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中国农产品贸易逆差影响因素实证分析

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农产品贸易在中国经济发展、"三农"问题以及推动乡村振兴发展等方面具有重要作用,研究中国农产品贸易逆差影响因素具有重要的现实意义.本研究选取农产品国内供给、国内需求、国外需求以及农产品进口价格等 8个指标,基于 2005-2021 年相关数据,运用灰色关联分析法选出关联度居前 3 位的变量建立岭回归模型.结果表明:农产品国内供给与国内需求对中国农产品贸易逆差均有正向影响,农产品贸易竞争力对中国农产品贸易逆差具有负向影响.中国属于农业大国,农业是根本性产业,但近年来中国农产品出口优势不断减弱,贸易逆差逐渐上升,这对中国经济发展与国家安全具有一定的威胁.基于此,提出发挥中国农产品优势、推动科技发展,提升国际竞争力、加大对农产品走出去支持力度等对策建议.
An Empirical Analysis of the Influencing Factors of China's Agricultural Trade Deficit
Agricultural trade plays an important role in China's economic development,the issues of agriculture,rural areas and farmers,and the promotion of rural revitalization and development,so it is of great practical significance to study the factors affecting China's agricultural products trade deficit.Eight indexes,including domestic supply,domestic demand,foreign demand and import price of agricultural products,were preliminarily selected,relevant data from 2005 to 2021 were calculated,and the top three variables with correlation degree were selected by the gray correlation analysis to establish a ridge regression model.The results show that the domestic supply and domestic demand of China's agricultural products have a positive impact on China's agricultural products trade deficit,and the competitiveness of agricultural products trade has a negative impact on China's agricultural products trade deficit.China belongs to a big agricultural country,agriculture is China's fundamental industry,but in recent years,China's agricultural export advantages have been weakening,and the trade deficit has gradually risen,which poses a certain threat to China's economic development and national security.Therefore,according to the results of the analysis,countermeasures and suggestions were put forward to give full play to the advantages of China's agricultural products,promote the development of science and technology,enhance international competitiveness,and increase support for agricultural products going global.

agricultural productstrade deficitgray correlation analysisridge regression modelinfluencing factors

邹芸姿、邹再进、王之曦、罗蔓玉

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西南林业大学经济管理学院 云南 昆明 650224

农产品 贸易逆差 灰色关联分析 岭回归模型 影响因素

西南林业大学校级科研专项

112124

2024

农业展望
中国农业科学院农业信息研究所

农业展望

影响因子:0.713
ISSN:1673-3908
年,卷(期):2024.20(4)
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