An Empirical Study of Carbon Emission Impact Factors Based on the Vector Autoregression Model

It is important to effectively reduce carbon emissions and ensure the simultaneous adjustment of economic development environmental protection. Therefore, we used Kaya identity screen factors influencing conducted preliminary qualitative analyses, including grey relation analysis linear regression analysis, on variables establish a vector autoregression (VAR) model based their annual data empirically analyze emissions. The results showed that growth effect, energy intensity effect embodied in foreign trade were key affecting emissions, among which contributed most. Accordingly, propose countermeasures technological innovation intensity, new sources improve structure, acceleration industrial structure transfer, optimization structure.