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  • 标题:Developing Novel Technique for Investigating Guidelines and Frameworks: A Text Mining Comparison between International and Japanese Green Bonds
  • 本地全文:下载
  • 作者:Kentaka Aruga ; Md. Monirul Islam ; Yoshihiro Zenno
  • 期刊名称:Journal of Risk and Financial Management
  • 印刷版ISSN:1911-8074
  • 出版年度:2022
  • 卷号:15
  • 期号:9
  • 页码:1-17
  • DOI:10.3390/jrfm15090382
  • 语种:English
  • 出版社:MDPI, Open Access Journal
  • 摘要:In most cases, the official documents related to guidelines and frameworks are complicated, long, and hard to understand for general readers, regardless of whether the government and financial companies follow international standards or not. In this context, the current study examines how the green bond (GB) guidelines created by the Japanese government are aligned with the Green Bond Principles (GBP) and Climate Bonds Standard (CBS) through a text mining technique. It also investigates whether the GB frameworks for the Japanese public and private companies follow the GB guidelines of the Japanese government. While the CBS is the guideline that focuses on climate bonds, the GBP specializes in GB whose scope is broader. The word frequency and word cloud analyses identify that the documents created by the Japanese government and companies have more similarities with the GBP, indicating that the Japanese GB guidelines and frameworks are more aligned with the GBP than the CBS. A pairwise word network matrix analysis also reveals that the Japanese GB guidelines and frameworks are more focused on broader environmental issues and sustainability than the CBS, which had more similarities with the GBP than the CBS.
  • 关键词:text mining;word cloud;network matrix;green bond;Japan
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