Multiple Regression Analysis of the Factors Influencing the Sales of New Energy Vehicles in China

In recent years, the global climate crisis and energy crisis have become increasingly serious, prompting countries to strongly support the development of clean energy technology. New energy vehicles represent a significant avenue for transforming and upgrading the automobile industry worldwide, offering environmental protection and energy-saving advantages. This thesis addresses the vital factors influencing the volume of new energy vehicle sales in China. Within an empirical research framework, multiple regression analysis is used. This study begins with the background of the new energy vehicle market, recognizing factors such as policy incentives, technological progress, and charging infrastructure improvements, and then proposes research hypotheses. By collecting relevant data, the study uses multiple linear regression models to evaluate the influence of various factors on both the demand and supply sides of sales. The results show that the amount of subsidy in vehicle purchases and charging time significantly affects sales, while factors like price and technological progress do not hold as much weight. Based on these findings, the thesis suggests policy recommendations such as increasing and improving vehicle purchase subsidies and enhancing charging facilities for the healthy development of the new energy vehicle industry. Finally, the limitations of this study, such as the limited data scope, the problem of multicollinearity, and the failure to consider the effects of external macroeconomic factors, are summarized. The paper concludes with a discussion of potential avenues for future research.