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on Transport Economics |
| By: | Balia, S.; Brau, R.; Nieddu, M.G. |
| Abstract: | This paper investigates how a vehicle power limit on young novice drivers impacts teen traffic accidents in Italy. First introduced in 2011, the reform prevents drivers from using high performance vehicles during their first license year. We combine rich administrative data on severe accidents over the period 2006-2016 with the driving license census to assess whether undergoing the power limit lowers the likelihood of causing a traffic accident. Our difference-in-difference estimates – we leverage on the between-cohort differences in the exposure to the reform – reveal that the power limit reduces road accidents per capita by about 18%, and accidents per licensee by 13%. The effect is entirely determined by a drop in accidents caused by above-limit vehicles and is primarily driven by fewer speed violations. Moreover, the beneficial impact of the one-year restriction period persists even after its expiration. Our findings highlight the importance of policies that, instead of directly targeting risky behaviours, are aimed at reducing exposure to high-risk settings. In frameworks where deterrence policies and screening mechanisms are hard to implement and maintain, these policies stand out as an effective, yet feasible strategy to increase teen road safety. |
| Keywords: | youth road accidents; driving restriction; graduated licensing; risky behaviours; risk exposure; |
| JEL: | D04 I12 I18 K32 |
| Date: | 2021–03 |
| URL: | http://d.repec.org/n?u=RePEc:yor:hectdg:21/06&r=all |
| By: | Anne de Bortoli; Zoi Christoforou |
| Abstract: | The indirect environmental impacts of transport disruptions in urban mobility are frequently overlooked due to a lack of appropriate assessment methods. Consequential Life Cycle Assessment (CLCA) is a method to capture the environmental consequences of the entire cause and effect chain of these disruptions but has never been adapted to transportat disruption at the city scale. This paper proposes a mathematical formalization of CLCA applied to a territorial mobility change. The method is applied to quantify the impact on climate change of the breakthrough of free-floating e-scooters (FFES) in Paris. A FFES user survey is conducted to estimate the modal shifts due to FFES. Trip substitutions from all the Parisian modes concerned are considered - personal or shared bicycles and motor scooters, private car, taxi and ride-hailing, bus, streetcar, metro and RER (the Paris metropolitan area mass rapid transit system). All these Parisian modes are assessed for the first time using LCA. Final results estimate that over one year, the FFES generated an extra thirteen thousand tons of CO2eq under an assumption of one million users, mainly due to major shifts coming from lower-emitting modes (60% from the metro and the RER, 22% from active modes). Recommendations are given to enhance their carbon footprint. A scenario analysis shows that increasing the lifetime mileage is insufficient to get a positive balance: reducing drastically servicing emissions is also required. A sensitivity analysis switching the French electricity mix for eleven other country mixes suggests a better climate change effect of the FFES in similar metropolitan areas with higher electricity carbon intensity, such as in Germany and China. Finally, the novelty and the limits of the method are discussed, as well as the results and the role of e-scooters, micromobility, and shared vehicles towards a sustainable mobility. |
| Date: | 2021–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2103.00680&r=all |
| By: | Grover, Charu (Shaheed Bhagat Singh College, University of Delhi, India); Bansal, Sangeeta (Centre for International Trade and Development, Jawaharlal Nehru University, India); Martinez-Cruz, Adan L. (CERE - the Center for Environmental and Resource Economics) |
| Abstract: | India's contribution to global CO2 emissions makes it a priority case for policy makers worldwide. The Indian government is considering the adoption of energy labels for new passenger cars to tackle CO2 emissions. This paper's first aim is to asses New Delhi's car buyers' preferences for cars displaying energy labels. To do so, a discrete choice experiment (DCE) has been designed to document both WTP for energy efficiency (212 USD for one kilometer per liter) and WTP for the best efficiency label (4.93 thousand USD). The informational nudge embedded in a labeling system may not be enough to boost uptake of efficient cars. Thus this paper investigates the potential of combining a labeling system and car driving restrictions. Via a split-sample approach, this paper documents an increase of 2.55 thousand USD in stated WTP for the best efficiency label. This number can be interpreted as reflecting the costs imposed by the driving restrictions on car drivers. Under this interpretation, 2.55 thousand USD fall within the range of estimations reported in previous studies. The results in this paper suggest that a combination of driving restrictions and a labeling system may deliver an increase in energy efficient cars in New Delhi. |
| Keywords: | Energy labeling system; driving restrictions; willingness to pay; discrete choice experiment; split-sample approach; New Delhi. |
| JEL: | Q48 Q50 |
| Date: | 2021–03–01 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:slucer:2021_004&r=all |
| By: | Francis Ostermeijer (Vrije Universiteit Amsterdam); Hans RA Koster (Vrije Universiteit Amsterdam); Leonardo Nunes (Vrije Universiteit Amsterdam); Jos van Ommeren (Vrije Universiteit Amsterdam) |
| Abstract: | We examine the eff ect of citywide parking policy on parking and traffic demand. Using a large increase in on-street parking prices for the city of Amsterdam, we show that the policy caused a substantial drop in on-street parking demand, which is not off set by an increase in off -street demand. The overall reduction in parking demand implies a 2% - 3% reduction in traffic, which is con firmed with traffic flow data. The reductions in traffic are larger during the evening peak, which indicates that parking prices are effective at reducing congestion in the evening peak, but lesser in the morning peak. |
| Keywords: | Parking, prices, traffic flow, congestion |
| JEL: | R41 R48 R51 R52 |
| Date: | 2021–02–05 |
| URL: | http://d.repec.org/n?u=RePEc:tin:wpaper:20210015&r=all |
| By: | Novak, David C.; Sullivan, James L.; Niles, Meredith T. |
| Abstract: | A key purpose of the transportation system is to provide access to critical services such as grocery stores. Maintaining food access during an emergency or other disruption is all the more important, particularly for vulnerable households. Most people in the United States rely on the use of private automobiles for grocery shopping. Thus, disruptions to road networks due to heavy precipitation, flooding, or even major maintenance and repair projects present notable threats to accessibility. Regional planning models that address food accessibility issues (not all do) typically do not consider households’ familiarity with grocery locations. However, during a disruptive event, a household’s familiarity with at least one available route to a retail grocery location becomes paramount. Identifying the roadways that are most critical to food access can help decision makers devise strategies to mitigate the risks of food insecurity for vulnerable households and populations. Researchers at the University of Vermont developed a methodology that provides an ordinal measure of demand-side food access. It takes into account the spatial distribution of both the origin and destination, the topology of the road network, and the characteristics of the roadway network such as capacities, volumes, and travel speeds. The analysis considers household familiarity with retail grocery locations, destination weighting to account for retail grocery characteristics (square footage), and origin weighting to account for household vulnerability. The researchers demonstrated the methodology using the travel demand model for Chittenden County, Vermont. This policy brief summarizes the findings from that research and provide policy implications. View the NCST Project Webpage |
| Keywords: | Engineering, Access, Food, Investments, Origin and destination, Risk assessment, Travel demand |
| Date: | 2021–03–01 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:itsdav:qt47v4g0zn&r=all |
| By: | Runst, Petrik; Höhle, David |
| Abstract: | Many countries have only recently introduced carbon taxation to reduce emissions and the time series data for evaluating these policies is not available yet. Consequently, we use the imposition quasi-carbon-taxes in the German transportation sector, i.e. taxes on fuel that are not calculated based on actual CO2content but which raise the implicit price of carbon emissions, to evaluate the effectiveness of environmental taxation. Our results indicate that the carbon price increase by about 66 €/t CO2led toa considerable decline of transport emissions by 0.2 to 0.35 t per person and year. Our quantitative results as well as a detailed qualitative analysis of a German car manufacturer's business reports suggests that the tax triggered an improvement in engine technology as well as an increased share of diesel engines. |
| Keywords: | Carbon taxation,transport sector,carbon emissions |
| JEL: | H23 Q48 R48 |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:ifhwps:292021&r=all |
| By: | Ghafelebashi, Ali; Razaviyayn, Meisam; Dessouky, Maged |
| Abstract: | With rapid population growth and urban development, traffic congestion has become an inescapable issue, especially in large cities. Many congestion reduction strategies have been proposed in the past, ranging from roadway extension to transportation demand management programs. In particular, congestion pricing schemes have been used as negative reinforcements for traffic control. This project studies a different approach of offering positive incentives to drivers to take alternative routes. More specifically, an algorithm is proposed to reduce traffic congestion and improve routing efficiency by offering personalized incentives to drivers. The idea is to use the wide-accessibility of smart communication devices to communicate with drivers and develop a look-ahead incentive offering mechanism using individuals’ routing preferences and aggregate traffic information. The incentives are offered after solving large-scale optimization problems in order to minimize the expected congestion (or minimize the expected carbon emission). Since these massive size optimization problems need to be solved continually in the network, a distributed computational approach is developed where a major computational burden is carried out on the individual drivers' smartphones (and in parallel among drivers). The convergence of the proposed is an established distributed algorithm under a mild set of assumptions (that are verified using real data). View the NCST Project Webpage |
| Keywords: | Engineering, Social and Behavioral Sciences, Congestion reduction, personalized incentives, routing, emissions |
| Date: | 2021–03–01 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:itsdav:qt5b82168n&r=all |
| By: | Fiona Burlig (University of Chicago); James B. Bushnell; David Rapson (University of California, Davis); Catherine D. Wolfram (University of California, Berkeley - Economic Analysis & Policy Group; National Bureau of Economic Research (NBER)) |
| Abstract: | We provide the first at-scale estimate of electric vehicle (EV) home charging. Previous estimates are either based on surveys that reach conflicting conclusions, or are extrapolated from a small, unrepresentative sample of households with dedicated EV meters. We combine billions of hourly electricity meter measurements with address-level EV registration records from California households. The average EV increases overall household load by 2.9 kilowatt-hours per day, less than half the amount assumed by state regulators. Our results imply that EVs travel 5,300 miles per year, under half of the US fleet average. This raises questions about transportation electrification for climate policy. |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:bfi:wpaper:2021-17&r=all |
| By: | Yuhei Miyauchi; Kentaro Nakajima; Stephen J. Redding |
| Abstract: | We provide new theory and evidence on the role of consumption access in understanding the agglomeration of economic activity. We combine smartphone data that records user location every 5 minutes of the day with economic census data on the location of service-sector establishments to measure commuting and non-commuting trips within the Greater Tokyo metropolitan area. We show that non-commuting trips are frequent, more localized than commuting trips, strongly related to the availability of nontraded services, and occur along trip chains. Guided by these empirical findings, we develop a quantitative urban model that incorporates travel to work and travel to consume non-traded services. Using the structure of the model, we estimate theoretically-consistent measures of travel access, and show that consumption access makes a sizable contribution relative to workplace access in explaining the observed variation in residents and land prices across locations. Undertaking counterfactuals for changes in travel costs, we show that abstracting from consumption trips leads to a substantial underestimate of the welfare gains from a transport improvement (because of the undercounting of trips) and leads to a distorted picture of changes in travel patterns within the city (because of the different geography of commuting and non-commuting trips). |
| JEL: | R2 R3 R41 |
| Date: | 2021–02 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:28497&r=all |
| By: | Gabriel E. Kreindler; Yuhei Miyauchi |
| Abstract: | We show how to use commuting flows to infer the spatial distribution of income within a city. A simple workplace choice model predicts a gravity equation for commuting flows whose destination fixed effects correspond to wages. We implement this method with cell phone transaction data from Dhaka and Colombo. Model-predicted income predicts separate income data, at the workplace and residential level, and by skill group. Unlike machine learning approaches, our method does not require training data, yet achieves comparable predictive power. We show that hartals (transportation strikes) in Dhaka reduce commuting more for high model-predicted wage and high-skill commuters. |
| JEL: | C55 E24 R14 |
| Date: | 2021–02 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:28516&r=all |
| By: | HAYAKAWA Kazunobu; Hans R.A. KOSTER; TABUCHI Takatoshi; Jacques-François THISSE |
| Abstract: | We investigate the effects of high-speed rail (HSR) on the location of economic activity. We set up a spatial quantitative general equilibrium model that incorporates spatial linkages between firms (including manufacturing and services), agglomeration economies, as well as commuting and migration. The model is estimated for Japan in order to investigate the impacts of the Shinkansen, i.e., the first HSR ever built. We show that traveling by train strengthens firm linkages, but is less important for commuting interactions. The Shinkansen increases welfare by about 5%. We show that extensions of the Shinkansen network may have large effects (up to a 30% increase in employment) on connected municipalities, although the effects are smaller for places with higher fixed costs. Our counterfactuals show that, without the Shinkansen, Tokyo and Osaka would be 6.3% and 4.4% larger, respectively. |
| Date: | 2021–01 |
| URL: | http://d.repec.org/n?u=RePEc:eti:dpaper:21003&r=all |