Modeling and Forecasting of Fuel Selling Price Using Time Series Approach: Case Study

Abstract

The liberalization of the petroleum sector in Morocco has a significant effect for petroleum product distributors. Since the beginning of December 2015, fuel prices are freely determined. This event presents many constraints affecting the balance of the sector plus the competition between its economic players. The lack of accompanying measures by the State makes this vital reform for public finances that stop subsidizing the price of gasoline vulnerable. With the halt of the competitive manufacturing's activity, Morocco's only refinery, distributors must, for their part, build up large stocks. As all fuel products are imported, we will be interested in the evolution by making forecasts of the price of fuels in the Moroccan market. In order to achieve their objectives, the oil companies must rely on precise forecasts. In this context, our paper aims mainly to study the time series of diesel and gasoline in order to provide precise forecasts to the company and to respect the permissible error margin of 3%. To this end, we worked with the ARIMA method. We found that the ARIMA model (1,1,1) gives forecasts of the price of gasoline near the margin to be met for the first quarter of the current year with an average error margin of 2,855%. In addition, the assumption that the residuals are a Gaussian white noise has always been verified.