Can digital economy improve urban ecological development? evidence based on double machine learning analysis

Abstract

The role of digital economy (DE) in improving urban ecological development (UED) has attracted scholarly attention. Additionally, traditional causal inference models encounter several challenges, such as model misspecification and the “curse of dimensionality.” In response to these problems, the double machine learning method is applied to assess the effect of DE on UED. Leveraging data from 282 Chinese cities in 2006–2021, several valuable conclusions emerge. First, DE improves UED and positively contributes to ecological resilience and recovery. Second, promoting green innovation, enhancing environmental efficiency, and optimizing industrial structures are the pathways through which DE contributes to UED. Third, the influence of DE on UED displays heterogeneity. Based on the results, this work proposes relevant recommendations grounded in empirical research.