Long-term and short-term forecasting techniques for regional airport planning

The aim of this paper is to explore forecast passenger demand techniques in long-term and short-term perspectives at regional airports. The analysis has been applied at Bologna Airport, a large regional airport in Italy with a balanced mix of low cost traffic and conventional airline traffic. In the long-term perspective, a time series model is applied to forecast a significant growth of passenger volumes at the airport in the period 2016-2026. In the short-term perspective, time-of-week passenger demand is estimated using two non-parametric techniques: local regression (LOESS) and a simple method of averaging observations. Adopting cross validation method to estimate the accuracy of the estimates, the simple averaging method and the more complex LOESS method are concluded to perform equally well. Peak hour passenger volumes at the airport are observed in historical data and by use of bootstrapping, these are proved to contain little variability and can be concluded to be stable.