Vehicle Characteristics and Their Association with US Electric Vehicle Prices, Model Year 2025 | RISE Research

This paper investigates which vehicle characteristics are associated with electric vehicle prices in the US market, using data on 108 battery electric vehicle configurations across 22 manufacturers from the 2025 model year, sourced from the Alternative Fuels Data Center. Using a progression of four OLS regression models plus decision tree and random forest models for comparison, the study tests whether battery capacity, driving range, DC fast charging rate, and fuel economy predict base MSRP, and how these relationships change once manufacturer, vehicle type, drivetrain, and motor configuration are controlled for. In the simplest model, battery capacity alone explains 28.2% of price variation and shows a strong, significant positive relationship with price. However, once fixed effects for manufacturer and vehicle segment are added, the model's explanatory power jumps to 93.5% and battery capacity's coefficient collapses to statistically insignificant, revealing that the earlier battery-price relationship was really capturing brand and segment differences. Driving range, despite being one of the most heavily marketed EV specifications, never shows an independent, significant relationship with price once battery capacity is controlled for, since the two variables are highly collinear. DC fast charging rate and fuel economy remain the only vehicle-level technical features that consistently and independently predict price across specifications. A CART decision tree, cross-validated against OLS and a random forest model, confirms manufacturer identity as the single strongest predictor of price, with the random forest achieving the best out-of-sample fit (R-squared = 0.911). The paper concludes that brand identity and positioning, not raw technical specifications like range, are the dominant force in EV pricing, suggesting that manufacturer marketing and consumer perception diverge from the actual mechanics of price formation in this market.