Compensation Disclosure: A Study via Semantic Similarity

40 Pages Posted: 3 Dec 2021

See all articles by Maclean Gaulin

Maclean Gaulin

University of Utah - David Eccles School of Business

Xiaoxia Peng

University of Utah - David Eccles School of Business

Date Written: November 1, 2021

Abstract

This paper studies how economic factors influence executive compensation disclosures. We employ a novel measure based on a natural language processing algorithm, document embeddings, to capture nuanced semantic aspects of compensation disclosure. Consistent with our predictions, we find that firm size, industry similarity, disclosed compensation peers, and common compensation consultants are all associated with more similar compensation disclosures. This semantics-based measure could be widely applicable to the literature on narrative disclosures as it addresses some of the shortcomings of traditional textual measures. Specifically, it could facilitate more research into cross-firm comparisons and disclosure clustering, among other subjects.

Keywords: Compensation disclosure, executive compensation, document embedding, semantic similarity, textual analysis

JEL Classification: J41, M12, M41, M52

Suggested Citation

Gaulin, Maclean and Peng, Xiaoxia, Compensation Disclosure: A Study via Semantic Similarity (November 1, 2021). Available at SSRN: https://ssrn.com/abstract=3971286 or http://dx.doi.org/10.2139/ssrn.3971286

Maclean Gaulin

University of Utah - David Eccles School of Business ( email )

1645 E Campus Center Dr
Salt Lake City, UT 84112-9303
United States
801.585.0324 (Phone)

HOME PAGE: http://mgaulin.com

Xiaoxia Peng (Contact Author)

University of Utah - David Eccles School of Business ( email )

1655 E Campus Center Dr
Salt Lake City, UT 84112
United States

HOME PAGE: http://www.xiaoxiapeng.com

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