Climate Change Disclosure Differentiation and Firm Financial Performance: A Deep Learning Approach

Abstract

With increasing attention to climate change, governments are mandating firms to disclose GHG emissions for better management. Firms’ climate change disclosure differentiation is becoming crucial to financial performance. We uses the Greenhouse Gas Reporting Program (GHGRP) as a natural experiment to examine the relationship between GHGRP and financial performance, mediated by the firm’s climate change disclosure differentiation and moderated by competitive intensity. Utilizing a novel deep-learning approach on over 180,000 earnings conference call transcripts from 2001-2023 in the US and Canada, we find that GHGRP positively influences both the climate change disclosure differentiation and financial performance. The differentiation mediates the relationship between GHGRP and financial performance. Interestingly, while the climate change disclosure differentiation can negatively affect financial performance, it exhibits a U-shaped relationship, turning positive beyond a certain level. Additionally, higher competitive intensity flattens the U-shaped curve, thereby weakening the positive impact of the climate change disclosure differentiation on financial performance. Finally, we offer several significant managerial insights for firms, policymakers, and investors.

Presenters

Shan Yang
Student, PhD, The Hong Kong Polytechnic University, Hong Kong

Details

Presentation Type

Paper Presentation in a Themed Session

Theme

2025 Special Focus—Sustainable Development for a Dynamic Planet: Lessons, Priorities, and Solutions

KEYWORDS

CLIMATE CHANGE DISCLOSURE DIFFERENTIATION,FIRM FINANCIAL PERFORMANCE,DEEP LEARNING,GHGRP