Assessment of TCFD Voluntary Disclosure Compliance in the Spanish Energy Sector: A Text Mining Approach to Climate Change Financial Disclosures

Matías Domínguez-Quiñones (), Iñaki Aliende and Lorenzo Escot
Additional contact information
Matías Domínguez-Quiñones: Faculty of Statistical Studies, Complutense University of Madrid (UCM), 28040 Madrid, Spain
Iñaki Aliende: Faculty of Economics and Business, Somosaguas Campus, Complutense University of Madrid (UCM), 28224 Madrid, Spain

World, 2025, vol. 6, issue 3, 1-0

Abstract: This study investigates voluntary compliance with the Task Force on Climate-Related Financial Disclosures (TCFD) framework in 64 financial, Environmental, Social, and Governance (ESG) reports from six Spanish IBEX-35 energy firms (2020–2023) and explores the implications for intangible assets and corporate reputation, employing empirical quantitative text mining and Natural Language Processing (NLP) in Python. A validated scale-based taxonomy within the TCFD framework applies query-driven rules to extract relevant text. This enables an evaluation of aspects of the reports, facilitating the development of a compliance index measuring each company’s adherence to TCFD recommendations. All companies showed year-on-year improvements (2023 was the most comprehensive), yet none fully adhered due to information gaps. Disparities in the disclosures of Scope 1,2 and 3, persisted, suggesting reputational risks. A replicable methodological model generating a compliance index that assesses the ‘being’ (‘true performance’) versus ‘seeming’ (‘external perception’) dichotomy within sustainability reports and acts as a potential reputational barometer for stakeholders. By providing unprecedented evidence of TCFD reporting in the Spanish energy sector, this study closes a significant academic gap. Future research may analyze ESG reports using AI agents, study the impact of ESG on energy-intensive companies from AI data centers, supporting services like Copilot, ChatGPT, Claude, Gemini, and extend this methodology to other industrial sectors.

Keywords: climate change; energy sector; ESG reporting; data science; corporate reputation; intangibles; TCFD; text mining (search for similar items in EconPapers)
JEL-codes: G15 G17 G18 L21 L22 L25 L26 Q42 Q43 Q47 Q48 R51 R52 R58 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2673-4060/6/3/92/pdf (application/pdf)
https://www.mdpi.com/2673-4060/6/3/92/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jworld:v:6:y:2025:i:3:p:92-:d:1692352

Access Statistics for this article

World is currently edited by Ms. Cassie Hu

More articles in World from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().