Forecasting Demand for Petroleum Products in Ghana using Time Series Models

Godfred Kwame Abledu, Boakye Agyemang, Semevor Reubin


The objective of this study was to forecast and analyse the demand for petroleum products in Ghana using annual data from 2000-2010. It focused on studying the feasibility forecast using nested conditional mean (ARMA) and conditional variance (GARCH, GJR, EGARCH) family of models under such volatile market conditions. A regression based forecast filtering simulation was proposed and studied for any improvements in the forecast results.

Keywords: time Series models, regression model, forecast filtering, petroleum products, stationarity of time Series data.


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ISSN (Paper)2222-1700 ISSN (Online)2222-2855

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