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on Transport Economics |
| By: | André de Palma; Zhenyu Yang; Pietro Giardina; Nikolas Gerolimnis (CY Cergy Paris Université, THEMA) |
| Abstract: | We aim to infer commuters’ scheduling preferences from their observed arrival times, given an exogenous traffic congestion pattern. To do this, we employ a structural model that characterizes how users balance congestion costs against the penalties for arriving early or late relative to an ideal time. In this framework, each commuter selects an arrival time that minimizes her overall trip cost by considering the within-day congestion pattern along with her individual scheduling preference. By incorporating the distribution of these preferences and desired arrival times across the population, we can estimate the likelihood of observing arrivals at specific times. Using synthetic data, we then apply the maximum likelihood estimation (MLE) method to recover the parameters of the joint distribution of scheduling preferences and desired arrival times. Our numerical results demonstrate the effectiveness of the proposed method. |
| Keywords: | Bottleneck, Scheduling preferences, Traffic flow; Travel demand management |
| JEL: | C25 R41 D12 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ema:worpap:2025-15 |
| By: | Madhavi Pundit (Asian Development Bank); Immanuel Sin (Asian Development Bank); Paolo Magnata (Asian Development Bank); R. Duncan McIntosh (Asian Development Bank); Priscille Villanueva (Asian Development Bank) |
| Abstract: | The automatic identification system (AIS) is a short-range coastal tracking system used to identify ships and their speed and location worldwide. This case study leverages high frequency AIS data to analyze the impact of typhoons on port activity in the Philippines. Maritime transport plays a pivotal role in facilitating trade and transportation of goods and passengers in an archipelago like the Philippines. The Philippines typically encounters 20 tropical cyclones each year, with significant impacts on port operations and economic activity. We study Typhoon Phanfone (known in the Philippines as Typhoon Ursula) that hit the Philippines in December 2019. Disruptions in maritime activity based on daily ship traffic were measured using AIS data over a 2-year period for the Philippines and its top trade partners. A Bayesian structural time series model was employed to build a counterfactual for quantifying the impact of Typhoon Phanfone on specific Philippine ports. This analytical framework that harnesses the potential of AIS data provides policymakers and stakeholders with a tool for near real-time impact assessment that informs planning regarding port operations, scheduling, and resource allocation, and can feed into medium-term disaster risk management decisions |
| Keywords: | AIS data;daily ship traffic;Bayesian structural time series model |
| JEL: | C11 C32 C55 Q54 |
| Date: | 2025–11–05 |
| URL: | https://d.repec.org/n?u=RePEc:ris:adbewp:021739 |
| By: | Ertian Chen |
| Abstract: | Distributional assumptions that discipline serially correlated latent variables play a central role in dynamic structural models. We propose a framework to quantify the sensitivity of scalar parameters of interest (e.g., welfare, elasticity) to such distributional assumptions. We derive bounds on the scalar parameter by perturbing a reference distribution, while imposing a stationarity condition for time-homogeneous models or a Markovian condition for time-inhomogeneous models. The bounds are the solutions to optimization problems, for which we derive a computationally tractable dual formulation. We establish consistency, convergence rate, and asymptotic distribution for the estimator of the bounds. We demonstrate the approach with two applications: an infinite-horizon dynamic demand model for new cars in the United Kingdom, Germany, and France, and a finite-horizon dynamic labor supply model for taxi drivers in New York City. In the car application, perturbed price elasticities deviate by at most 15.24% from the reference elasticities, while perturbed estimates of consumer surplus from an additional $3, 000 electric vehicle subsidy vary by up to 102.75%. In the labor supply application, the perturbed Frisch labor supply elasticity deviates by at most 76.83% for weekday drivers and 42.84% for weekend drivers. |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2510.22347 |
| By: | Florian Allroggen; R. John Hansman; Christopher R. Knittel; Jing Li; Xibo Wan; Juju Wang |
| Abstract: | Air transportation supports economic growth and global connectivity but imposes localized environmental costs, particularly through aircraft noise. We estimate the causal effect of aviation noise on housing prices using quasi-experimental variation from the Federal Aviation Administration's rollout of performance-based navigation (PBN) procedures and runway reconfigurations at three major U.S. airports. Combining high-resolution flight trajectory data with geocoded housing transactions, we apply a difference-in-differences hedonic framework to identify changes in exposure unanticipated by residents. A one-decibel increase in annual day-night average sound level reduces house prices by 0.6 to 1.0 percent. Among alternative noise metrics, average exposure explains property value impacts most strongly. Willingness to pay for quieter conditions varies systematically with income and race, indicating that aircraft noise externalities have meaningful distributional consequences. Our results highlight the need to incorporate localized environmental costs into aviation and urban land-use policy. |
| JEL: | L51 L62 L85 Q53 |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34431 |
| By: | Precetti, Josephine |
| Abstract: | France’s railway expansion following the Law of 11 June 1842 significantly reshaped nationwide connectivity and economic opportunities. This dissertation investigates the causal impacts of railway access between 1846 and 1861 on city-level industrial development. Using a dataset combining industrial surveys with digitized railway records, it employs a robust Difference-in-Differences approach, leveraging the quasi-exogenous roll-out of the centrally planned ‘étoile de Legrand’ railway network. Empirical results show railway access increased industrial activity primarily extensively: railway-connected cities saw approximately a 20% rise in the number of factories and workers, especially in labour-intensive sectors like textile in Lille and ceramics in Limoges. Yet, intensive effects such as factory size, productivity, and wages remained statistically and economically negligible. Contrary to theoretical predictions from trade and New Economic Geography models, capital-intensive sectors, such as metallurgy in Lorraine, did not exhibit statistically significant responsiveness. These findings reframe the role of transport infrastructure from being a deterministic catalyst to being better understood as a conditional enabler. While railways expanded market potential, their short to medium term transformative impact critically depended on complementary institutional frameworks notably financial markets and property rights, technological readiness, and regional contexts. Acknowledging the historical data limitations, this study underscores that transport infrastructure alone is insufficient for structural economic upgrading without the appropriate institutional, technological, and human capital conditions in place at the right time. |
| JEL: | N73 R40 |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:129951 |
| By: | López, Rigoberto A.; Seoane, Luis |
| Abstract: | The meatpacking industry is a crucial intermediary between ranchers and the downstream supply chain, and concentration within the industry has significant implications for stakeholders in terms of competition and transmission of efficiencies. Due to constraints on the efficient transportation of live animals over long distances, ranchers primarily operate within regional markets. In this paper we provide new knowledge about the degree of regional concentration in the beef packing industry and propose a model to examine its impact on the wholesale farm-price spread. Findings indicate a significant increase in concentration across all regions, with some regions experiencing up to a 300 percent rise in the Herfindahl index, although concentration levels vary considerably among the different regions. |
| Keywords: | Livestock Production/Industries |
| Date: | 2024–04 |
| URL: | https://d.repec.org/n?u=RePEc:ags:aaea23:341195 |
| By: | Runyu Wang; Haotian Zhong |
| Abstract: | Urban food delivery services have become an integral part of daily life, yet their mobility and environmental externalities remain poorly addressed by planners. Most studies neglect whether consumers pay enough to internalize the broader social costs of these services. This study quantifies the value of access to and use of food delivery services in Beijing, China, through two discrete choice experiments. The first measures willingness to accept compensation for giving up access, with a median value of CNY588 (approximately USD80). The second captures willingness to pay for reduced waiting time and improved reliability, showing valuations far exceeding typical delivery fees (e.g., CNY96.6/hour and CNY4.83/min at work). These results suggest a substantial consumer surplus and a clear underpricing problem. These findings highlight the need for urban planning to integrate digital service economies into pricing and mobility frameworks. We propose a quantity-based pricing model that targets delivery speed rather than order volume, addressing the primary source of externalities while maintaining net welfare gains. This approach offers a pragmatic, equity-conscious strategy to curb delivery-related congestion, emissions, and safety risks, especially in dense urban cores. |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2510.26636 |
| By: | Lohawala, Nafisa (Resources for the Future); Linn, Joshua (Resources for the Future); Bioret, Lucie (Resources for the Future); DeAngeli, Emma (Resources for the Future); Roy, Nicholas (Resources for the Future); Spiller, Beia (Resources for the Future) |
| Abstract: | This paper presents a retrospective analysis of the Environmental Protection Agency (EPA) 2007 regulations targeting NOx emissions from heavy-duty vehicles. We replicate EPA’s on-road emissions model and compare the assumptions used in its analysis—vehicle sales, scrappage rates, NOx emission rates, and vehicle use—with actual outcomes in 2022. This comparison evaluates the accuracy of EPA’s assumptions and their long-term impact on NOx reduction estimates, providing a basis to assess the accuracy of the similar methodology used in the recent 2022 standards. We find that EPA’s most significant prediction error was overestimating scrappage rates of older vehicles, which led to underestimated emissions both with and without the policy; on net, this resulted in an underestimation of emissions reductions by 0.52 million tons. Conversely, EPA underestimated miles traveled by older vehicles, which, on net, overestimated emissions reductions, as these high-emission vehicles traveled more than expected. Anticipatory sales effects before 2007 had minimal effects on emissions in 2022. Although certified emissions have consistently been below required standards, this discrepancy had only a minor effect on EPA’s overall emissions predictions. |
| Date: | 2025–04–23 |
| URL: | https://d.repec.org/n?u=RePEc:rff:dpaper:dp-25-12 |
| By: | Filkoski, Vasil; Tevdovski, Dragan |
| Abstract: | We develop a methodology that leverages open-source geospatial data on fuel station infrastructure and related services to construct the Gas Station Index (GSI), a novel indicator that augments official and alternative measures of regional economic development. Gas stations serve as consumer-facing infrastructure nodes, and their density and quality reflect local demand, purchasing power, and mobility. Using data on 19, 033 stations across 62 regions in nine European countries, the GSI explains 64% of the cross-regional variation in GDP per capita - a notable result for a single-variable indicator. Beyond its statistical fit, the GSI uncovers meaningful economic patterns. It reflects diminishing returns to infrastructure, consistent with core economic theory; it maps spatial inequality both visually and statistically, highlighting clusters of prosperity in capitals, port cities, transit corridors, and tourist destinations; and it classifies regional development typologies through bivariate LISA analysis. The unexplained variation underscores the structural differences between infrastructure-based indicator and GDP per capita, driven by sectoral specialization, mobility patterns, and informal economic activity. The GSI should therefore be viewed not as a substitute for national accounts, but as a complementary indicator particularly relevant at the subnational level. Compared to existing indicators, it offers distinct advantages: GDP per capita is delayed and masks heterogeneity, while night-time lights suffer from saturation and rural undercoverage. By contrast, the GSI provides a ground-level, behaviorally grounded, and real-time measure of economic development. By capturing both infrastructure and consumption dynamics, it complements—and in certain respects surpasses—conventional indicators in tracing regional growth trajectories and spatial inequality. |
| Keywords: | regional income, regional inequality, economic development measurement, infrastructure, geospatial data, nowcasting. |
| JEL: | C43 C55 E01 O18 O47 R12 |
| Date: | 2025–09–09 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:126108 |
| By: | Johanna Arlinghaus; Théo Konc; Linus Mattauch; Stephan Sommer |
| Abstract: | Do citizens support policy instruments because they appreciate their effects or because they are convinced by their objectives? We administered a large-scale representative survey with randomised video treatments to test how different policy frames - time savings, health and environment - affect citizens' attitudes towards urban tolls in two large European metropolitan areas, Berlin-Brandenburg and Paris-Ile de France. Presenting urban tolls as a solution to air pollution increases support by up to 11.4 percentage points, presenting them as a climate change or congestion relief measure increases support by 7.1 and 6.5 percentage points, respectively. We demonstrate via a causal mediation analysis that the observed changes in policy support are mainly framing effects; changes in beliefs about policy effects play a secondary role. Thus, we uncover a new mechanism shaping public opinion on economic policies: the stated objectives of an identical policy design can shape citizens' views in distinct ways. |
| Keywords: | political |
| Date: | 2025–10–20 |
| URL: | https://d.repec.org/n?u=RePEc:bdp:dpaper:0077 |
| By: | Verdugo, Gregory (University of Cergy-Pontoise); Kandoussi, Malak (University of Evry) |
| Abstract: | We examine how relocations from the center to the suburbs of establishments employing mainly skilled workers affect the composition and wages of their employees. Using data from the Paris metro area, we find that these relocations increase average commuting time by 19%. In response, firms compensate highly paid workers with 10 to 20% of their hourly wage per additional hour of commuting. Lower-paid workers receive no compensation and are more likely to leave. Consistent with workers valuing locational amenities, we find little increase in separation and no wage adjustment for increased commuting time when establishments relocate to more attractive neighborhoods. |
| Keywords: | firm’s location, commuting time, labor supply |
| JEL: | J16 D13 J18 |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18232 |
| By: | Adam Wiechman; John M. Anderies; Margaret Garcia |
| Abstract: | Our infrastructure systems enable our well-being by allowing us to move, store, and transform materials and information given considerable social and environmental variation. Critically, this ability is shaped by the degree to which society invests in infrastructure, a fundamentally political question in large public systems. There, infrastructure providers are distinguished from users through political processes, such as elections, and there is considerable heterogeneity among users. Previous political economic models have not taken into account (i) dynamic infrastructures, (ii) dynamic user preferences, and (iii) alternatives to rational actor theory. Meanwhile, engineering often neglects politics. We address these gaps with a general dynamic model of shared infrastructure systems that incorporates theories from political economy, social-ecological systems, and political psychology. We use the model to develop propositions on how multiple characteristics of the political process impact the robustness of shared infrastructure systems to capacity shocks and unequal opportunity for private infrastructure investment. Under user fees, inequality decreases robustness, but taxing private infrastructure use can increase robustness if non-elites have equal political influence. Election cycle periods have a nonlinear effect where increasing them increases robustness up to a point but decreases robustness beyond that point. Further, there is a negative relationship between the ideological sensitivity of candidates and robustness. Overall, the biases of voters and candidates (whether they favor tax increases or decreases) mediate these political-economic effects on robustness because biases may or may not match the reality of system needs (whether system recovery requires tax increases). |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2510.22411 |