经济学报2026，Vol.13Issue(3)：122-140,19.
中国大豆产业链需求弹性分析与仿真模拟
Elasticity Analysis and Simulation of Demand in China's Soybean Industry Chain
摘要
Abstract
Under the background of the big food view,it necessary to explore the diversification of protein feed sources.This paper analyzes the market competition structure of soybean from the perspective of industrial chain,calculates the price demand elasticity of soybean meal and other protein feed raw materials,soybean oil and other vegetable oil,and analyzes the deep-seated reasons for the rigidity of soybean demand.Based on system dynamics,the soybean demand system was constructed and simulated.The effects of soybean meal reduction and substitution,domestic soybean production capacity improvement,and diversification of import sources on reducing soybean external dependence were analyzed through scenario simulation.The main conclusions are as follows.1.There is a mismatch between supply and demand in the protein feed market.The proportion of soybean meal in the protein feed raw materials has increased year by year,squeezing the market share of other protein feeds.Compared with soybean meal,other protein feeds are more rigid in demand.2.The demand for soybean meal is the main factor causing the rigidity of soybean demand.Soybean meal-induced demand for soybeans has been much larger than soybean oil-induced demand for soybeans after 2019.And the substitutability of other protein feeds for soybean meal is poor,while there is strong substitutability between soybean oil and other vegetable oils.3.The demand for soybeans and their by-products in China has peaked and entered the stage of structural adjustment.Reducing the proportion of soybean meal in protein feed and increasing the yield and planting area can effectively improve the self-sufficiency rate of soybean.This paper has practical reference value in exploring the space and path of diversified sources of soybean and its by-products.关键词
大豆需求/大豆产业链/市场竞争结构/蛋白饲料市场分类
生物科学引用本文复制引用
章少宾,杨惠媛,石宝峰..中国大豆产业链需求弹性分析与仿真模拟[J].经济学报,2026,13(3):122-140,19.基金项目
本研究受国家重点研发计划课题"大宗商品价格风险监测评估与预警技术及平台"(2023YFC3305104)的资助. （2023YFC3305104）
