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The Effect of Fair Value versus Historical Cost Reporting Model on Analyst Forecast Accuracy

Lihong Liang

Syracuse University

Edward J. Riedl

Boston University - Questrom School of Business

December 1, 2013

Accounting Review, Forthcoming

This paper examines how the reporting model for a firm’s operating assets affects analyst forecast accuracy. We contrast UK and US investment property firms having real estate as their primary operating asset, exploiting that UK (US) firms report these assets at fair value (historical cost). We assess the accuracy of a balance sheet-based forecast (net asset value, or NAV) and an income statement-based forecast (earnings-per-share, or EPS). We predict and find higher NAV forecast accuracy for UK relative to US firms, consistent with the fair value reporting model revealing private information that is incorporated into analysts’ balance sheet forecasts. We find this difference is attenuated when the fair value and historical cost models are more likely to converge: during recessionary periods. Finally, we predict and find lower EPS forecast accuracy for UK firms when reporting under the full fair value model of IFRS, in which unrealized fair value gains and losses are included in net income. This is consistent with the full fair value model increasing the difficulty of forecasting net income through the inclusion of non-serially correlated elements such as these gains/losses. Information content analyses provide further support for these inferences. Overall, the results indicate that the fair value reporting model enhances analysts’ ability to forecast the balance sheet, but the full fair value model reduces their ability to forecast net income.

Number of Pages in PDF File: 49

Keywords: fair value, historical cost, analyst forecast accuracy, net asset value, real estate

JEL Classification: M4, L85

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Date posted: February 2, 2013 ; Last revised: December 19, 2013

Suggested Citation

Liang, Lihong and Riedl, Edward J., The Effect of Fair Value versus Historical Cost Reporting Model on Analyst Forecast Accuracy (December 1, 2013). Accounting Review, Forthcoming. Available at SSRN: http://ssrn.com/abstract=2210056 or http://dx.doi.org/10.2139/ssrn.2210056

Contact Information

Lihong Liang
Syracuse University ( email )
Whitman School of Management
Syracuse, NY 13244
United States
Edward J. Riedl (Contact Author)
Boston University - Questrom School of Business ( email )
595 Commonwealth Avenue
Boston, MA MA 02215
United States
617-353-2317 (Phone)
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