The impact of “zero-waste city” pilot policy on corporate green transformation: a causal inference based on double machine learning

Introduction Against 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. Methods Utilizing 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. Results Our 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. Discussion These 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.

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Publication Details

Journal
Frontiers in Environmental Science
Published
2025-03-20
DOI
https://doi.org/10.3389/fenvs.2025.1564418
Citations
14
Primary Topic
Energy, Environment, Economic Growth
Type
article
Field-Weighted Citation Impact
43.84
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article

The impact of “zero-waste city” pilot policy on corporate green transformation: a causal inference based on double machine learning

Bingnan Guo, Feng Hu, Yan Qian, Jianfeng Jiang
14 citations
Frontiers in Environmental Science
Energy, Environment, Economic Growth
43.84
article

The impact of “zero-waste city” pilot policy on corporate green transformation: a causal inference based on double machine learning

Bingnan Guo, Feng Hu, Yan Qian, Jianfeng Jiang
article en
14 citations

Abstract

Introduction Against 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. Methods Utilizing 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. Results Our 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. Discussion These 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.

Frontiers in Environmental ScienceVol. 13
Jiangsu University of Science and Technology (CN), Guangdong University of Finance (CN)
Openalex Percentile: Top 0%
Energy, Environment, Economic Growth
43.84
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