Otu Archibong Otu¹, Osuji George A.², Opara Jude^3,, Mbachu Hope Ifeyinwa³, Iheagwara Andrew I.⁴

This paper discussed the Application of SARIMA Models in Modeling and Forecasting Nigeria’s Inflation Rates. Time series analysis and forecasting is an efficient versatile tool in diverse applications such as in economics and finance, hydrology and environmental management fields just to mention a few. Among the most effective approaches for analyzing time series data, the method propounded by Box and Jenkins, the Autoregressive Integrated Moving Average (ARIMA) was employed in this study. In this paper, we used Box-Jenkins methodology to build ARIMA model for ’s monthly inflation rates for the period November 2003 to October 2013 with a total of 120 data points. In this research, ARIMA (1, 1, 1) (0, 0, 1)12 model was developed, and obtained as = 0.3587y_t+0.6413y_t-1-0.8840e_t-11 -0.7308912e_t-12+0.8268e_t. This model is used to forecast ’s monthly inflation for the upcoming year 2014. The forecasted results will help policy makers gain insight into more appropriate economic and monetary policy in other to combat the predicted rise in inflation rates beginning the first quarter of 2014.

ARIMA Model, SARIMA Model, forecasting, ARMA Model, Box-Jenkins Methods, inflation rates, Akaike Information Criteria, Bayesian Information Criterion