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Review of Quantitative Finance and Accounting

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28-01-2021 | Original Research

Discontinued operations and analyst forecast accuracy

Authors: Brooke Beyer, Binod Guragai, Eric T. Rapley

Published in: Review of Quantitative Finance and Accounting | Issue 2/2021

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Abstract

The Financial Accounting Standards Board requires separate reporting of discontinued operations within the income statement to provide better information about companies’ future earnings for financial statement users. However, discontinued operations can increase the complexity of forecasting earnings because a portion of permanent earnings is being eliminated, the future effect on continuing operations may be unclear, and there are incentives for opportunistic reporting. Additionally, anecdotal evidence also shows that analysts, an important proxy for financial statement users, have difficulty in adjusting their forecasts when companies report discontinued operations. This study empirically examines whether reporting of discontinued operations affects analyst earnings forecast accuracy. Our results suggest that forecast accuracy initially declines following the reporting of discontinued operations, and the effect is more pronounced for firms with lower quality discontinued operations disclosures. Results also show the initial decline in forecast accuracy dissipates after a year and is concentrated in firms with potentially more opportunistic reporting within discontinued operations.

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As discussed subsequently in the text, analyst forecast earnings generally focus on continuing operations and exclude discontinued operations (Bricker et al. 1995; Lalli 1997; Mest and Plummer 1999).

The sample does not include firm-year observations after 2014 to limit discontinued operations to APB 30 and SFAS 144 regimes.

Restructuring charges and discontinued operations are similar in the sense that they both represent nonrecurring portions of the current year’s net income. However, their nature, magnitude and potential effect are different enough that only discontinued operations require separate income statement reporting. Due to the separate line-item presentation, we assume that analysts are more likely to be aware of and adjust for discontinued operations compared to restructuring charges. Prior literature has also found different implications for continuing operations. While Chaney et al. (1999) and Lin and Yang (2006) find that analysts reduce their earnings forecasts in response to restructuring charges, Guragai and Hutchison (2020) find continuing operations improve after firms report discontinued operations. Because of the differences, it is not clear that the discontinued operations will necessarily affect analyst forecasts in the same manner as restructuring charges.

Inclusion of firm-year observations in the financial industry does not alter the interpretation of the main results documented in this study.

Testing the magnitude of discontinued operations also helps address concerns related to whether SFAS 144 is driving results. There was an increased occurrence of discontinued operations during the SFAS 144 era, but discontinued operations were generally smaller in magnitude (Barua et al. 2010; Curtis et al. 2014; Ji et al. 2020).

Authors confirmed this with S&P Global Market Intelligence employees (who code data for Compustat database) via emails and a phone conversation.

In a recent study, Guragai et al. (2020) show that managers aggregate the nonrecurring component with the continuing income of discontinued operations, especially in situations where such reporting would allow them to hide large losses on the nonrecurring component of discontinued operations. If managers hide nonrecurring components, it is likely that Compustat reports DONR as missing, further strengthening our argument that missing DONR in Compustat represents poor disclosure quality specific to the discontinued operations.

Reporting_Quality is calculated following Casey et al. (2019), which is based on financial statement disaggregation quality and articulation. Reporting_Quality “is a parsimonious measure of data disaggregation quality in the annual report that can be constructed through counting the number of non-missing financial statement items in Compustat” (Casey et al. 2019). An advantage of utilizing this measure is its robust coverage of our firm-year observations.

DO_Indicator = 1 (i.e., discontinued operations are reported) for all 4,580 firm-year observations that have values for DO_Detail and Reporting_Quality. Therefore, “n/a” is shown for DO_Indicator correlations with DO_Detail and Reporting Quality because there is no variation in DO_Indicator data due to variable construction.

Although a negative relation is expected, the results show a positive coefficient estimate for Analysts_initial_t+1. Further investigation reveals this is due to its high positive correlation between Analysts_initial_t+1 and Size (Table 3 reports correlation of 0.656). When the model is estimated (untabulated) without including Size variable, the coefficient estimate for Analysts_initial_t+1 is negative and significant. Similarly, two of the EarnVol coefficient estimates are not as expected (i.e., positive). Further investigation reveals this is due to its correlation with the model’s Loss variable (Table 3 reports correlation of 0.307).

The discretionary component of discontinued operations would lead to an increase in forecasting complexity. However, the discretionary component is unobservable and estimated with error. As a heuristic, we are using firms with income-decreasing discontinued operations because they would have a greater likelihood of discretionary expenses being shifted from core earnings to discontinued operations. Furthermore, the possibility of classification shifting (instead of just actual misreporting) may contribute to forecasting complexity. This provides additional support for splitting analysis between income-decreasing and income-increasing discontinued operations.

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Title: Discontinued operations and analyst forecast accuracy
Authors: Brooke Beyer
Binod Guragai
Eric T. Rapley
Publication date: 28-01-2021
Publisher: Springer US
Published in: Review of Quantitative Finance and Accounting / Issue 2/2021
Print ISSN: 0924-865X
Electronic ISSN: 1573-7179
DOI: https://doi.org/10.1007/s11156-021-00956-7

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