Alignment Vetting of Bloomberg's ISS: QualityScore [GQSTM]: Frequency of Provision of ESG & Related Disclosure Scores

Chuo-Hsuan Lee, Edward J. Lusk, Karen Naaman and Osamuyimen Omorogbe-Akpata

International Journal of Economics and Finance, 2022, vol. 14, issue 12, 40

Abstract: Context The Environment, Social, and Governance [ESGÓ]-platform offered by BloombergÔ Professional Services [https-//www.bloomberg.com/professional/] is a leading source of relevant, reliable, and timely information on the context within which market trading firms operate. The ESG-platform of the Bloomberg Terminals [BBT] includes more than 2,000 data fields that provide intel to aid in better understanding the “Stakeholder-impact” of the firm’s activities. One of the sub-platforms therein is the Institutional Shareholder Services [ISS] which offers Governance QualityScores- (GQSÔ). The BBT[ISS[GQS]]-platform is a data-driven approach to scoring & screening designed to help investors monitor a company’s control of governance risk. Previous studies have provided vetting information of the BBT[ISS[GQS]]-platform. As an enhancement to these vetting-studies, we offer the following. Study Design In the ESG-Platform, there are Disclosure Scores for- The General [ESG], Environment, Social & Governance categories. The vetting question of interest is- Does the ISS score those firms that provide more Disclosure information as ISS[1] and those firms that provide less as ISS[10]? If so, this would cast doubt on the relevance and reliability of the ISS-assignment taxonomy. Results We discuss the critical role of vetting. Then, the Dul- Necessity & Sufficiency Screen is offered as the organizing logic of the Inferential vetting platform. Finally, using the Gold Standard test- Linear Discriminant Analysis for the vetting inference, it is clear that the ISS-assignment is not aligned with the degree of provision of disclosure information for any of the four ESG-Disclosure Score variables. Thus, these vetting results are not inconsistent with a functioning taxonomic-allocation platform.

Date: 2022
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