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on Transport Economics |
| By: | Justin Tyndall (University of Hawaii Economic Research Organization and Department of Economics, University of Hawaii at Manoa) |
| Abstract: | Pedestrian deaths in the US have risen in recent years. Concurrently, US vehicles have increased in size, which may pose a safety risk for pedestrians. In particular, the increased height of vehicle front-ends may present a danger for pedestrians in a crash, as the point of vehicle contact is more likely to occur at the pedestrian’s chest or head. I merge US crash data with a public data set on vehicle dimensions to test for the impact of vehicle height on the likelihood that a struck pedestrian dies. After controlling for crash characteristics, I estimate a 10 cm increase in the vehicle’s front-end height is associated with a 22% increase in fatality risk. I estimate that a cap on front-end vehicle heights of 1.25 meters would reduce annual US pedestrian deaths by 509. |
| Keywords: | Transportation, Safety, Health Traffic fatalities, Externalities |
| JEL: | I1 R41 R42 R48 |
| Date: | 2024–01 |
| URL: | http://d.repec.org/n?u=RePEc:hae:wpaper:2024-1&r=tre |
| By: | William E. Bendinelli; Humberto F. A. J. Bettini; Alessandro V. M. Oliveira |
| Abstract: | This paper develops an econometric model of flight delays to investigate the influence of competition and dominance on the incentives of carriers to maintain on-time performance. We consider both the route and the airport levels to inspect the local and global effects of competition, with a unifying framework to test the hypotheses of 1. airport congestion internalization and 2. the market competition-quality relationship in a single econometric model. In particular, we examine the impacts of the entry of low cost carriers (LCC) on the flight delays of incumbent full service carriers in the Brazilian airline industry. The main results indicate a highly significant effect of airport congestion self-internalization in parallel with route-level quality competition. Additionally, the potential competition caused by LCC presence provokes a global effect that suggests the existence of non-price spillovers of the LCC entry to non-entered routes. |
| Date: | 2024–01 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2401.09174&r=tre |
| By: | Shawn Berry |
| Abstract: | The purpose of this article is to propose a novel model of the effects of changes in shelter and driving costs on car commuting distances in the overheated Toronto housing market from 2011 to 2016. The model borrows from theoretical concepts of microeconomics and urban geography to examine the Toronto housing market. Using 2011 and 2016 Census data for census metropolitan areas (CMAs) and census agglomerations (CAs) in Southern Ontario and computed driving costs, the model of car commuting distance is based on variables of allocation of monthly household income to monthly shelter costs and driving costs as a function of the car driving distance to Toronto. Using this model, we can predict the effect on car commuting distance due to changes in any of the variables. The model also offers an explanation for communities of Toronto car commuters beyond a driving radius that we might expect for daily commuting. The model confirms that increases in shelter costs in the Toronto housing market from 2011 to 2016 have forced the boundaries of feasible housing locations outward, and forced households to move farther away, thus increasing car commuting distance. |
| Date: | 2024–01 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2401.11343&r=tre |
| By: | Hannes Wallimann |
| Abstract: | Measures to reduce transport-related greenhouse gas emissions are of great importance to policy-makers. A recent example is the nationwide KlimaTicket in Austria, a country with a relatively high share of transport-related emissions. The cheap yearly season ticket introduced in October 2021 allows unlimited access to Austria's public transport network. Using the synthetic control and synthetic difference-in-differences methods, I assess the causal effect of this policy on public transport demand by constructing a data-driven counterfactual out of European railway companies to mimic the number of passengers of the Austrian Federal Railways without the KlimaTicket. The results indicate public transport demand grew slightly faster in Austria, i.e., 3.3 or 6.8 percentage points, depending on the method, than it would have in the absence of the KlimaTicket. However, the growth effect after the COVID-19 pandemic appears only statistically significant when applying the synthetic control method, and the positive effect on public transport demand growth disappears in 2022. |
| Date: | 2024–01 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2401.06835&r=tre |
| By: | Tanmay Ghosh; Nithin Nagaraj |
| Abstract: | The decision making involved behind the mode choice is critical for transportation planning. While statistical learning techniques like discrete choice models have been used traditionally, machine learning (ML) models have gained traction recently among the transportation planners due to their higher predictive performance. However, the black box nature of ML models pose significant interpretability challenges, limiting their practical application in decision and policy making. This study utilised a dataset of $1350$ households belonging to low and low-middle income bracket in the city of Bengaluru to investigate mode choice decision making behaviour using Multinomial logit model and ML classifiers like decision trees, random forests, extreme gradient boosting and support vector machines. In terms of accuracy, random forest model performed the best ($0.788$ on training data and $0.605$ on testing data) compared to all the other models. This research has adopted modern interpretability techniques like feature importance and individual conditional expectation plots to explain the decision making behaviour using ML models. A higher travel costs significantly reduce the predicted probability of bus usage compared to other modes (a $0.66\%$ and $0.34\%$ reduction using Random Forests and XGBoost model for $10\%$ increase in travel cost). However, reducing travel time by $10\%$ increases the preference for the metro ($0.16\%$ in Random Forests and 0.42% in XGBoost). This research augments the ongoing research on mode choice analysis using machine learning techniques, which would help in improving the understanding of the performance of these models with real-world data in terms of both accuracy and interpretability. |
| Date: | 2024–01 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2401.13977&r=tre |
| By: | Justin Beaudoin (Department of Economics, Acadia University); Justin Tyndall (University of Hawaii Economic Research Organization and Department of Economics, University of Hawaii at Manoa) |
| Abstract: | Bus Rapid Transit (BRT) systems have become increasingly common in US cities. BRT stations provide a local amenity by improving transportation options for local residents, but may also represent a local nuisance due to noise or displacement of other road users. We estimate whether BRT is priced into local real estate by studying a recently opened BRT project in Vancouver, Washington. We use a difference-in-difference method with both hedonic and repeat sales estimators to test for a price effect. We estimate a 5-7% price premium for homes located within a 20 minute walk of a BRT station. Overall, BRT generated new real estate value that exceeded the project’s construction costs by a factor of six. We discuss how government could leverage future residential property value increases to fund construction of BRT projects. |
| Keywords: | Transportation, Transit, Bus Rapid Transit, Real Estate |
| JEL: | R30 R32 R38 R40 R42 |
| Date: | 2023–08 |
| URL: | http://d.repec.org/n?u=RePEc:hae:wpaper:2023-3&r=tre |
| By: | Ankinée KIRAKOZIAN; Raphaël CHIAPPINI; Nabila ARFAOUI |
| Abstract: | The central issue of this paper is to understand how policy makers can design instruments to create incentives towards green mobility. With this in mind, we ran a field experiment in 89 French firms (both public and private organizations) over 54 weeks to investigate how nudges and financial incentives can decrease the use of polluting vehicles by employees during their commute to work each week. Based on data including 845 employees, our study highlights several results related to three important attributes of policy design: the type of instrument, the timing and the targeting. We find that individuals exposed to the nudges “Moral Appeal”, “Risk of Loss”, and a combination of these two, significantly decrease their use of polluting vehicles in their daily commute to work. We find no treatment effect, either for the other nudges or for the impact of financial incentives. Our findings also reveal a persistent effect in time of the three successful nudges on the transport behavior of employees. Using a causal forest method to evaluate the heterogeneous treatment effects of these three nudges, we demonstrate that distance from work and pro-environmental behavior are the strongest predictors of treatment effects. We find that the further the employees reside from their workplace, the lower the treatment effect estimates. It suggests that selective targeting can improve the efficiency of the nudging policy. |
| Keywords: | Nudge, field experiment, green mobility, transport mode. |
| JEL: | C93 D91 Q5 R4 |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:grt:bdxewp:2023-09&r=tre |
| By: | Pollitt, M. G.; Dolphin, G. G. |
| Abstract: | This paper considers the current proposal to extend the EU ETS to cover CO2 emissions from the combustion of heating and road transport fuels. We argue that increased coverage of the EU ETS, together with a binding cap consistent with a net zero trajectory, would be a powerful dynamic incentive to efficient emissions reduction. In addition, it would complement standards-based policies currently enacted in these sectors in several ways. Distributional implications remain a serious challenge to such an extension but several mechanisms are available to alleviate them. |
| Keywords: | climate policy, emissions trading, EU, net zero |
| JEL: | Q52 Q54 Q58 |
| Date: | 2024–02–09 |
| URL: | http://d.repec.org/n?u=RePEc:cam:camdae:2152&r=tre |
| By: | Francisco, Kris A.; Abrigo, Michael R.M. |
| Abstract: | High market concentration in the Philippine domestic shipping industry has always been a subject of concern among policymakers and researchers. While many reforms aimed at improving the level of competition in the industry have been implemented since the 1990s, studies show that domestic shipping operations remain in the hands of a few players, especially at the route level. This study aims to enrich the discussion by providing an alternative measure of market power in domestic shipping through the estimation of markups –a useful indicator of how firms can price their goods or services above marginal cost. Estimates confirm the exercise of market power in the domestic shipping industry, as evidenced by high markups. It was also found that the markup on freight is relatively larger than the markups on passenger services. Additional analysis confirms that having a high market share influences high markups significantly. Comments to this paper are welcome within 60 days from the date of posting. Email publications@pids.gov.ph. |
| Keywords: | market power;markups;domestic shipping |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:phd:dpaper:dp_2023-44&r=tre |
| By: | Kathryn Baragwanath Vogel; Gordon H. Hanson; Amit Khandelwal; Chen Liu; Hogeun Park |
| Abstract: | This paper integrates daytime and nighttime satellite imagery into a spatial general-equilibrium model to evaluate the returns to investments in new motorways. Our approach has particular value in developing-country settings in which granular data on economic activity are scarce. To demonstrate our method, we use multi-spectral imagery—publicly available across the globe—to evaluate India’s varied road construction projects in the early 2000s. Estimating the model requires only remotely-sensed data, while evaluating welfare impacts requires one year of population data, which are increasingly available through public sources. We find that India’s road investments from this period improved aggregate welfare, particularly for the largest and smallest urban markets. The analysis further reveals that most welfare gains accrued within Indian districts, demonstrating the potential benefits of using of high spatial resolution of satellite images. |
| JEL: | O1 R1 |
| Date: | 2024–01 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:32047&r=tre |