The ESG effect on the cost of debt financing: A sharp RD analysis |
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| Institution: | 1. Bocconi University, Finance Department, Via Röntgen, 1, Room C2/06, 20136 Milano MI, Italy;2. Bocconi University, Via Roberto Sarfatti, 25, 20100 Milano MI, Italy;1. Sasin School of Management, Chulalongkorn University, Bangkok, Thailand & UWA Business School, The University of Western Australia, Perth, Australia;2. NTNU Business School, Norwegian University of Science and Technology, Trondheim, Norway;3. Great Valley School of Graduate Professional Studies, Pennsylvania State University, United States;1. School of Economics, Qingdao University, Qingdao, Shandong, China;3. Excelia Business School, France;4. Suleman Dawood School of Business, Lahore University of Management Sciences, Lahore, Pakistan;1. School of Economics and Management, Southeast University;2. Institute of Economics and Finance, Nanjing Audit University;3. Chinese Academy of Finance and Development, Central University of Finance and Economics;1. Financial Technology Engineering and Technology Development Center, Guangdong University of Finance, No. 527, Yingfu Road, Tianhe District, Guangzhou City, Guangdong Province 510521, PR China;2. School of Economics & Management, Southeast University, Jiulong Lake Campus, Nanjing City, Jiangsu Province 211189, PR China |
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| Abstract: | Environmental, social, and governance (ESG) factors have become increasingly relevant within the financial world. Despite extensive evidence regarding the equity side, limited studies in the literature have investigated the potential effects of ESG performance on the main drivers of debt. This study aims to understand whether there is a positive effect from a cost of debt standpoint for corporations with relatively better ESG performance. Using the ESG score by Refinitiv and a sharp regression discontinuity design, we do not find statistically significant evidence for discrete jumps in correspondence with the ESG score average for the cost of debt of European nonfinancial corporates over the 2018–2020 period. In a sharp regression discontinuity setting, we obtain analogous results by developing a linear probability model. |
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