Using the ARIMA and ARIMAX Methodologies to Estimate, Model, Forecast, and Compare Airline Passenger Transportation Demand in Türkiye

Abstract

Determining air transportation demand is a very important input that impacts countries’ economies in terms of both micro and macroeconomics. Thus, almost all countries continuously conduct research studies on estimating and forecasting airline passenger demand. However, new estimating and forecasting methods have been improved since the past. The purpose of this study is to estimate and forecast airline passenger demand based on the autoregressive integrated moving average (ARIMA) and ARIMA with explanatory variables (ARIMAX) methods in light of updated time series data and to determine the best model between the two econometric methods. The data used in the study belong to quarterly data between 2010-2022, in which the total incoming and outgoing airline passengers and total incoming and outgoing aircraft are obtained from Türkiye’s General Directorate of State Airports Authority (DHMI), GDP values are obtained from the Turkish Statistical Institute (TurkSTAT), and crude oil import prices are obtained from the US Energy Information Administration (EIA). The collected data have been analyzed using the software program EViews 10.00. The study presents estimations and predictions for total number of airline passengers by first using ARIMA modeling based on the Box-Jenkins method for univariate time series analysis and then ARIMAX modeling by adding exogenous variables to the first model. The study first tested for effects from COVID-19 and found no significant structural break in the studied period. Thus, the seasonal ARIMA (1,1,0) x (1,1,2) effect model (SARIMA) was understood to have the best fit. The second part of the study added the exogenous variables to the model and found ARIMAX (1,1) x (0,0) to have the best fit. Therefore, while the number of aircraft movements and GDP variables are found to be significant and to support the model, imported crude oil price was found to not be significant and to not support the model. The forecasting analysis results found the Theil index; bias proportion; RMSE, MAE, and MAPE; variance, and covariance explanation ratios; and R square values to be at satisfactory levels for both models. When comparing the two models, the ARIMAX model is seen to perform better than the ARIMA model. JEL Classification : M31 , L93 , R41

Keywords

• ARIMA
• ARIMAX
• Passenger Transportation
• Model Estimation
• Model Forecasting

ARIMA-ARIMAX Yöntemiyle Türkiye Havayolu Yolcu Talep Tahmin Modellemesi, Öngörüsü Ve Karşılaştırması

Abstract

Havayolu yolcu talebinin belirlenmesi makro ve mikro ekonomik açından ülkelerin ekonomisine etki eden önemli bir girdi unsurudur. Bundan dolayı hemen hemen tüm ülkeler havayolu yolcu talebi tahmin ve öngörüsüne yönelik sürekli araştırmalar yapmaktadır. Bununla birlikte geçmişten günümüze tahmin ve öngörü modellerinde bir çok yeni yöntemler geliştirilmiştir. Bu çalışmanın amacı, güncel verilerin ışığı altında Türkiye havayolu yolcu sayısını ARIMA ve ARIMAX yöntemlerine dayalı olarak model tahminlemesi, öngörüsünün yapılması ve kullanılan ekonometrik modellerden hangisinin daha iyi olduğunun belirlenmesidir. Çalışmada kullanılan veriler 2010-2022 dönemleri çeyrek dönemlere ait olup; Devlet Hava Meydanları İşletmesinden (DHMİ) gelen- giden toplam yolcu sayıları, ticari gelen-giden toplam uçak hareket sayısı, TUIK’ten Gayri Safi Milli Hasıla (GHSY) ve Birleşik Devletler Enerji Bilgi İşletmesinden Ham Petrol Alış Fiyatı ve kullanılarak sağlanmıştır. Toplanan veriler Eviews 10.00 yardımıyla analiz edilmişlerdir. Araştırmada tek değişkenli zaman serisi analizi Box-Jenkins metoduna dayalı ARIMA modellemesi ve daha sonra modele dışsal değişkenlerin ilave edilerek ARIMAX modeliyle toplam yolcu sayısı tahminlemesi ve öngörüleri ortaya çıkarılmıştır. Yapılan çalışmada, ilk aşamada Covid-19 etkisi incelenmiş ve bu dönemde yapısal kırılmanın anlamlı bir etkisi olmadığı belirlenmiş, akabinde yapılan model tahimininde mevsimsel etkiyi de dikkate alan SARIMA (1,1,0)(1,1,2) modelinin en uygun model olduğu belirlenmiştir. İkinci çalışmada ARIMAX modellemesi yapılarak eklenen dışsal değişkenlerle birlikte en uygun modelin (1,1)(0,0) olduğu tespit edilmiş, dışsal değişkenlerden ülkeye giriş ve çıkış yapan ticari uçak sayısının, ve Gayri Safi Milli Hasılanın modeli anlamlı şekilde desteklediği, ham petrol fiyatı alış fiyatının ise yolcu sayısının belirlenmesine etkisinin anlamlı olmadığı belirlenmiştir. Yapılan her iki modelin öngörü analizleri sonucunda elde edilen Theil katsayıları, yansızlık oranları (Bias) varyans açıklama oranları, hataların ortalama kare kökü (RMSE), hataların mutlak ortalaması (MAE), hataların ortalama mutlak yüzdesi (MAPE) ve modeli açıklama gücü R kare değerlerinin oldukça iyi seviyede oldukları belirlenmiş olup bununla birlikte, yapılan model karşılaştırmaları neticesinde ARIMAX modelinin daha iyi öngörü gücü olduğu sonucuna ulaşılmıştır. JEL Classification : M31 , L93 , R41

Keywords

• ARIMA-ARIMAX
• Havayolu Yolcu Taşımacılığı
• Model Tahmini ve Öngörüsü

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