Research with XBRL Data



This website provides a repository of processed eXtensible Business Reporting Language (XBRL) data. XBRL is an open standard for reporting structured financial information which enables the efficient gathering of data and automated comparison of financial information over time and across firms. 


Public companies are required to file their financial statements in XBRL format. In so doing, companies tag information at 4 levels. Level 1 tagging is applied to each footnote in its entirety. Level 2 requires each significant accounting policy to be tagged as a block of text. Level 3 requires the tagging of each table or schedule within each footnote and level 4 requires the tagging of each numerical value in the financial statement or notes. Each level of tagging presents opportunities for researchers.


This website currently provides data based on levels 1 and 4 tagging. Firm complexity using Accounting reporting complexity (ARC) and related measures are based on level 4 tagging. We use level 1 tagging to provide complete data on common financial statement notes and their length. 


The paper below provides a review of the XBRL literature and discusses directions for future research.


Hoitash, R., U. Hoitash, and L. Morris. 2021. eXtensible Business Reporting Language (XBRL): A Review and Implications for Future Research. Forthcoming, Auditing: A Journal of Practice and Theory.


Firm Complexity and Accounting Reporting Complexity

Level 4 tagging enables research using the monetary value in each XBRL tag or the information about each tag (metadata). In a recent Accounting Review article (Hoitash and Hoitash 2018) we propose a new measure of accounting reporting complexity (ARC) constructed based on the count of accounting items (XBRL tags) disclosed in XBRL filings. The ARC data and several related measures are updated twice a year and can be downloaded in an Excel or SAS format from the accounting reporting complexity page. 

Financial Statement Notes  

Level 1 tagging enables an accurate extraction and classification of financial statement notes, a task that is otherwise hard to accomplish . In a recent article, forthcoming in The Accounting Review (Ahn, Hoitash, and Hoitash) we extract and examine the fair value footnote. Data on many prevalent footnotes, including the complete text and count of words is available for download in text and SAS format from the financial statement notes page.  


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