A Spatial Econometric and Deep Learning Evaluation of China's East-West Computing Resources Transmission Project Effects

To promote the high-quality development of digital economy, China has launched the construction of national arithmetic hub nodes and planned 10 national data center clusters in eight places, including Beijing, Tianjin and Hebei, implementing the East-West Computing Resources Transmission Project. This paper evaluates the impact of the EWCRT Project policy on the GDP of the relevant provinces based on the spatial measurement DID model, and predicts the key indicators of the digital economy by constructing a hybrid framework of “decomposition-prediction-integration”. The results show that the lagged GDP term is significantly positively correlated (β=0.6068, p<0.001), while the effect of the EWCRT policy does not pass the test of significance (β=0.0248, p=0.1715), which suggests that the regional policy needs to optimize the implementation mechanism to enhance the economic pulling effect. And there is a significant economic agglomeration effect in the Eastern region (e.g., Guangdong), while the Western provinces (Ningxia, Gansu, etc.) have small and discrete economies. In addition, the coefficient of the spatial lag term tends to be close to zero (p=0.9731), reflecting the lack of significant spatial spillover effects between provinces and regions and highlighting the need for coordinated regional development. The forecast finds that the average annual growth rate of the digital economy in the next five years will reach 15.7%, and the proportion of industrial digitization continues to expand. This paper provides a decision-making basis for promoting the coordinated development of digital economy in the East and West of China, which has both theoretical value and practical guidance significance.