Airline Travel Demand, the Derived Demand for Aircraft Fuel, and Fuel Utilization Forecasts Using Structural and Atheoretical Approaches

In the first chapter, we develop a dynamic model of collusion in city-pair routes for selected US airlines and specify the first order conditions using a state-space representation that is estimated by Kalman-filtering techniques using the Databank 1A (DB1A) Department of Transportation (DOT) data during the period 1979I-1988IV. We consider two airlines, American (AA) and United (UA) and four city pairs. Our measure of market power is based on the shadow value of long-run profits in a two person strategic dynamic game and we find evidence of relative market power of UA in three of the four city pairs we analyze.;The second chapter explores three models of forecasting airline energy demand: Trend line, ARIMA and Structural Model based on results from Chapter 1 and find that none of them is a dominant winner in American (AA) and United (UA) between Chicago and Salt Lake City.;In the third chapter, we use Model Averaging and Forecast Combination Techniques to provide a decisive conclusion focusing on discussing Equal Weighted Averaging, Mean Square Weighted Averaging and Optimized Weighted Averaging on UA and AA in City-Pairs Chicago -Seattle and Chicago-San Diego.