Measuring Accounting Reporting Complexity with XBRL

XBRL 会计 审计 解释力 会计信息系统 稳健性(进化) 业务 计算机科学 数据库 哲学 生物化学 化学 认识论 基因
作者
Rani Hoitash,Udi Hoitash
出处
期刊:The Accounting Review [American Accounting Association]
卷期号:93 (1): 259-287 被引量:335
标识
DOI:10.2308/accr-51762
摘要

ABSTRACT We propose a new measure of accounting reporting complexity (ARC) based on the count of accounting items (XBRL tags) disclosed in 10-K filings. The preparation and disclosure of more accounting items is complicated because it requires greater knowledge of authoritative accounting standards. This aspect of complexity can increase the likelihood of mistakes, incorrect application of GAAP, and can ultimately lead to less credible financial reports. Consistently, we find that ARC is associated with a greater likelihood of misstatements and material weakness disclosures, longer audit delay, and higher audit fees. In comparison to commonly used measures of operating and linguistic complexity, the associations between ARC and these outcomes are more consistent, exhibit greater explanatory power, and have stronger economic significance. These and additional validation and robustness tests suggest that ARC more completely reflects accounting complexity. In addition, ARC exhibits several advantageous properties, including across- and within-firm variation, availability for the universe of SEC filers, and a direct connection to accounting, inherent in its derivation from detailed accounting disclosures. Finally, because it relies on a comprehensive set of detailed accounting data, ARC broadly captures accounting complexity, while, at the same time, it can be disaggregated into account-specific measures of complexity. JEL Classifications: M41; M43. Data Availability: Data are available from sources identified in the paper. A similar version of ARC, based on company XBRL filings that were downloaded directly from the SEC, is available at http://www.xbrlresearch.com.
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