Transportation Economics, Pricing and Finance

A Study to Evaluate The Effect of Improved Fuel Economy on Vehicle Miles Traveled and Resulting Economic Impacts

Investigators: Kenneth Small, Kurt Van Dender, David Brownstone

Support: State of California − EPA Air Resources Board

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 California.  This assessment will include the variations of measurable demand parameters with region, socioeconomic characteristics, fuel prices, or other factors that might be different in California than in other locations.

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 California. We will describe the strengths and weaknesses of these data sets and their advantages and limitations for the empirical study.

Based on the review of data sets, we will design and undertake an econometric estimation of the rebound effect for California. Where possible, we will adapt methodologies from earlier studies to be specific to California. This may include limiting the estimates to California data and/or adjusting more broadly-based estimates to their values using California demographic and economic descriptors.

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

Kurt Van Dender

Support: U.S. Department of Transportation and California Department of Transportation/University of California Transportation Center

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

Support: U.S. Department of Transportation and California Department of Transportation/University of California Transportation Center

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.

Cross Sectional and Panel Analysis of Mode Choice Under Congestion Pricing:  Application to the San DiegoI-15 Congestion Pricing Project

Investigator: Arindam Ghosh

Support: U.S. Department of Transportation and California Department of Transportation/University of California Transportation Center

Understanding commuters' 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 San Diego 1-15 Congestion Pricing Project is an application of this proposal. Though mode choice decisions have been studied extensively for morning and afternoon commute rarely have they been studied together. Using survey data from 1-15 Congestion Pricing Project and linking that with network data, this project proposes a cross sectional and panel analysis of mode choice models for morning and afternoon commute. Preliminary results indicate that, while sharing some common features, the morning and afternoon commute are very different. The results also indicate that travel characteristics interact to affect mode choice, and the toll is used as a signal for congestion. The value-of-time calculations show a lot of heterogeneity depending on scheduling constraints, time of travel and income. It ranges from a low of $5 and goes up to a high of $30 for people traveling in the morning peak with arrival time constraints.


Defensive Driving and the External Costs of Accidents and Travel Delays

Investigator: Seiji S.C. Steimetz

Support: U.S. Department of Transportation and California Department of Transportation/University of California Transportation Center

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

Improved 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 U.S. has been discouraging due to the inability of public transit to compete effectively for market share in most urban settings. Many researchers have found that policies aimed directly at discouraging private vehicle use, especially pricing measures, are more promising.

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.