Forecasting and Technical Comparison of Inflation in Turkey with Box-Jenkins (ARIMA) Models and Artificial Neural Networks
Erkan IŞIĞIÇOK Ramazan Öz Savaş Tarkun
AbstractInflation refers to an ongoing and overall comprehensive increase in the overall level of goods and services price in the economy. Today; inflation, which is tried to be kept under control by the central banks, is trying to ensure price stability, the continuous price changes that arise in all the goods or services that consumers use includes. Undoubtedly in terms of economy, inflation expectations are also ganing importance, except for rhe realized inflation. This situation makes it necessary to predict the future vaules of inflation. In that case, a reliable estimate of the future values of inflation in any country will create an entry in determining the policies that decisionmaker units will implement on the economy. The aim of this article is to predict inflation in the next period by using the Consumer Price Index (CPI) data with two alternative techniques. It is also aimed to examine the prediction performances of these two techniques in comparisons. Thus, the first of the two main objectives of the study is to predict the future values of inflation with two alternative techniques. The second goal is to determine which of these two techniques well compared to statistical and econometric criteria. In this context, the estimated performance of both techniques was predicted by the 9-month inflation, Box-Jenkins (ARIMA) and Artificial Neural Networks (ANN) in the April – December 2019 period, using CPI data consisting of 207 in the period of January 2002 – March 2019. In the study, Eviews and Matlab programs were utilized.