Non Linear Time Series Modelling of the Diesel Prices in Kenya

Abstract

Modelling and forecasting diesel prices are a vital concern in most developing economies. A better understanding of a country’s diesel price situation and future prices can facilitate users to make appropriate decisions regarding buying and selling patterns and also to the government in making appropriate policy measures to maintain low and stable prices. The study employed the Autoregressive Integrated Moving Average Model (ARIMA) that could capture the volatility eminent in the fuel prices and forecasting. Findings of the study indicate that the monthly diesel prices in Kenya were non-stationary implying the non stability with regards to the diesel market. The study found that an ARIMA (2,1,2) model was suitable and valid model for estimating volatility and forecasting the diesel prices. The study recommends the government of Kenya through the Energy Regulatory Commission (ERC) should adopt a stable form of diesel prices that are low so as to improve the decisions regarding buying and selling patterns among the users and to improve economic growth rate by ensuring that the cost of production has been put at minimal levels diesel being one of the contributors of production inputs.