The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Measuring Country Differences in Enforcement of Accounting Standards: An Audit and Enforcement Proxy
Open accessAbstract
In this paper we present an index designed to capture differences between countries in relation to the institutional setting for financial reporting, specifically the auditing of financial statements and the enforcement of compliance with each country's accounting standards. The use of a common set of standards such as International Financial Reporting Standards (IFRS) aims, in broad terms, to promote the comparability and transparency of financial statements and to improve the quality of financial reporting. However, the effectiveness of IFRS adoption may be hampered by differences, across countries, in the institutional setting in which financial reporting occurs. Studies of outcomes from adopting IFRS use a range of legal system proxies to capture these country differences, but the proxies are deficient in that they seldom focus explicitly on factors that affect how compliance with accounting standards is promoted through external audit and the activities of independent enforcement bodies. To address this deficiency, we calculate measures of the quality of the public company auditors’ working environment (AUDIT) and the degree of accounting enforcement activity (ENFORCE) by independent enforcement bodies. We do this for 51 countries for each of the years 2002, 2005 and 2008, using publicly available data provided by the International Federation of Accountants (IFAC), the World Bank and the national securities regulators. Preliminary tests suggest our indices have additional explanatory power (over more general legal proxies) for country‐level measures of economic and market activity, financial transparency and earnings management. We expect they will prove useful to researchers and other interested parties who require country‐level measures that focus on the degree of enforcement of financial reporting practices.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
La Porta, R., Lopez‐de‐Silanes, F., Shleifer, A., & Vishny, R. W. (1998) · Journal of Political Economy · doi:10.1086/250042 · Cited by 18,025
Cited by
LEUZ, C., & WYSOCKI, P. D. (2016) · Journal of Accounting Research · doi:10.1111/1475-679x.12115 · Cited by 1,760
Gros, M., & Koch, S. (2019) · Corporate Ownership and Control · doi:10.22495/cocv16i1c1art4 · Cited by 5
Metadata
- Authors
- Brown, P., Preiato, J., & Tarca, A.
- Venue
- Journal of Business Finance & Accounting
- Publisher
- Wiley
- Published
- 2014-01
- Volume
- 41
- Issue
- 1-2
- Pages
- 1-52
- ISSN
- 0306-686X (ISSN-L)
- 1468-5957
- OpenAlex
- W2320876288
- Cited by
- 417
- References
- 1
- FWCI
- 135.27
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
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.