Forecasting InternationalAirTransport Arrivals using Monthly Seasonal Indices: Evidence at Entebbe InternationalAirport

Abstract

The study models international passenger air transport arrivals in SubSaharan Africa using evidence at Entebbe International Airport.Approach was quantitative analysis of monthly trends by generatingmonthly seasonal index model and using the model to make monthlyforecasts one year ahead. Monthly data from 1998 to 2012 were usedto describe and test characteristics in arrivals using Microsoft Excel2007. Modelling of the monthly seasonal indexes was by using a 12-month centred moving average. Findings revealed serial correlationand seasonality in the trends January, July, August, October, Novemberand December with higher volumes and the other months with lowervolumes than the annual monthly average volumes. The study revealedalso that there is a significant higher volume of arrivals in the secondhalf of the year than the first half. The model index was analysedusing different statistical tests and was proved to have goodness of fitfor the data. An estimate regression equation was generated to computethe model evaluation forecasts and later on an actual monthly forecastone year ahead were computed covering the period from June 2012 toMay 2013. The study contributes to existing literature on analysingand forecasting international airport arrivals using classicalapproaches, which are more appreciated to users and more efficient incapacity management as well as service delivery. The study has policyand management implications as discussed.Key words: International Airport Arrivals, Seasonal Indexes, Moving Average,Sub-SaharanAfrica, Forecasting