Inflation tends to be a relatively persistent process, which means that current and past values should be helpful in forecasting future inflation. Applying this intuition, we construct a basic stochastic model which exploits information embedded in past values of Ghana’s inflation data. Therefore the aim of this study is not to identify the drivers of Ghana’s inflation, but to identify and forecast with the best predicting model for Ghana’s inflation, based on the stochastic mechanisms that governs Ghana’s inflation series. We then use this identified model to forecast one-year-ahead (that is, 2018) inflation using past lags, specifically, monthly inflation, from January 2010 to September 2017. Per our forecast, the Bank of Ghana’s aim of hitting a single digit for the year 2018 will not be realized, even though the year closes with a lower inflation than what it began with.
Key words: Inflation, ARIMA model, forecasting, Ghana.
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