Carbon Emissions and Economic Growth in China : Based on Mixed Frequency VAR Analysis

This study aims to explore the relationship between carbon emissions and economic growth in China from 1992 to 2018 using mixed frequency vector autoregressive model (MF-VAR). The MF-VAR model used in this paper does not go through any filtering procedure, and the variables with different frequencies are directly used for regression calculation. After comparing the obtained results with the low frequency vector autoregressive model (LF-VAR), it is found that using the MF-VAR model can obtain the result of bidirectional causality between carbon emissions and economic growth, but this result cannot be proved in the LF-VAR model. Moreover, compared with the LF-VAR model, the prediction error variance decomposition results in the MF-VAR model have more explanatory power. The results have important implications for China and other global economies in achieving the Sustainable Development Goals (SDGS). The results of the analysis further emphasize the importance of greenhouse gas emission control in China while maintaining a certain level of economic development