Exploring Nature: Datasets and Models for Analyzing Nature-Related Disclosures

Tobias Schimanski, Chiara Colesanti Senni, Glen Gostlow, Jingwei Ni, Tingyu Yu and Markus Leippold
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Tobias Schimanski: University of Zurich
Chiara Colesanti Senni: University of Zurich - Department of Finance
Glen Gostlow: University of Zurich - Department Finance
Jingwei Ni: ETH Zurich
Tingyu Yu: University of Zurich - Department Finance
Markus Leippold: University of Zurich; Swiss Finance Institute

No 24-95, Swiss Finance Institute Research Paper Series from Swiss Finance Institute

Abstract: Nature is an amorphous concept. Yet, it is essential for the planet's well-being to understand how the economy interacts with it. To address the growing demand for information on corporate nature disclosure, we provide datasets and classifiers to detect nature communication by companies. We ground our approach in the guidelines of the Taskforce on Nature-related Financial Disclosures (TNFD). Particularly, we focus on the specific dimensions of water, forest, and biodiversity. For each dimension, we create an expert-annotated dataset with 2,200 text samples and train classifier models. Furthermore, we show that nature communication is more prevalent in hotspot areas and directly effected industries like agriculture and utilities. Our approach is the first to respond to calls to assess corporate nature communication on a large scale.

Keywords: Nature-related risks; TNFD; Natural Language Processing; Disclosure (search for similar items in EconPapers)
Pages: 12 pages
Date: 2024-01
New Economics Papers: this item is included in nep-big and nep-env
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Persistent link: https://EconPapers.repec.org/RePEc:chf:rpseri:rp2495

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