scholarly journals The Marginal Cost of Traffic Congestion and Road Pricing: Evidence from a Natural Experiment in Beijing

2017 ◽  
Author(s):  
Shanjun Li ◽  
Jun Yang
Keyword(s):  
Traffic Congestion ◽  
Marginal Cost ◽  
Natural Experiment ◽  
Road Pricing

scholarly journals The Marginal Cost of Traffic Congestion and Road Pricing: Evidence from a Natural Experiment in Beijing

2020 ◽  
Vol 12 (1) ◽  
pp. 418-453 ◽  
Author(s):  
Jun Yang ◽  
Avralt-Od Purevjav ◽  
Shanjun Li
Keyword(s):  
Traffic Congestion ◽  
Natural Experiment ◽  
Road Pricing ◽  
Traffic Density ◽  
Traffic Data ◽  
City Center ◽  
Urban Centers ◽  
Restriction Policy ◽  
The Relationship ◽  
The City

Severe traffic congestion is ubiquitous in large urban centers. This paper provides the first causal estimate of the relationship between traffic density and speed and optimal congestion charges using real-time fine-scale traffic data in Beijing. The identification relies on plausibly exogenous variation in traffic density induced by Beijing’s driving restriction policy. Optimal congestion charges range from 5 to 39 cents per km depending on time and location. Road pricing would increase traffic speed by 11 percent within the city center and lead to an annual welfare gain of ¥1.5 billion from reduced congestion and revenue of ¥10.5 billion. (JEL H23, O18, P25, R41, R48)

Traffic Restraint as a Transport Planning Policy 1: A Framework for Analysis

1974 ◽  
Vol 6 (5) ◽  
pp. 565-601 ◽  
Author(s):  
M R Wigan
Keyword(s):  
Marginal Cost ◽  
Road Pricing ◽  
Theoretical Framework ◽  
Planning Program ◽  
Transport Planning ◽  
Planning Policy ◽  
The Subject ◽  
Practical Algorithm ◽  
Traffic Restraint ◽  
Convergence Stability

This paper summarises the program of work carried out at TRRL up to 1971 on traffic restraint treated as a policy for transport planning. The special techniques required were developed and are described here. The theoretical framework within which local traffic effects can be treated at a strategic level is developed using marginal cost road pricing as an example, and the necessarily stringent pricing establishing the convergence, stability, and repeatability of the results is described for a practical algorithm which can readily be used in other transport planning program systems. The application of these techniques to analyse the comparative effects of different traffic restraint policies, and the variations on the techniques required to handle several groups of travellers who react differently to restraint measures, are the subject of companion papers to appear later in this journal.

scholarly journals An Analysis of Equity Among Policy Solutions for Traffic Congestion

2020 ◽  
Vol 27 ◽  
Author(s):  
Ethan Steakley
Keyword(s):  
United States ◽  
Traffic Congestion ◽  
Road Pricing ◽  
The United States ◽  
Vertical Equity ◽  
Flat Tax ◽  
Tax Rate ◽  
Evaluative Criteria ◽  
Future Policy ◽  
Policy Solutions

The emergence of ride-hailing in the United States has brought forth new issues for its cities, particularly a large influx of traffic congestion. Today, several cities have introduced distinct ideas to solve congestion issues while debating their implications for equity. This paper examines the equity implications of traffic congestion in America'•s cities by comparing a flat tax rate on ride-hailing to various road pricing mechanisms using specific evaluative criteria, including transportation access and vertical equity. This paper begins with an overview of ride-hailing in the United States and the congestion problem it poses for cities, then reviews the literature around congestion and equity, describes and assesses the equity of a flat tax rate and road pricing, and ends with broad implications resourced from the literature for future policy.

Research on the Urban Transportation Development in Our Country Based on the Traffic Congestion Pricing

2011 ◽  
Vol 97-98 ◽  
pp. 1032-1037
Author(s):  
Wei Kou ◽  
Lin Cheng
Keyword(s):  
Traffic Congestion ◽  
Marginal Cost ◽  
Demand Management ◽  
Urban Transportation ◽  
Congestion Pricing ◽  
Developed Countries ◽  
Urban Traffic ◽  
Theory And Practice ◽  
Traffic Demand ◽  
Transportation Development

With the development and realization of industrialization and urbanization in the world, urban traffic volume grows rapidly; many big cities face more and more serious traffic problem. As a mean of traffic demand management, traffic congestion pricing has important significance in theory and practice. Traffic congestion pricing can counteract external diseconomy caused by network congestion, and the price of congestion is tantamount to the difference between social marginal cost and private marginal cost. This paper analyzes the economic theory of congestion pricing. Combined the effect of traffic congestion pricing that implemented in the developed countries, it researches the influence of urban transportation development in our country in the future based on the implementing congestion pricing.

scholarly journals Effects of Smart City Policies on Green Total Factor Productivity: Evidence from a Quasi-Natural Experiment in China

2019 ◽  
Vol 16 (13) ◽  
pp. 2396 ◽  
Author(s):  
Xin ◽  
Qu
Keyword(s):  
Total Factor Productivity ◽  
Traffic Congestion ◽  
Smart City ◽  
Natural Experiment ◽  
Population Expansion ◽  
Factor Productivity ◽  
Negative Effects ◽  
Development Patterns ◽  
City Policy ◽  
The City

When cities develop rapidly, there are negative effects such as population expansion, traffic congestion, resource shortages, and pollution. It has become essential to explore new types of urban development patterns, and thus, the concept of the “smart city” has emerged. The purpose of this paper is to investigate the links between smart city policies and urban green total factor productivity (GTFP) in the context of China. Based on panel data of 200 cities in China from 2007–2016 and treating smart city policy as a quasi-natural experiment, the paper uses a difference-in-differences propensity score matching (PSM-DID) approach to prevent selection bias. The results show: (a) Smart city policies can significantly increase urban GTFP by 16% to 18%; (b) the larger the city, the stronger and more significant this promotion.

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