Methodological Framework for Air-Travel Demand Forecasting

Abstract

Air-transport demand forecasting constitutes an important determinant of airport planning, design, and operations. Errors in forecasting can be very costly. Underestimating demand may lead to increased congestion, delay, and inadequate airport facilities. Overestimating demand may also create serious economic problems for airport authorities. It is, therefore, very important for airport planners to develop reliable forecasting models and to understand possible limitations in the forecasting accuracy of these models. The objective of this paper is to examine the predicting ability and forecasting accuracy of air-travel demand models. In particular, an analytical framework for developing econometric models is presented and postfact analysis is used to test the accuracy of the models. Statistical data describing air-travel demand patterns for two major international airports, the Frankfurt and the Miami International Airports, are used to demonstrate the effectiveness of the proposed models. In addition, the effect of external factors such as the deregulation of the air-transport industry is examined. The results suggest that simple models with few independent variables perform as well as more complicated and costly models, and that external factors have a pronounced effect on air-travel demand.