Climate Transition Risk Metrics: Understanding Convergence and Divergence across Firms and Providers.

131 Pages Posted: 16 Sep 2021

See all articles by Julia Anna Bingler

Julia Anna Bingler

ETH Zürich - CER-ETH - Center of Economic Research at ETH Zurich

Chiara Colesanti Senni

ETH Zürich

Pierre Monnin

Council on Economic Policies

Date Written: September 14, 2021

Abstract

Climate risks are now fully recognized as financial risks by asset managers, investors, central banks, and financial supervisors. Against this background, a rapidly growing number of market participants and financial authorities are exploring which metrics to use to capture climate risks, as well as to what extent the use of different metrics delivers heterogeneous results. To shed a light on these questions, we analyse a sample of 69 transition risk metrics delivered by 9 different climate transition risk providers and covering the 1,500 firms of the MSCI World index. Our findings show that convergence between metrics is significantly higher for the firms most exposed to transition risk. We also show that metrics with similar scenarios (i.e. horizon, temperature target and transition paths) tend to deliver more coherent risk assessments. Turning to the variables that might drive the outcome of the risk assessment, we find evidence that variables on metric’s assumptions and scenario’s characteristics are associated with changes in the estimated firms’ transition risk. Our findings bear important implications for policy making and research. First, climate transition risk metrics, if applied by the majority of financial market participants in their risk assessment, might translate into relatively coherent market pricing signals for least and most exposed firms. Second, it would help the correct interpretation of metrics in financial markets if supervisory authorities defined a joint baseline approach to ensure basic comparability of disclosed metrics, and asked for detailed assumption documentations alongside the metrics. Third, researchers should start to justify the use of the specific climate risk metrics and interpret their findings in the light of the metric assumptions.

Keywords: financial climate risks, corporate finance, climate risk metrics, climate transition risk, spearman’s rank correlation, hierarchical cluster analysis, Ward’s minimum variance criterion, Lasso regression analysis

JEL Classification: C83, D53, D81, G12, G32, Q54

Suggested Citation

Bingler, Julia Anna and Colesanti Senni, Chiara and Monnin, Pierre, Climate Transition Risk Metrics: Understanding Convergence and Divergence across Firms and Providers. (September 14, 2021). Available at SSRN: https://ssrn.com/abstract=3923330 or http://dx.doi.org/10.2139/ssrn.3923330

Julia Anna Bingler (Contact Author)

ETH Zürich - CER-ETH - Center of Economic Research at ETH Zurich ( email )

Zürichbergstrasse 18
Zurich, 8092
Switzerland

Chiara Colesanti Senni

ETH Zürich ( email )

Zürichbergstrasse 18
8092 Zurich, CH-1015
Switzerland
+41766062605 (Phone)

HOME PAGE: http://www.resec.ethz.ch/people/person-detail.html?persid=220754

Pierre Monnin

Council on Economic Policies ( email )

Zurich
Switzerland

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
95
Abstract Views
294
rank
351,164
PlumX Metrics