A Study to Evaluate The Effect of Improved Fuel Economy on Vehicle Miles Traveled and Resulting Economic Impacts
Support: State of
This proposal will aim to understand the nature and strength of various mechanisms by which changes in fuel economy of motor vehicles influence the amount of motor vehicle travel. The guiding purpose is to answer questions relevant to regulation of greenhouse gas emissions.
We will first establish a theoretical framework to understand the rebound effect. This will establish the relationships among the rebound effect and other measurable aspects of demand for travel, such as the elasticities of fuel consumption and vehicle-miles traveled with respect to fuel prices. It will also show how the rebound effect is related to decisions on purchase and use of various vehicle types.
We will then
undertake a detailed review of past and ongoing studies of the rebound effect
and, more generally, of the responses of vehicle and travel decisions to fuel
and other operating costs. We will examine both the methodology and results of
these studies and assess their applicability to
Next, we will
review data sets in terms of their suitability for an econometric study of the
interaction between fuel economy and motor vehicle travel in
Based on the
review of data sets, we will design and undertake an econometric estimation of
the rebound effect for
The results should provide ARB and CEC with a more reliable basis for analyzing the possible effects of various regulations to control carbon dioxide emissions. In particular, they should enable ARB and CEC to understand the extent to which the rebound effect might tend to offset the emissions reductions that would otherwise result from a particular policy. The results will serve as guidance for interpreting more detailed micro-simulation results being obtained from research projects being performed under ARB and CEC sponsorship, and will serve as benchmarks for comparison with those results.
Capacity provision and pricing in road transport networks in an imperfectly competitive economy
The standard economic prescription for managing network congestion relies heavily on the internalization, through tolls, of the congestion externality. Two basic insights are that (a) charging appropriate tolls reduces congestion to -in principle- optimal levels, and (b) decisions on infrastructure expansion or contraction are less likely to be misguided when tolls are present.
These basic principles rely on the assumption that markets are perfectly competitive. More precisely, a trip is undertaken for one or more purposes, and the prices related to these purposes are competitive. That is, a commuting trip is undertaken to earn a competitive wage, and a shopping trip involves paying the competitive price for purchased goods.
This project will assess the impact of accounting for imperfect competition on the economic prescriptions for road infrastructure pricing and its provision.
The motivation is that the assumption of perfect competition is not realistic. It also is at odds with developments in mainstream economics, where imperfect competition models become the rule rather than the exception, precisely because of their higher degree of realism.
First, a model of the interactions between transport network management and competitive conditions in the economy is required. Preliminary work indicates that even small departures from the perfect competition assumption have major effects on p prescriptions. In fact, it shows that congestion itself generates non-competitive market results. Second, empirical evidence is sought in order to determine which of the available models best approximates real conditions. The data will be used to construct numerical models for policy analysis.
Congestion Pricing and Diversity in the Valuation of Travel Time and Reliability
Investigator: Jia Yan
Recent work has shown that the diversity in the valuation of travel time (VoT) and reliability (VoR) plays important role in understanding real transportation policies. Although past literature in measuring VoT empirically have addressed the heterogeneity among people to some extent, most of them focused on how VoT varies with observed characteristics, such as income and trip purpose. Studies in measuring VoR is still quite new and almost all existing studies in this topic are based on stated preference (SF) data. The purpose of this dissertation proposal is to finish the following two tasks: 1. Combining different data, including both revealed preference (RP) and stated preference (SF) data, to measure both observed and unobserved diversity in VoT and VoR; 2. Using an equilibrium simulation model based on the estimation results from the first part to investigate systematically the implications of diversity in VoT and VoR to various congestion pricing policies. The results from this dissertation will be useful. First, they would improve the ability of travel demand forecast. Second, they would enable one to evaluate existing transportation policies and design new policies.
Sectional and Panel Analysis of Mode Choice Under
Congestion Pricing: Application to the
Investigator: Arindam Ghosh
mode choice decision is a key component in formulating congestion policies
Carpool or HOV lanes were introduced to encourage car12ooling behavior and
reduce congestion. Due to the under-utilization of these carpool lanes, their
effectiveness has come under scrutiny. One suggested solution is to sell off
this excess capacity to solo drivers at a price. The
Defensive Driving and the External Costs of Accidents and Travel Delays
As the number of vehicles on the road increases, so does the risk of an accident. This gives rise to what economists refer to as "accident externalities" - the risk-related costs that motorists impose on one another. While some consider these costs to be paramount, an accepted convention is that no such costs exist. This convention is based on a modeling approach that reaches such a conclusion if observed accident rates do not vary with traffic volumes. However, when driving conditions become more hazardous, motorists naturally offset this risk to some extent by driving more carefully. Since this defensive effort is costly, positive accident externalities can exist even when observed accident rates are stable. This illustrates how the standard approach to modeling accident externalities can significantly understate these costs. Moreover, cautious driving often entails slower driving, warranting a joint model of accident and travel-delay costs. My research proposes such a model, from which an empirical framework can be developed to estimate these costs in a manner that jointly considers accident risk, efforts to offset this risk, and their impact on travel times. Estimates from this framework would generate direct implications for congestion pricing, highway expansion, and related transportation policies.
Viability of Public Transit with Road Pricing Measures
Investigator: Kenneth Small
Support: University of California Energy Institute
public transit service has long been viewed as a potential policy to reduce
energy consumption and other adverse effects of private motor vehicles.
However, experience in the
One little-noted effect of such pricing measures would be to improve the competitive edge for public transit. Of course there is the direct effect of encouraging modal shift from private vehicles to transit; but this effect would be magnified by the scale economies to which public transit has been shown to be subject when the access costs of users are taken into account. Specifically, when transit ridership density in a given corridor increases, it become economical to improve service frequency or route density or both, and thereby to improve transit service quality as viewed by the user. Furthermore, in the case of bus transit, reduced street congestion due to the pricing policies would reduce driver and equipment costs as well as further improve service quality to the user.
The proposed research will construct integrated models of travel demand, congestion formation, and transit supply in order to estimate the possible size of such effects. Outputs of the models include effects on transit patronage, transit agency finance, and energy consumption per passenger. This research is part of a broader effort, for which other funding will be sought, that will include consideration of shared-ride taxi service, shuttle service, and land-use implications.