Document Type

Article

Publication Date

2024

Publication Title

Journal of Information Systems

Keywords

disclosure quality, disaggregation, XBRL, SEC Financial Statement Data Sets, information processing cost

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.

DOI

10.2308/ISYS-2021-004

Comments

This is the accepted manuscript version of an article published in Journal of Information Systems 1 March 2024; 38 (1): 119–147. https://doi.org/10.2308/ISYS-2021-004.

Download

Included in

Accounting Commons

Share

COinS