Prediction of Electricity Generation in Nigeria using Exponential Regression and Cobb-Douglas Models

Aneke Chikezie, Harrison Osasogie Edokpolor, Uwakwe Chikwado


This study presents prediction of electricity generation in Nigeria using two different statistical models, namely; exponential regression and Cobb-Douglas models. Rainfall and temperature were used as the explanatory variables. Data on electricity generation in Nigeria between 2002 and 2014 were obtained from the Central Bank of Nigeria Statistical Bulletin while Data on rainfall and temperature between 2002 and 2014 were extracted from the National Bureau of Statistics (NBS) abstract. Test of model fitness and forecasting accuracy were done using generic statistical approach which include coefficient of determination and root mean square error. The prediction accuracy of the two statistical models was compared and the best model was selected. The best model was then used to forecast electric power generation in Nigeria for the next fifteen years (2015-2029). Among the two statistical models, Cobb-Douglas model was selected as the best model as it gave the highest value of coefficient of determination (r2=99.85%) and the least Root Mean Square Error (48.57%). Furthermore, the Cobb-Douglas model was used to forecast the electric power generation from 2015 to 2029. The forecasted data shows that power generation in Nigeria in 2029 will stand at 3446.85MWh as against the value of 3249MWh in 2014.


Electricity; Electricity Generation; Cobb-Douglas Model; Exponential Regression Model; Electricity Forecasting

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