Decomposing the drivers of aviation fuel demand using simultaneous equation models

Decomposition analysis is a widely used technique in energy analysis, whereby the growth in energy demand is attributed to different components. In this paper the decomposition analysis is extended in a system econometric modelling framework in order to understand the drivers of each of the components in the decomposition analysis. The growth in aviation fuel demand is decomposed into five components: population, passenger per capita, distances per passenger, load factor and fuel efficiency, and then seemingly unrelated regression methods is applied in order to model each of these. Results show that the fuel demand in the US air transport sector most closely follows the trend of passenger per capita. The growth in fuel demand is slowed by improvements in fuel efficiency and usage efficiency (load factor). Increases in income affects both passengers per capita and distances per passenger. However, increases in travel costs have opposite effects on passenger per capita (decreases) and distance per passenger (increases). Increases in jet fuel prices improves both the load factor and fuel efficiency.