Intelligent transformation and green development: a double debiased machine learning evaluation of china’s IIP initiatives
研究中国两化融合试点政策对制造业上市公司绿色发展的影响，发现该政策通过智能化转型显著提升环境效率和生产率，对长江经济带、重污染行业和大企业效果更明显。
Abstract In promoting the transformation, upgrading, and green development of traditional industries the Chinese government has been introducing Integration of Informatization and Industrialization Pilot (IIP) initiatives based on intelligent manufacturing and the green economy. As such this study examines the impact of China’s IIP policy on the green development of publicly listed manufacturing firms by applying both Difference-in-Differences (DID) and double debiased machine learning (DDML) models to a dataset that spans the period 2007–2022. The evidence suggests that the IIP policy initiative significantly improves firms’ green development via the mediating effect of intelligent transformation. Robustness checks, including DDML model regression and Propensity Score Matching-DID (PSM-DID) with nearest neighbour matching, consistently demonstrate significant improvements in environmental efficiency and productivity due to the IIP. Moreover, these effects are notably pronounced in the Yangtze River Economic Belt, heavily polluting industries, and larger firms. This research addresses a gap in micro-level policy analysis, highlighting the potential of intelligent manufacturing to promote sustainable practices. By offering both theoretical and practical insights, the findings guide policymakers and businesses in leveraging informatization and industrialization for green development.