Forecasting Monthly Inflation in Bangladesh: A Seasonal Autoregressive Moving Average (SARIMA) Approach

Abstract

The objective of this study is to forecast the trend of inflation in Bangladesh by utilizing past inflation data. To achieve this objective, we employed the Seasonal Autoregressive Integrated Moving Average (SARIMA) model which is an extension of the Autoregressive Integrated Moving Average (ARIMA) model. Monthly inflation data used for forecasting were derived from the Consumer Price Index (CPI) data obtained from the International Monetary Fund (IMF) database, covering the period from January 2010 to January 2023. Our analysis reveals that the SARIMA (2,0,0)×(1,0,1)12 model is the most appropriate fit. Based on this finding, we predicted the inflation trend in Bangladesh from February 2023 to December 2024. A comparison of our predicted values with the actual values indicates a high degree of correlation between the two. Although a few discrepancies were observed, they did not undermine our prediction since the parameters of the model lay within the 95% confidence interval.

Keywords

• c51, c53, e31, e37.