from this study demonstrate the significance of exploring research methods for rural green development and ways to improve the level of rural green development.

Keywords: Chongqing; green development; Theil index; optimal scale regression analysis; GIS (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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