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Modelling Monthly Inflation in the Philippines using Seasonal Autoregressive Integrated Moving Average (ARIMA)

Jacque Bon-Isaac Aboy1, Jane Rhica Magalona2, Dannah Ysabel Premacio2*

Inflation impacts the country's economy greatly. It is vital not only to the government, but also to the lifestyle of an average person. It plays a crucial role in decision-making done by households, firms, markets, and government. With the existing importance of inflation to a country, the role of forecasting becomes crucial. Better decision-making and reinforced preparations come with a good forecasting. Given that, this paper aims to model inflation rates in the Philippines in a Seasonal ARIMA (SARIMA) framework. The data used for modelling were monthly values from January 2015 to March 2020. Analysis reveals that inflation rates in the Philippines follow a seasonal ARIMA (0, 1, 0) (1, 1, 0) (12). The model has Mean Absolute Percentage Error (MAPE), Root Mean Square Error (RMSE) and Theil Inequality Coefficient value of 1.189417, 1.012582, and 0.089779, respectively. Therefore, the model is adequate since the values are close to zero. It is also shown to be accurate in forecasting inflation rates with an accuracy of 98.81058% for the 24-month forecast.