Economics of Transportation最新文献

This paper estimates congestion externalities on a broad sample of roads in England’s capital region. A fixed effects approach that compares across times of day finds that 10% more traffic increases travel time by 4%, erodes reliability, and finds smallest marginal effects on high-capacity roads. I incorporate both expected travel time and reliability into a model of congestion externalities. Combining the model with travel data, I find that Central London’s Congestion Charge exceeds tolled drivers’ external costs if they only reflect travel time and reliability. Despite the large toll in London’s city centre, I find that deadweight loss in untolled parts of the city remains substantial, and that accounting for reliability increases deadweight loss by as much as 55%.

This study investigates the impact of code-sharing (CS) agreements on airfares in Africa, a region largely overlooked in existing airline cooperation research. Analysing a comprehensive dataset covering international one-stop routes in Africa from 2017 to 2019, we examine the direct effects of CS agreements on connecting itinerary discount economy fares that swap from interline to CS. Additionally, we explore the spillover effects of airlines adopting CS on the fares of those that do not implement it. Our key findings reveal that the implementation of CS agreements results in an approximately 18% reduction in airfares for African international routes. Furthermore, we identify a negative spillover effect, demonstrating reduced airfares for interline itineraries by 12% when rival pairs adopt CS, while online and direct itineraries experience smaller reductions (around 4%).

We assess the effects of a short-haul flights ban on a transportation network that includes local, international and connecting markets and modal competition between high-speed rail (HSR), air and private car. When connecting markets are relatively important or there is sufficient modal substitution, bans induce more private car traffic, less local HSR traffic due to higher prices and also more international air and connecting traffic since international prices decrease. Our simulation results unveil that when air and private car are the closest substitutes the ban increases environmental damages. Welfare gross of damages typically falls.

MaaS (Mobility as a Service) is often presented as a means to solve some of the most pressing mobility issues such as car dependency and increasing vehicular greenhouse gas emissions. In this context, adequate models and simulations are key to estimating the impact of potential MaaS implementations and support decision-making to reap the benefits MaaS could bring. This article aims at reviewing MaaS representation in existing academic literature pertaining to transportation modelling, in order to assess its progress and identify trajectories for future improvements. We do so by considering mobility as an economic system in which MaaS interacts with both travel demand and supply. After identifying an adequate set of indicators to analyze MaaS models, we review 31 contributions and find out that most studies consist of demand-centered usage models while the integration of the system's supply side's operational and profitability factors is still lacking, especially in-MaaS financial flows.

Spain has deployed the world’s largest High-Speed Rail (HSR) network, in per capita terms, under the premise that this infrastructure provides a cleaner mode for reaching their environmental commitments. However, for observing environmental gains, there should be inter-modal substitution from polluter modes to the HSR. This paper analyzes the impact of new HSR openings on car traffic, using a Generalized and Staggered Difference-in-Difference approach. Unlike previous studies, we analyzes the entire Spanish HSR network. We matched the georeferenced data on car traffic with the origin–destination routes provided by Google Maps API to estimate the impact of the HSR on car traffic. We found that the HSR has not generated modal split, except for few of the HSR segments, in which we estimated a 6%–8% reduction in the annual average daily traffic. These results have public policy implications for the transport policy in the EU, and the effectiveness of decarbonization policies.

Empty trucks have a significant impact on the efficiency and sustainability of logistics operations, accounting for a substantial portion of the intercity truck flow, ranging from 15% to 40%. While some of these empty trips can be attributed to load imbalances, it is common to observe the flow of empty trucks in both directions of a route. This paper introduces a microeconomic model aimed at providing a deeper understanding of the flow of empty vehicles beyond load imbalances and its implications for freight flows, transport prices, and the number of carriers in the free-entry equilibrium. Our approach captures shippers’ preferences when selecting carriers within a system comprising two locations with cargo flow in both directions. The model incorporates price competition among carriers and the production of differentiated services, as shippers perceive carriers’ services in a heterogeneous manner. Given that carriers lack knowledge of shippers’ preferences, these are represented using a random utility model. The model enables the determination and comparison of equilibrium conditions with the social optimum. The results show that: (1) The transportation of goods results in not only empty vehicles due to imbalanced loads but also a natural occurrence of empty vehicles due to the stochastic demand patterns. (2) When a new carrier enters the market, it contributes to the negative impact of empty vehicles through the business stealing effect. (3) Empty trips disrupt the balance of prices and carriers, creating a gap between the free-entry equilibrium and the socially optimal values. (4) By coordinating carriers’ operations, the flow of empty vehicles due to the business stealing effect can be minimized, moving the system towards the socially optimal outcome.

Greenhouse gas emissions, such as carbon dioxide (CO2) from container terminal (CT) operations, generate an adverse impact on the ecological environment in ports. Yet, solutions to abate air pollution in port areas is controversial. To contribute to the relevant literature, this article aims to assess eco-efficiency for container terminals (CTs) inside a port when the unwanted output is taken into consideration. In doing so, the Slacks-Based Measure (SBM)-DEA model was adopted to evaluate the efficiency of CTs while the modality movement approach was deployed to estimate the amount of CO₂ released by CT operators. It is found that: (1) Wan-Han is the most efficient CT operator, with an average efficiency of 0.993 during 2017–2019; (2) the unwanted output (i.e., CO2) affects CT operators' efficiency score; (3) inefficient DMUs can improve their operating performance by adopting slack variables.

We study the effects of a country’s propensity to renegotiate transportation infrastructure contracts on the technical efficiency of the firms they attract. Firms are characterized by their ability to lobby and by their technical efficiency. In equilibrium, countries with a higher propensity to renegotiate contracts attract less efficient firms, that are better at renegotiating. This leads to costlier transportation infrastructure and lower welfare. Countries with institutional settings with a higher propensity for renegotiation, or where more net welfare is “up for grabs” in renegotiations, procure transportation infrastructure at a higher cost. We provide anecdotal evidence of the link between renegotiation in public procurement and a firm’s ability to renegotiate contracts.