Ejem Ejem Agwu, Igboji Marcellinus Uchenna C.J., Aikor Shirgba Timothy



Time Series Models for Forecasting Passengers Traffic at Nigeria’s Airports in Pre-COVID 19 Era

pdf PDF


This paper studied the forecasting of air traffic of passengers at Nigeria airports to address the growth of traffic, evident effects on future airport activity levels for the enabling of airport planning cum decision making and to provide criteria for facility requirements, associated financial planning and funding as part of airport development. As air traffic of passengers experiences considerable growth and changes in increased air travel, year in and year out, the number of various kinds of passengers (e.g. arriving, departing, and transit) influences airport terminal capacity and facility needs. The modelling and forecasting in this paper provided for short and medium out-of-sample forecasts of possible successive monthly and quarterly air traffic of passengers in Nigeria airports collectively for two markets geographical segments: Domestic and International air travel. The following time series models were utilized in this study: Winter's Triple Exponential Smoothing (TESMTH), Autoregressive Integrated Moving Average (ARIMA), AirLine-Model, and Seasonal Autoregressive Integrated Moving Average (SARIMA). The forecast accuracy of each model was assessed using Mean Absolute Percentage Error (MAPE) and Root Mean Squared Error (RMSE) criteria. It also investigated if merging forecasts from all models improved predicting accuracy. This section of the study was completed using the Combination of Forecasts Technique: Simple Averaging Method. The findings showed that the majority of our models gave accurate projections for the specified market, with MAPE and RMSE errors being less than 10% on average. The study evaluated forecast accuracy to determine the marketability of a model to avoid the traps caused by inaccurate forecast information. Furthermore, the combination of Estimates from Single Models surpassed several of the specific single model forecasts. Finally, these findings should urge the Nigerian government, the Nigerian air transport sector, and academia to address growth and current implications on future airport activity levels for airport planning and decision making.


Airport Planning, Decision making, Winter's Triple Exponential Smoothing, ARIMA, SARIMA


Cite this paper

Ejem Ejem Agwu Igboji, Marcellinus Uchenna C.J., Aikor Shirgba Timothy. (2022) Time Series Models for Forecasting Passengers Traffic at Nigeria’s Airports in Pre-COVID 19 Era. International Journal of Environmental Science, 7, 114-126


Copyright © 2022 Author(s) retain the copyright of this article.
This article is published under the terms of the Creative Commons Attribution License 4.0