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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/150176


    Title: 企業ESG評分對融資成本之影響分析
    Analyzing the Impacts of Corporate ESG Scores on Financing Costs
    Authors: 何坤霖
    Ho, Kun-Lin
    Contributors: 鄭宗記
    羅光達
    Cheng, Tsung-Chi
    Lo, Kuang-Ta
    何坤霖
    Ho, Kun-Lin
    Keywords: 企業ESG評分
    融資成本
    貸款利差
    線性混合效果模型
    分位數迴歸模型
    Corporate ESG scores
    Financing costs
    Loan spreads
    Linear Mixed-Effect Model (LME)
    Quantile Regression Model
    Date: 2024
    Issue Date: 2024-03-01 13:45:34 (UTC+8)
    Abstract: 隨ESG已蔚為金融市場的顯學，金融機構作為金融中介者亦透過其影響力引導資金投入永續發展議題。本研究探討企業在ESG議題上的表現如何影響融資成本，以北美企業為研究對象，使用S&P Global ESG Scores衡量企業ESG表現，並採用Refinitiv Loan Connector的Dealscan資料庫所揭露之北美地區聯貸案件資料，搭配Compustat資料庫之企業財務資料，分析企業ESG評分越佳是否可以得到較低的貸款利差，以及E、S、G這三項構面是否具有不同的影響力。
    參考過往文獻，此類議題大多採用線性廻歸模型中的最小平方法(Ordinary Least Squares，OLS)分析，然而本研究資料具有長期重覆觀測及階層結構資料的特性。為了有更準確的參數估計，本研究使用線性混合效果模型(Linear Mixed-Effect Model，LME)分析；同時為了解企業ESG評分在不同貸款利差區間內的影響，另採用分位數迴歸模型(Quantile Regression)分析。
    實證結果發現企業ESG評分確實與貸款利差呈現顯著負相關，且E、S、G三項構面對貸款利差影響不同，且在不同的貸款利差分位數區間內亦有不同程度的影響。
    With ESG (Environmental, Social, and Governance) becoming a prominent factor in the financial market., financial intermediaries have also leveraged their influence to direct funds towards sustainable development initiatives. This study investigates how corporate performance on ESG issues influences financing costs, focusing on North American companies. S&P Global ESG Scores are utilized to assess corporate ESG performance, data from the Refinitiv Loan Connector's Dealscan database, reveals syndicated loan information in the North American region, and the Compustat database contributes corporate financial data. The analysis aims to determine whether companies with higher ESG scores can secure loans at lower interest rates and whether the three dimensions of ESG have distinct impacts.
    Drawing from previous literature, most studies on similar topics commonly employ the Ordinary Least Squares (OLS) method within linear regression models. However, this study's data possesses characteristics of long-term repeated observations and hierarchical structure. To achieve more accurate parameter estimates, this research utilizes the Linear Mixed-Effect Model (LME) for analysis. Additionally, to comprehend the impact of corporate ESG scores across different loan spread intervals, Quantile Regression models are employed.
    Empirical results reveal a significant negative correlation between corporate ESG scores and loan spreads. Furthermore, the three dimensions of ESG exert varying influences on loan spreads. The study also finds that these effects vary across different quantile intervals of loan spreads.
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    Description: 碩士
    國立政治大學
    國際金融碩士學位學程
    111ZB1016
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0111ZB1016
    Data Type: thesis
    Appears in Collections:[Master’s Program in Global Banking and Finance] Theses

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