Detecting the Best Seasonal ARIMA Forecasting Model for Monthly Inflation Rates in Turkey

Yıl 2017, Cilt: 32 Sayı: 2, 143 - 182, 04.12.2017

Mehmet Özmen , Sera Şanlı

https://doi.org/10.24988/deuiibf.2017322602

Öz

In this study, it has been aimed to find the best ‘Seasonal Autoregressive Integrated Moving Average (SARIMA)’ model for monthly inflation rates for Turkish economy over the period 1995:01-2015:03. Before the model identification based on Box Jenkins methodology, HEGY monthly seasonal unit root test has been applied. The orders of seasonal differencing have been detected through OCSB and CH tests. Finally, ARIMA(1,1,1)(1,0,2)[12] with drift model chosen by using stepwise selection method and ARIMA(1,1,1)(2,0,0)[12] with drift model chosen by using non-stepwise selection have been compared. The results have shown that the former model is better as the best fitted SARIMA model.

Anahtar Kelimeler

Inflation, Box Jenkins, SARIMA, HEGY, OCSB, CH, Stepwise Selection

Türkiye İçin Enflasyon Oranının Uygun Mevsimsel ARIMA Modeli İle Belirlenmesi

Öz

Bu çalışmada Türkiye’nin 1995:01-2015:03 dönemine ilişkin aylık enflasyon oranları için en iyi ‘Mevsimsel Otoregresif Bütünleşik Hareketli Ortalama (SARIMA)’ modelini bulmak amaçlanmıştır. Box Jenkins metodolojisine dayalı model tanımlamasından önce HEGY mevsimsel birim kök testi uygulanmıştır. Mevsimsel fark alma dereceleri OCSB ve CH testleri kullanılarak saptanmıştır. Son olarak, sırasıyla adımsal (stepwise) ve adımsal olmayan (non-stepwise) seçim yöntemleri kullanılarak seçilen sürüklenmeli ARIMA(1,1,1)(1,0,2)[12] ve ARIMA(1,1,1)(2,0,0)[12] modelleri karşılaştırılmıştır. Sonuçlar adımsal yöntem kullanılarak seçilen sürüklenmeli ARIMA(1,1,1)(1,0,2)[12] modelinin en iyi uyan SARIMA modelini belirlemede adımsal olmayan modele göre daha iyi olduğunu göstermiştir.

Anahtar Kelimeler

Enflasyon, Box Jenkins, SARIMA, HEGY, OCSB, CH, Adımsal Seçim

Kaynakça

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