The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Big 4 Office Size and Audit Quality
Abstract
ABSTRACT: Larger offices of Big 4 auditors are predicted to have higher quality audits for SEC registrants due to greater in-house experience in administering such audits. We test this prediction by examining a sample of 6,568 U.S. firm-year observations for the period 2003–2005 and audited by 285 unique Big 4 offices. Results are consistent with larger offices providing higher quality audits. Specifically, larger offices are more likely to issue going-concern audit reports, and clients in larger offices evidence less aggressive earnings management behavior. These findings are robust to extensive controls for client risk factors and to controls for other auditor characteristics. While the evidence suggests audit quality is higher on average in larger Big 4 offices, we make no claims that audit quality is unacceptably low in smaller offices.
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Citations
Cites
Accruals Quality and Internal Control over Financial Reporting
Doyle, J. T., Ge, W., & McVay, S. (2007) · The Accounting Review · doi:10.2308/accr.2007.82.5.1141 · Cited by 1,366
Cited by
A review of archival auditing research
DeFond, M., & Zhang, J. (2014) · Journal of Accounting and Economics · doi:10.1016/j.jacceco.2014.09.002 · Cited by 3,188
Is artificial intelligence improving the audit process?
Fedyk, A., Hodson, J., Khimich, N., & Fedyk, T. (2022) · Review of Accounting Studies · doi:10.1007/s11142-022-09697-x · Cited by 461
Metadata
- Authors
- Francis, J. R., & Yu, M. D.
- Venue
- The Accounting Review
- Publisher
- American Accounting Association
- Published
- 2009-09-01
- Volume
- 84
- Issue
- 5
- Pages
- 1521-1552
- ISSN
- 0001-4826 (ISSN-L)
- 1558-7967
- OpenAlex
- W2023709878
- Cited by
- 1,273
- References
- 1
- FWCI
- 101.70
- Type
- journal article
- Language
- en
- Open access
- closed
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- Francis, J. R., & Yu, M. D. (2009). Big 4 Office Size and Audit Quality. The Accounting Review. https://doi.org/10.2308/accr.2009.84.5.1521
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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.
