01657888

Component

In order to examine the determinants of city-level private car ownership in China, a panel data of 212 target cities in China are collected for a period from 2006 to 2015. Nine variables including economic characteristics, urban characteristics, and transportation characteristics of cities are selected as possible explanatory variables. Pooled regression model, fixed effect model and random effect model are adopted and compared by fitting the panel data. The results of the Hausman test indicate that the fixed effect model should be used to explain the effect of determinants on private car ownership. Among them, gross domestic product per capita, average income of employed workers, urbanization, highway density and number of taxis per 10,000 population have significant positive effects on private car ownership. In addition, a geographically weighted regression (GWR) model is employed to explore the effects of geographical locations of target cities on private car ownership by fitting the data of 2015. The results show that regression coefficients vary across different geographical regions, indicating that a city should not simply copy the other cities’ strategies to control the private car ownership even if the strategies are effective in those cities because the influencing factors could be different across cities. The study results can provide reference for making policies for controlling private car ownership.

This paper was sponsored by TRB committee ADD20 Standing Committee on Social and Economic Factors of Transportation.

18-04131

English

6p

2018

Transportation Research Board 97th Annual Meeting

Digital/other

References; Tables

Automobile ownership; Data analysis; Panel studies; Regression analysis; Urban transportation

China

Economics; Highways; Society; Vehicles and Equipment

Transportation Research Board Annual Meeting 2018 Paper #18-04131

TRIS, TRB, ATRI

Jan 8 2018 11:01AM