Ratings of ESG
This lecture is based on the article: Berg, F., Koelbel, J. F., & Rigobon, R. (2022). Aggregate confusion: The divergence of ESG ratings. Review of Finance, 26(6), 1315-1344.
As mentioned in previous versions, there are two types of scores:
And there are many data providers: Sustainalytics, S&P Global, Moody’s, KLD, Refinitiv, MSCI.
Considerable evidence suggests that the scores of different providers do not correlate as strongly as anticipated, despite measuring the same ‘construct’.
Ratings of ESG
The purpose of ESG ratings is to assess a company’s ESG performance. Yet, ESG ratings disagree to an extent that leaves observers with considerable uncertainty as to how good the company’s ESG performance is. (p. 1323)
Ratings of ESG
This is the universe of firms the providers cover.
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Ratings of ESG
These are the descriptives for the same firms. They are different.
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Ratings of ESG
These are the correlations between the scores.
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Ratings of ESG
This is a plot of the scores.
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Ratings of ESG
This is a plot using Ranking, instead of the scores.
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Ratings of ESG
At the first level of disaggregation:
- Moody’s ESG, S&P Global, MSCI, and Sustainalytics have three dimensions (E, S, and G),
- Refinitiv has four,
- KLD has seven.
Below these first-level dimensions, there are between one and three levels of more granular sub-categories, depending on the rater.
At the lowest level, our data set contains between 38 and 282 indicators per rater, which often, but not always, relate to similar underlying attributes.
Ratings of ESG
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Ratings of ESG
When they compare only “comparable” items, correlations are still low.
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Ratings of ESG
The SASB framework does not seem to be an important driver.
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About today
Today, you will form groups of 4 students.
There is an excel file containing ESG data for several firms from several countries.
Your job is to create a report about stylized facts using this data.
- You are expected to select a country or an industry of your choice.
- There are many ESG-related variables. You should at least get familiar with each variable and use them in your analysis.
Your mission is to find evidence about which ESG factors might affect which financial variables in the sample you selected.
Additionally, you want to find whether the structure of the board of directors correlates with ESG variables.
You can use the article Gillan et al (2021) to have ideas of which correlations you wanna test.
About today
In order to find these correlations, you have two main approaches:
- Visualization.
- Create two-way graphs exploring the data
- Histograms
- Time-series analysis
- You can also explore variations in the ESG scores through time.
- Regression analysis.
- Run Ordinary Least Squares (OLS) regressions with Xs and Ys of your choice.
About today
The deliverable:
You have until the middle of the next class (Tuesday 16h) to deliver a word document containing your analyses, with all regressions and graphs.
You also may want to write an explanation about the regressions or graphs.
You need to provide at least 5 different analysis and justify them. Be smart and provide nice analyses.
In the second half of the next class, we will discuss your results and I am going to give a feedback about the evidence that all groups found or complementary evidence based on previous literature.
Ps. The total grading for this activity is 10% out of the 30% allocated for “class participation and problem resolution” (cf. the syllabus).
Ps. Groups that create a ppt presentation with the main topics discussed in the report AND present to the group will receive 2 extra points.
About the data
\[Size = Ln(Total\;Assets)\] \[Lev = \frac{Total\;debt}{Total\;Assets}\]
\[ROA = \frac{Net\;income}{Total\;Assets}\]
\[RD = \frac{RD\;Expeditures}{Total\;Assets}\]
\[Capex = \frac{Capital\;Expeditures}{Total\;Assets}\] \[Mkt = \frac{Market\;Value}{Total\;Assets}\]
THANK YOU!
