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Cited by 1,559

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Corporate Governance and Accounting Scandals

Open access
Agrawal, Anup, Chadha, Sahiba·2005·The Journal of Law and Economics

Abstract

This paper empirically examines whether certain corporate governance mechanisms are related to the probability of a company restating its earnings. We examine a sample of 159 U.S. public companies that restated earnings and an industry-size matched sample of control firms. We have assembled a novel, hand-collected dataset measuring corporate governance characteristics of these 318 firms. We find that several key governance characteristics are unrelated to the probability of a company restating earnings. These include the independence of boards and audit committees, and the provision of non-audit services by outside auditors. We find that the probability of restatement is lower in companies whose boards or audit committees have an independent director with financial expertise; it is higher in companies where the CEO belongs to the founding family. These relations are statistically significant, large in magnitude, and robust to alternative specifications. Our findings are consistent with the idea that independent directors with financial expertise are valuable in providing oversight of a firm's financial reporting practices.

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Metadata

Authors
Agrawal, A., & Chadha, S.
Venue
The Journal of Law and Economics
Published
2005-10
Volume
48
Issue
2
Pages
371-406
ISSN
  • 0022-2186 (ISSN-L)
  • 1537-5285
OpenAlex
W3125303042
Cited by
1,559
References
5
FWCI
217.20
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Corporate Governance and Accounting Scandals. https://app.cochat.ai/papers/10.1086/430808
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Agrawal, A., & Chadha, S. (2005). Corporate Governance and Accounting Scandals. The Journal of Law and Economics. https://doi.org/10.1086/430808

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.