Modeling and Forecasting Inflation Rates in Bangladesh: An Application of ARIMA Models

Abstract

As a key factor in an economy, inflation affects the buying power of currency and the stability of the financial condition of a country. This study aims to use the Autoregressive Integrated Moving Average (ARIMA) technique to model and forecast inflation, utilizing annual inflation data from 1987 to 2022 in Bangladesh. Data on Bangladesh’s annual inflation rate, spanning several years, were collected from the World Bank website. The analysis utilized graphical techniques and theoretical tests, including the Augmented Dickey-Fuller test, Ljung-Box test, and Shapiro-Wilk test. Our findings indicate that the ARIMA (2,1,0) model is the most suitable for the inflation data in Bangladesh because it has the lowest Akaike Information Criterion (AIC). The suggested model in this research will help policymakers foresee the future inflation rate of Bangladesh, supporting them in making economic decisions and crafting relevant policies.

Dhaka Univ. J. Sci. 73(1): 51-55, 2025 (January)