Abstract: The aim of this study was to empirically develop ARIMA-GARCH models for Kenya inflation and to forecast the rates of inflation using the historical monthly data from 2000 to 2014.
The empirical research employs time series analysis, ordinary least square and auto-regressive conditional heteroscedastic to find the estimators.
The forecasting inflation analysis have been conducted using two models, the ARIMA (1, 1, 12) model was able to produce forecasts based on the stationarity test and history patterns in the data compared to GARCH (1,2) model. The empirical results of 180 monthly data series indicate that the combination between ARIMA(1,1,12)-GARCH(1,2) model provide the optimum results and effectively improved estimating and forecasting accuracy compared to the other previous methods of forecasting.
Keywords: Inflation, ARIMA, GARCH, model, time series, modeling and forecasting.
Title: Forecasting Inflation in Kenya Using Arima -Garch Models
Author: Charline UWILINGIYIMANA, Joseph MUNGA’TU, Jean de Dieu HARERIMANA
International Journal of Management and Commerce Innovations
ISSN 2348-7585 (Online)
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