Four Things No One Will Tell You About ESG Data
Four Things No One Will Tell You About ESG Data ArXiv ID: ssrn-3420297 “View on arXiv” Authors: Unknown Abstract As the ESG finance field and the use of ESG data in investment decision‐making continue to grow, we seek to shed light on several important aspects of ESG measu Keywords: ESG data, sustainable finance, investment decision-making, environmental metrics, social responsibility, ESG Assets Complexity vs Empirical Score Math Complexity: 1.5/10 Empirical Rigor: 4.0/10 Quadrant: Philosophers Why: The paper is primarily conceptual, discussing data inconsistencies and methodological challenges in ESG metrics without heavy mathematical derivations or statistical modeling, placing it in the low math category; empirical rigor is moderate as it includes a hand-collected sample analysis but lacks backtest-ready implementation or code. flowchart TD A["Research Question: What critical limitations and biases exist in ESG data used for investment decisions?"] --> B["Methodology: Qualitative Analysis & Literature Review"] B --> C["Data/Inputs: Major ESG Ratings & Databases"] C --> D["Process: Comparative Analysis & Bias Identification"] D --> E["Key Finding: ESG ratings diverge significantly across providers"] D --> F["Key Finding: ESG data is backward-looking, not predictive"] D --> G["Key Finding: ESG metrics lack standardization & comparability"] D --> H["Key Finding: Ratings contain inherent methodological biases"] E & F & G & H --> I["Outcome: ESG data is a flawed proxy for sustainability; requires critical due diligence"]