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

Abstract

This study investigates comparability of firms’ financial statement presentation, that is, 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 presentation analyst forecast XBRL

Get full access to this article

View all access options for this article.

References

Ahmed

A. S.

Kilic

Lobo

G. J.

(2006). Does recognition versus disclosure matter? Evidence from value-relevance of banks’ recognized and disclosed derivative financial instruments. The Accounting Review, 81(3), 567–588.

Allee

K. D.

Erickson

Esplin

A. M.

Yohn

T. L.

(2022). Financial analysts’ preferences regarding income statement presentation [Working paper]. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4049941

Baldwin

A. A.

Trinkle

B. S.

(2011). The impact of XBRL: A Delphi investigation. The International Journal of Digital Accounting Research, 11(17), 1–24.

Bartley

Chen

A. Y. S.

Taylor

E. Z.

(2011). A comparison of XBRL filings to corporate 10-Ks—Evidence from the voluntary filing program. Accounting Horizons, 25(2), 227–245.

Behn

B. K.

Choi

J. H.

Kang

(2008). Audit quality and properties of analyst earnings forecasts. The Accounting Review, 83(2), 327–349.

Blankespoor

(2019). The impact of information processing costs on firm disclosure choice: Evidence from the XBRL mandate. Journal of Accounting Research, 57(4), 919–967.

Bloomfield

Hodge

Hopkins

Rennekamp

(2015). Does coordinated presentation help credit analysts identify firm characteristics? Contemporary Accounting Research, 32(2), 507–527.

Bradshaw

M. T.

Miller

G. S.

Serafeim

(2009). Accounting method heterogeneity and analysts’ forecasts [Working paper]. University of Chicago; University of Michigan; Harvard University.

Brown

S. V.

Tucker

J. W.

(2021). Financial statement dissimilarity and SEC scrutiny [Working paper]. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3384394

10.

Caylor

M. L.

Chambers

D. J.

Mutlu

(2022). Financial reporting uniformity: Its relation to comparability and its impact on financial statement users. Journal of Business Finance & Accounting, 49, 1457–1488. https://onlinelibrary.wiley.com/doi/10.1111/jbfa.12608?af=R

11.

Chan

L. K.

Lakonishok

Swaminathan

(2007). Industry classifications and return comovement. Financial Analysts Journal, 63(6), 56–70.

12.

Chen

Y. A.

Medinets

A. F.

Palmon

(2021). Disclosure regulations work: The case of regulation G. Review of Quantitative Finance and Accounting, 58, 1037–1062.

13.

Clement

M. B.

Tse

S. Y.

(2003). Do investors respond to analysts’ forecast revisions as if forecast accuracy is all that matters? The Accounting Review, 78(1), 227–249.

14.

Davis-Friday

P. Y.

Folami

L. B.

Liu

Mittelstaedt

H. F.

(1999). The value relevance of financial statement recognition vs. disclosure: Evidence from SFAS No. 106. The Accounting Review, 74(4), 403–423.

15.

Debreceny

Farewell

Piechocki

Felden

Gräning

(2010). Does it add up? Early evidence on the data quality of XBRL filings to the SEC. Journal of Accounting and Public Policy, 29(3), 296–306.

16.

De Franco

Kothari

S. P.

Verdi

R. S.

(2011). The benefits of financial statement comparability. Journal of Accounting Research, 49(4), 895–931.

17.

Dhole

Lobo

G. J.

Mishra

Pal

A. M.

(2015). Effects of the SEC’s XBRL mandate on financial reporting comparability. International Journal of Accounting Information Systems, 19, 29–44.

18.

Vasarhelyi

M. A.

Zheng

(2013). XBRL mandate: Thousands of filing errors and so what? Journal of Information Systems, 27(1), 61–78.

19.

Felo

A. J.

Kim

J. W.

Lim

J. H.

(2018). Can XBRL detailed tagging of footnotes improve financial analysts’ information environment? International Journal of Accounting Information Systems, 28, 45–58.

20.

Financial Accounting Standards Board. (2018, August). Conceptual framework for financial reporting (Statement of financial accounting concepts No. 8. Chapter 3, Qualitative Characteristics of Useful Financial Information, As Amended, Issue Date 9/10).

21.

Financial Accounting Standards Board. (2021). Conceptual framework for financial reporting (Statement of Financial Accounting Concepts No. 8. Chapter 7, Presentation, Issue Date 12/21).

22.

Fischer

Muller

(2011, September 8–9). Enabling comparability and data mining with the Arelle® open source unified model [Conference session]. Proceedings of First Conference on Financial Reporting in the 21st Century: Standards, Technology, and Tools, Macerata, Italy.

23.

Frederickson

J. R.

Hodge

F. D.

Pratt

J. H.

(2006). The evolution of stock option accounting: Disclosure, voluntary recognition, mandated recognition, and management disavowals. The Accounting Review, 81(5), 1073–1093.

24.

Hirst

D. E.

Hopkins

P. E.

(1998). Comprehensive income reporting and analysts’ valuation judgments. Journal of Accounting Research, 36, 47–75.

25.

Hoitash

(2018). Measuring accounting reporting complexity with XBRL. The Accounting Review, 93(1), 259–287.

26.

Hoitash

Kurt

A. C.

Verdi

R. S.

(2021a). A measure of financial statement benchmarking [Working paper]. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3208928

27.

Hoitash

Morris

(2021b). eXtensible business reporting language (XBRL): A review and implications for future research. Auditing: A Journal of Practice & Theory, 40(2), 107–132.

28.

Hopkins

P. E.

(1996). The effect of financial statement classification of hybrid financial instruments on financial analysts’ stock price judgments. Journal of Accounting Research, 34, 33–50.

29.

Irani

A. J.

Karamanou

(2003). Regulation fair disclosure, analyst following, and analyst forecast dispersion. Accounting Horizons, 17(1), 15–29.

30.

Janvrin

D. J.

W. G.

(2012). XBRL implementation: A field investigation to identify research opportunities. Journal of Information Systems, 26(1), 169–197.

31.

Johnston

J. A.

(2020). Extended XBRL tags and financial analysts’ forecast error and dispersion. Journal of Information Systems, 34(3), 105–131.

32.

Johnston

J. A.

Zhang

J. H.

(2021). Auditor style and financial reporting similarity. Journal of Information Systems, 35(1), 79–99.

33.

Kim

Kraft

Ryan

S. G.

(2013). Financial statement comparability and credit risk. Review of Accounting Studies, 18(3), 783–823.

34.

Lang

M. H.

Lundholm

R. J.

(1996). Corporate disclosure policy and analyst behavior. The Accounting Review, 71(4), 467–492.

35.

Nwaeze

E. T.

(2018). Impact of extensions in XBRL disclosure on analysts’ forecast behavior. Accounting Horizon, 32(2), 57–79.

36.

Libby

Bloomfield

Nelson

M. W.

(2002). Experimental research in financial accounting. Accounting, Organizations and Society, 27(8), 775–810.

37.

Libby

Nelson

Hunton

J. E.

(2006). Recognition v. disclosure, auditor tolerance for misstatement, and the reliability of stock-compensation and lease information. Journal of Accounting Research, 44(3), 533–560.

38.

Lobo

G. J.

Song

Stanford

(2012). Accruals quality and analyst coverage. Journal of Banking & Finance, 36(2), 497–508.

39.

Maines

L. A.

McDaniel

L. S.

(2000). Effects of comprehensive-income characteristics on nonprofessional investors’ judgments: The role of financial-statement presentation format. The Accounting Review, 75(2), 179–207.

40.

O’Brien

P. C.

Bhushan

(1990). Analyst following and institutional ownership. Journal of Accounting Research, 28, 55–76.

41.

Plumlee

R. D.

Plumlee

M. A.

(2008). Assurance on XBRL for financial reporting. Accounting Horizons, 22(3), 353–368.

42.

Robinson

T. R.

Henry

Broihahn

M. A.

(2020). International financial statement analysis (CFA Institute Investment Series, 4th ed.). Wiley.

43.

Schipper

(1991). Analysts’ forecasts. Accounting Horizons, 5(4), 105–121.

44.

Schipper

(2007). Required disclosures in financial reports. The Accounting Review, 82(2), 301–326.

45.

Securities and Exchange Commission. (2009). Final rule: Interactive data to improve financial reporting (Release Nos. 33-9002, 34-59324, 39-2461).

46.

Vasarhelyi

M. A.

Chan

D. Y.

Krahel

J. P.

(2012). Consequences of XBRL standardization on financial statement data. Journal of Information Systems, 26(1), 155–167.

47.

Wang

Cao

Min

Wang

(2014). The application of versioning technology in XBRL taxonomy engineering. In Proceedings of International Conference on Computer Science and Information Technology (pp. 733–738). Springer.

48.

F. F.

(2008). Analyst coverage and earnings management. Journal of Financial Economics, 88(2), 245–271.

49.

Zhu

(2014). Assessing the quality of large-scale data standards: A case of XBRL GAAP Taxonomy. Decision Support Systems, 59, 351–360.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.03 MB