Abstract

Using annual data on individual US airlines over the 1995-2015 period, this paper presents regression results relating an airline’s total fuel usage to seven variables: the available ton miles of capacity (passengers plus freight and mail) provided by the airline; the average seat capacity of its aircraft, average stage length (flight distance); average load factor (measured by weight); the average vintage (construction year) of its aircraft; the percentage of the airline’s flights that are delayed; and the average annual fuel price. The results show how fuel usage and carbon emissions depend on a small set of crucial variables. The estimated fuel-price effect allows the emissions impact of an optimal emissions charge to be computed, and the estimated delay effect shows the emissions impact of an industry-wide reduction in flight delays. The regression model is generated from a theoretical framework.

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