Can Disclosure Characteristics Improve Analyst Forecast Accuracy?

Hutchens, Michelle

doi:10.2139/ssrn.3042836

Cited by 13 publications

(4 citation statements)

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“…Because we hypothesize that tax aggressiveness alters the transparency of the firms' aggregate reporting environment (beyond just transparency of tax-specific reporting), in Table 2, Panel B we evaluate analysts' forecast errors of pre-tax income (PRETAX_AFError), after-tax preprint accepted manuscript income (NET_AFError), and implied tax expense (TAXEXP_AFError) for the sample where data are available on analysts' forecasts of these income statement line items (see Hutchens, 2015;Bratten, Gleason, Larocque, Mills, 2017). As described in our Appendix, analysts' forecast error measures adjusted for taxes rely on slightly different I/B/E/S metrics than AFError and AFDisp.…”

Section: The Relation Between Tax Aggressiveness and Transparencymentioning

confidence: 99%

Tax Aggressiveness and Corporate Transparency

Balakrishnan

Blouin

Guay

2018

The Accounting Review

437

288

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We investigate whether aggressive tax planning firms have a less transparent information environment. Although tax planning provides expected tax savings, it can simultaneously increase the financial complexity of the organization. And to the extent that this greater financial complexity cannot be adequately clarified through communications with outside parties, such as investors and analysts, transparency problems can arise. Our investigation of the association between tax aggressiveness and information asymmetry, analysts' forecast errors, and earnings quality suggests that aggressive tax planning is associated with lower corporate transparency. We also find evidence that managers at tax-aggressive firms attempt to mitigate these transparency problems by increasing various tax-related disclosures. Overall, our results suggest that firms face a trade-off between tax benefits and financial transparency when choosing the aggressiveness of their tax planning. JEL Classifications: G30; H26; M41.

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Section: The Relation Between Tax Aggressiveness and Transparencymentioning

confidence: 99%

Tax Aggressiveness and Corporate Transparency

Balakrishnan

Blouin

Guay

2018

The Accounting Review

437

288

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“…Additional recent evidence suggests that analysts underestimate the persistence of earnings created by changes in ETR (Kim et al 2020) and that they do not accurately forecast the implications of auditor‐provided tax services (Francis et al 2019). Consistent with analysts having difficulty with the complexity involved in ETRs, Hutchens (2017) finds that analysts struggle to forecast ETRs when tax disclosures contain legal jargon or complex words.…”

Section: Background and Research Questionsmentioning

confidence: 99%

Street versus GAAP: Which Effective Tax Rate Is More Informative?*

Beardsley

Mayberry

McGuire

2021

Contemporary Accting Res

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This study investigates how sophisticated market participants use tax‐based information by examining whether analysts' street effective tax rates (ETRs) are informative. When assessing firm performance, analysts exclude items they believe do not reflect current performance, resulting in “street” metrics such as street ETR. However, evidence on the properties of the components of street earnings is limited. Examining the informativeness of street ETRs is important because taxes are a significant component of earnings, and the extent to which analysts understand taxes and incorporate them into their analyses is not clear. Using a hand‐collected sample of analyst reports, we find that while approximately 35% of street ETRs have at least one tax‐specific exclusion, over 90% reflect the tax effects of pre‐tax exclusions. Further, both tax‐specific exclusions and the tax effects of pre‐tax exclusions significantly contribute to differences between GAAP and street ETRs. Consistent with analysts' understanding of the implications of tax and nontax exclusions, our results suggest that street tax metrics exhibit greater predictive ability about future tax outcomes and provide more information to investors than GAAP tax metrics. We also find that ETR exclusions are of higher quality when the magnitude of the potentially excluded item is greater and when managers disclose pro forma earnings. Collectively, our findings suggest that analysts understand taxes, but selectively exert effort to incorporate tax‐based information into their assessment of firm performance. Our study should be informative to regulators and users of financial information because it provides evidence regarding the usefulness of street earnings metrics.

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“…However, our study does not delve into whether accounting for the nuanced heterogeneity in the content and type of voluntary disclosure could improve the prediction of earnings or cash flows. Third, we extend the emerging literature that performs textual analyses of tax information (e.g., Hutchens 2017;Inger et al 2018) by introducing a disclosure score that captures the content and type of TLCF information. Our disclosure measure allows us to model disclosure decisions more precisely and to distinguish between the content and type of disclosure to overcome limitations of current natural language processing techniques.…”

Section: Introductionmentioning

confidence: 99%

“…At the same time, such information is not easy to collect, present or comprehend, which provides a unique setting with an unclear cost-benefit balance. Hutchens (2017) identifies disclosure characteristics that improve analysts' understanding of the tax footnote and emphasizes the need for more research examining how disclosure characteristics affect users' ability to process tax information. Our findings improve the understanding of the content and type of voluntary disclosure (e.g., Chen et al 2017;Li 2010;Loughran and McDonald 2016).…”

Section: Introductionmentioning

confidence: 99%

Tax Loss Carryforward Disclosure

Flagmeier,

Müller

2024

Schmalenbach J Bus Res

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This study examines firms’ voluntary disclosure of tax loss carryforward (TLCF) information. We measure the content and presentation of TLCF information by a disclosure score based on hand collected data from annual reports. Our identification strategy employs new proprietary data to control for overall reporting quality. We argue and find that uncertainty about the usability of TLCF is a key driver of voluntary TLCF disclosure. The disclosure score is on average 3.86 points higher for firms with a strong loss history vis-à-vis firms without such a loss history. This positive association is economically meaningful, since the sample mean for the disclosure score is 8.88 (median 7.5). We also find that the content and type of disclosure vary systematically with the signal of uncertainty. In instances of historic uncertainty, firms exhibit increased reporting on the reasons and mechanisms behind changes in TLCF. Conversely, in the case of future uncertainty, they increase disclosure related to valuation allowance information. Our study provides detailed and unique insights into TLCF disclosure, suggesting that managers enrich the information environment with voluntary disclosure that caters to expected investors’ needs.

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Can Disclosure Characteristics Improve Analyst Forecast Accuracy?

Cited by 13 publications

References 0 publications

Tax Aggressiveness and Corporate Transparency

Tax Aggressiveness and Corporate Transparency

Street versus GAAP: Which Effective Tax Rate Is More Informative?*

Tax Loss Carryforward Disclosure

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