Measuring Financial Statement Disaggregation Using XBRL
Author:
Johnston Joseph A.1,
Reichelt Kenneth J.2ORCID,
Sapkota Pradeep3ORCID
Affiliation:
1. Illinois State University
2. Louisiana State University
3. University of North Texas
Abstract
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.
Publisher
American Accounting Association
Subject
Management of Technology and Innovation,Information Systems and Management,Human-Computer Interaction,Accounting,Information Systems,Software,Management Information Systems
Cited by
1 articles.
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