摘要
农产品价格波动对城乡居民生活和社会经济发展有着深远影响。以我国农产品生产价格指数中的油料生产价格指数为例,探究我国农产品价格的影响因素。选取气候变化、人口增长等13个维度的34个影响因子,分别使用LASSO回归和随机森林算法定量揭示因子对农产品价格的影响程度,结果表明:东部气温变化和消费者价格指数对价格波动有正向影响,日照时数变化、货物周转总量、国际石油价格、新冠疫情对农产品价格波动有负向影响。基于此,应积极应对气候变化风险,提高农产品流通系统运行效率,加强农产品运输基础设施建设,宏观调控农产品价格。
The price fluctuation of agricultural products has a profound impact on the life of urban and rural residents and social and economic development.Taking the oilseed producer price index in China's agricultural product producer price index as an example,this paper explores the influencing factors of agricultural product prices.This paper selects 34 influencing factors in 13 dimensions such as climate change and population growth,and uses LASSO regression and random forest algorithm to quantitatively reveal the impact of factors on agricultural product prices.The results show that:temperature changes in the east and the consumer price index have a positive impact on price fluctuations,and changes in sunshine hours,total cargo turnover,international oil prices,and the new crown epidemic have negative impacts on agricultural product price fluctuations.Based on this,we should actively respond to the risk of climate change,improve the operating efficiency of the agricultural product circulation system,strengthen the construction of agricultural product transportation infrastructure,and macro-control the price of agricultural products.
作者
谷政
张悦
GU Zheng;ZHANG Yue
出处
《价格理论与实践》
北大核心
2023年第4期122-126,共5页
Price:Theory & Practice
基金
江苏省研究生科研与实践创新计划项目“得分驱动多元GARCH波动率模型及其应用研究”研究成果(项目编号:KYCX21_1855)
关键词
农产品
价格风险
机器学习
LASSO回归
随机森林
agricultural product
price risk
machine learning
LASSO regression random forest
