Digital Economy, Industrial Structure Optimization, and Agricultural Green Development Efficiency: A Double Machine Learning Causal Analysis

The digital economy plays a role in encouraging green development in agriculture, which helps achieve food security, resource conservation, and sustainable development, and also helps promote the United Nations Sustainable Development Goals. This paper employs a double machine learning (DML) method to analyze the impact of the digital economy on agricultural green development efficiency and the mechanism by which it exerts this impact across 282 prefecture‐level cities in China from 2010 to 2020. The results indicate that the digital economy positively affects the efficiency of agricultural green development, even after addressing endogeneity issues and conducting robustness checks. Analysis of the mechanism shows that vertical industrial upgrading and horizontal industrial integration are the main drivers. Furthermore, heterogeneity analysis uncovers a strong compensatory effect of the digital economy, showing a more pronounced impact in non‐major grain‐producing, resource‐based, and low‐income regions. This study provides a reference for using the digital economy to promote agricultural green development efficiency in other developing countries.