No. 51 - Environmental data and scores: lost in translation
This paper addresses the methodological issues and limited coverage of environmental scores, which are widely used by financial institutions and policymakers. Its contribution is twofold. First, regression analysis highlights significant deviations among the environmental scores of seven providers compared to the granular data published by companies, despite some environmental indicators play a significant role in the scores of multiple providers. The residual component of the regression analysis varies across providers, presumably because some pay more attention to the environmental impact itself, while others place greater emphasis on the related financial risks. Second, we propose a classification system based on granular data, which can also be applied to assess unrated companies and to implement investment strategies, such as best-in-class and exclusion. The resulting portfolios have similar environmental and financial profiles to those based on providers' scores. The paper underscores the importance of improving corporate disclosure on granular data and transparency on providers' methodologies to foster sustainable finance development.
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18 October 2024