Diagnosing Grey Areas in National Green Taxonomy Frameworks and Corporate Misleading Statements

• Abbas Ahsun

  Texas University

  Author

National green taxonomy frameworks have emerged as the central regulatory instrument for distinguishing genuinely sustainable economic activities from those that merely claim to be so. Yet a persistent diagnostic gap remains: taxonomies classify activities, not corporate intent, and firms routinely exploit the space between technical eligibility and substantive alignment to construct misleading environmental narratives. This study addresses that gap by developing and validating a diagnostic framework for identifying grey areas in taxonomy-based corporate disclosures and linking them to patterns of misleading statements. Drawing on a mixed-methods design combining content analysis of taxonomy-aligned disclosures from 240 European non-financial firms (2022–2024) with a structured expert validation panel, the study constructs a four-dimensional diagnostic instrument encompassing eligibility-alignment divergence, capital expenditure denominator manipulation, narrative-verification asymmetry, and cross-objective double counting. Results demonstrate that the framework achieves 89.4% classification accuracy in identifying firms whose taxonomy disclosures exhibit material divergence from underlying financial and operational data, with capital expenditure denominator errors and selective activity reporting emerging as the strongest predictors of misleading statement risk. The study concludes that taxonomy frameworks require complementary diagnostic instruments to function as credible anti-greenwashing mechanisms, and offers a replicable tool for regulators, auditors, and investors seeking to distinguish substantive alignment from performative compliance.

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Copyright (c) 2026 Abbas Ahsun (Author)

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