摘要：Energy is a key infrastructural element for economic growth. It is a multitalented item that underpins a wide range of products and services that improve the quality of life, increase worker productivity and encourage entrepreneurial activity. This makes Energy consumption to be positively and highly correlated with real per capita GDP. In Ghana, between 2000 and 2008, while real per capita GDP growth averaged 5.5% per annum, annual Energy consumption growth averaged 1.21%. Inspite of the fact that real per capita GDP and Energy consumption are positively correlated, it is still not clear the direction of causality between real per capita GDP and Energy consumption. These underscore the importance of and the need to develop modeling and forecasting tools as strategies for long-term planning. Herein lays the motivation for studying and modeling patterns of energy consumption the Ghanaian economy using seasonal ARIMA models. We obtained historical data of average monthly maximum energy consumption for the period 2001-2011 for the studies and those of 2009 for forecast validation of the chosen model, from the Ministry of energy. Model identification was by visual inspection of both the sample ACF and sample PACF to postulate many possible models and then use the model selection criterion of Residual Sum of Square RSS , Akaike’s Information Criterion AIC complemented with the Schwartz’s Bayesian Criterion SBC, to choose the best model. The chosen model is the SARIMA (1, 1, 1) (0, 1, 2) process which met the criterion of model parsimony with low AIC value of -845.79253 and SBC value of -812.34153. Model adequacy checks shows that the model is appropriate. The model was used to forecast energy consumption for 2013 and the forecast compared very well with the observed empirical data for 2012.
