Linear and non-linear modelling of Nigerian Inflation Rate

Indigofera tinctoria is a tropical plant that has een used to dye cloth since at least 9000 B C but being a natural dye it has poor to moderate fastness. In order to model Nigeria’s inflation rate, this analysis compared univariate linear models to univariate nonlinear models. The data for this analysis was gathered from the Central Bank of Nigeria statistical bulletin on a monthly basis from January 2006 to December 2019. The upward and downward movement in the series revealed by the time plot suggest that the series exhibit a regime-switching pattern: the cycle of expansion and contraction. At lag one, the Augmented Dickey-Fuller test was used to screen for stationary. For univariate linear ARIMA (p d q)) and univariate non-linear MS-AR, seven models were estimated for the linear model and two for the non-linear model. The best model was chosen based on the criterion of least information criterion, AIC (2.006612), SC (2.156581), and the maximum log-likelihood of(-150.5480) for the inflation rate were used to pick MS-AR (1) for the series. In analysing inflation rate data, the MS-AR model proposed by Hamilton outperforms the linear autoregressive models proposed by Box Jenkins. The model was used to predict the series’ values over a one-year cycle (12 months).