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on Transport Economics |
| By: | Alix Le Goff (LAET - Laboratoire Aménagement Économie Transports - UL2 - Université Lumière - Lyon 2 - ENTPE - École Nationale des Travaux Publics de l'État - CNRS - Centre National de la Recherche Scientifique); Guillaume Monchambert (LAET - Laboratoire Aménagement Économie Transports - UL2 - Université Lumière - Lyon 2 - ENTPE - École Nationale des Travaux Publics de l'État - CNRS - Centre National de la Recherche Scientifique); Charles Raux (LAET - Laboratoire Aménagement Économie Transports - UL2 - Université Lumière - Lyon 2 - ENTPE - École Nationale des Travaux Publics de l'État - CNRS - Centre National de la Recherche Scientifique) |
| Abstract: | We conduct a discrete choice experiment on 931 solo-driving commuters in Lyon, France to estimate the values of end-to-end travel time (VoTT) in the presence of an HOV lane for four modes: Solo Driver, Carpool Driver, Carpool Passenger and Public Transport. Mixed and latent class logit models are estimated. We find that Carpool Passenger, Carpool Driver and Public Transport median VoTTs are respectively around 20%, 40% and 60% higher than Solo Driver VoTT. The analysis of individual heterogeneity distinguishes three classes of behavior in our sample: open to carpool as a driver (41%), open to passenger modes (32%) and resistant to all alternatives to solo driving (28%). These three categories allow to identify solo drivers who could switch to carpool as drivers. We show that encouraging current solo drivers to switch to carpool as passengers will be more sensitive if public transport services are also improved. |
| Keywords: | HOV-lane,Commuting Trips,Carpool,Values of Time,Discrete Choice Experiment,Working Papers du LAET |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:halshs-02988756&r=all |
| By: | Elisa Borowski; Jason Soria; Joseph Schofer; Amanda Stathopoulos |
| Abstract: | Mobility resilience refers to the ability of individuals to complete their desired travel despite unplanned disruptions to the transportation system. The potential of new on-demand mobility options, such as ridesourcing services, to fill unpredicted gaps in mobility is an underexplored source of adaptive capacity. Applying a natural experiment approach to newly released ridesourcing data, we examine variation in the gap-filling role of on-demand mobility during sudden shocks to a transportation system by analyzing the change in use of ridesourcing during unexpected rail transit service disruptions across the racially and economically diverse city of Chicago. Using a multilevel mixed model, we control not only for the immediate station attributes where the disruption occurs, but also for the broader context of the community area and city quadrant in a three-level structure. Thereby the unobserved variability across neighborhoods can be associated with differences in factors such as transit ridership, or socio-economic status of residents, in addition to controlling for station level effects. Our findings reveal that individuals use ridesourcing as a gap-filling mechanism during rail transit disruptions, but there is strong variation across situational and locational contexts. Specifically, our results show larger increases in transit disruption responsive ridesourcing during weekdays, nonholidays, and more severe disruptions, as well as in community areas that have higher percentages of White residents and transit commuters, and on the more affluent northside of the city. These findings point to new insights with far-reaching implications on how ridesourcing complements existing transport networks by providing added capacity during disruptions but does not appear to bring equitable gap-filling benefits to low-income communities of color that typically have more limited mobility options. |
| Date: | 2020–10 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2010.15889&r=all |
| By: | Pihnastyi, Oleh; Khodusov, Valery; Subbotin, Sergey |
| Abstract: | This article discusses the prospects of using linear regression models to describe multi-section branched transport systems of conveyor type. A characteristic feature of the functioning of a multi-section transport system is the presence of resonant peak values for the flow parameters of the transport system and transport delay. Various variants of the linear regression model are investigated. It is shown that for multisection transport systems with a periodic nature of the magnitude of the incoming material flow into the transport system and periodic nature of the regulation of the belt speed the value of the transport delay is a quasi-stationary value. The transport delay can be excluded from model variables. Analysis of the various variants of linear regression models considered in the article shows that using them to describe branched transport systems is ineffective. The considered models can only be used for a qualitative analysis of the output stream from the transport system. The absence of a linear relationship between the input and output flow parameters of the transport system is shown. |
| Keywords: | conveyor PDE-model; distributed system; linear regression model |
| JEL: | C02 C15 C25 C44 D24 |
| Date: | 2020–09–26 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:103881&r=all |
| By: | Michael Pollmann |
| Abstract: | I propose a framework, estimators, and inference procedures for the analysis of causal effects in a setting with spatial treatments. Many events and policies (treatments), such as opening of businesses, building of hospitals, and sources of pollution, occur at specific spatial locations, with researchers interested in their effects on nearby individuals or businesses (outcome units). However, the existing treatment effects literature primarily considers treatments that could be assigned directly at the level of the outcome units, potentially with spillover effects. I approach the spatial treatment setting from a similar experimental perspective: What ideal experiment would we design to estimate the causal effects of spatial treatments? This perspective motivates a comparison between individuals near realized treatment locations and individuals near unrealized candidate locations, which is distinct from current empirical practice. Furthermore, I show how to find such candidate locations and apply the proposed methods with observational data. I apply the proposed methods to study the causal effects of grocery stores on foot traffic to nearby businesses during COVID-19 lockdowns. |
| Date: | 2020–10 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2011.00373&r=all |
| By: | Jasper Verschuur; Elco Koks; Jim Hall |
| Abstract: | The implementation of large-scale containment measures by governments to contain the spread of the COVID-19 virus has resulted in a large supply and demand shock throughout the global economy. Here, we use empirical vessel tracking data and a newly developed algorithm to estimate the global maritime trade losses during the first eight months of the pandemic. Our results show widespread trade losses on a port level with the largest absolute losses found for ports in China, the Middle-East and Western Europe, associated with the collapse of specific supply-chains (e.g. oil, vehicle manufacturing). In total, we estimate that global maritime trade reduced by -7.0% to -9.6% during the first eight months of 2020, which is equal to around 206-286 million tonnes in volume losses and up to 225-412 billion USD in value losses. The fishery, mining and quarrying, electrical equipment and machinery manufacturing, and transport equipment manufacturing sectors are hit hardest, with losses up to 11.8%. Moreover, we find a large geographical disparity in losses, with some small islands developing states and low-income economies suffering the largest relative trade losses. We find a clear negative impact of COVID-19 related business and public transport closures on country-wide exports. Overall, we show how real-time indicators of economic activity can support governments and international organisations in economic recovery efforts and allocate funds to the hardest hit economies and sectors. |
| Date: | 2020–10 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2010.15907&r=all |