Too Much of a Good Thing? ESG Disclosure, the Social Dimension, and Future Stock Price Crash Risk Evidence of a Nonlinear Effect from an Emerging Market

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

🔬研究者:Provides evidence of a nonlinear ESG disclosure-crash risk relationship, urging future studies to consider dimension-specific and threshold effects.

🏢実務担当者:Suggests that excessive social disclosure beyond a moderate level may increase stock price crash risk, warranting a balanced approach to transparency.

🏛政策担当者:Highlights the need to consider the optimal level of disclosure in regulation, as more disclosure may not always reduce information asymmetry.

Whether environmental, social, and governance (ESG) disclosure stabilizes share prices or merely masks bad news, it remains unsettled, and the evidence is conspicuously weak whenever the relationship is assumed to be linear. This study revisits the question by allowing the effect of ESG disclosure on future stock price crash risk to be nonlinear and by breaking down disclosure into its environmental, social, and governance components. Using an unbalanced panel of non-financial firms listed on the Ho Chi Minh Stock Exchange over 2018–2024, we estimate firm and year fixed effects models with firm-clustered standard errors, measuring one-year-ahead crash risk by negative conditional skewness (NCSKEW) and down-to-up volatility (DUVOL). Consistent with prior work, the linear association between overall ESG disclosure and crash risk is statistically insignificant. Once a quadratic term is introduced, however, a U-shaped relationship emerges, and dimension-level tests show that this curvature is driven almost entirely by social disclosure: the linear term is negative and the squared term positive and significant for both crash risk proxies, with turning points of 0.3316 (NCSKEW) and 0.2918 (DUVOL). The U shape is confirmed by the formal test of Lind and Mehlum for both proxies, is robust to additional profitability and valuation controls and, most strongly for NCSKEW, to panel-corrected and feasible-GLS estimators. Low variance inflation factors confirm that multicollinearity does not affect the estimates. The findings support a “too-much-of-a-good-thing” interpretation: social disclosure improves transparency and reduces crash risk up to a moderate threshold, beyond which incremental, hard-to-verify narrative disclosure becomes consistent with impression management and heightens crash risk. Because the turning point lies below the first quartile of social disclosure, most sample firms already operate where additional disclosure raises crash risk. This study reframes the ESG crash risk debate around the level and dimension of disclosure rather than its mere quantity.

• openalex https://doi.org/10.3390/jrfm19070541first seen 2026-07-22 05:19:37