Environmental, Social, and Governance (ESG) ratings have become a fundamental tool for investors, policymakers, and financial institutions aiming to assess corporate sustainability performance. However, significant inconsistencies in ESG rating methodologies lead to market distortions, misallocation of capital, and reduced investor confidence. The ambiguity in ESG ratings stems from variations in disclosure levels, methodological differences across rating agencies, and the influence of subjective investor perceptions.

This study presents a structured framework based on an information-based distortion model, which integrates an information matrix assessing data reliability and a garbling matrix capturing subjective market biases. By applying this approach, it is possible to evaluate the effects of policy shocks on the companies’ ratings, evaluating the sentiment of market participants towards the different ESG scores.

From the empirical side, we assess how the environmental components is slightly undervalued for most agents, while an increasing pressure on the Social component of the score could favor the evaluation of those companies that operate in environmentally intense sectors. Conversely, governance factors, along with environmental considerations, are currently undervalued, consistently yielding negative impacts across almost all sectors for company rating.