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on Transport Economics |
| By: | Bonacina, Monica; Demir, Mert; Sileo, Antonio; Zanoni, Angela |
| Abstract: | The transition to a zero-emission vehicle fleet represents a pivotal element of Europe’s decarbonization strategy, with Italy’s participation being particularly significant given the size of its automotive market. This study investigates the potential for battery electric cars (BEVs) to drive decarbonization of Italy’s passenger vehicle fleet, focusing on the feasibility of targets set in the National Integrated Plan for Energy and Climate (PNIEC). Leveraging artificial neural networks, we integrate macroeconomic indicators, market-specific variables, and policy instruments to predict fleet dynamics and identify key factors influencing BEV adoption. We forecast that while BEV registrations will continue growing through 2030, the growth rate is projected to decelerate, presenting challenges for meeting ambitious policy targets. Our feature importance analysis demonstrates that BEV adoption is driven by an interconnected set of economic, infrastructural, and behavioral factors. Specifically, our model highlights that hybrid vehicle registrations and the vehicle purchase index exert the strongest influence on BEV registrations, suggesting that policy interventions should prioritize these areas to maximize impact. By offering data-driven insights and methodological innovations, our findings contribute to more effective policy design for accelerating sustainable mobility adoption while accounting for market realities and consumer behavior. |
| Keywords: | Climate Change, Environmental Economics and Policy, Sustainability |
| Date: | 2025–08–01 |
| URL: | https://d.repec.org/n?u=RePEc:ags:feemwp:369002 |
| By: | Pyddoke, Roger (Swedish National Road and Transport Research Institute (VTI)); From, Emma (Swedish National Road and Transport Research Institute (VTI)); Fukushima, Nanna (Swedish National Road and Transport Research Institute (VTI)) |
| Abstract: | This paper aims to describe the distribution of private car ownership, car use, and fuel consumption in Sweden, and to assess how increased fuel prices resulting from climate policy impact the distribution of fuel expenditure and disposable income. We also estimate the potential need for compensating low-income car owners in rural areas in the event of higher climate taxes on fuels. The analysis is based on detailed administrative data for all adults in Sweden in 2022, including information on private car ownership and car use. The main finding is that individual fuel consumption was highly skewed: approximately 15 percent of car owners account for 50 percent of all fuel consumed by privately owned cars, while the remaining 85 percent account for the other half. Most of these high consumers are found among high-income earners, many of whom reside in rural rather than urban areas. Most high-income earners, however, tend to spend a modest share of their disposable income on fuel, with a median of about 4 percent and a 75th percentile of about 7 percent. Similar expenditure shares are found in most low-income earners, with the striking exception of the lowest income octile. A yearly compensation is calculated as the difference in median fuel costs for owners of fossil-fueled cars residing in rural areas with disposable incomes below the median and the corresponding car owners in large cities. In 2022, the estimated compensation for a tax increase equivalent to EUR 0, 5 per liter of fuel ranged from 0 to EUR 80 per year. |
| Keywords: | Climate policy; fuel tax; car ownership; fuel consumption; income distribution; spatial distribution; compensation |
| JEL: | D31 H23 Q52 R12 R48 |
| Date: | 2025–09–01 |
| URL: | https://d.repec.org/n?u=RePEc:hhs:vtiwps:2025_004 |
| By: | Chiavini, Nicholas |
| Abstract: | Albany, New York’s historic streetcar network, decommissioned in 1946, played a central role in shaping the city’s development and the vestiges of this now defunct transit system are clearly visible. While much of the literature on the legacy of streetcar networks has focused on urban form and density, fewer studies have examined their continued influence on contemporary transit ridership and policy. This research investigates whether Albany’s former streetcar corridors continue to sustain elevated transit ridership and whether current land use and transportation policies effectively leverage this historic transit legacy. Using a mixed-methods approach, this research combines geospatial analysis, ridership data, demographic and land use trends, and policy review. A key component was the digitization of Albany’s 1923 streetcar network in Geographic Information Systems (GIS), enabling spatial comparisons with the city’s current transit conditions. Findings show that bus stops located along former streetcar routes experience significantly higher ridership than non-streetcar stops and are characterized by higher housing density and lower car ownership rates. These results reinforce earlier studies documenting the persistence of streetcar-era development patterns, particularly the concentration of density and transit-supportive land uses along former lines, while also extending the literature by directly connecting these legacies to present-day ridership. The Capital District Transportation Authority’s Bus Rapid Transit (BRT) lines also largely align with these historic corridors, underscoring their continued importance as transit spines in the city. Despite these historic advantages, this research found that Albany’s zoning and land use regulations often fail to reinforce these corridors, permitting development patterns that undermine their transit potential. The results highlight the need for policies that integrate land use and transportation planning, ensuring that new development leverages the city’s streetcar legacy for contemporary transit success. The enduring influence of Albany’s streetcar network demonstrates how historic infrastructure continues to shape mobility patterns and offers lessons for cities seeking to strengthen transit-oriented development today. |
| Date: | 2025–08–18 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:r6nfh_v1 |
| By: | Megan Yeo; Sebastian Nosenzo; Daniel S. Palmer; Alexei K. Varah; Lucas Woodley; Ashley Nunes |
| Abstract: | Premium air travel is often associated with a disproportionately large carbon emissions footprint. This association reflects the increased space and amenities typically found in premium cabins that existing discourse suggests makes their carriage more fuel, and consequently carbon, intensive. One increasingly popular solution is disincentivizing the use of premium cabins in favor of all-economy cabins. How effective might such a policy be. To what extent. And how may the revenue impact affect travelers. We address these questions by leveraging an empirical model that integrates cabin configuration data, fuel burn profiles across various aircraft types, and multi-month airfare datasets. Our findings are threefold. First, we find that favoring entirely foregoing premium travel classes can reduce per-passenger emissions by between 8.1 and 21.5 percent, the precise figure varying based on the type of aircraft and aircraft stage length involved. Second, we observe that these emissions reductions are far less assured on a per-flight and a lifespan basis. Here, an all-economy configuration can reduce emissions by 0.45 percent or increase emissions by as much as 1.43 percent. Third, we enumerate pronounced revenue consequences associated with an all-economy configuration. This configuration produces aggregate revenue declines of between 4.92 and 23.1 percent, necessitating airfare increases of between 6 and 30 percent to maintain baseline revenue. This increase risks imposing a profound and regressive economic burden on working-class travelers who exhibit markedly higher price elasticities of demand compared to their wealthier counterparts and highlights the cross-subsidization airlines leverage to ensure the accessibility of air travel. |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2508.12507 |
| By: | Joshua S. Gans |
| Abstract: | When should travellers leave for the airport? This paper develops a model for optimal airport arrival timing when travellers face uncertain travel times and can potentially board earlier flights. We show that access to earlier flights creates a ``recourse option" that fundamentally changes optimal behaviour. While earlier flights always reduce the probability of missing one's scheduled departure, they may paradoxically increase expected waiting time when travellers adjust their arrival strategies. Using renewal theory, we establish that with frequent service, the expected waiting time converges to half the headway between flights—a fundamental limit that cannot be improved through better planning. We connect the problem to newsvendor theory, showing how the fixed penalty for missing flights (rather than linear costs) leads to distinct optimality conditions. Our results explain why rational travellers should occasionally miss flights and provide practical guidelines for airlines designing standby policies and for travellers making departure decisions. |
| JEL: | C44 D81 L93 R41 |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34169 |
| By: | Xin Dong; Jose Ventura; Vikash V. Gayah |
| Abstract: | Ride-hailing platforms (e.g., Uber, Lyft) have transformed urban mobility by enabling ride-sharing, which holds considerable promise for reducing both travel costs and total vehicle miles traveled (VMT). However, the fragmentation of these platforms impedes system-wide efficiency by restricting ride-matching to intra-platform requests. Cross-platform collaboration could unlock substantial efficiency gains, but its realization hinges on fair and sustainable profit allocation mechanisms that can align the incentives of competing platforms. This study introduces a graph-theoretic framework that embeds profit-aware constraints into network optimization, facilitating equitable and efficient cross-platform ride-sharing. Within this framework, we evaluate three allocation schemes -- equal-profit-based, market-share-based, and Shapley-value-based -- through large-scale simulations. Results show that the Shapley-value-based mechanism consistently outperforms the alternatives across six key metrics. Notably, system efficiency and rider service quality improve with increasing demand, reflecting clear economies of scale. The observed economies of scale, along with their diminishing returns, can be understood with the structural evolution of rider-request graphs, where super-linear edge growth expands feasible matches and sub-linear degree scaling limits per-rider connectivity. |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2508.19192 |
| By: | Hung Tran; Tien Mai; Minh Ha Hoang |
| Abstract: | The recursive logit (RL) model has become a widely used framework for route choice modeling, but it suffers from a key limitation: it assigns nonzero probabilities to all paths in the network, including those that are unrealistic, such as routes exceeding travel time deadlines or violating energy constraints. To address this gap, we propose a novel Constrained Recursive Logit (CRL) model that explicitly incorporates feasibility constraints into the RL framework. CRL retains the main advantages of RL-no path sampling and ease of prediction-but systematically excludes infeasible paths from the universal choice set. The model is inherently non-Markovian; to address this, we develop a tractable estimation approach based on extending the state space, which restores the Markov property and enables estimation using standard value iteration methods. We prove that our estimation method admits a unique solution under positive discrete costs and establish its equivalence to a multinomial logit model defined over restricted universal path choice sets. Empirical experiments on synthetic and real networks demonstrate that CRL improves behavioral realism and estimation stability, particularly in cyclic networks. |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2509.01595 |
| By: | Ballantyne, Patrick Dr. (University of Liverpool); Cabrera, Carmen (University of Liverpool); Garofani, Giada; Singleton, Alex |
| Abstract: | The strategic placement of pedestrian crossings is critical for promoting road safety in urban environments. While previous research has used Geographic Information Systems (GIS) to identify underserved areas, existing approaches often fail to integrate empirical data with stakeholder expertise, or directly link road safety concerns with wider spatial equity considerations. This study develops a novel GIS-Multi Criteria Decision Analysis (GIS-MCDA) framework to evaluate the suitability of sites for new pedestrian crossings, incorporating four key criteria: existing provision of pedestrian infrastructure, road safety risks, proximity to urban amenities, and socio-demographic vulnerability. Applied to Liverpool City Region as a policy case study, the framework integrates advanced spatial analysis techniques with stakeholder informed weights, to assess the suitability of postcodes for new pedestrian crossings. Site suitability scores are generated which reflect both the considerations relevant to key stakeholders, as well as the distribution of controlled pedestrian crossings, road traffic collisions, urban amenities and census-derived vulnerability indicators. The results reveal significant spatial inequalities where, specific locations with high socio-demographic vulnerability also experience the greatest road safety risks and poorest access to pedestrian crossings, despite proximity to essential services. The framework successfully pinpoints priority locations where road safety and spatial inequality concerns compounded negatively, providing evidence-based guidance for data-driven, stakeholder-informed pedestrian infrastructure investment. |
| Date: | 2025–09–01 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:z456t_v1 |
| By: | Toger, Marina; Türk, Umut; Östh, John; Fischer, Manfred M. |
| Abstract: | This study applies a heteroscedastic spatial Durbin panel data model to investigate how sociodemographic and socioeconomic factors influence regional commuter mobility in the Greater Stockholm Area. Commuter mobility, defined as the flow of people to and from workplaces across regions and over time, is measured using high-frequency, high-resolution origin-destination data derived from mobile phone records, providing high-frequency, high-resolution insights into commuting patterns. The analysis uses a balanced panel of 681 regions from 2018–2024, incorporating an 18-nearest-neighbor spatial weight matrix to capture the topological relationships. Direct (withinregion) and indirect (spillover) effects are estimated using Bayesian inference, enabling robust interpretation of marginal effects in the presence of spatial lags in dependent and independent variables. Results show that spatial spillovers exert a more decisive influence than direct effects, with educational attainment and car ownership emerging as the most influential determinants of commuter mobility. According to total impact estimates, the demographic structure plays a comparatively minor, yet still significant, role. |
| Keywords: | Spatial econometrics; Bayesian estimation; heteroscedastic spatial Durbin panel data model; GSM- based mobility flow data, ; spatial spillover effects; Greater Stockholm Area |
| Date: | 2025–08–22 |
| URL: | https://d.repec.org/n?u=RePEc:wiw:wus046:76951486 |
| By: | Vinzenz Pyka |
| Abstract: | Using administrative data from Germany, this study provides first evidence on the wage effects of collective bargaining compliance laws. These laws require establishments receiving public contracts to pay wages set by a representative collective agreement, even if they are not formally bound by one. Leveraging variation in the timing of law implementation across federal states, and focusing on the public transport sector -- where regulation is uniform and demand is driven solely by state-level needs -- I estimate dynamic treatment effects using event-study designs. The results indicate that within five years of the law's implementation, wage increases were on average 2.9\% to 4.6\% higher in federal states with such a law compared to those without one -- but only in East Germany. These findings highlight the potential for securing collectively agreed wages in times of declining collective bargaining coverage. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.01458 |
| By: | liu, kerry |
| Abstract: | The rapid development of Chinese automotive, particularly in the new energy vehicle sector, have garnered global attention. This study focuses on a niche area that has yet to be thoroughly examined: automotive finance. First, it explores the evolution of automotive finance in China within the context of the broader automotive market. Second, it reviews key policy initiatives from Chinese authorities related to the automotive industry, automotive finance companies, and automotive consumption. Third, it analyzes recent regulations on automotive finance companies, concluding that these measures are designed to mitigate systemic risks within China's financial system while supporting the new energy vehicle sector. |
| Date: | 2025–08–22 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:py648_v1 |
| By: | Gaurav Singh |
| Abstract: | This study analyzes and forecasts daily passenger counts for New York City's iconic yellow taxis during 2017-2019, a period of significant decline in ridership. Using a comprehensive dataset from the NYC Taxi and Limousine Commission, we employ various time series modeling approaches, including ARIMA models, to predict daily passenger volumes. Our analysis reveals strong seasonal patterns, with a consistent linear decline of approximately 200 passengers per day throughout the study period. After comparing multiple modeling approaches, we find that a first-order autoregressive model, combined with careful detrending and cycle removal, provides the most accurate predictions, achieving a test RMSE of 34, 880 passengers on a mean ridership of 438, 000 daily passengers. The research provides valuable insights for policymakers and stakeholders in understanding and potentially addressing the declining trajectory of NYC's yellow taxi service. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.10588 |
| By: | Salome Baslandze; Simon Fuchs |
| Abstract: | We study the role of supply chain disruptions in shaping consumer prices, focusing on both firms’ own import shocks and strategic responses to competitors’ disruptions. Using a newly constructed micro-level dataset that links transaction-level U.S. import data from Bills of Lading with high-frequency consumer prices and sales from a consumer panel, we develop a novel approach to estimate the price effects of cost shocks and product availability. Motivated by a model of delivery delays, cost shocks, and firm pricing, we implement a shift-share identification strategy based on delivery shortfalls, port congestion, and freight and import costs. We find sizable pass-through elasticities: firms raise prices in response to higher import costs and delivery delays, especially when disruptions persist. We also identify strategic pricing: firms—including non-importers—increase prices in response to competitors’ supply chain disruptions. Using our estimates and back-of-the-envelope calculations from the model, we show that strategic interactions significantly amplified the direct effects of supply chain shocks on consumer prices during the pandemic. |
| Keywords: | supply chains, inflation, delivery delays, strategic interactions, pass-through, inventory |
| JEL: | E31 F14 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12079 |