摘要
文章首先论述了中长期粮食需求预测的战略意义和科学意义,然后从中国粮食消费的特点和趋势、粮食消费的主要影响因素、粮食需求总量预测方法、分类粮食需求量预测方法四个方面对国内外研究现状进行了综述.进一步对已有研究的预测结果存在很大差异和较高误差的原因进行了总结.一是对中长期不同地区、不同收入水平的居民膳食结构的变化规律往往难以把握,而且高度聚集的粮食(食物)分类掩盖了居民膳食结构变化这一重要趋势,影响到了预测精度.二是模型中对粮食需求的主要影响因素考虑不全面,未能够将人口年龄结构、性别结构、膳食结构、收入水平、食物生产转化、食物浪费等影响粮食需求的关键因素整合起来量化分析.三是需求系统中收入水平、价格弹性、动物性食物和饲料粮之间的转化率、消费阶段粮食的浪费率等设置的差异、居民在外就餐的忽略或简单估计,造成模型预测值的较大差异.最后,对中长期粮食需求预测研究提出如下展望.第一,需要构建跨领域多学科融合的理论体系,更加关注新趋势、新因素及跨学科跨部门关键因素的整合.第二,注重相关数据的统计和校准,结合文本挖掘、机器学习等数据处理方法,充分发挥多源数据在预测中的作用.第三,模拟仿真人口政策、粮食价格、税收和补贴政策等变化对中长期粮食需求和粮食安全的影响,为中长期粮食供给的恰当方案提供政策依据.
This paper first discusses the strategic and scientific significance of forecasting medium-and long-term grain demand.Then it summarizes the current status of domestic and foreign research from four aspects,including the characteristics and trends of grain consumption in China,the main impacting factors of grain consumption,the forecasting methods for the total grain demand,and categorical grain demand.Then the paper analyzes the reasons that lead to the apparent differences among the existing prediction results and unsatisfied forecasting accuracy.First,it is difficult to grasp the changing patterns of residents’ dietary structure in the medium and long term in different regions with various income levels.And the highly aggregated grain(food) classifications cover up the critical trends of the changing dietary structure of residents.These affected the prediction accuracy.Second,the main impacting factors of grain demand were not comprehensively considered and quantitatively analyzed in the models,such as the age and gender structure of the population,dietary structure,income level,food production transition,food waste,etc.Third,the differences in designed income level,price elasticity,the conversion rate from feed grains to animal foods,food waste rate at the consumption stage,and the neglect or simple estimation of residents’ eating out had caused significant differences in prediction results.Finally,this paper puts forward the following outlook on medium and long-term grain demand forecasting research.1) Some interdisciplinary and cross-sectoral frameworks should be established.More attention should be paid to new trends,impacting factors of grain demand,and integrating key factors of interdisciplinary and cross-sectoral frameworks.2) Emphasis should be placed on combining text mining,machine learning,and other data processing methods for statistics and calibration of relevant data,and giving full play to the role of multisource data in forecasting.3) Based on the forecasting model for grain demand,we shou
作者
刘秀丽
相鑫
秦明慧
窦羽星
LIU Xiuli;XIANG Xin;QIN Minghui;DOU Yuxing(Academy of Mathematics and Systems Science,Chinese Academy of Sciences,Beijing 100190;Center for Forecasting Science,Chinese Academy of Sciences,Beijing 100190;University of Chinese Academy of Sciences,Beijing 100049)
出处
《系统科学与数学》
CSCD
北大核心
2022年第6期1490-1502,共13页
Journal of Systems Science and Mathematical Sciences
基金
国家自然科学基金面上项目(71874184)
中国科学院重点部署项目“新时期国民营养与粮食安全研究”资助课题。
关键词
粮食需求
中长期预测
影响因素
综述
展望
Demand for grain
the medium-and long-term forecasting
impacting factors
review
outlook
