English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 113656/144643 (79%)
Visitors : 51709812      Online Users : 270
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    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.
    Reference: 1. Atella, V., Pace , N., & Vuri , daniela. (2008). Are Employers Discriminating with Respect to Weight?: European Evidence Using Quantile Regression. Economics & Human Biology, 6(3), 305–329.
    2. Bae, S. C., Chang, K., & Yi, H. (2017). Corporate Social Responsibility, Credit Rating, and Private Debt Contracting: New Evidence from Syndicated Loan Market. Available at SSRN: https://ssrn.com/abstract=2939853
    3. Bénabou, R., & Tirole, J. (2005). Incentives and Prosocial Behavior. IZA Discussion Paper No. 1695; Princeton Economics Discussion Paper, No. 230, Available at SSRN: https://Ssrn.Com/Abstract=639043
    4. Chava, S., & Roberts, M. R. (2008). How Does Financing Impact Investment? The Role of Debt Covenants. The Journal of Finance, 63(5), 2085–2121.
    5. Cheng, I., Hong, H. G., & Shue, K. (2023). Do Managers Do Good with Other Peoples’ Money? Chicago Booth Research Paper, No. 12-47, Available at SSRN: https://ssrn.com/abstract=1962120
    6. Cooper, E. W., & Uzun, H. (2015). Corporate Social Responsibility and the Cost of Debt. Journal of Accounting and Finance, 15(8), 11–29.
    7. Dallal, R. M., Quebbemann, B., Hunt, L., & Braitman, L. E. (2009). Analysis of Weight Loss After Bariatric Surgery Using Mixed-Effects Linear Modeling. Obesity Surgery, 19(6), 732–7.
    8. Dennis, S., Nandy, D., & Sharpe, L. G. (2000). The Determinants of Contract Terms in Bank Revolving Credit Agreements. Journal of Financial and Quantitative Analysis, 35(1), 87–110.
    9. Drago, D., & Carnevale, C. (2020). Do CSR Ratings Affect Loan Spreads? Evidence from European Syndicated Loan Market. Sustainability, 12(18), 7639.59
    10. Edmans, A. (2011). Does the Stock Market Fully Value Intangibles? Employee Satisfaction and Equity Prices. Journal of Financial Economics, 101(3), 621–640.
    11. El Ghoul, S., Guedhami, O., Kwok, C. C. y., & Mishra, D. R. (2011). Does Corporate Social Responsibility Affect the Cost of Capital? Journal of Banking & Finance, 35(9), 2388–2406.
    12. Fatemi, A., Glaum, M., & Kaiser, S. (2018). ESG Performance and Firm Value: The Moderating Role of Disclosure. Global Finance Journal, 38, 45–64.
    13. Ferrell, A., Hao, L., & Renneboog, L. (2016). Socially Responsible Firms. Journal of Financial Economics, 122(3), 585–606.
    14. Goss, A., & Roberts, G. S. (2011). The Impact of Corporate Social Responsibility on the Cost of Bank Loans. Journal of Banking & Finance, 35(7), 1794–1810.
    15. Harjoto, M., Laksmana, I., & Lee, R. (2015). Board Diversity and Corporate Social Responsibility. Journal of Business Ethics, 132(4), 641–660.
    16. Koenker, R., & Bassett, G. (1978). Regression Quantiles. Econometrica, 46(1), 33–50.
    17. Laird, N., M., & Ware, J., H., (1982) Random-Effects Models for Longitudinal Data. Biometrics, 38, 963-974.
    18. Luger, T. M., Suls, J., & Vander Weg, M. W. (2014). How Robust Is the Association between Smoking and Depression in Adults? A Meta-Analysis Using Linear Mixed-Effects Models. Addictive Behaviors, 39(10), 1418–1429.
    19. Magnanelli, B. S., & Izzo, M. F. (2017). Corporate Social Performance and Cost of Debt: The Relationship. Social Responsibility Journal, 13(2), 250–265.
    20. Masulis, R. W., & Reza, S. W. (2014). Agency Problems of Corporate Philanthropy. Review of Financial Studies, Forthcoming, ECGI - Finance Working Paper, No. 370, Available at SSRN: https://ssrn.com/abstract=2234221.60
    21. Michaels, A., & Grüning, M. (2017). Relationship of Corporate Social Responsibility Disclosure on Information Asymmetry and the Cost of Capital. Journal of Management Control, 28, 251–274.
    22. Nelling, E., & Webb, E. (2008). Corporate Social Responsibility and Financial Performance: The “Virtuous Circle” Revisited. Review of Quantitative Finance and Accounting, 32, 197-209.
    23. Oikonomou, I., Brooks, C., & Pavelin, S. (2012). The Impact of Corporate Social Performance on Financial Risk and Utility: A Longitudinal Analysis. Financial Management, 41(2), 483–515.
    24. Oikonomou, I., Brooks, C., & Pavelin, S. (2014). The Effects of Corporate Social Performance on the Cost of Corporate Debt and Credit Ratings. The Financial Review, 49(1), 49–75.
    25. Pastor, L., Stambaugh, R. F., & Taylor, L. A. (2020). Sustainable Investing in Equilibrium. Chicago Booth Research Paper, No. 20-12, Available at SSRN: https://ssrn.com/abstract=3498354.
    26. Pedersen, L. H., Fitzgibbons, S., & Pomorski, L. (2021). Responsible Investing: The ESG-Efficient Frontier. Journal of Financial Economics, 142(2), 572–597.
    27. Sassen, R., Hinze, A., & Hardeck , I. (2016). Impact of ESG Factors on Firm Risk in Europe. Journal of Business Economics, 86, 867–904.
    28. Sharfman, M. P., & Fernando, C. S. (2008). Environmental Risk Management and the Cost of Capital. Strategic Management Journal, 29(6), 569–592.
    29. Sun, W., & Cui, K. (2014). Linking Corporate Social Responsibility to Firm Default Risk. European Management Journal, 32(2), 275–287.
    30. Van binsbergen, J. H., Graham, J. R., & Yang, J. (2010). The Cost of Debt. The Journal of Finance, 65(6), 2089–2136.61
    31. Zietz, J., Zietz, E., & Sirmans, G. (2008). Determinants of House Prices: A Quantile Regression Approach. The Journal of Real Estate Finance and Economics, 37(4), 317–333.
    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:[國際金融碩士學位學程] 學位論文

    Files in This Item:

    File Description SizeFormat
    101601.pdf2638KbAdobe PDF0View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,惟仍請適度,合理使用本網站之內容,以尊重著作權人之權益。商業上之利用,則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作,已盡力防止侵害著作權人之權益,如仍發現本網站之數位內容有侵害著作權人權益情事者,請權利人通知本網站維護人員(nccur@nccu.edu.tw),維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback