Climate bonds toward achieving net zero emissions and carbon neutrality:Evidence from machine learning technique

作     者：Hermas Abudu Presley K.Wesseh Jr. Boqiang Lin 

作者机构：College of Overseas EducationChengdu UniversityChengdu610106SichuanChina School of ManagementChina Institute for Studies in Energy PolicyCollaborative Innovation Center for Energy Economics and Energy PolicyXiamen UniversityFujian361005China Center for African Development Strategy(CFADS)MonroviaLiberia 

出 版 物：《Journal of Management Science and Engineering》 (管理科学学报（英文版）)

年 卷 期：2024年第9卷第1期

页      面：1-15页

核心收录：

学科分类：12[管理学] 02[经济学] 0202[经济学-应用经济学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 020204[经济学-金融学（含∶保险学）] 

基　　金：supported by the funding of Belt and Road Research Institute,Xiamen University(No:1500-X2101200) National Natural Science Foundation of China(Key Program,No:72133003) 

主　　题：Climate bonds funds utilization Climate bonds policy text mining Machine learning technique Net zero emissions Policy sentiment analysis 

摘      要：The Conference of the Parties(COP26 and 27)placed significant emphasis on climate financing policies with the objective of achieving net zero emissions and carbon ***,studies on the implementation of this policy proposition are *** address this gap in the literature,this study employs machine learning techniques,specifically natural language processing(NLP),to examine 77 climate bond(CB)policies from 32 countries within the context of climate *** findings indicate that“sustainabilityand“carbon emissions controlare the most outlined policy objectives in these CB ***,the study highlights that most CB funds are invested toward energy projects(i.e.,renewable,clean,and efficient initiatives).However,there has been a notable shift in the allocation of CB funds from climate-friendly energy projects to the construction sector between 2015 and *** shift raises concerns about the potential redirection of funds from climate-focused investments to the real estate industry,potentially leading to the greenwashing of climate ***,policy sentiment analysis revealed that a minority of policies hold skeptical views on climate change,which may negatively influence climate ***,the findings highlight that the effective implementation of CB policies depends on policy goals,objectives,and ***,this study contributes to the literature by employing NLP techniques to understand policy sentiments in climate financing.