Inflation is defined as an increase in the general price level of goods and services within a period of time. For any economic agent to formulate a policy, it must take into consideration inflation and the aim of this study is to use autoregressive integrated moving average (ARIMA) model to predict inflation in Ghana. In order to fulfil this objective, monthly inflation figures were collected from Ghana Statistical Service covering the period 2000:6 to 2010:12 to build the ARIMA model. In building the ARIMA model, the Box- Jenkins approach has been used, thus inflation was found to integrated of order one and follows (6,1,6) order. Inflation was predicted highest for the months of March, April and May to be 8.95, 10.07 and 10.24% respectively. The root mean squared error (RMSE) was calculated at 0.115453, indicating the efficiency of predictability of the model built to predict inflation. It was therefore recommended that the appropriate measures must be put in place to prevent inflation spiral from setting in motion. This is so because our model suggests that, inflation has a long memory and that once the inflation spiral is set in motion, it will take at least 12 periods (months) to bring it to a stable state.
Key words: AR, MA, autoregressive integrated moving average (ARIMA), Inflation.
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