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on Transport Economics |
| By: | João Amador; Carlos Melo Gouveia; Ana Catarina Pimenta |
| Abstract: | This paper studies the determinants of exporters’ transport mode choices by combining a simple calibrated model of a profit-maximizing firm with a conditional logit econometric exercise based on very detailed international trade data for Portuguese firms. The paper considers three transport modes – sea, road, and air – and data for the period between 2012 and 2023. The database signals that road transport dominates on short distances, whereas sea and air are preferred for longer routes. Results from model calibration indicate that, for some product–transport mode combinations, longer transit times substantially reduce profits, thus increasing the likelihood of switching transport modes. Empirical results state that the probability of selecting a mode is lower when either transit time or transport costs increase. Product bulkiness, degree of perishability and technological content also affect transport mode selection. In addition, higher unit prices of exported goods shift firms away from sea transport and towards air transport. Simulation exercises using estimated coefficients indicate that a closure of the Suez Canal sizably reduces the probability of choosing a maritime route to Asia, while a one order increase in the price of CO2 emissions would not materially alter the choice of transport mode. |
| JEL: | C35 F14 R41 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ptu:wpaper:w202517 |
| By: | Alessandro V. M. Oliveira; Moises D. Vassallo |
| Abstract: | This study investigates how the layout and density of seats in aircraft cabins influence the pricing of airline tickets on domestic flights. The analysis is based on microdata from boarding passes linked to face-to-face interviews with passengers, allowing us to relate the price paid to the location on the aircraft seat map, as well as market characteristics and flight operations. Econometric models were estimated using the Post-Double-Selection LASSO (PDS-LASSO) procedure, which selects numerous controls for unobservable factors linked to commercial and operational aspects, thus enabling better identification of the effect of variables such as advance purchase, reason for travel, fuel price, market structure, and load factor, among others. The results suggest that a higher density of seat rows is associated with lower prices, reflecting economies of scale with the increase in aircraft size and gains in operational efficiency. An unexpected result was also obtained: in situations where there was no seat selection fee, passengers with more expensive tickets were often allocated middle seats due to purchasing at short notice, when the side alternatives were no longer available. This behavior helps explain the economic logic behind one of the main ancillary revenues of airlines. In addition to quantitative analysis, the study incorporates an exploratory approach to innovative cabin concepts and their possible effects on density and comfort on board. |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2512.08066 |
| By: | Anna Alberini; Javier Bas; Cinzia Cirillo |
| Abstract: | We devise a difference-in-difference study design to assess the impact of fare-free bus service in Alexandria, located in the Washington, DC metro area. Our surveys show modest to no effect, with at most 6% more residents in Alexandria increasing their bus usage compared to control locations. We find no effect on ground-level ozone or road crashes, suggesting little to no impact on road traffic. One-third of respondents in control locations indicated they would use buses more frequently if fare-free service were available in their areas. Based on the respondent-reported reductions in car miles, the program led to a reduction of 0.294 to 0.494 tons of CO2 per year, or 5% to 9% of the average annual emissions from a US car, at a cost of $70-$120 per ton of CO2. We predict a CO2 reduction of 0.454 tons per year, equivalent to 8% of the average US car's annual emissions if the fare-free bus covered all of the study areas. |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2601.02190 |
| By: | Palak Suri; Maureen L. Cropper |
| Abstract: | We estimate the effects of the first metro rail line in Mumbai using administrative data on assessed property prices from 2011-18 for 723 subzones in the city. Comparing areas within 1 km of the metro with those beyond 1 km but within 3 km, we estimate the effects on property values for commercial, industrial, and residential properties. We find a significant and persistent increase in prices of 6-8% for residential and commercial land use categories in treated areas relative to control areas after Metro Line 1 opens. We show that commute time savings and improvements in employment accessibility are plausible mechanisms underlying these effects. |
| JEL: | O18 R1 R3 R4 |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34650 |
| By: | Tang, Junxian; Zhang, Ruohao; Lei, Zhen; Wan, Xibo; Hu, Xianbiao |
| Keywords: | Resource/Energy Economics and Policy |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ags:aaea25:361222 |
| By: | Shigeharu Okajima (Kobe University, Graduate School of International Cooperation Studies, 2-1 Rokkodai-cho, Nada-ku, Kobe 657- 8501.); Hiroko Okajima (Nagoya University, Nagoya University Graduate School of Economics, Furocho, Chikusa Ward, Nagoya City Aichi 464-8601.); Kenta Nakamura (Kobe University, Graduate School of Economics, 2-1 Rokkodai-cho, Nada-ku, Kobe 657-8501); Yoshito Nakayama (Osaka University of Economics, 2-2-8 Osumi HigashiYodogawa-ku Osaka-shi, 533-8533.) |
| Abstract: | This study evaluates the environmental effectiveness of Japan’s eco-car tax incentive program by explicitly accounting for the strategic weight manipulation by automobile manufacturers. Using monthly vehicle- level panel data from 2005 to 2021, we estimate a structural demand model for the Japanese passenger car market to examine how firms respond to weight-based fuel economy standards. Our results show that vehicles strategically adjusted to exceed regulatory weight thresholds experienced a 31% increase in relative market share, reflecting a substantial demand expansion driven by regulatory compliance rather than genuine fuel efficiency improvements. To assess the broader implications, we conduct a structural substitution counterfactual analysis comparing the observed outcomes with a no- manipulation benchmark. The counterfactual analysis reveals that strategic weight manipulation increases the sales of manipulated vehicles by 102, 771 units and reduces the sales of compliant vehicles by only 3, 707 units. This asymmetric displacement indicates that manipulation primarily expands overall demand rather than reallocating sales among substitutes. The resulting demand distortion produced a net increase of 133, 162 tons of CO2 emissions over the sample period, substantially undermining the policy’s emissions-reduction objectives. Our findings demonstrate that weight-class-based fuel economy regulation creates strong incentives for regulatory gaming, which materially weakens environmental effectiveness. The results highlight the need for policy designs that minimize discrete eligibility thresholds and reward continuous and verifiable improvements in real-world fuel efficiency. |
| Keywords: | eco-car policy, strategic manipulation, vehicle demand, CO2 emissions |
| JEL: | Q51 Q53 Q58 |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:was:dpaper:2504 |
| By: | Robert D. Metcalfe; Andrew Schein; Cohen R. Simpson; Yixin Sun |
| Abstract: | One of the promising opportunities offered by AI to support the decarbonization of electricity grids is to align demand with low-carbon supply. We evaluated the effects of one of the world’s largest AI managed EV charging tariffs (a retail electricity pricing plan) using a large-scale natural field experiment. The tariff dynamically controlled vehicle charging to follow real-time wholesale electricity prices and coordinate and optimize charging for the grid and the consumer through AI. We randomized financial incentives to encourage enrollment onto the tariff. Over more than a year, we found that the tariff led to a 42% reduction in household electricity demand during peak hours, with 100% of this demand shifted to lower-cost and lower-carbon-intensity periods. The tariff generated substantial consumer savings, while demonstrating potential to lower producer costs, energy system costs, and carbon emissions through significant load shifting. Overrides of the AI algorithm were low, suggesting that this tariff was likely more efficient than a real-time-pricing tariff without AI, given our theoretical framework. We found similar plug-in and override behavior in several markets, including the UK, US, Germany, and Spain, implying the potential for comparable demand and welfare effects. Our findings highlight the potential for scalable AI managed charging and its substantial welfare gains for the electricity system and society. We also show that experimental estimates differed meaningfully from those obtained via non-randomized difference-in-differences analysis, due to differences in the samples in the two evaluation strategies, although we can reconcile the estimates with observables. |
| JEL: | Q4 |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34709 |
| By: | Pranshu Raghuvanshi (India Institute of Science, Bangalore, India); Anjula Gurtoo (India Institute of Science, Bangalore, India) |
| Abstract: | This study uses the Theory of Planned Behaviour (TPB) framework and expands it by including Optimism, Innovativeness and Range Anxiety constructs. In this study, conducted in Lucknow, the capital of India's most populous province (Uttar Pradesh), a multi stage random sampling design was employed to select 432 respondents from different city areas. The survey instruments were adapted from similar studies and suitably modified to suit the context. Using exploratory factor analysis, 18 measurement items converged into six factors, namely attitude, subjective norms, perceived behavioural control, optimism, innovativeness and range anxiety. We confirmed the reliability and validity of the constructs using Cronbach's alpha, composite reliability, average variance extracted and discriminant validity analysis. We explored the relationship between them using structural equation modelling. All factors but Optimism were found to be significantly associated with adoption intention. We further employed mediation analysis to examine the mediation pathways. The TPB components mediated the effect of innovativeness but not range anxiety. The study's insights can help policymakers and marketers design targeted interventions that address consumer concerns, reshape consumer perceptions, and foster greater EV adoption. The interventions can target increasing the mediating variables or decreasing range anxiety to facilitate a smoother transition to sustainable transportation. |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2512.07188 |
| By: | Ei Phyu Kyi; Tao Feng; Jieyuan Lan; Ying Liu |
| Abstract: | The potential for drone delivery services to transform logistics systems and consumer behavior has gained increasing attention. However, comprehensive empirical evidence on consumer delivery choice behavior within the context of transportation and urban air logistics remains limited, particularly in Japan. This study addresses this gap by examining Japanese consumers' preferences and behavioral intentions toward drone delivery services. Using a stated preference (SP) survey and discrete choice modeling approaches, including multinomial logit (MNL) and mixed logit (MMNL) models, the analysis evaluates how delivery cost, delivery time, drop-off location, product type, and social influence affect delivery mode choices across different demographic groups. The results indicate that although consumers express interest in drone delivery, perceived cost and concerns related to reliability continue to constrain adoption. Younger and male consumers exhibit higher preferences for drone delivery, while product type, particularly daily consumer goods and medical or healthcare items, plays a significant role in shaping preferences. Post-estimation willingness-to-pay and elasticity analyses further highlight consumers' sensitivity to delivery pricing and speed attributes. Overall, the findings provide actionable insights for logistics service providers and policymakers regarding pricing strategies, service targeting, and deployment approaches for integrating drone delivery into Japan's evolving logistics system. |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2601.08660 |
| By: | Samuel Darwisman |
| Abstract: | The science of pipeline transport is currently governed by a collection of fragmented, discipline-specific theories that are inadequate for addressing the systemic challenges of 21st-century infrastructure. This paper introduces and formalizes a new, unified theory: the General Theory of Piping Transportation (GTPT), formulated by Darwisman. The GTPT posits that a pipeline system is a complex socio-technical entity whose state and long-term viability are determined by the fully coupled interaction of three interdependent domains: Physical Dynamics ({\Phi}), Life-Cycle Dynamics ({\Lambda}), and Socio-Economic Dynamics ({\Sigma}). This paper presents the core postulates of the GTPT, which are derived from a systematic synthesis of the fragmented existing literature. The prescriptive power of the theory is illustrated by contrasting the strategic outcomes derived from the GTPT against those from classical theories. By defining resilience as the primary design objective and operationalizing the UN Sustainable Development Goals (SDGs), the GTPT provides a new theoretical foundation for the design, management, and governance of infrastructure across all critical sectors. |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2512.13081 |