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on Transport Economics |
| By: | Shaheen, Susan A.; Pan, Alexandra |
| Abstract: | The growth of carsharing in North America since the service was first introduced in 1994 has had notable impacts on travel behaviour, including vehicle ownership and modal shift. Existing forms of carsharing (e.g., roundtrip, one-way, and peer-to-peer) alter the conventional cost structure of driving from one of fixed cost to variable cost. Multiple studies have shown that overall, carsharing users increase public transit and non-motorized modal use, with some users also selling their vehicle or postponing future vehicle purchases as a result of being a carsharing member. These modal impacts have led to a reduction in greenhouse gas emissions associated with driving. Further, research has shown that carsharing may provide additional accessibility to individuals without a personal vehicle. In this chapter, we provide an overview of the travel behaviour impacts of carsharing and findings on the demographics of carsharing users. |
| Keywords: | Social and Behavioral Sciences |
| Date: | 2024–04–01 |
| URL: | https://d.repec.org/n?u=RePEc:cdl:itsrrp:qt9qf5h094&r= |
| By: | Hong Yuan; Minda Ma |
| Abstract: | The transportation sector is the third-largest global energy consumer and emitter, making it a focal point in the transition toward the net-zero future. To accelerate the decarbonization of passenger cars, this work is the first to propose a bottom-up charging demand model to estimate the operational electricity use and associated carbon emissions of best-selling battery electric vehicles (BEVs) in various climate zones in China during the 2020s. The findings reveal that (1) the operational energy demand of the top-20 selling BEV models in China, such as Tesla, Wuling Hongguang, and BYD, increased from 601 to 3054 giga-watt hours (GWh) during 2020-2022, with BEVs in South China contributing more than half of the total electricity demand; (2) from 2020 to 2022, the energy and carbon intensities of the best-selling models decreased from 1364 to 1095 kilowatt-hour per vehicle and from 797 to 621 kilograms of carbon dioxide (CO2) per vehicle, respectively, with North China experiencing the highest intensity decline compared to that in other regions; and (3) the operational energy demand of BEV stocks in China increased from 4774 to 12, 048 GWh during 2020-2022, while the carbon emissions of BEV stocks rose to 6.8 mega-tons of CO2 in 2022, reflecting an annual growth rate of ~50%. In summary, this work delves into the examination and contrast of benchmark data on a nation-regional scale, as well as performance metrics related to BEV chargings. The primary aim is to support nationwide efforts in decarbonization, aiming for carbon mitigation and facilitating the swift evolution of passenger cars toward a carbon-neutral future. |
| Date: | 2024–05 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2405.10851&r= |
| By: | Tayarani, Hanif; Nitta, Christopher J.; Tal, Gil |
| Abstract: | To maximize the greenhouse gas (GHG) emission reduction potential of Battery Electric Vehicles (BEVs), it is critical to develop EV dynamic charging management strategies. These strategies leverage the temporal variability in emissions associated with generated electricity to align EV charging with periods of low-carbon power generation. This study introduces a deep neural network tool to enable BEV drivers to make charging sessions align with the availability of cleaner energy resources. This study leverages a Long Short-Term Memory network to forecast individual BEV vehicle miles traveled (VMT) up to two days ahead, using a year-long dataset of driving and charging patterns from 66 California-based BEVs. Based on the predicted VMT, the model then estimates the vehicle's energy needs and the necessity of a charging session. This allows drivers to charge theirvehicles strategically, prioritizing low-carbon electricity periods without risking incomplete journeys. This framework empowers drivers to actively contribute to cleaner electricity consumption with minimal disruption to their daily routines. The tool developed in this project outperforms benchmark models such as recurrent neural networks and autoregressive integrated moving averages, demonstrating its predictive capabilities. To enhance the reliability of predictions, confidence intervals are integrated into the model, ensuring that the model does not disrupt drivers' daily routine trips when skipping non-critical charging events. The potential benefits of the tool are demonstrated by applying it to real-world EV data, finding that if drivers follow the tool’s predictive suggestion, they can reduce overall GHG emissions by 41% without changing their driving patterns. This study also found that even charging in regions with higher carbon-intensity electricity than California can achieve Californian emission levels for EV charging in the short term through strategic management of non-critical charging events. This findingreveals new possibilities for further emissions reduction from EV charging, even before the full transition to a carbon-neutral grid. View the NCST Project Webpage |
| Keywords: | Engineering, Social and Behavioral Sciences, Charging behavior, forecasting, machine learning |
| Date: | 2024–06–01 |
| URL: | https://d.repec.org/n?u=RePEc:cdl:itsdav:qt77t9p8sf&r= |
| By: | Bontemps, Christian; Martini, Gianmaria; Porta, Flavio |
| Abstract: | This paper studies the relationship between air transportation, tourist _ows, and subsidies to Low Cost Carriers (LCCs), a policy used by many national and local governments to stimulate tourist arrivals. To test the policy empirically, we use a two-stage empirical model. In the _rst stage, we estimate a structural model applied to air transport, and in the second stage, we link passenger arrivals to regional tourism _ows. In this way, we use exogenous shocks (subsidies to LCCs) in airline supply to analyze the causal link with tourist arrivals. This model is applied to tourist _ows from European regions to Italian regions from 2016 to 2018. Our counterfactual analyses consider two regimes for implementing subsidies to LCCs, following the literature coming from Oates (1993, 1999) contributions: a centralized, uniform policy for all regions and a decentralized policy in which subsidies are adopted by a single region. Our simulations reveal that subsidies to LCCs are e_ective in stimulating tourism, and that a centralized regime is more e_ective than a decentralized one. In fact, the latter generates externalities in regions that do not implement the subsidy, making the decentralised policy economically sub-optimal and unsustainable. |
| Keywords: | Air transportation and tourism; Structural model |
| JEL: | R41 R48 O18 |
| Date: | 2024–05–23 |
| URL: | http://d.repec.org/n?u=RePEc:tse:wpaper:129352&r= |
| By: | Giulia Brancaccio (New York University); Myrto Kalouptsidi (Harvard University); Theodore Papageorgiou (Boston College) |
| Abstract: | Transportation infrastructure is vital for the smooth functioning of international trade. Ports are a crucial gateway to this system: with more than 80% of trade carried by ships, they shape trade costs, and it is critical that they operate efficiently. Yet ports are susceptible to disruptions, causing costly delays. With enormous budgets spent on infrastructure to alleviate these costs, a key policy question emerges: in a world with high volatility, what are the returns to investing in infrastructure? To address this question, we introduce an empirical framework that combines insights from queueing theory to capture port technology, with tools from demand estimation. We use our framework, together with a collection of novel datasets, to quantify the costs of disruptions and evaluate transportation infrastructure investment. Our analysis unveils three policy-relevant messages: (i) investing in port infrastructure can lead to substantial trade and welfare gains, but only if targeted properly– in fact, net of costs, investment has positive returns at a minority of US ports; (ii) there are sizable spillovers across ports, as investing in one port can decongest a wider set of ports, suggesting that decision-making should not be decentralized to local authorities; (iii) macroeconomic volatility can drastically change returns to investment and their geography. |
| Keywords: | transportation, infrastructure, ports, congestion, macroeconomic volatility, disruptions, spillovers, welfare |
| JEL: | E39 F1 F14 L0 L90 L91 R4 R41 R42 |
| Date: | 2024–05–10 |
| URL: | http://d.repec.org/n?u=RePEc:boc:bocoec:1072&r= |
| By: | Fabien Leurent (CIRED - Centre International de Recherche sur l'Environnement et le Développement - Cirad - Centre de Coopération Internationale en Recherche Agronomique pour le Développement - EHESS - École des hautes études en sciences sociales - AgroParisTech - ENPC - École des Ponts ParisTech - Université Paris-Saclay - CNRS - Centre National de la Recherche Scientifique) |
| Abstract: | A line ride-sharing service is supplied along a given roadway path by an operator that matches Users (riders) and Agents (drivers), under specific protocol that involves price schedule on both the U and A sides, waiting policy on either side and transaction times. The resulting time and money items add up over trip legs, yielding trip time and money cost depending on the service role, A or U, compared to Non-commitment, called role N for Neutral. The article brings about a traffic model of people involvement in the service. Service conditions of frequency φ and average number of users per car run ω are key factors of the time and money features of the alternative roles A, U and N. Individual choice of role is modeled as a rational behavior of minimizing the generalized cost depending on the individual Value-of-Time (VoT). Aggregation over trip-makers according to the statistical distribution of VoT yields the respective role flows (y_A, y_U, y_N), which in turn determine the macroscopic factors (φ, ω). Traffic equilibrium is defined as a balance condition between the "supplied flows" and the "demanded flows" of the three roles. A computational scheme is provided, with graphical interpretation in the (y_A, y_U) plane as well as in the (φ, ω) plane. A numerical experiment is conducted, showing that two alternative configurations can arise at equilibrium: either {A, U, N} with less wealthy Agents driving wealthier Users, or {U, A, N} where less wealthy Users are driven by wealthier Agents: in both cases the Neutral role attracts the upper range of the VoT distribution. |
| Keywords: | bi-sided platform, traffic equilibrium, multi-sided equilibrium, equilibration algorithm, Ride-sharing service |
| Date: | 2024 |
| URL: | http://d.repec.org/n?u=RePEc:hal:ciredw:hal-04579457&r= |
| By: | Giulia Brancaccio; Myrto Kalouptsidi; Theodore Papageorgiou |
| Abstract: | Transportation infrastructure is vital for the smooth functioning of international trade. Ports are a crucial gateway to this system: with more than 80% of trade carried by ships, they shape trade costs, and it is critical that they operate efficiently. Yet ports are susceptible to disruptions, causing costly delays. With enormous budgets spent on infrastructure to alleviate these costs, a key policy question emerges: in a world with high volatility, what are the returns to investing in infrastructure? To address this question, we introduce an empirical framework that combines insights from queueing theory to capture port technology, with tools from demand estimation. We use our framework, together with a collection of novel datasets, to quantify the costs of disruptions and evaluate transportation infrastructure investment. Our analysis unveils three policy-relevant messages: (i) investing in port infrastructure can lead to substantial trade and welfare gains, but only if targeted properly– in fact, net of costs, investment has positive returns at a minority of US ports; (ii) there are sizable spillovers across ports, as investing in one port can decongest a wider set of ports, suggesting that coordinated decision-making may result in more efficient investment decisions; (iii) macroeconomic volatility can drastically change returns to investment and their geography. |
| JEL: | E39 F1 F14 L0 L90 L91 R4 R41 R42 |
| Date: | 2024–05 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:32503&r= |
| By: | Sharma, Anjali; Peng, Wei; Urpelainen, Johannes; Dai, Hancheng; Purohit, Pallav; Wagner, Fabian |
| Abstract: | Transitioning to electric vehicles (EVs) is a central strategy for reducing carbon dioxide and air pollutant emissions. Although the emission impacts of reduced gasoline combustion and increased power generation are well recognized, the impacts of growing EV manufacturing activities remain understudied. Here we focus on China and India, two of the fastest growing EV markets. Compared to a 2030 baseline scenario, we find national emissions of air pollutants could increase in certain high EV penetration scenarios as a result of the emission-intensive mineral production and battery manufacturing processes. Notably, national sulfur dioxide emissions could increase by 16%-79% if all batteries have nickel- and cobalt-based cathodes and are produced domestically. Subnational regions that are abundant in battery-related minerals might emerge as future pollution hotspots. Our study thus highlights the importance of EV supply chain decisions and related manufacturing processes in understanding the environmental impacts of the EV transition. |
| Date: | 2024–05–07 |
| URL: | http://d.repec.org/n?u=RePEc:osf:osfxxx:27hvu&r= |
| By: | Romero, Sandra MCP |
| Abstract: | The Universal Basic Mobility (UBM) pilots in Oakland and Los Angeles, launched in 2021, were innovative initiatives to address transportation equity and access issues in historically underserved communities. These experimental programs examined the impact of providing flexible transportation benefits to low-income residents. However, the current program designs fall short of achieving accessibility and sustainability objectives. Instead, they serve as initial steps in exploring UBM as a potential transportation equity strategy. The report explores the motivation behind local agencies initiating UBM pilots despite existing transportation benefit initiatives, and provides insights from program practitioners on the challenges and opportunities in UBM implementation. |
| Keywords: | Social and Behavioral Sciences, Universal Basic Mobility, Mobility as a Service, transportation disadvantaged persons, transportation equity, pilot studies, user side subsidies, accessibility, sustainable transportation |
| Date: | 2024–05–01 |
| URL: | https://d.repec.org/n?u=RePEc:cdl:itsrrp:qt4b73k640&r= |
| By: | Broader, Jacquelyn |
| Abstract: | In the United States, public transit agencies are increasingly growing interested in deploying open-loop payment systems for public transit fare payments. This interest is based on the benefits these systems can offer, from faster boarding times to the potential of attracting more riders. Open-loop fare payment systems’ popularity is evidenced by the growing number of American public transit agencies who have deployed them; most of whom (63%) are located in California. The overlap between public transit riders who are both transit-dependent and financially excluded (i.e., have no or limited access to financial services) creates the opportunity for public transit agencies deploying open-loop payment systems to leverage these systems to increase financial service access for transit dependent, financially excluded riders. Individuals who are both transit-dependent and financially excluded are typically low-income, identify as part of a racial or ethnic minority group, immigrants, and/or women. As a result of these demographic characteristics, this work focuses on these populations. Additionally, financial inclusion, especially for these populations, is a critical step for economic and social mobility in the United States. This research focuses on California and explores how to leverage public transit agency deployment of open-loop payment systems to increase riders' financial service access. This research is comprised of a literature review, expert interviews (n=11), population needs mapping, and partnership proposals. In general, public transit agencies can strategically work with financial sector-based partners who focus on serving the transit agencies' priority rider groups. |
| Keywords: | Social and Behavioral Sciences, Public transit, automatic fare collection, transportation disadvantaged persons, low income groups, transportation equity |
| Date: | 2024–06–01 |
| URL: | https://d.repec.org/n?u=RePEc:cdl:itsrrp:qt88v9c0wm&r= |
| By: | Huntington, Hillard |
| Abstract: | This study measures the response of gasoline consumption to improved vehicle fuel efficiency (miles per gallon). Although an inverse relationship exists, the percentage decline is always less than the percentage efficiency improvement. As usually measured by past researchers, the long-run response in this study is approximately 80% of the efficiency improvement. The remaining 20% is the direct rebound effect and comports well with previous estimates. However, this rebound estimate escalates to 40-50% if horsepower or vehicle size are controlled. Even larger estimates (about 70%) are possible if carmakers change both fuel efficiency and horsepower when required to meet energy efficiency standards. Larger rebound effects are also possible when VFE improvements also reduce gasoline prices, but these price reductions may also improve welfare. |
| Keywords: | Gasoline; Energy efficiency; Technological change |
| JEL: | O33 Q41 Q48 |
| Date: | 2024–05 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:121095&r= |
| By: | Coskun, Sena (Institute for Employment Research (IAB), Nuremberg, Germany); Dauth, Wolfgang (Institute for Employment Research (IAB), Nuremberg, Germany); Gartner, Hermann (Institute for Employment Research (IAB), Nuremberg, Germany); Stops, Michael (Institute for Employment Research (IAB), Nuremberg, Germany); Weber, Enzo (Institute for Employment Research (IAB), Nuremberg, Germany ; Univ. Regensburg) |
| Abstract: | "This paper examines how the shift towards working from home during and after the Covid-19 pandemic shapes the way how labor market and locality choices interact. For our analysis, we combine large administrative data on employment biographies in Germany and a new working from home potential indicator based on comprehensive data on working conditions across occupations. We find that in the wake of the Covid-19 pandemic, the distance between workplace and residence has increased more strongly for workers in occupations that can be done from home: The association of working from home potential and work-home distance increased significantly since 2021 as compared to a stable pattern before. The effect is much larger for new jobs, suggesting that people match to jobs with high working from home potential that are further away than before the pandemic. Most of this effect stems from jobs in big cities, which indicates that working from home alleviates constraints by tight housing markets. We find no significant evidence that commuting patterns changed more strongly for women than for men." (Author's abstract, IAB-Doku) ((en)) |
| Keywords: | Bundesrepublik Deutschland ; Pandemie ; IAB-Open-Access-Publikation ; Auswirkungen ; Berufsgruppe ; Entwicklung ; geschlechtsspezifische Faktoren ; abhängig Beschäftigte ; Integrierte Erwerbsbiografien ; Integrierte Erwerbsbiografien ; Pendelwanderung ; regionale Verteilung ; regionaler Arbeitsmarkt ; Stadtregion ; Telearbeit ; Wohnsituation ; Arbeitsplatzwechsel ; Arbeitsweg ; 2016-2022 |
| JEL: | J61 R23 |
| Date: | 2024–04–12 |
| URL: | https://d.repec.org/n?u=RePEc:iab:iabdpa:202406&r= |
| By: | Rainald Borck (University of Potsdam, CESifo, CEPA); Peter Mulder (Netherlands Organization for Applied Scientific Research (TNO), Utrecht University) |
| Abstract: | We study the effect of energy and transport policies on pollution in two developing country cities. We use a quantitative equilibrium model with choice of housing, energy use, residential location, transport mode, and energy technology. Pollution comes from commuting and residential energy use. The model parameters are calibrated to replicate key variables for two developing country cities, Maputo, Mozambique, and Yogyakarta, Indonesia. In the counterfactual simulations, we study how various transport and energy policies affect equilibrium pollution. Policies may be induce rebound effects from increasing residential energy use or switching to high emission modes or locations. In general, these rebound effects tend to be largest for subsidies to public transport or modern residential energy technology. |
| Keywords: | pollution, energy policy, discrete choice, developing country cities |
| JEL: | Q53 Q54 R48 |
| Date: | 2024–05 |
| URL: | https://d.repec.org/n?u=RePEc:pot:cepadp:78&r= |
| By: | Cohen, Achituv; Nelson, Trisalyn; Schattle, Lizzy; Zanotto, Moreno; Herr, Seth; Fitch-Polse, Dillon; Winters, Meghan |
| Abstract: | Our goal is to reduce the negative impacts of bicycle theft by better understanding patterns in bicycle theft and recovery. We analyzed data from 1823 responses to a North American survey on bicycle theft conditions, recovery circumstances, and demographics. Survey recruitment was done in partnership with BikeIndex, a non-profit bicycling registration service. Most bikes were stolen from inside a shed or garage (28%) or from outdoor bicycle racks (18%) and most thefts occur overnight (41%). 15% of stolen bicycles were recovered. Key factors in recovery include police involvement, bike registration, and reporting the theft through multiple channels. |
| Keywords: | Social and Behavioral Sciences |
| Date: | 2023–11–28 |
| URL: | https://d.repec.org/n?u=RePEc:cdl:itsdav:qt9zd4w15w&r= |