The Unreasonable Attractiveness of More ESG Data
2021
Sustainable investing is of tremendous interest in both academia and the investment industry. However, despite the interest and the surge in assets under management (AUM) inflow, environment, social, and governance (ESG) data currently remain a fundamental challenge because they are deficient in quantity, consistency, and quality. In light of this data challenge, many investors and academics have come to rely on commercial ESG raters to assess the ESG quality of various corporations. However, the commercial ESG ratings still suffer some notable biases. This article documents one possible bias, termed quantity bias. The authors find that the amount of ESG data available for a given company is positively correlated with the commercial ESG rating of that company and the weighted average cost of its capital. The implication for investors is that they should do their homework and examine what the ESG data actually say rather than simply check the box. For corporations, it implies that they will get favorable treatment in the capital market if they publish more ESG data. TOPICS:ESG investing, information providers/credit ratings, performance measurement Key Findings ▪ The current state of ESG data is severely deficient. To get around ESG data challenges, people have come to rely on commercial ESG raters. However, commercial ESG ratings also exhibit various biases. The bias documented in this article is termed the quantity bias. ▪ The authors found this bias to be statistically significant; not only does it lead to higher commercial ESG ratings, but more importantly for corporations, it leads to lower cost of funding. ▪ The implication of this bias is twofold. For corporations, publishing more ESG data helps the bottom line. For investors, one must carefully examine what the ESG data say about the company’s sustainability practices, rather than performing a simple box-ticking exercise.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
12
References
1
Citations
NaN
KQI