Measuring Firm Complexity with Accounting Reporting Complexity (ARC)

 

Background

 

We share a new measure of firm complexity based on accounting information. Accounting is the “language of business,” and accounting disclosures of most business activities are mandated. Therefore, relying on accounting disclosures is the best approach for consistently capturing a wide range of firm activities for a large cross-section of firms. Firm complexity is measured with accounting reporting complexity (ARC) and is based on the count of accounting items disclosed in eXtensible Business Reporting Language (XBRL) filings.  ARC is associated with lower financial reporting quality, higher audit fees, greater filing delays, poor analysts' performance, and various other measures that are correlated with firm complexity. ARC possesses properties of a good measure of firm complexity: First, it is “valid,” i.e., it captures the intended construct of firm complexity. Second, it is “reliable,” meaning it is objectively and consistently measured across firms and over time. Third, it captures “variation” in the construct across firms and within-firm over time that is consistent with changes in complexity. Fourth, it is “usable,” which means that it is easily constructed for a broad population of public companies.  

 

The data includes filings from 2011 through March 31, 2022. The most recent data also includes ARC of recognized (financial statements) vs. disclosed information (financial statement notes), ARC for each financial statement (e.g., Income Statement), and several additional measures. Annual and quarterly measures of ARC are included in the dataset. 

 

Relevant papers that use ARC:

 

If you decide to use the data, please consider citing one or more of the following papers. These papers develop, validate, provide code, review of the literature, and/or use ARC:

 

Hoitash, R., and Hoitash, U. 2018. Measuring Accounting Reporting Complexity with XBRL. The Accounting Review,  Vol. 93, No. 1, pp. 259-287.

 

Hoitash, R., and Hoitash, U. 2022. A Measure of Firm Complexity: Data and Code.  Journal of Information Systems. Forthcoming. 

 

Hoitash, R., U. Hoitash, and A. Yezegel. 2021. Can sell-side analysts’ experience, expertise and qualifications help mitigate the adverse effects of accounting reporting complexity? Review of Quantitative Finance and Accounting. 57: 859–897. 

 

 

Below we provide links to files that include ARC and several related measures. The Firm Complexity files contain only the primary ARC measure (Hoitash and Hoitash 2018). The ARC files include several other measures. We are happy to help. Please feel free to reach out to us with questions!

 

 

Firm Complexity (ARC) Data- SAS Format
FirmCompleixty.zip
Compressed archive in ZIP format [4.8 MB]

 

 

Firm Complexity (ARC) Data- Excel Format
FirmComplexity.xlsx
Microsoft Excel sheet [18.1 MB]

 

 

ARC and Several Related Measures Data- SAS Format
ARC.zip
Compressed archive in ZIP format [23.2 MB]

 

 

ARC and Several Related Measures Data- Excel Format
ARC.xlsx
Microsoft Excel sheet [54.6 MB]

 

 

Data Dictionary
ARC Data Dictionary.docx
Microsoft Word document [23.5 KB]

 

 

SAS Code to Generate ARC and Related Measures
ARC (Firm Complexity) SAS Code Macro.zip
Compressed archive in ZIP format [4.8 KB]

XBRL and Firm Complexity in the Media  

Accounting Today:

Professors propose new measure of accounting complexity

FEI Daily: Measuring Accounting Disclosure Complexity with XBRL

Compliance Week: As Complexity Rises, Quality Slides, XBRL-Based Study Says

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A Measure of Firm Complexity