Impact of environmental, social and governance (ESG) on foreign institutional investments in India: a machine learning perspective

Barnali Chaklader, Garima Chaklader, S. Shrivastav
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Abstract

PurposeThis study thoroughly examines the relationship between environmental, social and governance (ESG) scores and their subcategories with the investment decisions made by foreign institutional investors (FII). These subcategories include resource use, emission reduction and innovation under the environmental pillar, workforce, human rights, community and product responsibility under the social pillar and management, shareholders and CSR strategy under the governance pillar.Design/methodology/approachA machine learning technique known as “topic modeling” is used to analyse the current literature on ESG. To investigate the correlation between ESG scores and their subcategories with the investment decisions made by FII and to address concerns regarding multicollinearity and overfitting, a penalty-based regression model is employed.FindingsThe findings indicate that FIIs invest in firms with higher emission reduction and innovation scores under the environmental indicator. Additionally, firms with high human rights, community and product responsibility scores under the social indicator category have a positive relationship with FII investors. All subcategories of governance indicators, such as corporate social responsibility (CSR), strategy, shareholders and management scores, also positively impact FII investment. Of the three indicators, i.e. ESG, non-promoter FIIs give maximum weightage to governance indicators.Research limitations/implicationsSince ESG is a contemporary topic, the findings on the relationship between different categories of ESG on FII investment will support managers in their FII investment. Also, the study will help the government frame policy decisions on ESG.Originality/valuePrevious studies have explored the impact of the overall ESG indicators on FII investments, but they have not specifically studied the influence of sub-indicators within these categories on investment decisions. By addressing this gap, the study enhances stakeholder theory by identifying and prioritizing the various subcategories of ESG indicators that impact FII investment decisions.
环境、社会和治理 (ESG) 对印度外国机构投资的影响:机器学习视角
目的 本研究深入探讨了环境、社会和治理(ESG)评分及其子类别与外国机构投资者(FII)投资决策之间的关系。这些子类别包括环境支柱下的资源利用、减排和创新,社会支柱下的劳动力、人权、社区和产品责任,以及治理支柱下的管理、股东和企业社会责任战略。为了研究 ESG 分数及其子类别与 FII 投资决策之间的相关性,并解决有关多重共线性和过度拟合的问题,采用了基于惩罚的回归模型。研究结果研究结果表明,FII 投资于环境指标下减排和创新得分较高的公司。此外,在社会指标类别下,人权、社区和产品责任得分高的公司与外国投资机构投资者有积极的关系。治理指标的所有子类,如企业社会责任(CSR)、战略、股东和管理得分,也都对 FII 投资产生积极影响。在 ESG 这三项指标中,非倡导型 FII 对治理指标的权重最大。研究局限/意义由于 ESG 是一个当代话题,关于 ESG 不同类别与 FII 投资之间关系的研究结果将为管理者的 FII 投资提供支持。原创性/价值以往的研究探讨了总体 ESG 指标对 FII 投资的影响,但没有专门研究这些类别中的子指标对投资决策的影响。针对这一空白,本研究通过识别影响外国投资机构投资决策的各类环境、社会和公司治理指标并确定其优先次序,加强了利益相关者理论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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