Determinants of China's Oil Production: Review of Current Developments and Future Prospects

Abstract

Crude oil is a key tool for national financial expansion, and the persistence of fluctuations in crude oil prices has affected all aspects of the economy. In order to maximize its global oil production, China's rapid economic development has necessitated an increase in claim for crude oil and increased its requirement on imported oil. This paper uses a combination of regression analysis and a time series model to achieve greater accuracy. The consequences of the Johansen Cointegration Test demonstrate the existence of a long-term association among crude oil production, the CP index, crude oil prices and GDP Per Capita. After the co-integration of the variables, VEC Model was then applied and Parsimonious model was established. In addition, the multiple regression analysis also shows that there are significant linear relationships between crude oil output, the CPI index, international crude oil prices and GDP per capita which specify that the model is well fit to the information and therefore reliable for future predictions. Diagnostic test such as normality, multicollinearity, heteroscedasticity and autocorrelation were performed and it was revealed that both OLS regression and VEC model did not suffer from a problem of first order autocorrelation, and heteroscedasticity. The OLS model shows that there is no problem of multicollinearity between the CPI index and Global crude oil values and this make the model not misleading and reliable. The satisfactory outcome of the diagnostic test which is also conformity to satisfaction of the basic underlying assumption show that the product is excellent, sturdy, and trustworthy.