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个人信息Personal Information
副教授
硕士生导师
性别:男
毕业院校:大连理工大学
学位:博士
所在单位:力学与航空航天学院
学科:飞行器设计. 航空宇航制造工程. 人机与环境工程
办公地点:海涵楼320
联系方式:gaojunjie@dlut.edu.cn
电子邮箱:gaojunjie@dlut.edu.cn
Chinese automobile sales forecasting using economic indicators and typical domestic brand automobile sales data: A method based on econometric model
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论文类型:期刊论文
发表时间:2018-02-16
发表刊物:ADVANCES IN MECHANICAL ENGINEERING
收录刊物:SCIE、SSCI
卷号:10
期号:2
ISSN号:1687-8140
关键字:Econometric model; Chinese automobile sales forecasting; Chery sales; economic variables; vector auto-regression model; vector error correction model
摘要:Accurate sales forecasting plays an increasingly important role in automobile companies due to fierce market competition. In this article, an econometric model is proposed to analyze the dynamic connections among Chinese automobile sales, typical domestic brand automobile (Chery) sales, and economic variables. Four tests are required before modeling, which include unit root, weak exogeneity, cointegration, and Granger-causality test. The selected economic variables consist of consumer confidence index, steel production, consumer price index, and gasoline price. Monthly is used to empirical analysis and the result shows that there is long-term cointegration relationship between Chinese automobile sales and the endogenous variables. A vector error correction model in econometric based on cointegration is applied to quantify long-term impact of endogenous variables on Chinese automobile sales. Compared with other classical timeseries methods, root mean square error (0.1243) and mean absolute percentage error (10.2015) by vector error correction model for 12-period forecasting are minimal. And the forecasting result is better when the impact of Chery sales is considered. That means that the fluctuation trends of Chinese automobile sales and typical domestic brand automobile sales are closely linked.