The impact of “zero-waste city” pilot policy on corporate green transformation: a causal inference based on double machine learning - Qian, Yuren; Jiang, Jianfeng; Guo, Bingnan; Hu, Feng (Frontiers in Environmental Science, 2025)
IntroductionAgainst the backdrop of China’s ambitious “dual carbon” objectives and ongoing economic transformation, this study investigates the efficacy of solid waste management reform through the “Zero-Waste City” pilot program.MethodsUtilizing a comprehensive dataset of listed companies from pilot regions spanning 2016-2023, we employ sophisticated double machine learning models to empirically evaluate the program’s impact on corporate green transformation.ResultsOur findings demonstrate that the pilot policy implementation significantly accelerates the green transformation trajectory of enterprises within designated regions. Through rigorous mechanism analysis, we identify three primary channels through which the policy operates: enhanced green technological innovation, heightened government environmental oversight, and increased investor environmental awareness. Heterogeneity analysis reveals differential policy impacts across ownership structures and industry characteristics, with more pronounced effects observed in non-state-owned enterprises, non-heavily polluting industries, and traditional (non-high-tech) sectors.DiscussionThese nuanced findings provide valuable empirical evidence and policy implications for the strategic expansion of the “Zero-Waste City” initiative during China’s 14th Five-Year Plan period, contributing to the broader literature on environmental policy effectiveness and corporate sustainability transitions.