FORECASTING INFLATION RATE OF KAZAKHSTAN BASED ON THE CONSUMER PRICE INDEX, CONSIDERING THE IMPACT OF SEASONALITY

Abstract

The purpose of this work is to study and compare existing models and methods, and build an optimal model for forecasting inflation in Kazakhstan, taking into account seasonal adjustment of CPI. This paper compares the performance of two seasonal adjustment methods, TRAMO-SEATS and X-13-ARIMA-SEATS. Based on the results of seasonal adjustment, the X-13-ARIMA-SEATS method detects more outliers than the TRAMO-SEATS method; however, the difference in the seasonally adjusted time series is negligible. Thus, further comparison of these two methods is conducted based on the result analysis of the forecast models. To forecast the inflation rate, two models are used - the ARIMA-GARCH model, and the VAR model. The out-of-sample forecast is made for a short-term period of six months from June 2019 to December 2019. Based on the error measures in the validation period the most adequate and accurate model is the VAR(2) model with CPI seasonally adjusted by the X-13-ARIMA-SEATS method.