Research on Evaluation Elements of Urban Agricultural Green Bases: A Causal Inference-Based Approach

Yuchong Long, Zhengwei Cao (), Yan Mao, Xinran Liu, Yan Gao, Chuanzhi Zhou and Xin Zheng
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Yuchong Long: College of Agriculture and Biology, Shanghai Jiao Tong University, Dongchuan Street, Minhang District, Shanghai 200240, China
Zhengwei Cao: College of Agriculture and Biology, Shanghai Jiao Tong University, Dongchuan Street, Minhang District, Shanghai 200240, China
Yan Mao: Institute for Public Policy, Zhejiang University, Hangzhou 310058, China
Xinran Liu: College of Agriculture and Biology, Shanghai Jiao Tong University, Dongchuan Street, Minhang District, Shanghai 200240, China
Yan Gao: College of Agriculture and Biology, Shanghai Jiao Tong University, Dongchuan Street, Minhang District, Shanghai 200240, China
Chuanzhi Zhou: College of Agriculture and Biology, Shanghai Jiao Tong University, Dongchuan Street, Minhang District, Shanghai 200240, China
Xin Zheng: College of Agriculture and Biology, Shanghai Jiao Tong University, Dongchuan Street, Minhang District, Shanghai 200240, China

Land, 2023, vol. 12, issue 8, 1-27

Abstract: The construction of agricultural green bases is an important part of sustainable agricultural development. This paper takes urban agriculture green bases in Shanghai as an example, choosing base construction elements, production, and ecological construction elements, as well as status assessment elements as evaluation indicators, in order to construct an evaluation system for urban agriculture green bases. Using a Bayesian network, typical urban agricultural green bases in six agricultural districts of Shanghai were evaluated. The construction of the evaluation system was analyzed by using intervention, counterfactual inference, and other methods to analyze the correlation and importance of the indicators. The results show that there are differences among the bases in various indicators, but they all reach a high level overall; base construction elements as well as production and ecological construction elements are the main factors affecting the level of urban agricultural green bases; improving the base management system (BMS), innovativeness (IN), and economic benefits (EBs) are key ways to improve the production capacity of agriculture green bases. Green base construction should pay attention to top-level design, coordinate the planning of industrial layout, technical mode, scientific and technological support, and supporting policies. Based on the conclusion, this paper provides some useful recommendations for creating urban agriculture green bases, which help promote urban agriculture transformation, upgrading, and coordinating development between urban and rural areas.

Keywords: urban agriculture; green base evaluation; Bayesian network; causal inference (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2023
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