|
on Transport Economics |
| By: | 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, UL2 - Université Lumière - Lyon 2, Université de Lyon) |
| Abstract: | Long-distance carpooling is an emerging mode in France and Europe, but little is known about monetary values of this mode attributes in transport economics. We conducted a discrete choice experiment to identify and measure the values of attributes of long-distance transport modes for a trip as a driver and as a passenger, with a special focus on carpooling. Around 1.700 French individuals have been surveyed. We use discrete mixed logit models to estimate the probability of mode choice. We find that the value of travel time for a driver who carpools is on average 13% higher than the value of travel time when driving alone in his/her car. The average value of travel time for a carpool trip as passenger is around 26 euros per hour, 60% higher than for a train trip and 20% higher than for a bus trip. Moreover, our study confirms a strong preference for driving solo over taking carpoolers in one's car. We also show that individuals traveling as carpool passenger incur a "discomfort" cost of on average 4.5 euros per extra passenger in the same vehicle. Finally, we identify robust socioeconomic effects affecting the probability of carpooling, especially gender effects. When they drive a car, females are less likely to carpool than male, but they prefer to carpool two passengers over only one passenger. JEL Codes: R41; C35 |
| Keywords: | Value of time,Long-distance,Carpooling,Discrete choice experiment |
| Date: | 2019–05–06 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:hal-02121589&r=all |
| By: | Mercedes Ayuso (Department of Econometrics, Riskcenter-IREA, University of Barcelona Av. Diagonal 690, 08034 Barcelona.); Rodrigo Sánchez-Reyes (Department of Econometrics, Riskcenter-IREA, University of Barcelona Av. Diagonal 690, 08034 Barcelona.); Miguel Santolino (Department of Econometrics, Riskcenter-IREA, University of Barcelona Av. Diagonal 690, 08034 Barcelona.) |
| Abstract: | This article seeks to demonstrate differences in the severity of traffic accidents among two subgroups of older drivers – young-older (65–75) and old-older (75+). Spain, in common with other countries, has recorded an increase in its number of older drivers due to an increase in this population cohort, an increase that is set to become significant over coming years. Moreover, older drivers are now living and driving for longer periods given increasing levels of life expectancy for the elderly. The greater frequency and longevity of older drivers suggests the need to introduce a possible segmentation within this group at risk, in line with practices for drivers below the age of 65 (thus eliminating the generic interval of 65 and over as applied today in road safety data and in the automobile insurance sector). Here, we draw on data for 2016 provided by the Dirección General de Tráfico de España (Spanish Traffic Authority) and apply generalized additive and generalized linear models to demonstrate that accident severity and the expected costs of accidents increase when the driver is over the age of 75. We identify the factors related to the accident, vehicle and driver that have a significant impact on the probability of the accident being slight, serious or fatal for different age groups. Our results have obvious implications for regulators responsible for road safety policies – most specifically as they consider the need to introduce an upper age limit for driving – and for the automobile insurance industry, which to date has not examined the impact that the longevity of drivers is likely to have on their balance sheets. |
| Keywords: | Older drivers, groups at risk, bodily injuries, accident costs. JEL classification:J11, J14, I10, C5. |
| Date: | 2019–05 |
| URL: | http://d.repec.org/n?u=RePEc:ira:wpaper:201908&r=all |
| By: | Doggett, Sarah; Ragland, David R.; Felschundneff, Grace |
| Abstract: | This study examines data from the California EMS Information System (CEMSIS) to identify factors that influence prehospital time for EMS events related to motor vehicle collisions (MVCs). While only 19 percent of the United States population resides in rural areas, over half of all traffic fatalities involve rural motor vehicle collisions. Rural and urban MVCs result in similar injury severities, however relative inaccessibility of trauma centers and prehospital EMS time (activation, response, and transport time) likely contribute to the generally higher mortality rate in rural areas. For the present study, 24 CEMSIS data variables were requested, many of which involved missing data, which severely restricted the potential analysis of the impact of EMS response times. However, the findings did show that average overall EMS time (including response, scene and transport time) were approximately twice as long for collisions in rural zip codes compared with urban zip codes. Several limitations influence the interpretation of these results. Data on prehospital EMS times is missing for much of the state—even for zip codes with records of EMS events, data is likely incomplete. In addition, zip code level location data is insufficient for adequate study of the effects of the built environment and road network on prehospital time. Furthermore, according to the National EMS Information System (NEMSIS) User Manual, the national dataset suffers from selection and information bias, which are likely also present in the CEMSIS data. Although the present study cannot analyze the effect of longer prehospital times on patient outcome, other research has found that longer prehospital times may negatively impact patient health. Recommendations for reducing time from injury to appropriate medical care in rural areas include improving cell phone coverage, compliance of rural 911 center with FCC wireless, use of GPS technology, and integration of automatic vehicle location and computer aided navigation technologies into all computer-aided dispatch systems. In addition, CEMSIS should improve the coverage of their dataset and ensure that all EMS activities are recorded. To expand the type of analyses that can be conducted using CEMSIS data, EMS records must include fields that allow them to be linked to hospital and police datasets. When such data becomes available, research must be conducted to determine whether prehospital time is significantly related to patient outcome following motor vehicle collisions. |
| Keywords: | Engineering, CEMSIS, EMS, data, response time, collisions |
| Date: | 2019–05–14 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:itsrrp:qt01j3411t&r=all |
| By: | Jenn, Alan; Lee, Jae Hyun; Hardman, Scott; Tal, Gil |
| Abstract: | We investigate the impacts of a combination of incentives on the purchase decisions of electric vehicle (EV) buyers in California from 2010 through 2017. We employ a comprehensive survey on over 14,000 purchasers of EVs in California. The survey covers a range of purchase intentions, general demographics, and the importance of various incentives. Our results indicate that the most important incentives for plug-in electric vehicle (PEV) owners are the federal tax credit, the state rebate, and HOV lane access. In addition, the importance of the incentives and their associated effect on purchase behaviour has been changing over time: respondents are more likely to change their decisions and to not buy a vehicle at all as time passes and the technology moves away from early adopters. |
| Keywords: | Engineering, Electric vehicles, incentives, high occupancy vehicle lanes, consumer behavior, automobile ownership |
| Date: | 2019–05–01 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:itsdav:qt0x28831g&r=all |
| By: | Braun, Sebastian Till; Franke, Richard |
| Abstract: | This paper provides a comprehensive assessment of the effect of railways on the spatial economic development of a German economy, the Kingdom of Württemberg, during the Industrial Revolution. Our identification strategy compares the economic development of `winning' municipalities that were connected to the railway in 1845-54 to the development of `losing' municipalities that were the runners-up choice for a given railway line between two major towns. Estimates from both differences-in-differences and inverse-probability-weighted models suggest that railway access increased annual population growth by 0.4 percentage points over more than half a century. Railways also increased wages, income and housing values, in line with predictions of economic geography models of transport infrastructure improvements, reduced the gender wage gap, and accelerated the transition away from agriculture. We find little evidence that these effects are driven by localised displacement effects. |
| Keywords: | Railway access, growth, sectoral employment, Industrial Revolution, Württemberg |
| JEL: | N73 N93 O14 R12 R40 |
| Date: | 2019–05–03 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:93644&r=all |
| By: | Laurent Franckx |
| Abstract: | The new Belgian CAr Stock MOdel, which is linked to the national transport demand model PLANET, is structured as follows: (a) The total desired car stock in each future year is a function of the country's population and GDP per capita. (b) The probability that a car is scrapped is modelled as a function of its age and accumulated mileage. The desired car stock is then confronted with the remaining car stock to determine total car purchases. (c) Total sales are allocated to individual emission classes, using the parameter values of a Stated Preference discrete choice model. The model is then calibrated in order to reflect the current market and policy context in Belgium (d) The results are mapped into an inventory that is aggregated according to the EURO emission class. (e) In order to represent that the non-price barriers to electrified cars will decrease over time, we have implemented an alternative approach where the perceived acquisition costs decrease over time. Alternatively, this approach can be used to explore what would be the required decrease in subjective costs to reach a given future market share. |
| JEL: | R00 R20 R40 C25 Q50 |
| Date: | 2019–01–31 |
| URL: | http://d.repec.org/n?u=RePEc:fpb:wpaper:1901&r=all |
| By: | Kong, Nathaniel; Hardman, Scott |
| Keywords: | Social and Behavioral Sciences, plug-in electric vehicle, electric vehicle, incentive |
| Date: | 2019–05–01 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:itsdav:qt0fm3x5bh&r=all |
| By: | Kimbrough, Gray |
| Abstract: | Research into the relationships between commuting and other activities has been hampered by the lack of suitably comprehensive datasets. This paper identifies a possible source of detailed information for such studies, the American Time Use Survey (ATUS). This paper surveys approaches used by researchers to analyze commuting in the ATUS and outlines a method of measuring commuting in a clear and consistent way. This analysis details the advantages of this method over other approaches. Commuting measured in the ATUS using this methodology is shown to be consistent with commuting measures in other large, nationally representative studies. The proposed methodology makes possible a range of analyses exploiting the unique information in the ATUS. |
| Keywords: | commuting, time use data, travel classification, American Time Use Survey |
| JEL: | J22 R41 |
| Date: | 2019–05–05 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:93239&r=all |