Evaluation, Regional Disparities and Driving Mechanisms of High-Quality Agricultural Development in China

Based on China’s new development philosophy and the connotation of high-quality agricultural development, this study constructed a six-dimensional comprehensive evaluation framework: innovation-effectiveness-sustainability-coordination-openness-sharing. The spatio-temporal-range-improved entropy app...

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Bibliographic Details
Published in:Sustainability 2023-04, Vol.15 (7), p.6328
Main Authors: Wang, Yaoyao, Kuang, Yuanpei
Format: Article
Language:English
Subjects:
Agribusiness
Agricultural development
Agricultural industry
Agriculture
Economic development
Efficiency
Evaluation
Forecasts and trends
Heterogeneity
Industrial productivity
Innovations
Modernization
Productivity
Regional development
Regions
Rural areas
Service industries
Social change
Sustainability
Sustainable development
Variables
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Summary:Based on China’s new development philosophy and the connotation of high-quality agricultural development, this study constructed a six-dimensional comprehensive evaluation framework: innovation-effectiveness-sustainability-coordination-openness-sharing. The spatio-temporal-range-improved entropy approach and the Dagum Gini coefficient were applied to evaluate and analyze the level of regional disparities and the dynamic distribution characteristics of high-quality agricultural development in China in the period from 2010 to 2018. The result shows that the level of high-quality agricultural development in China has steadily improved in general, but there exist prominent structural problems. Concerning regional differences, it indicated a pattern dominated by the pattern of “high in the east and low in the west”, mainly arising from the inter-regional disparity, with a gradual downward trend during the selected period. This study also comprehensively explored the four-dimensional driving mechanisms (production conditions, productivity, production relations, and production efficiency), and further examined the driving paths of various variables and regional heterogeneity using a panel Tobit model.
ISSN:2071-1050
2071-1050
DOI:10.3390/su15076328