Divergence and aggregation of ESG ratings: A survey

Open Research Europe, Journal Year: 2025, Volume and Issue: 5, P. 28 - 28

Published: Jan. 30, 2025

Purpose This paper reviews the existing literature on divergence of Environmental, Social, and Governance (ESG) ratings explores various aggregation methods. It highlights challenges posed by inconsistent ESG their implications for investment decisions. Design/methodology/approach The study conducts a comprehensive review prior research focusing ratings, examining correlation levels methodologies employed to assess corporate sustainability. also investigates traditional techniques modern machine learning approaches used address these inconsistencies. Findings Past reveals that exhibit low level across different providers, raising concerns about reliability as indicators. Although some studies propose advanced methods enhance accuracy, significant gaps remain in understanding how effectively consolidate information create dependable sustainability indicator. Originality provides critical analysis current state rating methodologies, emphasizing need improved strategies. underscores importance future leveraging data develop more consistent reliable measures sustainability.

Language: Английский

Multidimensional Spatiotemporal Clustering – An Application to Environmental Sustainability Scores in Europe

Environmetrics, Journal Year: 2025, Volume and Issue: 36(2)

Published: Feb. 4, 2025

ABSTRACT The assessment of corporate sustainability performance is extremely relevant in facilitating the transition to a green and low‐carbon intensity economy. However, companies located different areas may be subject environmental risks policies. Henceforth, main objective this paper investigate spatial temporal pattern evaluations European firms. We leverage large dataset containing information about companies' performances, measured by MSCI ESG ratings, geographical coordinates firms Western Europe between 2013 2023. By means modified version Chavent et al. (2018) hierarchical algorithm, we conduct clustering analysis, combining information, spatiotemporal which combines time dynamics multiple features dissimilarities, detect groups with homogeneous performance. are able build cross‐national cross‐industry clusters remarkable differences terms scores. Among other results, spatio‐temporal observe high degree overlap among clusters, indicating that within multidimensional approach. Our findings help capture diversity ratings across assist practitioners policymakers evaluating facing sustainability‐linked areas.

Language: Английский

Climate change risk pricing in the European stock market

Applied Economics, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 23

Published: Nov. 14, 2024

Climate risk is the potential for societies or ecosystems from impacts of climate change. Whether financial markets price risks critical to ensuring that necessary funding flows into environmentally sound projects and stranded assets adequately managed along a 'green transition path'. In this paper, we assess European stock market. We show measures returns spread green vs. brown investment reflect assets' exposition systematic macro-financial factors, which should be filtered out measure accurately. are priced by focusing on aggregate, industry, company-level data. propose market-based rating procedure evaluate non-transparent non-disclosing companies ESG information unavailable. illustrate its implementation using sample over 800 firms.

Language: Английский