Munich Personal RePEc Archive

Modelling and forecasting inflation rate in Nigeria using ARIMA models

Olalude, Gbenga Adelekan and Olayinka, Hammed Abiola and Ankeli, Uchechi Constance (2020): Modelling and forecasting inflation rate in Nigeria using ARIMA models. Published in: KASU Journal of Mathematical Sciences , Vol. 1, No. 2 (6 January 2021): pp. 127-143.

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Abstract

This study modelled and forecast inflation in Nigeria using the monthly Inflation rate series that spanned January 2003 to October 2020 and provided three years monthly forecast for the inflation rate in Nigeria. We examined 169 ARMA, 169 ARIMA, 1521 SARMA, and 1521 SARIMA models to identify the most appropriate model for modelling the inflation rate in Nigeria. Our findings indicate that out of the 3380 models examined, SARMA (3, 3) x (1, 2)12 is the best model for forecasting the monthly inflation rate in Nigeria. We selected the model based on the lowest Akaike Information Criteria (AIC) and Schwarz Information Criterion (SIC) values, volatility, goodness of fit, and forecast accuracy measures, such as Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE). The AIC and SIC of the model are 3.3992 and 3.5722, respectively with an adjusted R2 value of 0.916. Our diagnostic tests (Autocorrelation and Normality of Residuals) and forecast accuracy measures indicate that the presented model, SARMA (3, 3)(1, 2)12, is good and reliable for forecasting. Finally, the three years monthly forecast was made, which shows that the Inflation rate in Nigeria would continue to decrease but maintain a 2 digits value for the next two years, but is likely to rise again in 2023. This study is of great relevance to policymakers as it provides a foresight of the likely future inflation rates in Nigeria. Keywords: Inflation; Modelling, Forecasting; ARMA; ARIMA; SARMA; SARIMA;

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