Traffic density, congestion externalities, and urbanization in China

ABSTRACT

Although there is an abundant regional literature analyzing traffic congestion, only a few studies have explored extending such analysis with spatial effects. This study uses a dynamic spatial Durbin model and city-level panel data for the period 2003–14 to investigate the spatial spillover effects of traffic congestion on urbanization in China. The results show that there is an inverted ‘U’-shaped relationship between urbanization and traffic density in local and neighbouring cities, and congestion effects have appeared. In the short and long run, the spatial effects of traffic congestion have become an important force restricting the effective promotion of urbanization in China.

KEYWORDS:

• traffic density
• congestion effect
• urbanization
• dynamic spatial Durbin model

JEL:

• J61
• O18
• R41

ACKNOWLEDGEMENTS

The authors gratefully acknowledge the Editor-in-Chief Paul Elhorst, and three anonymous referees for their constructive comments.

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the authors.

Notes

1 Auto Navigating Map is China’s leading digital map content, navigation and location service solution provider. Data are from http://report.amap.com/download.do/.

2 Under the hypothesis of classical NEG theory, the total amount of labour in city j can be obtained by solving the firm-maximization condition of the manufacturing firm, i.e., . Therefore, there is a one-to-one correspondence between the number in the urban labour force and the number of product varieties.

3 Han and Ke (2016) tested the effects of factor proximity and market potential on manufacturing output. They used different distance-decay parameters (δ = 1, 2, 3) to test the accessibility variables (including market potential) and found that the models were better fitted and the coefficients slightly more significant using δ = 1. Therefore, we set the distance attenuation parameter in the market potential to 1 in the present paper.

4 China’s important sea trade partners include the United States, Japan, Germany, France, the UK, South Korea, Australia, Hong Kong, Taiwan, Canada, Singapore, Malaysia etc. The important partners in land trade are Russia, India, Thailand, Vietnam, Laos, Kazakhstan, Pakistan, Kyrgyzstan, Tajikistan, Uzbekistan, Mongolia etc.

5 China’s major coastal port cities are Dandong, Dalian, Yingkou, Jinzhou, Qinhuangdao, Tangshan, Tianjin, Yantai, Weihai, Qingdao, Lianyungang, Zhenjiang, Nantong, Shanghai, Ningbo, Fuzhou, Xiamen, Shantou, Guangzhou, Zhongshan, Shenzhen, Zhuhai, Zhanjiang, Haikou and Sanya. Its main land port cities are Pingxiang, Dongxing, Kashgar, Alashankou, Mohe and Manzhouli.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [grant numbers 71603124, 71420107027, 71673083 and 71303076], the Natural Science Foundation of Jiangsu Province [grant number BK20161054], the Natural Science Foundation of the Jiangsu Higher Education Institutions [grant number 16KJB610009], the ‘Qing Lan Project’ of Outstanding Young Teachers Training Programme of Jiangsu, and the Science & Technology Department of Hunan Province in China [grant number 2015zk2002].