The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
Evaluating Financial Reporting Quality: The Effects of Financial Expertise vs. Financial Literacy
Abstract
Audit committees evaluate financial reporting quality as part of their corporate oversight responsibilities. Given this responsibility, the national stock exchanges now require all audit committee members to be financially literate and at least one member to have financial expertise. In light of recent debates over this requirement, we provide evidence on how experts and literates differ in their evaluations of financial reporting quality. Results suggest that experts' evaluations of financial reporting quality are more strongly associated with their assessments of characteristics underlying reporting quality (e.g., relevance) espoused in Statement of Financial Accounting Concepts No. 2's framework than literates' evaluations. Additionally, literates are more likely than experts to identify concerns about reporting treatments for business activities that are prominent in the business press or are distinguished by their nonrecurring nature, while experts are more likely to raise concerns about reporting treatments for less prominent, recurring activities. This same pattern occurs in the ratings of the quality of the reporting treatments for specific financial statement items with respect to elements underlying reporting quality (e.g., neutrality); literates (experts) assess the quality elements for the reporting treatments of prominent and nonrecurring items (less prominent and recurring items) comparatively lower than experts (literates). These results suggest that including financial experts on audit committees is likely to change the structure and focus of audit committee discussions about financial reporting quality, and may affect the committee's overall assessment of the quality of a company's financial reports.
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Citations
Cites
Availability: A heuristic for judging frequency and probability
Tversky, A., & Kahneman, D. (1973) · Cognitive Psychology · doi:10.1016/0010-0285(73)90033-9 · Cited by 9,984 · cited 2×
“Specifically, psychology research indicates that individuals’ frequency assessments are formed using the availability heuristic, in which instances that are easier to recall are perceived as more frequent ( Tversky and Kahneman 1973 ).”
BackgroundRegression Diagnostics: Identifying Influential Data and Sources of Collinearity
Belsley, D. A., Kuh, E., & Welsch, R. E. (1980) · Wiley Series in Probability and Statistics · doi:10.1002/0471725153 · Cited by 7,297
Regression Diagnostics -- Identifying Influential Data and Sources of Collinearity
Beaumont, C. D., Belsley, D. A., Kuh, E., & Welsch, R. E. (1981) · The Journal of the Operational Research Society · doi:10.2307/2581267 · Cited by 6,359
Cognitive Psychology and Its Implications
Anderson, J. R. (2014) · Cited by 4,121
DECHOW, P. M., SLOAN, R. G., & SWEENEY, A. P. (1996) · Contemporary Accounting Research · doi:10.1111/j.1911-3846.1996.tb00489.x · Cited by 4,065
Payne, J. W., Bettman, J. R., & Johnson, E. J. (1993) · doi:10.1017/cbo9781139173933 · Cited by 3,487
Leave, C. (1994) · Journal of the Operational Research Society · doi:10.1057/jors.1994.133 · Cited by 3,309
The robust beauty of improper linear models in decision making.
Dawes, R. M. (1979) · American Psychologist · doi:10.1037/0003-066x.34.7.571 · Cited by 1,966
Judged frequency of lethal events.
Lichtenstein, S. (1978) · Journal of Experimental Psychology: Human Learning & Memory · doi:10.1037//0278-7393.4.6.551 · Cited by 1,520
American Institute of Certified Public Accountants (AICPA)
(2018) · The Grants Register 2018 · doi:10.1007/978-1-349-94186-5_84 · Cited by 1,504
Cited by
DHALIWAL, D., NAIKER, V., & NAVISSI, F. (2010) · Contemporary Accounting Research · doi:10.1111/j.1911-3846.2010.01027.x · Cited by 623
Financial literacy, financial advice, and financial behavior
Stolper, O. A., & Walter, A. (2017) · Journal of Business Economics · doi:10.1007/s11573-017-0853-9 · Cited by 471
“…context is an interesting and still largely under-researched subject: as can be inferred from Table 1, 19 out of the 20 most cited papers focus on financial decisions of households, the only exception being McDaniel et al. (2002), who discuss financial literacy in the context of audit committees.”
BackgroundAudit committee characteristics and earnings management: evidence from Malaysia
Mohd Saleh, N., Mohd Iskandar, T., & Mohid Rahmat, M. (2007) · Asian Review of Accounting · doi:10.1108/13217340710823369 · Cited by 273
Metadata
- Authors
- McDaniel, L., Martin, R. D., & Maines, L. A.
- Venue
- The Accounting Review
- Publisher
- American Accounting Association
- Published
- 2002-03-01
- Volume
- 77
- Issue
- s-1
- Pages
- 139-167
- ISSN
- 0001-4826 (ISSN-L)
- 1558-7967
- OpenAlex
- W2004240179
- Cited by
- 377
- References
- 23
- FWCI
- 29.99
- Type
- journal article
- Language
- en
- Open access
- closed
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