我国猪肉消费需求量集成预测--基于ARIMA、VAR和VEC模型的实证  

Integration forecast of Chinese pork consumption demand——Empirical based on ARIMA、VAR and VEC models

作　　者：郑莉[1] 段冬梅[2] 陆凤彬[1] 许伟[2] 杨翠红[1] 汪寿阳[1] 

机构地区：[1]中国科学院数学与系统科学研究院管理、决策与信息系统重点实验室,北京100190 [2]中国人民大学信息学院,北京100872

出　　处：《系统工程理论与实践》2013年第4期918-925,共8页Systems Engineering-Theory & Practice

基　　金：国家科技支撑计划课题(2009BADA9BB01);国家自然科学基金(70871108,71001096,71001103)

摘　　要：猪肉消费需求量预测对稳定猪肉消费市场具有重要意义.通过建立ARIMA、VAR和VEC模型,利用Granger因果检验筛选出显著影响因素,分别预测我国猪肉消费量.最后,基于动态集成预测方法对三种模型的预测结果进行综合集成.通过对2009-2011年我国猪肉消费需求量预测,实证结果表明样本外集成预测精度更高,更稳定.Forecasting pork consumption is very important to stabilize the pork market. By using Granger causality test to choose significant factors, we forecasted China＇s pork consumption with ARIMA. VAR and VEC model respectively. Based on a dynamic integration method, we integrated the forecast results of three models above. Finally, empirical results show that the dynamic integration method is more accurate and stable by forecasting China＇s pork consumption from 2009 to 2011 with the four methods above.

关 键 词：猪肉消费需求 集成预测 ARIMA模型 VAR模型 VEC模型 

分 类 号：F224[经济管理—国民经济] F304.3