ACCOUNTING REPORTING COMPLEXITY MEASURED BEHAVIORALLY
Dirk Beerbaum (),
Maciej Piechocki and
Julia Puaschunder ()
Additional contact information
Dirk Beerbaum: Aalto University School of Business, Helsinki, Finland
Maciej Piechocki: BearingPoint, Frankfurt, Germany
Internal Auditing and Risk Management, 2019, vol. 56, issue 4, 35-47
We propose a new measure of accounting reporting complexity (ARC) based on customized extensions XBRL elements in relation to the number of reporting tags (NRT), expressed as the relative Extension Rate (ER) as a behavioral economics solution to improve markets. Behavioral insights have recently gained attention in different scientific and applied fields. Thereby behavioral economists set out to improve market conditions to aid practitioners and consumers make wiser and more informed decisions that have a positive impact over time. XBRL extensions reduce comparability of financial disclosures and complicate financial analysis and investor decision making. We find that ER is negatively associated with market capitalization and profitability. ER is on average higher in industries perceived as complex. The preparation and disclosure of more accounting items deviating from the base taxonomy is more complex for consumers of financial and non-financial information. Increasing ER imply comparability among peers is less enabled. 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. The ER resulting from IFRS-filers, i.e. companies which prepare their financial statements under International Financial Reporting Standard (IFRS) are on average significantly higher than US GAAP filers, i.e. companies which prepare their financial statements under United States General Accepted Accounting Principles (US GAAP). This article is based on the â€œtransparency technology XBRL (eXtensible Business Reporting Language)â€ (Sunstein, 2013), which should make data more accessible as well as usable for private investors. Overall, the findings contribute to the emerging behavioral economics trend with a novel application in data science and accounting.
Keywords: accounting reporting complexity; behavioral economics; behavioral insights; customized extensions elements; financial reporting quality and inductive method; ifrs taxonomy; nudging; relative extension rates; XBRL (search for similar items in EconPapers)
JEL-codes: D03 F32 G15 G32 P34 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
http://aimr.univath.ro/en/article/ACCOUNTING-REPOR ... HAVIORALLY~1195.html (text/html)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:ath:journl:v:56:y:2019:i:4:p:35-47
Access Statistics for this article
Internal Auditing and Risk Management is currently edited by Emilia Vasile
More articles in Internal Auditing and Risk Management from Athenaeum University of Bucharest Contact information at EDIRC.
Bibliographic data for series maintained by Cosmin Catalin Olteanu and Emilia Vasile ().