FORECASTING OF INFLATION RATES IN WEST AFRICA USING AUTOREGRESSIVE INTEGRATED MOVING AVERAGE MODEL

Authors

  • S. B. Mu’azu Department of Accounting, A.B.U. Business School, Ahmadu Bello University, Zaria.
  • S. L. Ladan Department of Vocational and Technical Education, Ahmadu Bello University, Zaria.
  • A. A. Unyime Department of Business Administration and Management, Federal Polytechnic Daura, Katsina State
  • A. Mohammed Department of Business Administration and Management, Federal Polytechnic Daura, Katsina State

Keywords:

ARIMA, Economic policy, Forecasting, Inflation rate, Unit root, West Africa

Abstract

Inflation as a persistent increase in the overall price level of goods and services holds
significant implications for a nation's economic landscape. This quantitative study employs
data sourced from the World Bank spanning 1970 to 2021 for Key Five West African
countries (Gambia, Ghana, Nigeria, Senegal, and Togo); using purposive sampling. The
primary aim is to forecast inflation rates in West Africa using tailored autoregressive
integrated moving average (ARIMA) models. Augmented Dickey-Fuller (ADF) unit root tests
confirm the first-order integration of inflation rates in the examined West African nations.
Subsequent time series analysis, specifically ARIMA modeling, identifies optimal models—
ARIMA (1,1,2), ARIMA (1,1,1), and ARIMA (2,1,2)—based on various selection criteria
including significant coefficients, volatility, adjusted R-squared, Akaike Information
Criterion, and Schwarz Criterion. However, the study underscores the necessity for
governments to enact suitable policy measures to alleviate inflationary effects on the
economy. Projections indicate a downward trend in inflation rates for West African
countries, signaling a positive economic trajectory.

Published

2024-12-20

Issue

Vol. 2 No. 2 (2024)

Section

Articles