Does Financial Statement Line-item Comparability Affect Analysts’ Forecasts?

56 Pages Posted: 8 Mar 2018 Last revised: 17 Apr 2023

See all articles by Elaine Henry

Elaine Henry

Stevens Institute of Technology - School of Business

Fang-Chun Liu

University of South Florida

Steve Y. Yang

Stevens Institute of Technology

Xiaodi Zhu

New Jersey City University

Date Written: December 30, 2022

Abstract

This study investigates comparability of firms’ financial statement presentation, i.e., the display of line items on financial statements. The line items that are displayed on financial statements are the result of disclosure choices such as placement, formatting, and aggregation. Given the emergence of machine-readable data (for example XBRL-tags used in this paper in creating our test variable), a question arises about the relevance of items’ presentation on the face of the human-readable financial statements. This paper examines the relation between line-item comparability (based on the face of financial statements) and financial statement users’ judgments as proxied by attributes of analysts’ forecasts. We posit that greater line-item comparability likely lowers analysts’ processing costs and enhances analysts’ ability to evaluate firms’ economic performance. Our results indicate that greater line-item comparability is associated with more analyst coverage, increased forecast accuracy, reduced forecast dispersion, and greater timeliness of forecasts. Overall, these results suggest that comparability of line items on the face of financial statement enhances informativeness.

Keywords: comparability, financial statement structure, analyst forecast, XBRL

Suggested Citation

Henry, Elaine and Liu, Fang-Chun and Yang, Steve Y. and Zhu, Xiaodi, Does Financial Statement Line-item Comparability Affect Analysts’ Forecasts? (December 30, 2022). Journal of Accounting, Auditing & Finance, Forthcoming, Available at SSRN: https://ssrn.com/abstract=3133324 or http://dx.doi.org/10.2139/ssrn.3133324

Elaine Henry (Contact Author)

Stevens Institute of Technology - School of Business ( email )

Hoboken, NJ 07030
United States

Fang-Chun Liu

University of South Florida ( email )

Tampa, FL 33620
United States

Steve Y. Yang

Stevens Institute of Technology ( email )

Hoboken, NJ 07030
United States

Xiaodi Zhu

New Jersey City University ( email )

2039 Kennedy Boulevard
Jersey City, NJ 07305-1597
United States

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