Does corruption control enhance ESG-induced firm value? Insights from machine learning analysis

IF 7.4 2区经济学 Q1 BUSINESS, FINANCE

Finance Research Letters Pub Date : 2025-02-01 DOI:10.1016/j.frl.2024.106572

Mahfuja Malik , Khawaja Mamun , Syed Muhammad Ishraque Osman

引用次数: 0

Abstract

This study adopts advanced causal machine learning (ML) techniques to investigate the impact of country-level corruption on the market valuation of firms’ environmental, social, and governance (ESG) performance. By employing double-debiased machine learning (DML) and linear regression analysis, we find that ESG performance positively influences firm value. This positive relationship is more pronounced for firms operating in countries with lower levels of corruption. The use of DML enhances effect identification and yields findings that closely align with those derived from linear regression, thereby providing robust support for the pivotal role of corruption control in enhancing ESG-induced firm value.

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控制腐败是否能提升esg诱导的公司价值？来自机器学习分析的见解

本研究采用先进的因果机器学习（ML）技术来调查国家层面的腐败对企业环境、社会和治理（ESG）绩效的市场估值的影响。通过双去偏机器学习（DML）和线性回归分析，我们发现ESG绩效对企业价值有正向影响。在腐败程度较低的国家经营的公司，这种正相关关系更为明显。DML的使用增强了效果识别，并产生了与线性回归结果密切一致的结果，从而为腐败控制在提高esg诱导的公司价值方面的关键作用提供了强有力的支持。

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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来源期刊

Finance Research Letters BUSINESS, FINANCE-

CiteScore

11.10

自引率

14.40%

发文量

863

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