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ESG quality, price volatility, and market governance: disentangling the information distortion and risk-reduction channels in UK equity markets
Journal article   Open access

ESG quality, price volatility, and market governance: disentangling the information distortion and risk-reduction channels in UK equity markets

Yiu-Fai Chan, Lawrence M. Ngoe, William Tannor, Shailendra Baghel, Charles Nzeh and Giamene Odom
Scientific Culture, Vol.12(4), pp.11232-11245
01/06/2026

Abstract

This paper shows that environmental and social (ES) quality affects stock price volatility through two opposing channels whose dominance depends systematically on externality salience. The market-governance channel of Chen, Gupta, and Starmans (2026, Journal of Financial Economics) predicts that ESG investor trading distortions reduce price informativeness, generating a positive ES quality–volatility association for negative externality firms under high externality salience. The competing risk-reduction channel predicts a negative association through operational risk mitigation. A formal comparative statics analysis of the dual-channel model shows that ∂Volatility/∂ES_Quality = β₁+ β₃×Salience, where β₁< 0 reflects risk-reduction dominance at baseline and β₃> 0 captures salience amplification of the CGS mechanism. We test this prediction using a panel of 140 firm-year observations across 20 FTSE-listed firms (2018–2024). A COVID-19 difference-in-differences design provides evidence consistent with salience-driven between-group effects: the cross-group volatility differential expands by 4.8 percentage points during the pandemic period (p < 0.05), with partial post-COVID persistence. The mechanism test—an ES quality × salience interaction for negative externality firms—yields a positive coefficient (β₃= +0.0019, p < 0.10) consistent with CGS channel strengthening under elevated salience, representing a 61% attenuation of the baseline risk-reduction slope (−0.0031 to −0.0012). This interaction result is robust across three alternative salience proxies (COVID binary, Google Trends ESG search intensity, sector ESG ETF trading volume), each capturing a distinct dimension of investor attention. We characterise our findings as patterns consistent with salience-amplified trading distortions under maintained assumptions, rather than causal identification, and specify the research design—annual panel ESG data, active ESG fund ownership, and the UK TCFD quasi-experiment—required for causal channel separation.
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Published (Version of record) Open Access Open CC BY V4.0  — This license enables reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator.

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