Unveiling how financial markets could intensify climate change risks

Juan Laborda, Cristina Suárez, Alejandro Fernández, Haoran Wang, Emilio Cerdá, Liana Ricci and Sonia Quiroga

Ecological Economics, 2026, vol. 239, issue C

Abstract: This paper proposes a sustainable finance-based methodology to assess climate change vulnerability in Spain's key economic sectors. It pioneers a panel database merging biophysical, economic, and financial data, analysing private sales responses to climate change. Employing the RCP4.5 scenario, aligned with the EU's 2030 climate policy, it forecasts 10-year financial and economic variables via autoregressive neural networks, emphasizing confidence intervals across scenarios. The obtained results highlight the complexity of climate impacts on business revenues, the importance of considering both climate and financial variables, and the need for business adaptation and resilience in the face of climate change.

Keywords: Climate change; Business resilience; Sustainable finance; Panel data; Autoregressive neural networks (search for similar items in EconPapers)
JEL-codes: C33 C45 G17 Q01 Q54 (search for similar items in EconPapers)
Date: 2026
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0921800925002563
Full text for ScienceDirect subscribers only

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:eee:ecolec:v:239:y:2026:i:c:s0921800925002563

DOI: 10.1016/j.ecolecon.2025.108773

Access Statistics for this article

Ecological Economics is currently edited by C. J. Cleveland

More articles in Ecological Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().