The Determinants of Fuel Use in the Trucking Industry – Volume, Size and the Rebound Effect

We analyse the determinants of trucking firm fuel use. We develop a simple model to show that trucking firm fuel use depends, in addition to the fuel price and the traffic volume, also on the output of the trucking firm’s production process (the movement of cargo) measured in ton- kilometres, characteristics of the truck stock, and congestion. We also analyse the rebound effect for road freight transportation, i.e. the percentage of increased energy efficiency that does not result in the reduction of fuel used. For the purpose of analysing the rebound effect for road freight transportation, we decompose the standard definition of the rebound effect for motor vehicles, i.e. the elasticity of traffic volume with respect to fuel cost, into the elasticity by which changes in fuel costs affects freight activity and the elasticity by which changes in freight activity affect traffic volume. We estimate these elasticities using a simultaneous-equation model based on aggregate time-series data for Denmark for 1980-2007. Our best estimates of the short run and the long run rebound effects for road freight transportation are 19% and 28%, respectively. We also find that an increase in the fuel price surprisingly has a small but significant negative effect on the fuel efficiency (measured here as vehicle kilometres travelled (VKT) per litre of consumed fuel), i.e. a 1% increase in the fuel price decreases the fuel efficiency by 0.13% in the long run. However, less distance has to be driven for the same payload. An 1% increase in the fuel price decreases the VKT by 0.19% in the short run and 0.28% in the long run. Finally, a 1% increase in the fuel price results in a 0.19% reduction in the trucking firms’ overall fuel use

Modeling the relation between income and commuting distance

We discuss the distribution of commuting distances and its relation to income. Using data from Denmark, the UK, and the US, we show that the commuting distance is (i) broadly distributed with a slow decaying tail that can be fitted by a power law with exponent $\gamma \approx 3$ and (ii) an average growing slowly as a power law with an exponent less than one that depends on the country considered. The classical theory for job search is based on the idea that workers evaluate the wage of potential jobs as they arrive sequentially through time, and extending this model with space, we obtain predictions that are strongly contradicted by our empirical findings. We propose an alternative model that is based on the idea that workers evaluate potential jobs based on a quality aspect and that workers search for jobs sequentially across space. We also assume that the density of potential jobs depends on the skills of the worker and decreases with the wage. The predicted distribution of commuting distances decays as $1/r^{3}$ and is independent of the distribution of the quality of jobs. We find our alternative model to be in agreement with our data. This type of approach opens new perspectives for the modeling of mobility.Comment: 9 pages, 3 figure

Does improving public transport decrease car ownership? Evidence from a residential sorting model for the Copenhagen metropolitan area

Car ownership is lower in urban areas, where public transport is of high quality. This suggests that better public transport offers the possibility to relieve the many problems (congestion, pollution, and parking) associated with the presence of cars in urban areas. To investigate this issue, we develop a model for the simultaneous choice of residential location and car ownership by households, and estimate it on Danish data, paying special attention to accessibility of the metro network. We use the estimated model to simulate the impact of an extension of the metro network. We show that for the Greater Copenhagen Area an extension of the metro network decreases car ownership by 2–3%, while the average compensating variation is approximately 3% of household income

Transportation and Quality of Life

This paper studies the importance of transportation for the quality of life in Denmark. The average Dane spends about 55 minutes on transport per day (DTU [2013]) and the average household's expenditure devoted to transport is about 20 % of the total household budget (Berri et al. [2014]).1 It is therefore important to recognize the importance of transportation for the quality of life. Transportation is derived demand as individuals often consume the service not because they benet from consumption directly, but because they partake in other consumption or activities elsewhere (see e.g. Small and Verhoef [2007]). Transportation allows households to buy consumption goods and activities, get to work and enjoy leisure. Households therefore face in general trade-o between, on one hand productivity and consumption advantages (high-paying jobs and high quality local urban amenities), and on the other hand higher costs of living and dis-amenities (high housing costs, congestions and pollution), when they decide where to live. Transportation infrastructure facilitates interaction within cities. It relieves pressure on urban land by enabling workers to live at some distance from their jobs at reasonable commutes. Transport infrastructure thus aect the attractiveness of urban areas. We construct a transport adjusted Quality of Life Index (QLI) for the 98 urban areas - municipalities - covering Denmark. Using this index we investigate the importance of adjusting for the inter area commute patterns in terms of the quality of life of a typical household. We also investigate the relationship between transport infrastructure investments and the QLI