Incorporating multiple uncertainties into projections of Chinese private car sales and stock

Abstract

China is in a fast-growing stage of mobility development, and its increasing demand for private cars comes with growing energy consumption and pollutant emissions. Uncertainty in Chinese parameterization of car ownership models makes forecasting these trends a challenge. We develop an application of the Monte Carlo method, conditioned on historical data, to sample parameters for a model projecting aspects of private car diffusion, such as the mix of new and replacement sales. Our model includes changes in per-capita disposable income—both the mean and level of inequality—and a measure of car affordability. By incorporating multiple uncertainties, we show a distribution of possible future outcomes: a low stock of 280 million (1st decile); median of 430 million; and high of 620 million vehicles (9th decile) in 2050. This illustrates the limitations of attempts to model vehicle markets at the national level, by showing how uncertainties in fundamental descriptors of growth lead to a broad range of possible outcomes. While uncertainty in projected per-capita ownership grows continually, the share of first-time purchases in sales is most uncertain in the near term and then narrows as the market saturates. Replacement purchases increasingly capture the sales market from 2025. Our results suggest that stakeholders have a narrow window of opportunity to regulate the fuel economy, pollution and other attributes of vehicles sold to first-time buyers. These may, in turn, shape consumers’ experience and expectations of car ownership, affecting their additional and replacement purchases. ©2018