Demand Forecasting in Regional Airports: Dynamic Tobit Models with Garch Errors

In this paper we discuss the general issue of forecasting highly seasonal demand in regional airports, where peak flows approach airport capacity. For this, we propose a modeling combination, dynamic Tobit models with GARCH errors/disturbances, that is able to capture many of the shortcomings of most traditional models. Models are calibrated using monthly passenger and flight data for a 20 year period for the airport of Corfu in Greece, where traffic over the summer approaches airport capacity and seasonal fluctuations in demand are very intense. Results show that: i. Not explicitly accounting for seasonal variations in demand or for traffic approaching capacity may significantly bias model parameter estimates and affect demand predictions; and, ii. Improved demand model specifications are an invaluable tool in obtaining more accurate demand estimates.