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The value of ESG in emerging markets: Evidence from Indonesia, Malaysia, and Singapore

新興市場におけるESGの価値:インドネシア、マレーシア、シンガポールからのエビデンス (AI 翻訳)

Yatmoko Baroto, Igka Ulupui, E. Gurendrawati

International Journal of Management and Sustainability📚 査読済 / ジャーナル2026-01-16#ESG対象セクター: cross_sector
DOI: 10.18488/11.v15i1.4713
原典: https://archive.conscientiabeam.com/index.php/11/article/download/4713/9001
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🤖 gxceed AI 要約

日本語

インドネシア、マレーシア、シンガポールの上場企業1420社(2012-2023)のパネルデータを用い、First-Difference GMMとSystem GMMによりESGスコアとROEの因果関係を推定。主な結果はESGがROEに正の影響を与え、企業規模の調整効果は有意でないことを示した。ESGの利益効果が企業規模に依存しないという新興市場からの証拠を提供。

English

Using a panel of 1,420 listed firms from Indonesia, Malaysia, and Singapore (2012-2023), this study employs FD-GMM and SYS-GMM to establish causality. It finds a positive ESG-ROE relationship and, counterintuitively, that firm size does not moderate this link, suggesting ESG benefits all firms regardless of scale in emerging markets.

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

📝 gxceed 編集解説 — Why this matters

日本のGX文脈において

東南アジアでのESGと収益性の因果関係を実証した点で、日本企業の同地域進出や日系中小企業のESG投資判断に示唆を与える。ただし、SSBJやTCFD等の気候開示に特化した議論ではない。

In the global GX context

This paper provides causal evidence from a region underrepresented in ESG-finance literature, supporting the universal value of ESG for profitability. For global audiences, it challenges the assumption that only large firms benefit financially from ESG, informing investors and policymakers in emerging markets.

👥 読者別の含意

🔬研究者:Provides rigorous causal estimation (GMM) and a counterintuitive finding on the non-moderating role of firm size in the ESG-profitability link.

🏢実務担当者:Demonstrates that ESG investments can improve profitability for firms of any size in emerging markets, strengthening internal business cases for sustainability.

🏛政策担当者:Offers evidence that ESG mandates can benefit all firms, not just large ones, in emerging economies, supporting inclusive policy design.

📄 Abstract(原文)

This study addresses a critical gap in the corporate finance literature by empirically investigating the causal link between Environmental, Social, and Governance (ESG) performance and firm profitability, as measured by Return on Equity (ROE), within the heterogeneous economies of Indonesia, Malaysia, and Singapore. Going beyond simple correlation, we advance the discourse by examining a theoretically salient moderating variable: firm size, a relationship that has received limited attention, particularly in the under-researched Southeast Asian context. Utilizing a comprehensive panel dataset of 1,420 publicly listed companies from 2012 to 2023, we employ sophisticated econometric methodologies, including First-Difference GMM (FD-GMM) and System GMM (SYS-GMM), to mitigate endogeneity and dynamic panel bias. Our main findings, derived from the robust SYS-GMM model, reveal a positive and statistically significant effect of ESG scores on ROE across all three countries, providing strong empirical support for the "doing well by doing good" hypothesis. Crucially, our analysis yields a novel and counterintuitive finding: the moderating effect of firm size on the ESG-ROE relationship is statistically insignificant. This result challenges the prevailing notion that only larger, resource-rich firms can effectively translate ESG investments into financial gains. It suggests that the positive financial spillovers of ESG practices are universal and not contingent on a firm's scale. The consistency of these findings was validated through a series of robustness checks. This research makes three key contributions: (1) it provides rigorous, methodologically advanced evidence from a globally underrepresented region; (2) it introduces new empirical insights on the non-conditional nature of the ESG-profitability nexus; and (3) it offers valuable implications for investors and policymakers, demonstrating that ESG can be a universal value driver, thereby strengthening the case for integrated sustainability strategies across diverse corporate landscapes.

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gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。