Socially responsible investing, also known as ESG investing, is a recent trend in the world of portfolio management. More and more investors have started to look into the Environmental, Social, and Governance scores of the companies they invest in. However, one major problem with ESG scoring is that there is not one universal scoring system. Many companies sell ESG data, but the scores are not comparable, and additionally, the ESG data providers are not very transparent about how they create the ratings. These problems with ESG data mean we need to have a method to grade and merge the information from multiple providers.
The authors of this research paper analyze the various scoring systems and the attributes that can explain the movement in ESG ratings. Ultimately, the authors aim to find the most relevant elements of ESG ratings for the firms from each sector. The paper focuses on the ordered probit model proposed in Hausman, Lo, and Machkinlay (1992), because of the discrete nature of the data. Firstly, they examine the credibility of every sector individually. Then, after accounting for each sector’s credibility, they apply the probit transformation to combine the data from all providers. Lastly, they explore multiple ways of weighting the information from various providers to end up with the most reliable ESG score.
Author: Invest Verte
Title: InvestVerte Framework
“This paper explores how to merge statistically the information from different providers and explores a larger source of attributes that can explain the movement in ESG ratings. the aim is to have an in-house and transparent scorecard and to find the most relevant attributes for ESG ratings for the firms belonging to a certain sector.”
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