Quantifying Causality between Climate Change and Credit Risk: A Bibliometric Study and Research Agenda

Noluthando Mngadi () and Hossana Twinomurinzi
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Noluthando Mngadi: Centre of Applied Data Science, University of Johannesburg, Johannesburg 2006, South Africa
Hossana Twinomurinzi: Centre of Applied Data Science, University of Johannesburg, Johannesburg 2006, South Africa

Sustainability, 2023, vol. 15, issue 12, 1-15

Abstract: There is increasing pressure on organisations and countries to manage the financial risks associated with climate change. This paper summarises research on climate change, credit risk and the associated losses, and specifically identifies methods that could contribute to quantifying the causal relationships between climate change and credit risk. We conducted a bibliometric analysis using the Web of Science database to analyse 3138 documents that investigated climate change and credit risk. The key results reveal that climate change has a quantifiable effect on credit risk, and that the most affected industries or sectors are energy, transportation/mobility, agriculture and food, manufacturing, and construction. The prominent methods to quantify causal relationships between climate change and credit risk are regression models, but these are mostly used in preliminary and testing stages. Distance to default and credit risk are the main areas of focus when quantifying climate change and credit risk. Banks are the main type of organisation that have sought to quantify the causal relationship. We identify a research agenda to quantify these causal relationships.

Keywords: credit risk; climate risk; climate change; modelling; quantification; default; probability; bibliometrics (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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