Chinese automobile sales forecasting using economic indicators and typical domestic brand automobile sales data: A method based on econometric model

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 time-series 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.

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