An Analysis of Forecasting Model of Crude Oil Demand Based on Cointegration and Vector Error Correction Model (VEC)

This paper establishes a cointegration and vector error correction model to forecast the crude oil demand in China after analyzing main factors affecting crude oil demand. The model proves that GDP, population, the share of industrial sector in GDP and the oil price are the main factors influencing crude oil demand. Especially population and the share of industrial sector make significance influences on crude oil demand, since the large-scale population, ever-increasing living standard and fast industrialization in China in the past thirty years. After implementing ex post forecast which implies that the cointegration and vector error correction model that established before fits the demand trend very well, the paper forecasts Chinapsilas crude oil demand from 2008-2020 using the model. The forecast indicates that the demand will be as great as 0.599 billion tons in 2020, which means that China will encounter more and more serious energy problems, for which some suggestions are proposed to policy-makers.