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Review of Accounting Studies

Erschienen in:

01.06.2016

Analysts’ pre-tax income forecasts and the tax expense anomaly

verfasst von: Bok Baik, Kyonghee Kim, Richard Morton, Yongoh Roh

Erschienen in: Review of Accounting Studies | Ausgabe 2/2016

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Abstract

This paper examines whether analysts’ pre-tax income forecasts mitigate the tax expense anomaly documented by Thomas and Zhang (J Account Res 49:791–821, 2011). They find that seasonal changes in quarterly income tax expense are positively related to future returns after controlling for the earnings surprise and conclude that investors underreact to value-relevant information in tax expense. When analysts issue both earnings and pre-tax income forecasts, they implicitly provide a forecast of income tax expense. We posit that this implicit forecast helps investors recognize the persistence of current tax expense surprise for future earnings. Accordingly, we expect that mispricing of tax expense will be less severe for firms with earnings and pre-tax income forecasts. As expected, we find that the presence of pre-tax income forecasts significantly weakens the positive relation between tax expense surprise and future returns, consistent with analysts’ implicit forecasts of tax expense mitigating the tax expense anomaly.

Vorheriger Artikel The effects of anticipated future investments on firm value: evidence from mergers and acquisitions

Nächster Artikel Errors and questionable judgments in analysts’ DCF models

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Although Hanlon et al. (2005) frame their analysis in terms of changes in taxable income, they estimate taxable income by grossing up current income tax expense at the maximum statutory rate.

Although supplemental forecasts of pre-tax income were relatively scarce before 2002, the numbers have increased substantially such that roughly 60 % of analysts in the I/B/E/S database now issue both pre-tax and after-tax income forecasts.

As Thomas and Zhang discuss, their use of changes in tax expense to identify a “momentum” anomaly differs fundamentally from the ratio of tax and book income levels used by Lev and Nissim (2004) and Weber (2009). Thomas and Zhang find that these two variables exhibit nearly independent relations with future returns.

Thomas and Zhang (p. 798) note: “If investors have difficulty projecting the implications of earnings and accruals, it is likely that investors have more difficulty projecting the implications of tax variables.”

Radhakrishnan and Wu (2014) and Mohanram (2014) address these alternative explanations and conclude that, while they contribute to a decline in the accrual anomaly, cash flow forecasts have a significant incremental effect.

This ensures that a tax expense investment strategy could be implemented based on initial information released to the market. However, when we conduct our analyses using restated information, results remain unchanged.

We find some pre-tax income forecasts available in the fourth quarter of 2001, but the number of forecasts (25 firms) is extremely small compared to the total number of earnings forecasts in that quarter.

Thomas and Zhang also include a tax change component (TCC) in their model. Because we find that TCC is highly correlated with tax expense surprise (correlation = 0.376 with p value < 0.01), we drop TCC from the model to avoid potential multi-collinearity with our variable of interest. However, our results hold even when TCC is included in the model.

We follow Thomas and Zhang and use a return accumulation period beginning three months after the quarter’s end. This provides greater assurance that tax expense information would be available to market participants. If tax expense is not disclosed at the time of the earnings announcement, it would be available with the release of the 10-Q or 10-K.

Using per share amounts rather than undeflated amounts conforms to the approach of Thomas and Zhang and is particularly relevant in our setting because financial analysts provide per-share-basis forecasts.

If these variables are missing in the quarterly database, we instead use the imputed value from the annual database. If these are still missing, we treat such variables as having a value of zero.

Our inferences remain the same when we use raw values.

We analyze a more recent period (2002–2013) with larger market values than Thomas and Zhang’s sample period (1977–2007).

Although we employ similar models, the coefficient estimates in our Table 3 differ considerably from Thomas and Zhang’s because we transform independent variables using quintile ranks to fit the unit interval.

To further control for the possibility that D_TAXF_i,q proxies larger firms with a richer information environment, we also interact ΔTAX_i,q with firm size and include that in our model. We continue to find that the coefficient on ΔTAX_i,q*D_TAXF_i,q is negative and significant (t-stat. = − 3.44).

DeFond and Hung (2003) model the decision to issue a cash flow forecast. However, we note in Table 2 that these same explanatory variables are significantly different for firms with and without pre-tax income forecasts.

In untabulated subsample analysis, we find that our inferences remain unchanged when we exclude firm-quarters without any analyst following or firms without any pretax income forecasts across the sample period.

We further examine whether the number of pre-tax income forecasts has an incremental effect beyond the presence of pre-tax income forecasts. When we add PTIF and its interaction with ΔTAX to the models reported in Table 4, we find that the coefficient on ΔTAX*N_PTIF is insignificant, while the coefficient on ΔTAX*D_TAXF remains significantly negative (results untabulated). This implies that the presence of pre-tax income forecasts is more important than the number of pre-tax income forecasts with respect to dissipation of the tax expense anomaly.

Unlike our multivariate regression results reported in Table 5, which show little evidence of an incremental role for cash flow forecasts, the hedge portfolio analysis reported in Table 6 does not control for the accrual and other market anomalies that could be correlated with the tax expense anomaly.

Results are robust to using 5, 7, or 11 firm-quarters centered on the initiation event.

In untabulated analysis, we also construct a matched-pair sample using the initiation and pseudo intiation quarters of the constant and matched samples and re-estimate Eq. (1). We find that the actual initiation of pre-tax forecasts, relative to the pseudo initiation, is associated with less mispricing in this combined sample (t-stat = −3.08).

We also compute CAR(−5, 5)_q+1 and CAR(−3, 3)_q+1 and find that our inferences are similar.

In contrast to McInnis and Collins (2011), who conclude that implicit forecasts of accruals improve accrual quality, the scenario we describe would imply the opposite effect. That is, implicit forecasts of income tax expense would have to result in lower quality tax expense.

Evidence of positive correlation in analysts’ forecast errors is consistent with prior research suggesting that analysts are not fully efficient. See Ramnath et al. (2008) for a review.

We also calculate hedge portfolio returns based on quintiles of the analysts’ tax expense surprise and find an insignificant abnormal return of 0.035 %.

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Titel: Analysts’ pre-tax income forecasts and the tax expense anomaly
verfasst von: Bok Baik
Kyonghee Kim
Richard Morton
Yongoh Roh
Publikationsdatum: 01.06.2016
Verlag: Springer US
Erschienen in: Review of Accounting Studies / Ausgabe 2/2016
Print ISSN: 1380-6653
Elektronische ISSN: 1573-7136
DOI: https://doi.org/10.1007/s11142-016-9349-z

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