Abstract
The growth of vehicle ownership not only brings opportunity for the economy, but also brings environment and transport problems, which is not good for sustainable transportation. It is of great significance to build supporting infrastructure and other services based on accurate forecasts of vehicle ownership in various provinces because of the variance of economic development stages, the carrying capacity of resources, and different degrees of transport planning in each province. We used the Gompertz model in order to predict China’s provincial vehicle ownership from 2018 to 2050. Considering the impact of the population structure, we summed up the growth rate of GDP per labor, the growth rate of population and the growth rate of employment rate to get the growth rate of GDP and then the GDP per capita of each province. We found that the vehicle ownership in each province will grow rapidly in the next 30 years; however, the change in the ranking of vehicle ownership among provinces varies. The ranking of some provinces with high or middle ranking now will decline in the following years, especially Beijing, Tianjin, Shanghai and Xinjiang. While the ranking of some provinces that locates in the middle and low ranking now will increase, such as Chongqing, Hubei, Anhui, Sichuan, Heilongjiang, Jiangxi, Hunan and Guangxi. We also investigate the reasons that affect the trend in each province and we find that the suitable vehicle growth pattern of each province, the stage of economic development and government policy, which are related to the growth rate of GDP per labor, employment rate, and GDP per capita, can affect vehicle ownership in the future.
Highlights
We used the method in Bai and Zhang [16] to estimate the GDP per capita of each province, and estimated the vehicle ownership per thousand people of each province until 2050
Our results show that due to the different vehicle growth model and growth rate of GDP per capita, the trend and ranking of vehicle ownership in different provinces will vary in the future
The difference in economic development stages, the impact of artificial intelligence and the ageing process lead to a difference in GDP per labor and the employment rate, and lead to a difference in GDP per capita
Summary
The process of economic development around the world has shown that the demand for vehicles, which include the passenger cars, buses, lorries and vans, increases with growth of the economy. The government uses different policies in different provinces, for example, large, developed cities like Beijing, Shanghai, Hangzhou, Guangzhou, and Shenzhen have announced different kinds of vehicle-purchasing limitations to avoid problems that come from excessive consumption [15], e.g., policy of a rigidly limited quota of car licenses, car license auction policy and policy of allocating vehicle indicators by lottery. It is of great significance to build supporting infrastructure and other services based on accurate vehicle ownership forecasts in various provinces
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