FORECASTING PRICE OF FUEL USING TIME SERIES AUTOREGRESSIVE INTEGRATED MOVING AVERAGE MODEL: A ZAMBIAN REVIEW FROM 1998 TO 2022

Abstract

Fuel plays a pivotal role in the economic development of every developing country, which means many sectors of the economy will be unfavourably affected by increasing the price of fuel. This paper reviews and analyses annual data on fuel prices from 1998 to 2022. Data were analysed using Autoregressive Integrated Moving Average (ARIMA) (1,1,2) to predict the price of fuel from 2022 to 2032. The ARIMA (1,1,2) model was used due to its accuracy, mathematical soundness, and flexibility, thanks to the inclusion of AR and MA terms over a regression analysis. The results showed that ARIMA (1, 1, 2) was the best fit for the price of fuel since its errors are smaller than Simple Exponential Smoothing (SES), Double Exponential Smoothing (DES), and Triple Exponential Smoothing (TES). Results of the study also showed that the fuel price will increase from 2022 to 2032 in Zambia. These results are useful to policy and decision-makers such as Zambia Revenue Authority (ZRA), Energy Regulation Board (ERB), and Ministry of Transport, Works, Supply and Communications (MoTWSC) in a bid to plan and execute their duties effectively.