Forecasting the Demand of Oil in Ghana: A Statistical Approach

Valentina Boamah

doi:10.52812/msbd.25

Authors

Valentina Boamah Nanjing University of Information Science and Technology

DOI:

https://doi.org/10.52812/msbd.25

Keywords:

Forecasting, Oil demand/consumption, Statistical models, Energy, Ghana Africa

Abstract

Oil plays a vital role in the economic growth and sustainability of industries and their corporations. The current study sought to forecast oil demand in Ghana for the next decade. The variables analyzed in this study were Petroleum and other liquids, motor gasoline, distillate fuel, and liquefied petroleum gases (LPG). The study utilized three univariate models; thus, linear regression, exponential regression, and exponential smoothing for forecasting various oil components. The linear regression model was deemed a better fit for the analysis of most of the variables. Furthermore, the findings revealed that the LPG growth rate is faster and requires less time to double in numbers than the other energy sources. Also, the exponential smoothing model was ineffective and inefficient. Overall, the demand for oil components analyzed will follow an increasing pattern from 2017 to 2027.

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