Measuring Financial Statement Disaggregation Using XBRL
Document Type
Article
Publication Date
3-1-2024
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.
Publication Source (Journal or Book title)
Journal of Information Systems
First Page
119
Last Page
147
Recommended Citation
Johnston, J., Reichelt, K., & Sapkota, P. (2024). Measuring Financial Statement Disaggregation Using XBRL. Journal of Information Systems, 38 (1), 119-147. https://doi.org/10.2308/ISYS-2021-004