Managerial Self-References in Corporate Disclosures: An Analysis of MD&A

This study examines strategic pronoun usage in the Management Discussion and Analysis (MD&A) section of annual reports. Through automated textual analysis of a large sample of MD&As, we find that managers of firms with higher earnings growth tend to use more self-inclusive pronouns(e.g., “ we, ” “ us, ” and “ our ”) and fewer self-exclusive words (e.g., “the company ”). This self-referential language pattern is associated with a higher likelihood of future financial restatements. Our findings contribute to the literature on corporate narrative disclosures and identify a potential new indicator of financial misstatements. The results have implications for investors, analysts, auditors, and regulators.

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Publication Details

Journal
Journal of Applied Business and Economics
Published
2024-10-12
DOI
https://doi.org/10.33423/jabe.v26i5.7290
Primary Topic
Impact of AI and Big Data on Business and Society
Type
article
Field-Weighted Citation Impact
0.00

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article

Managerial Self-References in Corporate Disclosures: An Analysis of MD&A

Yamin Hao, Wang Xiao-jia, Ying Mao
Journal of Applied Business and Economics
Impact of AI and Big Data on Business and Society
article

Managerial Self-References in Corporate Disclosures: An Analysis of MD&A

Yamin Hao, Wang Xiao-jia, Ying Mao
article en

Abstract

This study examines strategic pronoun usage in the Management Discussion and Analysis (MD&A) section of annual reports. Through automated textual analysis of a large sample of MD&As, we find that managers of firms with higher earnings growth tend to use more self-inclusive pronouns(e.g., “ we, ” “ us, ” and “ our ”) and fewer self-exclusive words (e.g., “the company ”). This self-referential language pattern is associated with a higher likelihood of future financial restatements. Our findings contribute to the literature on corporate narrative disclosures and identify a potential new indicator of financial misstatements. The results have implications for investors, analysts, auditors, and regulators.

Journal of Applied Business and EconomicsVol. 26(5)
Lingnan University (HK), Western Washington University (US), MacEwan University (CA)
Western Washington University, MacEwan University, Lingnan University
Openalex Percentile: Top 77%
Impact of AI and Big Data on Business and Society
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Managerial Self-References in Corporate Disclosures: An Analysis of MD&A — Yamin Hao, Wang Xiao-jia, et al. · Journal of Applied Business and Economics (2024) | TGRS Research Map | TGRS