Abstract: The transition to a green and low-carbon economy requires an innovation-driven approach. Consequently, it is crucial to scientifically measure the sustainable development level of China's green economic innovation. Existing studies often focus exclusively on either the green economy or technological innovation, leading to a fragmented understanding of their interconnections. To address this gap, this study adopts the green economic innovation index concept proposed by Holger (2017) and selects 22 indicators across three dimensions: green ecology, technological innovation, and social economy. Utilizing newly constructed the Mixed-Frequency Time-Varying-Parameters Stochastic-Variance Dynamic Factor Model (MF-TVP-SV-DFM), we construct three sub-indices that capture the dynamics of China's green economic innovation. Subsequently, we apply newly constructed the Mixed-Frequency Mixed-Innovation Time-Varying-Parameters Stochastic-Variance Vector Autoregression (MF-MI-TVP-SV-VAR) model to derive the weights for the first Chinese Mixed-Frequency Flexible-Time-Varying Green Economic Innovation Index (MF-FTV-GEII) based on the flexible dynamic generalized impulse response function, culminating in the compilation of the MF-FTV-GEII. Our analysis yields several significant findings. First, robustness checks confirm that the MF-FTV-GEII serves as a comprehensive and effective measure of China's green economic innovation, outperforming traditional indices in predictive power and correlation with key economic indicators. Comparisons with Holger's index and the innovation index from the China National Bureau of Statistics reveal that the MF-FTV-GEII demonstrates superior leading, correlational, and causal relationships with green economic innovation. Second, trend analysis shows a positive trajectory in the sustainable development of China's green economic innovation, which reached a level of 64.20% by December 2022, with an average annual growth rate of 11.89%. Finally, comparative assessments indicate that while progress has been made, China's green economic innovation still lags behind Germany's performance and remains significantly below the theoretical maximum of 100%. This study not only fills a critical research gap but also provides a robust framework for policymakers and researchers to better understand and promote green economic innovation in China.

Keywords: Green economy; scientific and technological innovation; sustainable development; MF-TVP-SV-DFM model; MF-MI-TVP-SV -VAR model