discuss whether or not an increase in car ownership will improve living standard in China
Answers
Therefore, many researches have been done to analyze and predict the development trends of vehicle sales or stock, and some are used as the basic assumption for further studies, like energy consumption or GHG emissions of vehicle fleet. Some studies found the laws and provided the prediction of vehicle stock in household level, because data are relatively comprehensive and available from household surveys and it could point out regional differences [5–8]. Meanwhile, some researches are focused on national level analyzation, and some China cases have been analyzed in the provincial level [9–20]. These ones are based on fewer variables and made the prediction from a macroperspective without much consideration of diversities in individual behavior.
Most of the researches are based on economic development level, as shown in Table 1 [5–23]. Vehicle ownership per thousand people is almost always mentioned with gross domestic production (GDP) per capita [10, 11, 16–20]. It is treated as a reliable variable to forecast vehicle growth curve. However, the previous studies always only included positive factors, like economic index, population, urbanization level, and so on, and ignored the limitation factors in vehicle stock.
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The Impact of Purchase Restriction Policy on Car Ownership in China’s Four Major Cities
Feiqi Liu,1,2 Fuquan Zhao,1,2 Zongwei Liu,1,2 and Han Hao 1,2,3
Abstract
With the improvement of living standards, the demand for residents’ travel has grown rapidly. At present, China has surpassed the U.S. to become the world’s largest vehicle sales country. By the end of 2018, there had been over 200 million private passenger cars in China. Meanwhile, the increase in the number of cars has also brought a series of other problems: energy consumption, air pollution, traffic congestion, etc. Therefore, some first-tier cities have successively introduced motor vehicle purchase restriction policies to constrain the surge of local private cars. However, existing researches have overemphasized the factors that promote the development of China’s motor vehicle market and ignored the importance of the purchase restriction policies. In this study, policies in Beijing, Tianjin, Shanghai, and Guangzhou are introduced, and their impacts on local private passenger car stock are analyzed. The results indicate that purchase restriction policies kept the car ownership per thousand people in these cities in a relatively stable level with growing economy. Therefore, as the number of cities with restriction policies increases, it is necessary to take those policies into consideration in the forecast of possession. Meanwhile, the local governments should still think over policy contents from more aspects, like number of issued plates every year, special measures for new energy vehicles, and travel demand of residents.
1. Introduction
The development of vehicle industry leads to great concerns about life quality, energy, environment, infrastructure construction, etc. [1]. Vehicle sales and stock grow quickly with the surge of economy and life quality. Especially in developing countries, vehicles can not only meet the travel demand but also represent wealth and identity [2]. Therefore, more and more people become interested in vehicle ownership. Meanwhile, the rapid growth of vehicle stock (vehicle population) brings problems. Large amount of oil consumption has contributed to energy security and greenhouse gas (GHG) emissions. Based on the research of International Energy Agency (IEA), 20% GHG emissions come from road transportation in 2015 [3]. At the same time, traffic congestion becomes another critical problem. More and more time is wasted on daily commuting. According to the report from Beijing Transport Institute, in researches are based on economic development level, as shown in Table 1 [5–23]. Vehicle ownership per thousand people is almost always mentioned with gross domestic production (GDP) per capita [10, 11, 16–20]. It is treated as a reliable variable to forecast vehicle growth curve. However, the previous studies always only included positive factors, like