The rebound effect in the aviation sector

TLDR: In this paper, the authors present a quantitative estimate of the rebound effect for an air traffic network including the 22 busiest airports, which serve 14 of the highest O-D cities within the domestic U.S. aviation sector.

About: This article is published in Energy Economics.The article was published on 2013-03-01 and is currently open access. It has received 34 citations till now. The article focuses on the topics: Rebound effect (conservation).

Figures

Table 3. Average change per percent reduction in aircraft fleet energy use per seat-km and associated R-squared of the reduced form least-squared fits.

Figure 1. Modeling framework for simulating airline and passenger responses to lower fuel burn technology.

Table 1. Observed Indicators of Fare Competition within the Studied Flight Network

Figure 2. Comparison of modeled results and observed data: (a) O-D demand, (b) segment flight frequency.

Table 2. Parameter estimates and t-statistics (in parenthesis) for the demand equation (N = 182 observations)

Figure 3. Simulated changes in average system-wide flight arrival delay, aircraft operations, passenger demand, airfare, and system energy use with reductions in aircraft fleet energy use per seat-km, relative to a 2005 baseline.

Frequently asked questions

Q1. What are the contributions in "The rebound effect in the aviation sector" ?

In this paper, the authors studied the effect of fuel-efficient aircraft on the U.S. domestic aviation sector and found that the average rebound effect in the studied network ranges from 10 to 30 %. 

Q2. What is the effect of the curved shape of the system energy use?

The slightly convex curved shape of the system energy use (curve 5) translates into a rebound effect that gradually decreases from 21% (for a 5% decline in aircraft energy use) to 16% (for a 30% decline in aircraft energy use). 

Q3. Why does the rebound effect decrease faster than in the case of airport capacity constraints?

Because there are no flight delays, operating costs decrease faster than in the case with airport capacity constraints, resulting in simulated fares decreasing, on average, by 0.24% for every percent reduction in aircraft energy use – slightly faster than in the case with airport capacity constraints. 

Q4. Why do the simulation results not form a smooth curve?

Because of the integer nature of the problem being solved at different percentage changes in aircraft fleet energy use per seat-km, the plotted simulation results do not form a smooth curve. 

Q5. How much does the rebound effect mean?

In this case, system energy use only declines at an average rate of 0.78% per percentage decrease in fuel burn, corresponding to an average rebound effect of 22%. 

Q6. How much does the increase in passenger demand affect the aircraft operations?

As passenger demand increases, aircraft operations also increase, on average, by 0.12% for every percentreduction in aircraft energy use. 

Q7. Why do the authors study the rebound effect?

Because of the competitive nature of the airline industry within the network the authors study, any decline in operating costs would lead to reduced fares. 

Q8. What is the effect of a drastic increase in capital costs on the rebound effect?

annualized capital costs are only a small percent of total operating expenses (4%, on average, across U.S. major carriers in 2005) and thus even a drastic increase in capital cost would only have a very small effect on the rebound effect. 

Q9. What is the effect of declining air fares on the economy?

An increase in passenger demand as a result of declining air fares will induce airlines to increase the supply of air transportation services. 

Q10. How much of the rebound effect is expected to increase in the U.S.?

The analysis presented in this paper suggests that the average rebound effect in the studied network within the domestic U.S. aviation sector is about 19%, for the range of aircraft fuel burn reductions considered. 

Q11. What is the relative change in aircraft fleet energy use per seat-km?

For reference, the relative change in aircraft fleet energy use per seat-km is also plotted—a straight line with a gradient of -1.10 Although reductions in fleet fuel burn would materialize gradually, the rate of fleet turnover would not affect the magnitude of the rebound effect. 

Q12. Why was the equation estimated using OLS and 2SLS?

Because of possible endogeneity with flight frequency, equation 1 was estimated using both ordinary least squares (OLS) and two-stage least squares (2SLS) regression.