Modified sectoral average greenhouse gas intensity for more accurate carbon risk analysis

Renato Ritter ()
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Renato Ritter: Hungarian National Bank, Budapest, Hungary

Cognitive Sustainability, 2023, vol. 2, issue 4, 20-29

Abstract: Thanks to the existing data gaps, Monitoring climate-related financial risks is no easy task. Greenhouse gases play an important role in climate change; therefore, examining economic activities’ emissions can be a suitable way to analyse climate risks. However, relying only on activities’ average greenhouse gas emissions can be misleading, as substantial emitters can greatly divert the average values upwards. Modifying these sectoral average emissions by subtracting substantial emitters’ data results in a clearer picture of climate risk analysis. The modified sectoral average method, which primarily relies on data from the emission trading systems, treats companies under the EU Emissions Trading System (ETS) regulation separately. With this treatment, sectors with high emission values can experience a significant drop in sectoral average emission intensity compared to companies under ETS regulation. To use an already available but not applied data cluster is an affordable, easy-to-implement way to increase the accuracy of climate risk indicators. Results in Hungary show that implementing this information reduces sectoral average intensity for companies not under ETS regulation.

Keywords: transition risk; sectoral exposure; greenhouse gas; intensity (search for similar items in EconPapers)
JEL-codes: D81 G32 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.55343/CogSust.74

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