###### Abstract  
A digital economy parallel with green development holds profound significance for achieving sustainability. The primary objective of this study was to explore the synergistic interaction effects between the digital economy and green development in China and forecast their future development. This study analyzed the spatio-temporal characteristics of provincial digital economy and green development in China by integrating a combined assignment method, an unconditional spatial kernel density estimation method, and a standard deviation ellipse model. The interplay between the digital economy and green development was examined using a panel vector autoregression model. Additionally, digital economy and green development levels were forecasted using univariate time series and radial basis function kernel \(\epsilon\)-support vector regression models. The results indicate that both the digital economy and green development levels in China exhibited an upward trend from 2013 to 2021, with the digital economy increasing at a faster rate. However, both domains demonstrated regional disparities in their development processes. The mutual interaction between the digital economy and green development intensified as the lag period increased. The digital economy contributed 21% to green development, whereas green development contributed 18% to the digital economy. The initial effect of the digital economy on green development was negative, however, this impact gradually diminished over time. Additionally, the influence of green development on the digital economy was shown to follow a consistent trend of transitioning from negative to positive across the eastern, central, and western regions. Therefore, it can be seen that the digital economy exerts a sustainable impact on green development, albeit with a one-phase lag. This research provides a scientific basis for the deep integration of the digital economy and green development, thereby fostering sustainable socioeconomic growth. digital economy; green development; spatio-temporal characteristics; panel vector auto regression; support vector regression 2020 October 202  
thereby exerting a profound influence on regional sustainable development [5]. Research revealed that a 1% increase in China's DE corresponds to a 0.50% rise in GD levels [6]. Effectively harmonizing the intricate relationship between DE and sustainable development has emerged as the linchpin for realizing China's economic sustainability ambitions. Since the concept of the DE was introduced in 1996, it has emerged as a prominent research hotspot. In the early stages, research primarily focused on enriching the understanding of the essence of the DE and delineating its scope [7; 8; 9; 10; 11]. As research progressed, interest surged in constructing an evaluation framework and measuring the DE [12; 13; 14; 15; 16; 17]. Recently, studies on the role of the DE in promoting high-quality and sustainable growth across various industries have attracted growing interest, spanning fields like marine fisheries [18], agriculture [19], and tourism [20]. Additionally, to capture the development trends of the DE, forecasting research has garnered interest [2]. Extensive research on GD has been undertaken by scholars. To refine the concepts associated with GD, scholars have delved into the scientific implications of GD [21; 22]. However, the research content exhibits variations in focal points. Therefore, constructing appropriate evaluation index systems based on distinct research objectives is essential [23] as it allows for the precise assessment of GD levels [24; 25; 26; 27; 28; 29; 30]. Furthermore, scholars have proposed targeted research to advance GD, grounded in their empirical findings [31; 32]. Studies concerning the DE and GD have primarily focused on how the DE influences GD. Certain scholars believe that the DE exerts a favorable influence on GD.