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on Transport Economics |
| By: | Simon Fuchs; Woan Foong Wong |
| Abstract: | We examine the economic and environmental impacts of improvements and disruptions in multimodal transport networks. Our quantitative spatial equilibrium model incorporates routing over multiple modes and congestion at intermodal terminals. We estimate a modal substitution elasticity with highway and rail data, and a terminal congestion elasticity with vessel-positioning data. Calibrated to the U.S. freight network, our model identifies key bottlenecks and quantifies $300-700 million in additional real GDP gains from intermodal terminal improvements. These gains are 2.5 times higher without congestion, and substitution away from roads yield additional environmental benefits. Losing rail network access, factoring in modal substitution and general equilibrium effects, is estimated to reduce real GDP by $230 billion. |
| Keywords: | multimodal transport, transport network, spatial equilibrium, endogenous transport costs, infrastructure investments, disruptions, bottlenecks |
| JEL: | F11 R12 R42 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11362 |
| By: | Belloc, Ignacio (University of Zaragoza); Gimenez-Nadal, José Ignacio (University of Zaragoza); Molina, José Alberto (University of Zaragoza) |
| Abstract: | Telework has gained increasing popularity in recent years, particularly following the COVID-19 pandemic, and is often considered a work practice that contributes to environmental sustainability by reducing commuting trips. However, the existing literature presents mixed findings regarding its potential effects on other types of travel, such as leisure and personal care trips. This paper examines the relationship between telework and daily travel time, utilizing data from the 2023 Extended Light Diary Digital Instrument (ELiDDI) survey, a nationally representative time use survey conducted in the UK in March 2023. Our findings indicate that teleworkers spend fewer minutes (e.g., 61 minutes) traveling per day compared to those working away from home, a result that remains robust even after excluding daily commuting time, suggesting that telework may lead to significant daily travel time savings. Further exploration reveals that telework is primarily related to reduced travel time for personal and housework-related activities, particularly among male teleworkers. These findings suggest that promoting telework policies could be an effective strategy not only for reducing commuting trips but also for achieving broader reductions in daily travel time, which may contribute to sustainability goals in the transportation sector and alleviate transportation-related environmental impacts. |
| Keywords: | daily travel time, travel purposes, telework, time use, ELiDDI data, COVID-19 |
| JEL: | J21 J22 R41 |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp17413 |
| By: | Barthélémy Bonadio |
| Abstract: | What determines the relative gains from improving different parts of a transportation network? Ports and roads are key components of a country’s infrastructure to access international markets. I provide a framework to jointly estimate the quality of different ports and trade costs on normal roads and expressways. I then build a general equilibrium model of international and internal trade with port and road infrastructure to assess the relative importance of ports versus roads in shaping international market access, and estimate it using a novel transaction-level export dataset for India. A key elasticity of route switching governs the relative gains from port vs road improvements. I find that returns of improving ports are higher than those for roads under the existing Indian infrastructure network, but improvements in ports and roads have different distributional implications. |
| Keywords: | ports, infrastructure, market access, India |
| JEL: | F10 R40 H54 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11383 |
| By: | Katsiaryna Bahamazava (Department of Mathematical Sciences G.L. Lagrange, Politecnico di Torino, Italy, iLaVita Nonprofit Foundation, Italy - USA) |
| Abstract: | Urbanization and technological advancements are reshaping the future of urban mobility, presenting both challenges and opportunities. This paper combines foresight and scenario planning with mathematical modeling using Ordinary Differential Equations (ODEs) to explore how Artificial Intelligence (AI)-driven technologies can transform transportation systems. By simulating ODE-based models in Python, we quantify the impact of AI innovations, such as autonomous vehicles and intelligent traffic management, on reducing traffic congestion under different regulatory conditions. Our ODE models capture the dynamic relationship between AI adoption rates and traffic congestion, providing quantitative insights into how future scenarios might unfold. By incorporating industry collaborations and case studies, we offer strategic guidance for businesses and policymakers navigating this evolving landscape. This study contributes to understanding how foresight, scenario planning, and ODE modeling can inform strategies for creating more efficient, sustainable, and livable cities through AI adoption. |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2410.19915 |
| By: | Qasim Ajao; Lanre Sadeeq; Oluwatobi Oluwaponmile Sodiq |
| Abstract: | Electric vehicles (EVs) represent a significant advancement in automotive technology, utilizing electricity as a power source instead of traditional fossil fuels, while incorporating sophisticated navigation and autopilot systems. These vehicles align with multiple Sustainable Development Goals (SDGs) by offering a more environmentally sustainable alternative to internal combustion engine vehicles (ICEVs). Despite their potential, the adoption of EVs in developing nations such as Nigeria remains constrained. This study expands the Unified Theory of Acceptance and Use of Technology (UTAUT) framework by incorporating key enablers, including poor infrastructure, affordability issues, and government support, within the broader category of facilitating conditions. Additionally, it examines factors such as trust, performance expectations, social influences, and network externalities to identify the primary determinants influencing Nigerian consumers' propensity to adopt EVs. Results show that the percentage increase of H6 (facilitating conditions - behavioral intentions) compared to H5 (network externalities - behavioral intentions) is approximately 32.35%, indicating that traditional drivers significantly influence individuals' willingness to purchase EVs and are particularly strong factors in adoption decisions. The paper concludes with a discussion of these findings and proposes strategies for future research to further explore the barriers and drivers of EV adoption in Nigeria. |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2410.17282 |
| By: | Christopher FINDLAY (Australian National University) |
| Abstract: | The COVID-19 pandemic period offered the opportunity to consider the adjustment of elements of the transport system to the shock. This paper reviews the experience of the air freight system. It discusses how initially the pandemic led to rising rates, especially because of restrictions on passenger travel, which in turn induced a supply response that allowed capacity to recover. The consequences for trade costs are also examined using data on product imports by Australia by mode. The rise in trade costs for air freight during the pandemic was significant but less than that for sea freight. The drivers of variation in trade costs at the levels of product and economy of origin are identified, including distance, unit value, and institutional variables. The long run trend is for trade costs to fall in both sea and air freight modes. There is scope for further reduction in costs associated with air freight when supported by innovation in the sector, including the application of digital technology. This shift is facilitated by a number of policy initiatives, including more open policy regimes for air freight services and implementation of commitments in the World Trade Organization’s Trade Facilitation Agreement. |
| Keywords: | air freight, COVID-19, trade costs, services trade restrictiveness |
| JEL: | R41 F14 |
| Date: | 2024–07–03 |
| URL: | https://d.repec.org/n?u=RePEc:era:wpaper:dp-2024-19 |
| By: | Grimaldi, Daniel (George Mason University); Mitnik, Oscar A. (Inter-American Development Bank); Zimmermann, Beatrice (Inter-American Development Bank) |
| Abstract: | How does the proximity to a metro station affect urban development in Latin America? While the literature assessing the causal impacts of transportation infrastructure has grown in recent years, only a few papers have focused on the effects of metro systems in Latin America and the Caribbean (LAC) region, and identifying the precise impacts of such investments is far from straightforward. We apply a Synthetic Difference-in-Differences (SDiD) approach to estimate the effects of the expansion of Line 5 of the São Paulo metro system in Brazil on land use and property features. Our results show positive impacts on constructed area, with a treatment effect that is half the magnitude of the average constructed area in untreated units in the pre-treatment period. Additionally, our findings indicate an increase in the number of properties around the stations, with a shift in property composition towards more commercial units. We also find a strong anticipation effect associated with the new metro infrastructure and dynamic impacts after the opening of the first metro station, with effects that increase over time. |
| Keywords: | land use, infrastructure investments, impact evaluation |
| JEL: | R14 R40 R42 |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp17414 |
| By: | Jo, Ah-Hyun (Korea Maritime Institute); Cho , Seong-Hyun (Korea Maritime Institute); Kim, Bo-Kyung (Korea Maritime Institute); Kim , Kijin (Asian Development Bank); Gaduena, Ammielou (Asian Development Bank) |
| Abstract: | This study measures congestion in major container ports and investigates how port characteristics and regional factors influence congestion during the COVID-19 periods. We develop port congestion indicators, including vessel arrivals, vessels staying in a period, waiting time, and service time. First, descriptive analysis reveals significantly higher service and waiting times in 2021 due to global supply chain disruptions. Import/export-focused ports were more affected than transshipment hubs. Short-term events such as labor strikes also substantially impacted port congestion. Next, using econometric analyses, estimated impulse response functions indicate a decrease in the number of ship calls following increased mobility restrictions, with average waiting time at anchorage promptly increasing, while average service time at berth was comparatively less affected by the mobility measures. Additionally, we find significant mobility impacts from neighboring ports, comparable in magnitude to those from the respective ports. |
| Keywords: | container port; automatic identification system; lockdown; impulse-response |
| JEL: | C32 F14 L81 R41 |
| Date: | 2024–10–28 |
| URL: | https://d.repec.org/n?u=RePEc:ris:adbewp:0747 |
| By: | Krantz, Sebastian |
| Abstract: | Using rich geospatial data and causal machine learning (ML), this paper maps potential economic benefits from incremental investments in all major types of public and economic infrastructure across Africa. These 'infrastructure potential maps' cover all African populated areas at a spatial resolution of 9.7km (96km2). They show that the local returns to infrastructure are highly variable and context-specific. For example 'hard infrastructure' such as paved roads and communications is more beneficial in cities, whereas 'social infrastructure' such as education, health, public services and utilities is more critical in rural areas. Market access and agglomeration effects largely govern these returns. The open Africa Infrastructure Database built for this project provides granular data in 54 economic categories/sectors. It reveals that Africa's infrastructure is concentrated in urban areas, with cities exhibiting marked heterogeneity in infrastructure, public services, and economic activities. Spatial inefficiency is common. The findings are consistent with economic literature, highlighting causal ML and explainable AI's potential to generate insights from geospatial data and assist spatial planning. |
| Keywords: | Africa, infrastructure, investment potential, geospatial big data, causal ML, explainable AI |
| JEL: | O18 R11 R40 C14 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:ifwkwp:305261 |
| By: | Rungsee Benjaanunphong; Pornraht Pongprasert |
| Abstract: | This research aims to analyze the factors affecting the price of condominium projects along the Mass Rapid Transit (MRT) Orange Line, an electric train that is expected to start operation in 2025. It is the main Heavy Rail line connecting Eastern Bangkok suburbs with the city's new Central Business District (New CBD). To provide more opportunities for land development, the city plan of Bangkok has also changed along the Orange Line, especially Ramkhamhaeng Road. The price of land will rise as a result. Researchers are interested about how the price of the condominium will change if additional factors are taken into consideration, such as the project's proximity to the MRT station, the main road, the expressway entrance and exit points, private facilities, and other factors related to the operator's reliability and the expense of the common area. To construct the project and set the price in line with the actual circumstances, this research outcome aims to provide real estate developers with an understanding of the factors that determine the pricing of condominiums along MRT Orange. Buyers of condominiums can use the proper price information to inform their selections. When making investing decisions, investors of stocks in real estate companies could consider this information into consideration and this data can be used as an outline by the Revenue Department to collect land taxes. In this research was used to analyse data from 28 condominium projects along Orange Line with a project life of no more than five years, covering areas close to the new CBD to the Eastern Bangkok suburbs, such as Min Buri. There are a total of 17 factors used in running regression under 3 groups: Locational, Physical and neighborhood characteristics. In result, it is found that 3 factors that affect the price are: Floors, Distance from Train Station and Distance from Department Store. |
| Keywords: | Central Business District (CBD); Condominium; Eastern Bangkok suburbs; MRT Orange Line |
| JEL: | R3 |
| Date: | 2024–01–01 |
| URL: | https://d.repec.org/n?u=RePEc:arz:wpaper:eres2024-239 |