Author/Authors :
AKDAĞ, Murat Türkiye Cumhuriyet Merkez Bankası, Erzurum Şubesi, Turkey , YİĞİT, Vecihi Atatürk Üniversitesi - Mühendislik Fakültesi - Endüstri Mühendisliği Bölümü, Turkey
Title Of Article :
FORECASTING INFLATION WITH BOX-JENKINS AND ARTIFICIAL NEURAL NETWORK MODELS
Abstract :
Inflation forecasting is significantly important for the countries and investments are made according to this data. Slow inflation rate is one of the most important target for developing countries. Thus, accurate forecasting with past data is significant. Time series analysis is one of the most suitable methods for the short period forecasting works. In this study, time series analysis methods known as Box-Jenkins and Artificial Neural Network which are used for inflation rate time series and the results has been served comparative. In this study, ARIMA model shows slightly better performance than Artificial Neural Network model.
NaturalLanguageKeyword :
Time series , Artificial Neural Networks , Inflation Forecasting , ARIMA , Box , Jenkins , CBRT
JournalTitle :
Journal Of Economics and Administrative Sciences, Ataturk University
