01697407

Component

With rapid auto growth, many Chinese municipalities implemented car restriction policies. Research identified several groups of underlying factors that possibly prompted the municipalities to adopt the policies, but no study has yet systematically evaluated these factors. The authors collected a panel dataset for all 287 Chinese municipalities from 2001 to 2014, extracted information of car restriction policies from 116 legal documents and other online resources. Duration models were used to assess the statistical significance and the predictive accuracy of 14 indicators measuring economic power, population, air pollution, automobiles, urban density, and local transportation conditions in predicting the adoption of large-scale car restriction policies, supplemented by the cross-examination with text analysis of policy documents. The authors found that the adoption of large-scale car restriction policies primarily responded to air pollution and secondarily to motor per capita and congestion. Policy adoption responded to local subway line constructions, but not other transportation or land use conditions. Local economic power and population size cannot effectively explain policy adoption. Idiosyncratic effects at provincial or city levels were important, although the underlying mechanism was unclear. Broadly, the findings suggest that 1) Chinese municipalities were partially rational in making policies to address local problems; 2) legal documents were reliable to illustrate the real motivations of policies.

This paper was sponsored by TRB committee ABE90 Standing Committee on Transportation in the Developing Countries.

19-05443

English

0000-0003-4374-8193

0000-0002-1929-7583

5p

2019

Transportation Research Board 98th Annual Meeting

Digital/other

References

Air pollution; Automobiles; Cities and towns; Policy analysis; Traffic congestion; Traffic restraint

Vehicle restrictions

China

Highways; Operations and Traffic Management; Policy

Transportation Research Board Annual Meeting 2019 Paper #19-05443

TRIS, TRB, ATRI

Dec 7 2018 9:26AM