An Econometric Investigation of Forecasting Premium Fuel


Abstract views: 142 / PDF downloads: 187

Authors

  • Samuel Asuamah Yeboah
  • Joseph Ohene-Manu

Abstract

For a sustainable economic development, premium fuel forecasting is becoming increasingly relevant to policy makers and consumers. The current paper develops a structural econometric model of premium fuel using the Autoregressive Integrated Moving Average (ARIMA) to analyse and forecast premium demand. The results show that the ARIMA models (1, 1, 0); (0, 1, 1) and (1, 1, 1) are the appropriate identified order. The estimated models included a constant term. All the coefficients of the variables in the model except the constant term were significant. The diagnostic checking of the estimated model shows ARIMA (1, 1, 1) as the best fitted model since all the series were randomly distributed. The data for the forecast covers the period 2000:01 to 2011:12. The results indicated that the forecasted values fitted the actual consumption of the energy variables since the forecasted values insignificantly underestimate the actual consumption and thus indicate consistency of the results. The evaluation statistics indicate that the estimated models are suitable for forecasting. The model developed in the work is helpful to the energy sector and policy makers in making energy related decisions and investigating the changes in premium demand. Keywords: Premium fuel; ARIMA; ForecastingJEL Classifications: C51; C52; C53; E17; Q47

Downloads

Download data is not yet available.

Author Biography

Samuel Asuamah Yeboah

Marketing Department, HOD, PhD Candidate

Downloads

Published

2015-07-13

How to Cite

Yeboah, S. A., & Ohene-Manu, J. (2015). An Econometric Investigation of Forecasting Premium Fuel. International Journal of Energy Economics and Policy, 5(3), 716–724. Retrieved from https://econjournals.com/index.php/ijeep/article/view/1288

Issue

Section

Articles