Abstract:We estimate the rebound effect for motor vehicles, by which improved fuel efficiency causes additional travel, using a pooled cross section of US states for 1966-2001. Our model accounts for endogenous changes in fuel efficiency, distinguishes between autocorrelation and lagged effects, includes a measure of the stringency of fuel-economy standards, and allows the rebound effect to vary with income, urbanization, and the fuel cost of driving. At sample averages of variables, our simultaneous-equations estimates of the short-and long-run rebound effect are 4.5% and 22.2%. But rising real income caused it to diminish substantially over the period, perhaps aided by falling fuel prices. With variables at 1997-2001 levels, our estimates are only 2.2% and 10.7%, considerably smaller than values typically assumed for policy analysis. The point estimates suggest that the rebound effect would remain constant if real incomes continue to grow and fuel prices were to grow about 3.5 times as fast. JEL-codes: Q0, D5, R4, C2 Keywords:carbon dioxide, fuel economy, travel demand, motor vehicle use, rebound effect Acknowledgment:

This paper analyzes aggregate personal motor-vehicle travel within a simultaneous model of aggregate vehicle travel, fleet size, fuel efficiency, and congestion formation. We measure the impacts of driving costs on congestion, and two other well-known feedback effects affecting motor-vehicle travel: its responses to aggregate road capacity ("induced demand") and to driving costs including those caused by fuel-economy improvements ("rebound effect"). We measure these effects using cross-sectional time series data at the level of US states for 1966 through 2004. Results show that congestion affects the demand for driving negatively, as expected, and more strongly when incomes are higher. We decompose induced demand into effects from increasing overall accessibility of destinations and those from increasing urban capacity, finding the two elasticities close in magnitude and totaling about 0.16, somewhat smaller than most previous estimates. We confirm previous findings that the magnitude of the rebound effect decreases with income and increases with fuel cost, and find also that it increases with the level of congestion.

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We estimate the rebound effect for motor vehicles, by which improved fuel efficiency causes additional travel, using a pooled cross section of US states for 1966-2001. Our model accounts for endogenous changes in fuel efficiency, distinguishes between autocorrelation and lagged effects, includes a measure of the stringency of fuel-economy standards, and allows the rebound effect to vary with income, urbanization, and the fuel cost of driving. At sample averages of variables, our simultaneous-equations estimates of the short-and long-run rebound effect are 4.5% and 22.2%. But rising real income caused it to diminish substantially over the period, aided by falling fuel prices. With variables at 1997-2001 levels, our estimates are only 2.2% and 10.7%, considerably smaller than values typically assumed for policy analysis. With income at the 1997-2001 level and fuel prices at the sample average, the estimates are 3.1% and 15.3%, respectively.

We study how air travel consumers departing from a multi-airport region trade-off across airport and airline supply characteristics. We empirically investigate this trade-off by estimating a weighted conditional logit model of airport-airline choice, using survey data on travels departing from one of three San Francisco Bay Area airports and arriving at one of four airports in greater Los Angeles in October 1995. Non-price characteristics like airport access time, airport delay, flight frequency, the availability of particular airport-airline combinations, and early arrival times are found to strongly affect choice probabilities. We calculate marginal effects and counterfactual scenarios to compare the values of these characteristics among each other and across traveler type. In order to examine the robustness of the conditional logit model, we estimate a mixed logit model, and find that the results are similar. We attribute the similarity to our strictly defined travel market and to our distinction between leisure and business travelers, thus controlling for two important sources of consumer heterogeneity. We consider the implications of our empirical findings on vertical integration between airlines and airports, on the effectiveness of "airport dominance," and on the competitive effect of entry by low cost carriers.