发电技术 ›› 2024, Vol. 45 ›› Issue (6): 1121-1134.DOI: 10.12096/j.2096-4528.pgt.23077

• 碳中和 • 上一篇    

发电上市公司低碳信息披露与低碳转型效率研究

赵长红1,2, 张李琳1, 邵云姝3, 袁家海1,2, 邓祎璐1   

  1. 1.华北电力大学经济与管理学院,北京市 昌平区 102206
    2.新能源电力与低碳发展研究北京市重点实验室(华北电力大学),北京市 昌平区 102206
    3.韩国高丽大学经济学院,韩国 首尔 02841
  • 收稿日期:2023-12-17 修回日期:2024-03-12 出版日期:2024-12-31 发布日期:2024-12-30
  • 作者简介:赵长红(1971),男,硕士,副教授,研究方向为企业管理,zchh21@126.com
    张李琳(1997),女,硕士研究生,研究方向为企业管理、能源转型,120212206084@ncepu.edu.cn
    邵云姝(1996),女,博士研究生,研究方向为生态经济、电力市场、碳交易、绿色能源等;
    袁家海(1979),男,博士,教授,研究方向为资源环境经济、电力经济规划与转型等,yuanjh126@126.com
    邓祎璐(1994),女,博士,讲师,研究方向为会计与资本市场、公司财务与公司治理、证券监管,dengyilu@ncepu.edu.cn
  • 基金资助:
    国家自然科学基金面上项目(72173043);教育部哲学社会科学研究后期资助项目(22JHQ096)

Research on Low Carbon Information Disclosure and Low Carbon Transition Efficiency of Listed Power Generation Companies

Changhong ZHAO1,2, Lilin ZHANG1, Yunshu SHAO3, Jiahai YUAN1,2, Yilu DENG1   

  1. 1.School of Economics and Management, North China Electric Power University, Changping District, Beijing 102206, China
    2.Beijing Key Laboratory of New Energy and Low-Carbon Development (North China Electric Power University), Changping District, Beijing 102206, China
    3.Department of Economics, Korea University, Seoul 02841, South Korea
  • Received:2023-12-17 Revised:2024-03-12 Published:2024-12-31 Online:2024-12-30
  • Supported by:
    Project Supported byFoundation: National Natural Science Foundation of China(72173043);Post-stage Funding Project for Philosophy and Social Sciences Research by the Ministry of Education of China(22JHQ096)

摘要:

目的 “双碳”目标提出后,电力行业加快推进低碳转型,发电企业纷纷将低碳转型纳入企业发展规划与战略当中。为探讨低碳转型目标承诺与执行成效的一致性,挖掘低碳转型效率的重要影响因素,研究了文本信息与低碳转型效率之间的内在联系。 方法 以2016—2022年31家发电上市公司作为研究对象,采用文本分析技术构建了低碳转型文本信息披露水平的衡量指标,利用双向固定效应的面板回归模型对低碳转型文本信息披露与低碳转型效率的关系进行了实证检验。 结果 发电上市公司低碳转型文本信息披露水平越高,碳排放强度越低,环境绩效表现越良好,即转型效率越高,公司的“言”“行”更加一致。此外,在会计信息披露质量较高、火电装机占比较低的公司中,低碳转型文本信息披露水平对低碳转型效率的影响效果与作用更加显著。 结论 发电上市公司应当提高低碳转型文本信息披露质量,发挥年报文本信息的监督管理作用,以推动低碳转型的发展,落实文本信息披露与转型效率的“言”“行”一致。

关键词: 双碳, 电力行业, 低碳转型, 效率, 信息披露, 火电, 发电上市公司, 文本分析

Abstract:

Objectives After the “dual-carbon” goal was put forward, the electric power industry has accelerated the low-carbon transition, and power generation enterprises have incorporated low-carbon transition into their corporate development plans and strategies. In order to explore the consistency between low-carbon transformation goal commitments and implementation results, important factors influencing low-carbon transformation efficiency were explored, and the intrinsic connection between textual information and low-carbon transformation efficiency was studied. Methods This paper took 31 listed power generation companies as the research object from 2016 to 2022, and adopted the text analysis technique to construct a measurement index of the level of textual disclosure of low-carbon transition, and empirically examined the relationship between textual disclosure and the efficiency of low-carbon transition by using the panel regression model with bidirectional fixed effects. Results The higher the level of textual information disclosure of low-carbon transition of listed power generation companies is, the lower the carbon emission intensity is, the better the environmental performance is, i.e., the higher the efficiency of the transition is, and the more consistent the company’s “words” and “actions” are. In addition, in companies with higher quality of accounting information disclosure and lower thermal power installed capacity, the effect of the disclosure level of low-carbon transition text on low-carbon transition efficiency is more significant. Conclusions The listed power generation companies should improve the quality of textual information disclosure of low-carbon transition, and play the role of supervision and management of annual report textual information to promote the development of low-carbon transition, and realize the consistency between textual information disclosure and transition efficiency.

Key words: dual-carbon, electric power industry, low carbon transition, efficiency, information disclosure, thermal power, listed power generation companies, textual analysis

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