Title: Forecasting annual inflation rate of Ethiopia (2023-2027): autoregressive moving average model approach

Authors: Sintayehu Ermias Lolemo

Addresses: S.D. School of Commerce, Gujarat University, Navrangpura, Ahmedabad, India

Abstract: This research addresses the significant implications of increased inflation volatility, highlighting the heightened uncertainty it brings to producers and consumers when anticipating future prices. Recognising the profound impact of inflation volatility on market dynamics, this study focuses on forecasting the annual inflation rate in Ethiopia from 2023 to 2027. Using annual inflation data from 1966 to 2022, obtained from worlddata.info, the researcher developed an autoregressive moving average (ARMA) model. A thorough examination of the model specification, stationarity, normality, and heteroscedasticity was done using the residual diagnostic checks, correlogram, and augmented Dickey-Fuller test. The unit root test revealed the stationary nature of the inflation rate at this level. The findings established that the ARMA (0, 4) model is appropriate and most suitable for predicting Ethiopia's inflation rate. Moreover, the results suggest a gradual decline in the inflation rate over the next five years.

Keywords: annual inflation rate; ARMA model; correlogram; Ethiopia; Inflation forecasting; residual diagnostic checks; stationarity; time series analysis; unit root test.

DOI: 10.1504/IJEBANK.2025.143025

International Journal of Electronic Banking, 2025 Vol.5 No.1, pp.37 - 49

Received: 26 May 2023
Accepted: 28 Jan 2024
Published online: 02 Dec 2024 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article