TY - JOUR

T1 - It's Hard to Hit a Target that Doesn't Exist

T2 - A Novel Conceptual Framework for ESG Ratings

AU - Cruz-Lopez, Jorge

AU - Neyland, Jordan B.

AU - Smirnow, Dasha

PY - 2024

Y1 - 2024

N2 - We introduce a conceptual framework to understand some of the persistent shortcomings we observe in ESG ratings and their potential consequences for financial stability, corporate policy, and regulation. Our framework consists of analyzing three different stages in the pro-duction of ESG ratings: (1) Data Collection and Disclosure, (2) Measurement, and (3) Dissemination. At each stage, we clearly identify the parties involved, their incentives and limitations, and the noise or bias introduced to ESG ratings due to misaligned incentives, data constraints, or inadequate regulations. In the Data Collection and Disclosure stage, noise and bias are introduced when rated companies dis-close data selectively or have limited capacity for collecting or sharing relevant data. In addition, the data collection and disclosure methods used across companies and rating providers are usually not standardized. Because of these deficiencies, it is possible that some companies engage in greenwashing. At the Measurement stage, when ESG ratings are calculated, noise and bias are introduced to the process due to a lack of consensus on what constitutes “good” ESG performance, as well as the use of widely diverging methodologies that tend to lack transparency or replicability. These issues may lead to limited competition among rating providers and a race to the bottom, where rating providers cater to rated companies by providing inflated ratings. At the Dissemination stage, noise and bias are introduced because ratings produced by different providers are not always directly comparable. For example, it is not clear if some ratings focus on risk exposure or risk contribution. In addition, some ratings are difficult to verify or lack timeliness, which might bias the perception of end users and the way they use these ratings for investment decisions, regulations, or internal corporate policies. Importantly, our framework allows us to devise potential solutions for some of the problems highlighted in our analysis. These solutions include improving disclosure standards, incentivizing public data access to foster competition as well as transparency of rating methodologies, and re-lying on regular audits to verify the accuracy of corporate disclosures and ESG ratings.

AB - We introduce a conceptual framework to understand some of the persistent shortcomings we observe in ESG ratings and their potential consequences for financial stability, corporate policy, and regulation. Our framework consists of analyzing three different stages in the pro-duction of ESG ratings: (1) Data Collection and Disclosure, (2) Measurement, and (3) Dissemination. At each stage, we clearly identify the parties involved, their incentives and limitations, and the noise or bias introduced to ESG ratings due to misaligned incentives, data constraints, or inadequate regulations. In the Data Collection and Disclosure stage, noise and bias are introduced when rated companies dis-close data selectively or have limited capacity for collecting or sharing relevant data. In addition, the data collection and disclosure methods used across companies and rating providers are usually not standardized. Because of these deficiencies, it is possible that some companies engage in greenwashing. At the Measurement stage, when ESG ratings are calculated, noise and bias are introduced to the process due to a lack of consensus on what constitutes “good” ESG performance, as well as the use of widely diverging methodologies that tend to lack transparency or replicability. These issues may lead to limited competition among rating providers and a race to the bottom, where rating providers cater to rated companies by providing inflated ratings. At the Dissemination stage, noise and bias are introduced because ratings produced by different providers are not always directly comparable. For example, it is not clear if some ratings focus on risk exposure or risk contribution. In addition, some ratings are difficult to verify or lack timeliness, which might bias the perception of end users and the way they use these ratings for investment decisions, regulations, or internal corporate policies. Importantly, our framework allows us to devise potential solutions for some of the problems highlighted in our analysis. These solutions include improving disclosure standards, incentivizing public data access to foster competition as well as transparency of rating methodologies, and re-lying on regular audits to verify the accuracy of corporate disclosures and ESG ratings.

M3 - Journal article

VL - 8

JO - The Business, Entrepreneurship & Tax Law Review (“BETR”)

JF - The Business, Entrepreneurship & Tax Law Review (“BETR”)

IS - 1

M1 - 5

ER -