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The primary aim for this paper is to examine the pattern of rainfall in the western region of Ghana. Data was obtained from the Ghana Meteorological Agency. The sample include January to September pattern of the amount of rainfall, for the years 2006 to 2016. That is nominal daily rainfall recorded (1485) aggregated into monthly rainfall value (99 data point). The analysis includes fitting an auto regression moving average model (ARMA) model for the data. The series was found to be non-stationary which resulted from the presence of a unit root in it. The series became stationary after eliminating the unit root by finding the first difference in the amount of rainfall. The time series component found in the model were a trend and random variation. ARMA (1, 1) which has all parameters significant was fitted for the data and found to be the most suitable model for the conditional mean. A Ljung Box test statistic of 47.207 with a normalised BIC of 6.420 and a Root Mean Square error of 24.16 supported by a probability value of 0.001 show that the fitted model is appropriate for the data. An = 0.532 indicates that about 53% of the variations seen in the pattern of rainfall recorded for the period is being explained by the fitted model. The 18-month forecast for the mean actual rainfall and mean returns could show that the fitted model is appropriate for the data and an increasing trend of rainfall for the forecasted period.