A Methodology for Evaluating Economic and Policy Impacts on Airline and Passenger Behavior

Abstract

This dissertation describes an equilibrium model to examine domestic airline scheduling and pricing behavior in response to changes in fuel prices and runway capacity limits. A major re-design of an equilibrium model developed by Le (2006) was performed that allows one to look at the responses of the airline industry as costs change and/or as capacity limits are altered. Part of this re-design required an analysis of the sensitivity of airfares to supply changes and the development of general elasticity models for each of the major markets served by the airports in this study. The US Government expects to spend $37 billion in order to increase airspace capacity in the US (e.g. SESAR/NextGen) while economists argue that there are market-based mechanisms that can better manage congestion at airports where expansion is impossible and during the interim before the technologies are fully functional. Those that argue against market-based approaches worry that passengers in smaller markets will lose air-transportation access, airlines are too fragile to incur any new taxes, airfares will increase and it will not force the up-gauging that will improve throughput with current technologies. By evaluating how cost changes and/or capacity changes impact airline behavior, one can evaluate if these arguments are justified. Airline domestic scheduling and pricing behavior is examined at eight congested airports (BOS, DFW, EWR, JFK, LGA, ORD, PHL, and SFO) because they generated 47.5% of the flight delays in 2007 and 42.6% of the flight delays in 2010. We record changes in the markets served by each of these airports, the frequency of service to these markets, changes in the aircraft size, the number of passengers served and the average airfares when fuel price are increased and when runway capacity limits are imposed. We also examine the effect of these changes on the profitability of the airline industry and the amount of fuel used. The results of this analysis show that: • The system is very sensitive to fuel price changes and less sensitive to capacity changes, especially between Visual Flight Rules (VFR) and Marginal Visual Flight Rules (MVFR). • The Airport Schedule Optimization Model (ASOM) developed in this dissertation indicates that the airline industry is robust but will alter their schedules and service to maintain profitability. • As fuel prices increase, airlines are likely to show greater changes in their schedules and the model reflects an increase in airfares, a decrease in passengers served and a decrease in aircraft gauge. • As fuel prices start to increase operational costs are dominated by fuel costs. When this occurs, airlines no longer see the economies of scale related to aircraft size that are exhibited at lower fuel costs.