Electricity has proved to be a vital input to most developing economies. As the Kenyan government aims at transforming Kenya into a newly-industrialized and globally competitive, more energy is expected to be used in the commercial sector on the road to 2030. Therefore, modelling and forecasting of electricity costs in Kenya is of vital concern. In this study, the monthly costs of electricity using Autoregressive Integrated Moving Average models (ARIMA) were used so as to determine the most efficient and adequate model for analysing the volatility of the electricity cost in Kenya. Finally, the fitted ARIMA model was used to do an out-off-sample forecasting for electricity cost for September 2013 to August 2016. The forecasting values obtained indicated that the costs will rise initially but later adapt a decreasing trend. A better understanding of electricity cost trend in the small commercial sector will enhance the producers make informed decisions about their products as electricity is a major input in the sector. Also it will assist the government in making appropriate policy measures to maintain or even lowers the electricity cost.
Keywords: ARIMA, Electricity, Forecast, Kenya
