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Lima e Alves, Denis 
ORCID: https://orcid.org/0000-0002-8041-6801, Gietzmann, Miles B. and Marques, Ana Cristina ORCID: https://orcid.org/0000-0003-1595-0028
(2023)
Effects of amendments to Rule 12b-2: evidence from XBRL-based reporting complexity.
Abstract
This study empirically evaluates the impact of changes made to the SEC’s definition of Smaller Reporting Companies (SRCs) in 2018. Using a novel measure of reporting complexity based on the structure of XBRL filings, the authors examine how the increased public float threshold for SRCs from $75 million to $250 million affected reporting behaviour. The analysis reveals that this reduction in mandatory reporting requirements was simultaneously associated with increased voluntary reporting complexity within the affected float range, particularly among SRCs that also classify as Accelerated filers. Unlike previous studies that focused on textual complexity, this study introduces a complexity measure that is based on the structure of the XBRL reporting system, and captures regulatory effects, business models, and accounting choices. The findings suggest that XBRL-based structural complexity captures important aspects of revised compliance with Section 404 of the Sarbanes-Oxley Act, shedding light on the relationship between reporting complexity and internal controls. The study’s methodology, based on established graph theoretical analysis of XBRL filings, provides insights into how companies organize their financial statements and adapt to regulatory changes within the context of their actual reporting systems. It allows us to model the interplay between regulatory complexity, business models, and companies’ reporting requirements and choices. This paper shows that a reduction in mandatory disclosure requirements can lead to firms increasing their voluntary disclosure. Overall, this research contributes with valuable insights into how the dynamics of reporting complexity is determined by companies, regulators, and investors, emphasizing the significance of structural complexity measures in understanding reporting behavior and decision-making processes.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | 3* ,/dk/atira/pure/researchoutput/REFrank/3_ |
| Faculty \ School: | Faculty of Social Sciences > Norwich Business School |
| UEA Research Groups: | Faculty of Social Sciences > Research Groups > Accounting & Quantitative Methods |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 17 Jan 2024 01:38 |
| Last Modified: | 17 Jan 2024 01:38 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/94194 |
| DOI: |
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