Automotive industry structure

Forecasting sales and need over 6–24 thirty days horizon is vital for planning the production processes of automotive and other complex item sectors (e.g., electronics and hefty equipment) where typical concept-to-release times are 12–60 thirty days long. But nonlinear and nonstationary advancement and dependencies with diverse macroeconomic factors hinder precise long-term prediction into the future of automotive product sales. In this report, a structural commitment recognition methodology that utilizes a battery of statistical unit root, weakly exogeneity, Granger-causality and cointegration tests, is presented to recognize the powerful couplings among vehicle product sales and financial indicators. Our empirical evaluation shows that vehicle sales at section levels have actually a long-run equilibrium relationship (cointegration) with identified economic indicators. A vector mistake modification design (VECM) of multi-segment automobile sales was expected considering impulse reaction features to quantify long-term effect among these financial signs on sales. Reviews of forecast accuracy illustrate that VECM model outperforms other classical and higher level time-series strategies. The empirical results suggest that VECM can considerably improve prediction accuracy of automotive sales for 12-month ahead prediction in terms of RMSE (42.73per cent) and MAPE (42.25percent), when compared to classical time series practices.

Keywords

• Vehicle sales forecasting;
• Long-run equilibrium commitment;
• Vector mistake correction model