Climate Risk Disclosure and Corporate Financial Performance: Pathways to Sustainable Value Creation

As an integral component of environmental, social, and governance (ESG) reporting, climate risk disclosure (CRD) has received growing attention from firms, investors, and regulators. Using 4501 Chinese A-share listed firms over 2009–2024, this study examines the association between CRD and corporate financial performance using return on assets (ROA) and Tobin’s Q (TQ) as separate accounting- and market-based outcomes. We construct a firm-year CRD index from annual-report text and interpret it as a normalized measure of climate-related disclosure intensity. CRD is positively associated with both ROA and TQ, and the results remain robust across alternative disclosure construction, sample windows, future outcomes, high-dimensional fixed effects, and complementary endogeneity analyses. Pathway tests show that greater CRD is associated with lower financing costs and greater green innovation, both of which are associated with stronger financial outcomes. Institutional ownership and accounting information quality positively moderate the CRD–performance relationship. Heterogeneity analyses indicate stronger associations among non-state-owned and heavily polluting firms, while both physical and transition risk disclosure are positively associated with financial performance. Overall, the findings support a conditional value-relevance interpretation of climate risk disclosure.

Authors

Institutions

Publication Details

Journal
Sustainability
Published
2026-08-27
DOI
https://doi.org/10.3390/su18178790
Primary Topic
Corporate Social Responsibility Reporting
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Climate Risk Disclosure and Corporate Financial Performance: Pathways to Sustainable Value Creation

Ziyang Shuang, Yong Li
Sustainability
Corporate Social Responsibility Reporting
article

Climate Risk Disclosure and Corporate Financial Performance: Pathways to Sustainable Value Creation

Ziyang Shuang, Yong Li
article en

Abstract

As an integral component of environmental, social, and governance (ESG) reporting, climate risk disclosure (CRD) has received growing attention from firms, investors, and regulators. Using 4501 Chinese A-share listed firms over 2009–2024, this study examines the association between CRD and corporate financial performance using return on assets (ROA) and Tobin’s Q (TQ) as separate accounting- and market-based outcomes. We construct a firm-year CRD index from annual-report text and interpret it as a normalized measure of climate-related disclosure intensity. CRD is positively associated with both ROA and TQ, and the results remain robust across alternative disclosure construction, sample windows, future outcomes, high-dimensional fixed effects, and complementary endogeneity analyses. Pathway tests show that greater CRD is associated with lower financing costs and greater green innovation, both of which are associated with stronger financial outcomes. Institutional ownership and accounting information quality positively moderate the CRD–performance relationship. Heterogeneity analyses indicate stronger associations among non-state-owned and heavily polluting firms, while both physical and transition risk disclosure are positively associated with financial performance. Overall, the findings support a conditional value-relevance interpretation of climate risk disclosure.

SustainabilityVol. 18(17)
University of Science and Technology of China (CN)
Climate action
Openalex Percentile: Top 7%
Corporate Social Responsibility Reporting
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.