摘要
社会消费品零售总额是反映人们消费水平的重要度量指标,也是国民经济体系中的一个重要评价指标.因此,分析研究社会消费品零售总额发展趋势对于转型期的中国经济高质量发展具有重要意义.基于乘积季节模型对2001年至2020年的社会消费品零售总额数据进行时间序列分析,经过差分、单位根检验、模型识别与拟合等过程,确定最终模型为ARIMA(1,1,1)(1,1,0)12,结果表明,社会消费品零售总额数据具有明显的线性趋势和季节性特征,并进一步得出其波峰和波谷到达的时间,另外,该模型对社会消费品零售总额有非常好的拟合效果,且有较高的预测精度.
The total retail sales of consumer goods is not only an important measure to reflect people’s consumption level,but also an important evaluation index in the national economic system.Therefore,it is of great significance to analyze and study the development trend of total retail sales of social consumer goods for the high-quality development of China’s economy in the transitional period.Based on the product seasonal model,this paper analyzes the total retail sales data of social consumer goods from 2001 to 2020.Through the methods of difference,unit root test,model identification and fitting,the final model is ARIMA(1,1,1)(1,1,0)12.The results show that the data of total retail sales of social consumer goods has obvious linear trend and seasonal characteristics,and further obtains the arrival time of wave crest and trough.In addition,the model has a very good fitting effect on the total retail sales of social consumer goods,and the model has a high prediction accuracy.
作者
马强
张琛婕
陈雪平
张孔生
MA Qiang;ZHANG Chen-jie;CHEN Xue-ping;ZHANG Kong-sheng(School of Mathematics and Physics,Jiangsu University of Technology,Changzhou 213001,China;School of Statistics and Applied Mathematics,Anhui University of Finance and Economics,Bengbu 233030,China)
出处
《数学的实践与认识》
2021年第6期87-94,共8页
Mathematics in Practice and Theory
基金
国家自然科学基金(11971204)
江苏省自然科学基金(BK20200108)
教育部人文社科青年基金(19YJCZH250)
安徽省教育厅高校自然科学研究项目(KJ2017A433)。
关键词
社会消费品
季节模型
差分
单位根检验
Social consumer goods
seasonal model
difference
unit root test