Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/246853 
Year of Publication: 
2021
Series/Report no.: 
Economics Working Paper Series No. 21/363
Publisher: 
ETH Zurich, CER-ETH - Center of Economic Research, Zurich
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.
Subjects: 
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: 
C83
D53
D81
G12
G32
Q54
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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