Dataset of “Determinants and forecasting of corporate greenwashing behavior”: Corporate greenwashing accusations

Published: 12 December 2025| Version 3 | DOI: 10.17632/czsf8899jm.3
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Description

This dataset accompanies the paper: Jens Eckberg, Gregor Dorfleitner, Manuel C. Kathan, Sebastian Utz; Determinants and forecasting of corporate greenwashing behavior, Journal of Economic Behavior & Organization, Volume 241, 2026, 107354, ISSN 0167-2681, https://doi.org/10.1016/j.jebo.2025.107354 The dataset comprises a list of third-party accusations of greenwashing against STOXX Europe 600 companies, published in the media and on social media platforms, between 2011 and 2023. These accusations were manually collected and the severity of the accusations was assessed by humans based on a predefined framework. The authors raised no accusations; the dataset solely evaluates and codes greenwashing accusations made publicly available by external sources. Each third-party accusation was assessed for its severity. The variable “GW_SCORE” captures this assessment on a scale from 0 (no greenwashing) to 1 (greenwashing). A detailed description of the construction, coding procedure, and validation of the greenwashing severity score is provided in the paper. The dataset includes the company name (“COMPANY_NAME”) and is structured as a panel dataset with annual observations for the period 2011–2023. It also contains the column “USED_FOR_ANALYSIS”, which indicates True if a given company-year score was included in the empirical analyses of the paper, and False if it was not. Please cite the following studies when using the dataset, as they provide the rationale for its development. Eckberg, J., Dorfleitner, G., Kathan, M. C., & Utz, S. (2026). Determinants and forecasting of corporate greenwashing behavior. Journal of Economic Behavior & Organization, 241, 107354. https://doi.org/10.1016/j.jebo.2025.107354 Kathan, M. C., Utz, S., Dorfleitner, G., Eckberg, J., & Chmel, L. (2025). What you see is not what you get: ESG scores and greenwashing risk. Finance Research Letters, 74, 106710. https://doi.org/10.1016/j.frl.2024.106710

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Steps to reproduce

A detailed description of the construction of the greenwashing severity score is provided in the paper.

Institutions

  • Universitat Regensburg
  • Universitat Augsburg

Categories

Risk Management, Environmental Corporate Issue, Environmental Performance Indicator, Environmental Performance Evaluation, Environmental, Social and Corporate Governance

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