“无废城市”政策能否激发高耗能企业绿色创新？——基于双重机器学习的因果推断

Does the “Zero-Waste City” Policy Stimulate Green Innovation in Energy - Intensive Enterprises?—A Causal Inference Analysis Based on Double Machine Learning

中文关键词:  “无废城市”试点  绿色技术创新  高耗能企业  空间溢出效应  双重机器学习

英文关键词:Zero-Waste City pilot  green technological innovation  energy-intensive firms  spatial spillover effects  Double Machine Learning

中文摘要:

      在资源约束日益趋紧与固体废物存量持续攀升的双重压力下，中国启动“无废城市”试点以探索循环经济与绿色转型路径，但企业的政策响应机制仍缺乏系统检验。本文利用2015—2023年沪深A股高耗能上市企业微观数据，结合“无废城市”分批试点的准自然实验，构建双重机器学习模型评估政策对高耗能企业绿色创新的影响及其作用机制。实证结果显示，该政策显著提升了高耗能企业的探索式与利用式绿色创新；其作用主要通过外部激励缓解资金约束与内部治理优化两条路径实现，并呈现所有制与地区条件上的异质性；空间计量结果显示政策存在邻近外溢，表现为环境竞争加剧与绿色知识扩散共同推动区域绿色转型。本研究将企业微观行为与区域绿色治理相结合，拓展了环境规制与企业应对行为的研究边界，为政策优化与区域绿色转型提供了经验支持。

英文摘要:

      Under the dual pressures of increasingly stringent resource constraints and continuously rising solid waste accumulation, China has launched the“Zero-Waste City” pilot to explore pathways toward a circular economy and green transition. However, corporate responses to this policy remain insufficiently examined. Using micro-level data on energy-intensive listed firms in Shanghai and Shenzhen from 2015 to 2023, and leveraging the quasi-natural experiment of the phased“Zero-Waste City” pilot program, this study constructs a double machine learning (DML) model to evaluate the policy’s impact on green innovation in energy-intensive firms and its underlying mechanisms. Empirical results show that the policy significantly enhances both exploratory and exploitative green innovation in energy-intensive firms. The effects are mainly realized through two pathways: external incentives that alleviate financial constraints, and internal governance improvements, with heterogengity observed across ownership structures and regional conditions. Spatial econometric analysis further reveals notable spillover effects to neighboring areas, as intensified environmental competition and green knowledge diffusion, collectively promoting regional green transformation. By linking firmlevel behavior with regional environmental governance, this study advances the understanding on environmental regulation and corporate adaptive behavior, and provides empirical evidence to inform policy refinement and regional green transition.