Joseph A. Johnston, Kenneth J. Reichelt, Pradeep Sapkota
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Measuring Financial Statement Disaggregation Using XBRL
ABSTRACT We develop a measure of disclosure quality using disaggregation of financial statement items from the Form 10-K XBRL filing. Our measure (ITEMS) extends Chen, Miao, and Shevlin’s (2015) DQ measure and is distinct from R. Hoitash and U. Hoitash’s (2018) ARC measure. Our measure provides a simple measure of disaggregation by counting the balance sheet and income statement line items, it does not depend on the data aggregators’ collection process and is readily available shortly after the Form 10-K is filed. We validate ITEMS by showing that firm fundamentals correlate to ITEMS in the predicted direction using OLS regression. We find that ITEMS explains consequences of disclosure quality: forecast error, forecast dispersion, bid-ask spread, and cost of equity capital. Further, ITEMS has explanatory power of disclosure quality consequences incremental to DQ and ARC, and it is distinct from ARC evident from different associations with disclosure quality consequences and reporting quality. Data Availability: Data are available from public sources identified in the text. JEL Classifications: M10; M40; M41.
期刊介绍:
The Journal of Information Systems (JIS) is the academic journal of the Accounting Information Systems (AIS) Section of the American Accounting Association. Its goal is to support, promote, and advance Accounting Information Systems knowledge. The primary criterion for publication in JIS is contribution to the accounting information systems (AIS), accounting and auditing domains by the application or understanding of information technology theory and practice. AIS research draws upon and is informed by research and practice in management information systems, computer science, accounting, auditing as well as cognate disciplines including philosophy, psychology, and management science. JIS welcomes research that employs a wide variety of research methods including qualitative, field study, case study, behavioral, experimental, archival, analytical and markets-based.