南京工业大学学报（社会科学版）2025，Vol.24Issue(4)：75-96,22.
企业级空间集聚与污染排放强度
Enterprise Level Agglomeration and Pollution Emission Intensity:Evidence from Micro Geographic Information and Pollution Emission Data of Listed Enterprises
摘要
Abstract
Green development is an important connotation of Chinese path to modernization in the new era.Promoting enterprise pollution reduction during the agglomeration process is an important way to achieve the"win-win"goal of economic development and environmental protection.This article uses micro geographic information data and potential models of Chinese listed manufacturing enterprises to calculate spatial agglomeration indicators at the enterprise level,uses detailed pollution emission data of enterprises to calculate pollution emission intensity indicators,and based on panel data of Chinese listed manufacturing enterprises,explores the impact of enterprise agglomeration on their pollution emission intensity.The results show that enterprise agglomeration can significantly reduce the intensity of enterprise pollution emissions through green knowledge spillover effects,green labor pool effects,and green intermediate goods sharing effects;This conclusion still holds true after using urban and enterprise level natural geographic data to construct instrumental variables for endogeneity analysis,considering extreme sample values,and replacing core variable estimates.Further analysis reveals that the digital transformation and domestic market advantages have further strengthened the pollution reduction effect of enterprise spatial agglomeration.The conclusion of this article has important policy implications for further optimizing the spatial layout of enterprises and achieving green and high-quality development of enterprises.关键词
企业集聚/集聚外部性/企业污染排放强度/上市制造业企业/绿色发展分类
管理科学引用本文复制引用
韩峰,乔一周,李陈华..企业级空间集聚与污染排放强度[J].南京工业大学学报（社会科学版）,2025,24(4):75-96,22.基金项目
国家自然科学基金面上项目"空间集聚优势与制造业高质量发展研究:理论机制、效应识别与政策优化"(72073071) （72073071）
国家社会科学基金重点项目"统筹发展和安全视角下'泛电商'平台秩序治理研究"(23AJY018) （23AJY018）
江苏高校"青蓝工程"中青年学术带头人资助项目(D202062045) （D202062045）
2023年江苏省研究生科研创新计划项目(KYCX23_2289) （KYCX23_2289）
