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on Transport Economics |
| By: | Isaksen, Elisabeth T.; Johansen, Bjørn G. |
| Abstract: | Decarbonizing transportation requires a shift from conventional to zero-emission vehicles. We examine whether congestion pricing with electric vehicle (EV) exemptions accelerates this transition by encouraging a shift toward cleaner cars. To identify causal effects, we combine administrative data on car ownership with a triple-differences design that exploits household-level variation in policy exposure across metropolitan areas and work commutes. We find that higher rush hour charges for conventional vehicles significantly increase EV adoption, primarily through replacement rather than fleet expansion. However, responses vary by socioeconomic characteristics, with higher-income and well-educated households more likely to adopt EVs. Beyond car ownership, we document behavioral adjustments, including relocation to avoid tolls, re-routing around the cordon, and shifting travel timing. Overall, congestion pricing reduced traffic volumes and improved air quality. Our findings offer insights for designing equitable and effective transportation policies. |
| Keywords: | congestion pricing; electric vehicles; car ownership; transportation policy; traffic; air polution |
| JEL: | H23 R41 R48 Q58 Q52 Q55 |
| Date: | 2025–05–31 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:127836 |
| By: | Cody Cook; Aboudy Kreidieh; Shoshana Vasserman; Hunt Allcott; Neha Arora; Freek van Sambeek; Andrew Tomkins; Eray Turkel |
| Abstract: | Starting in January 2025, New York City became the first city in the United States to introduce a fee for vehicles entering its central business district (CBD). Using Google Maps Traffic Trends, we show that the policy increased speeds in the CBD, had spillovers onto non-CBD roads, and reduced estimated vehicle emissions throughout the metro area. Relative to a set of control cities, average traffic speeds in NYC’s CBD increased by 15% following the introduction of congestion pricing, with larger effects during the most congested hours. Roads commonly traversed on routes to the CBD before the policy have also seen an increase in speeds and a decrease in estimated vehicle CO₂ emission rates. Overall, these speed changes reduced realized travel times on trips to and within the CBD by approximately 8%. The increase in speed is greatest in neighborhoods closer to the CBD, with no significant difference between neighborhoods with different income levels. |
| JEL: | R4 R41 R48 R5 |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33584 |
| By: | Pan, Alexandra Q; Deakin, Elizabeth; Shaheen, Susan A |
| Abstract: | The relationship between housing and transportation costs has been the focus of much research, with classic urban theory positing that housing costs decrease and commuting costs increase as households move away from city centers. The growing population of low and low-moderate (LMI) households in suburbs may be taking advantage of lower housing costs, though research shows that housing cost savings in suburbs are offset by higher transportation costs. Our research explores dimensions of housing and transportation cost burden on LMI households in Contra Costa County in the San Francisco Bay Area using qualitative data from online/in-person surveys (n=208) and interviews conducted in English and Spanish (n=25). We found that housing burden is high, suggesting that LMI households choose to live in suburbs for diverse reasons, including rising rents and other requirements (e.g., credit score, rental history) in core cities, and desire for home ownership and a safer environment for children. Yet LMI suburban residents are still vulnerable to rising rents and housing instability in suburban areas. In addition to high housing costs, transportation costs are higher in suburbs due to longer commutes and higher reliance on personal vehicles. Car access is necessary, especially for households with young children. Reliance on cars becomes an issue as LMI households often encounter maintenance issues of used cars or inability to make car payments. When faced with lack of car ownership, households rely on social networks or public transit, and in some cases, forgo trips or relinquish their vehicles entirely. The lack of quality transportation alternatives in suburban contexts, as existing public transit services have long headways and are not well-suited to serving off-peak trips between suburban areas, leaves LMI households vulnerable. |
| Keywords: | Engineering |
| Date: | 2023–12–01 |
| URL: | https://d.repec.org/n?u=RePEc:cdl:itsrrp:qt90f5j3mb |
| By: | Ostrovsky, Michael (Stanford U); Yang, Frank (U of Chicago) |
| Abstract: | In this paper, we argue that the New York City congestion pricing plan whose implementation was paused in the summer of 2024 had a major shortcoming: as designed, it would have had a much more severe impact on the drivers of personal vehicles than on the passengers of taxis and ride-hailing vehicles, as well as on the clients of delivery services. In addition to being inequitable, this shortcoming would have likely made the congestion pricing scheme ineffective at solving the traffic congestion problem, due to the fact that the drivers of personal vehicles constitute a minority of traffic in the congestion pricing zone. We propose a simple modification to the scheme that addresses this shortcoming. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:ecl:stabus:4228 |
| By: | Eliseo Curcio |
| Abstract: | This study evaluates ethanol blending as a practical near-term strategy for significant transportation decarbonization in the United States. Despite rapid growth in electric vehicle adoption, gasoline is projected to remain dominant, with annual demand around 135 billion gallons by 2035, necessitating immediate complementary solutions. Analysis indicates ethanol use will notably expand, driven by regulatory incentives such as RFS Renewable Identification Numbers (RINs) and IRA tax credits (45V), leading to potential market penetration of E15 at about 25% and E85 also expanding substantially. Ethanol derived from waste achieves notably lower carbon intensity at approximately 58.34 gCO2e/MJ, substantially better than conventional gasoline (~92 gCO2e/MJ), providing clear environmental advantages. Economic assessments show robust investor returns and local economic growth driven by policy incentives, including Renewable Identification Numbers (RINs) and IRA tax credits (45V). Infrastructure analysis confirms manageable costs and feasible adjustments for widespread adoption of higher ethanol blends. |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2504.06278 |
| By: | Kumar, Santosh (University of Notre Dame); Shandal, Monica (University of California, Santa Cruz); Zucker, Ariel (UC Santa Cruz) |
| Abstract: | We examine the impact of rural road connectivity on economic and social outcomes in the context of India’s PMGSY, the world’s largest rural road program. Using a novel village-level survey explicitly designed around PMGSY’s rollout, we exploit quasi-random variation in road placement to estimate causal effects. We find that roads increase producer prices by 1.4 SD, reduce consumer prices by 0.6 SD, shift labor from agriculture to local casual work, and decrease short-term migration. Additionally, road connectivity improves governance, delays marriages, and improves wedding quality. Our findings highlight the role of infrastructure in shaping rural economies and social institutions. |
| Keywords: | migration, wages, prices, PMGSY, rural roads, India |
| JEL: | I15 J43 O12 O18 R23 R42 |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp17775 |
| By: | Credit, Kevin |
| Abstract: | As per capita on-road CO2 emissions continue to rise in the US, a better understanding of the emissions-reduction benefits of building a new transit system is needed. Employing a novel quasi-experimental event study methodology, the results of this paper indicate that after 8 years of operation, construction of a light rail system has led to a small but significant reduction in regional on-road CO2 per capita of 8.4% - 12.9%. These results are robust to selection of control group and are larger than the estimated impact of light rail construction on population density (1.0%), evaluated in a comparative quasi-“placebo” study. |
| Date: | 2025–03–14 |
| URL: | https://d.repec.org/n?u=RePEc:osf:osfxxx:euyj6_v2 |
| By: | Credit, Kevin |
| Abstract: | As per capita on-road CO2 emissions continue to rise in the US, a better understanding of the emissions-reduction benefits of building a new transit system is needed. Employing a novel quasi-experimental event study methodology, the results of this paper indicate that after 8 years of operation, construction of a light rail system has led to a small but significant reduction in regional on-road CO2 per capita of 8.4% - 12.9%. These results are robust to selection of control group and are larger than the estimated impact of light rail construction on population density (1.0%), evaluated in a comparative quasi-“placebo” study. |
| Date: | 2025–03–07 |
| URL: | https://d.repec.org/n?u=RePEc:osf:osfxxx:euyj6_v1 |
| By: | Morando, Alberto |
| Abstract: | Many low-severity crashes with no injuries are not reported in crash databases due to specific sampling criteria. If this sampling bias is not addressed, safety assessment analyses could yield inaccurate results. Unreported cases in crash databases are an example of missing not at random (MNAR) data. Recognizing and addressing MNAR data can be difficult; it requires domain expertise and clear assumptions to build accurate statistical models to recover the complete sample. Previous studies have often created ad-hoc procedures with arbitrary or implicit assumptions. These procedures are not directly adaptable to different use cases, do not account well for uncertainty from the biased data and the modelling choices, and are harder to critique due to the multiple steps involved, which can sometimes be intricate. This paper illustrates a method to address MNAR data while maintaining the set of observations intact. Based on principles of probability and clear modeling assumptions, the method is implemented using modern Bayesian probabilistic programming techniques. We include two examples: in the first, we used simulated data to demonstrate that the procedure is correct; in the second, we used crash data to estimate the complete distribution of Δv for passenger vehicles involved in personal damage-only (PDO) rear-end crashes. We estimated that about 77% of data on these vehicles is missing. The method can be used as a preliminary step in safety benefit analyses---for example, to accurately estimate baseline conditions for safety benefit estimation. This method is not restricted to the traffic safety domain but can be tailored to any use case involving systematic sampling bias. The code has been made publicly available. |
| Date: | 2025–03–05 |
| URL: | https://d.repec.org/n?u=RePEc:osf:osfxxx:u8wp6_v1 |
| By: | Nikolaos Kalyviotis; Christopher D. F. Rogers; Geoffrey J. D. Hewings |
| Abstract: | Transport infrastructure systems operate in, and are shaped by, the specific context in which they are expected to perform and contribute to the system-of-systems that support civilised life; they must strive to be sustainable and resilient. However, transport, one of the economic infrastructures, is viewed narrowly in political circles as a vehicle for economic prosperity: political focus falls on the economic pillar of sustainability. One perennial challenge concerns the inclusion of social and environmental value into such performance judgements. A deep understanding of system interdependencies is essential when comparing input output tables (a top down approach) with cost benefit analysis (CBA, a bottom up approach). CBA works best when there is adequate information to calculate a monetary value for all economic, social, and environmental outcomes, whereas input output tables are most effective when environmental and social value are kept distinct from economic value and where the beneficial economic impacts extend across multiple sectors (CBA is inadequate in this regard). This research uses the World Input Output Database and principal component analysis to develop a model to capture this complex accounting process.In recognising how past interdependencies inform future development, this study s model provides new insights into indirect economic value creation within infrastructure systems. |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2504.15306 |
| By: | Caitlin K. Myers; Daniel L. Dench; Mayra Pineda-Torres |
| Abstract: | We use difference-in-differences research designs to estimate the effects of abortion bans on births at the county level, leveraging data on changes in driving distance and appointment availability at the nearest facility where abortion remains legal. We find that bans alone increase births, but their total impact depends on geographic barriers to access. Even in counties where distance and appointment availability remain unchanged, a total ban leads to a 1.0% increase in births, suggesting a chilling effect—potentially due to legal uncertainty, misinformation, or logistical hurdles—that is independent of measurable barriers. However, the effects grow substantially with travel burdens. In counties where the nearest abortion facility was 50 miles away pre-Dobbs, a total ban increases births by 2.8% when distance rises to 300 miles. Limited appointment availability in destination cities further amplifies these effects, resulting in an additional 0.4 percentage point increase in births. The largest increases occur among Black and Hispanic women, those without a college degree, and unmarried women. We do not observe evidence that the effects have diminished with time despite expanded logistical, financial, and telehealth abortion support, underscoring the persistent role that geographic barriers play in abortion access. |
| JEL: | I11 I12 I18 J13 K23 |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33548 |
| By: | Adam Gill; Lena E. Hensvik; Oskar Nordström Skans |
| Abstract: | In this article, we show that working from home is much more prevalent in the Nordic countries than in the rest of Europe and we discuss potential causes and labor market consequences of this stylized fact. Likely contributing causes include a good technological infrastructure and comparatively widespread digital preparedness in the population. Recent research also suggests that trust is a crucial prerequisite for maintaining a spatial separation between supervisors and workers in marginal occupations. We show that survey measures of trust are extremely high in all Nordic countries, and that these measures correlate very strongly with work-from-home across countries and industries in Europe even controlling for a range of cross-country differences. Finally, we discuss potential spillover effects of increased hybrid work on the Nordic labor markets. We show evidence suggesting that increased hybrid work has caused a relocation of the production of local service firms from business centers to high-work-from-home residential areas, without affecting average commuting distances of service workers. |
| JEL: | J32 M54 R30 |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33581 |
| By: | Jun Nakabayashi; Juan M. Ortner; Sylvain Chassang; Kei Kawai |
| Abstract: | Auctioneers suspecting bidder collusion often lack the formal evidence needed for legal recourse. A practical alternative is to design auctions that hinder collusion. Since Abreu et al. (1986), economic theory has emphasized imperfect monitoring as a constraint on collusion, but evidence remains scarce on whether: (i) information frictions meaningfully limit real-world collusion; and (ii) auctioneers can effectively exploit these frictions. Indeed, transparency concerns often prevent the introduction of explicit randomness in auction design. We make progress on this issue by studying the impact of subjective scoring in auctions run by Japan’s Ministry of Land, Infrastructure, and Transportation. The adoption of scoring auctions significantly reduced winning bids in ways inconsistent with competition. Model-based inference suggests that the cartel’s dynamic obedience constraints were binding and were tightened by imperfect monitoring. Subjective scoring can successfully leverage imperfect monitoring frictions to reduce the scope of collusion. |
| JEL: | C57 C72 D44 L41 |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33668 |