Determinants and Consequences of Presentation Format: The Case of ETR Reconciliations Roman Chychyla * Diana Falsetta † Sundaresh Ramnath ‡ ABSTRACT: SEC Regulation S-X requires companies to reconcile deviations be- tween their actual tax expense and their expected tax expense under federal statutory tax rates (effective tax rate (ETR) reconciliation). However, companies can choose between a dollar or percentage format for the ETR reconciliation. In our sample, roughly half the firms choose one of the two formats. We investigate the causes and consequences of this disclosure decision. We find, consistent with a political cost ar- gument, that firms with low (high) ETRs tend to highlight the dollar (percentage) amount of their tax expense, suggesting a strategic choice of presentation method. We also find that users such as analysts seem to find the percentage format easier to use and tend to make smaller errors in their ETR forecasts when firms present their ETR reconciliation in the percentage format, consistent with analysts’ comfort (struggles) when information is presented in an easily usable (less straightforward) format. A follow up experiment confirms that participants presented with the percentage format make more accurate tax expense forecasts than do participants presented with the dol- lar format. * Roman Chychyla: School of Business Administration, University of Miami, Coral Gables, FL 33146. Email: [email protected]. Phone: (305) 284-2324. † Diana Falsetta: School of Business Administration, University of Miami, Coral Gables, FL 33146. Email: [email protected]. Phone: (305) 284-8624. ‡ Sundaresh Ramnath: School of Business Administration, University of Miami, Coral Gables, FL 33146. Email: [email protected]. Phone: (305) 284-6668.
Transcript
Determinants and Consequences of
Presentation Format: The Case of ETR
Reconciliations
Roman Chychyla∗
Diana Falsetta†
Sundaresh Ramnath‡
ABSTRACT: SEC Regulation S-X requires companies to reconcile deviations be-tween their actual tax expense and their expected tax expense under federal statutorytax rates (effective tax rate (ETR) reconciliation). However, companies can choosebetween a dollar or percentage format for the ETR reconciliation. In our sample,roughly half the firms choose one of the two formats. We investigate the causes andconsequences of this disclosure decision. We find, consistent with a political cost ar-gument, that firms with low (high) ETRs tend to highlight the dollar (percentage)amount of their tax expense, suggesting a strategic choice of presentation method. Wealso find that users such as analysts seem to find the percentage format easier to useand tend to make smaller errors in their ETR forecasts when firms present their ETRreconciliation in the percentage format, consistent with analysts’ comfort (struggles)when information is presented in an easily usable (less straightforward) format. Afollow up experiment confirms that participants presented with the percentage formatmake more accurate tax expense forecasts than do participants presented with the dol-lar format.
∗Roman Chychyla: School of Business Administration, University of Miami, Coral Gables, FL 33146.Email: [email protected]. Phone: (305) 284-2324.†Diana Falsetta: School of Business Administration, University of Miami, Coral Gables, FL 33146. Email:
[email protected]. Phone: (305) 284-8624.‡Sundaresh Ramnath: School of Business Administration, University of Miami, Coral Gables, FL 33146.
In this study we investigate the causes and consequences of the effective tax rate (ETR)
reconciliation presented in the footnotes to companies’ annual reports (10-K). Prior research
has shown that the format of presentation influences reader/investor perceptions. Nelson
and Rupar (2014), in their experimental setting, examine the consequences of presenting
earnings changes in a percentage vs. dollar disclosure format, and find that investors perceive
potential earnings decreases as riskier when disclosures are presented in dollars than when
they are presented as percentages. In this paper, we examine in an archival setting, the
determinants, as well as the consequences, of the percentage vs. dollar choice of disclosure
format in ETR reconciliations presented in the footnotes to firms’ 10-Ks.
The ETR reconciliation presentation in firms’ 10-Ks is an ideal setting to examine the
determinants of firms’ potentially strategic choices of disclosure format as opposed to dis-
closure content. Both the dollar and percentage formats convey the same information, in
that each method contains enough information to be converted into the other, with minimal
skill or effort; thus, firms’ choices are more likely driven by the expected reaction of readers
to the form of the presentation, rather than its substance. In addition, the ETR setting
also presents us with an opportunity to examine how even sophisticated investors, such as
analysts, could be affected by information presented in different formats. Investors value
post-tax earnings, which makes tax expense an important component of the earnings fore-
cast. While both dollar and percentage format presentations can easily be converted into the
other, presentation of information in a format that better helps predict tax expense will also
improve estimates of forecasts of post-tax earnings. We argue that reconciling tax expense
in percentages presents tax information in a format that is more readily usable by market
participants because future tax expense is a function of future pre-tax income and expected
effective tax rates (ETR, which is a percentage of pre-tax income).
While firms may benefit from providing information in a user friendly format, they also
1
face the costs of potential political scrutiny if the presentation format draws attention to the
seemingly lower taxes that they pay.1 Expressing ETRs in percentages when the effective
tax rate is low may draw attention to how little taxes some of the profitable companies may
be paying, which could drive them to strategically divert attention to the dollar amount of
tax expense reported, rather than to the equivalent percentage of tax expense. Consistent
with this political cost argument, we find that firms that pay lower (higher) taxes relative
to their pre-tax income, tend to reconcile ETRs in dollar amounts (percentages). A one
standard deviation increase in a firm’s ETR increases the likelihood of the firm using the
percentage format by 12.32%. We find this effect of ETR level on ETR reconciliation format
to be more pronounced for firms with higher marginal political cost as measured by firm
size and firm’s media coverage. Moreover, for the sample of firms that switched their ETR
reconciliation format, we document the likelihood of switching to the percentage format is
positively associated with the level of ETR, such that a one standard deviation increase in
the firm’s ETR increases the likelihood of the firm switching to the percentage format by
66.74%.
In terms of consequences, we find that analysts’ forecasts of ETRs tend to be more
accurate when firms present reconciliations in percentages than in dollars. Specifically, we
document that using the dollar format increases analyst tax expense forecast error by $3.63
million on average. While it seems simple enough to translate tax expense in dollars into
percentages (ETRs), analysts seem to either not exert the effort or not understand the
concept of ETRs in making their predictions.
We also investigate relative forecast accuracy of tax expense across the two ETR formats
in a laboratory setting. Ninety-two participants responded to an online survey, in which they
were randomly assigned to one of the two ETR reconciliation formats, and asked to forecast
tax expense based on a given pretax income amount. Consistent with the archival-empirical
1Although all companies are required to discuss changes in the ETR in their MD&A, the MD&A is notaudited like footnotes and there are concerns that it contains mainly boilerplate and generic disclosures (SEC2003); therefore, we focus on footnote disclosures, even though ETRs may be presented and discussed in theMD&A section.
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results, we find that participants presented with the percentage format were more accurate
in predicting tax expense than were participants with the dollar format.
Our findings are important to regulators and investors, as well as constituents that care
about corporate social responsibility. The presentation format can influence users’ percep-
tions of the contributions that corporations make to society and could also affect sophisti-
cated users’ forecasts of future estimates of corporate tax expense. Our results also highlight
the importance of the significance of users’ ability to easily translate one format of presen-
tation to a more usable format.
II. MOTIVATION AND HYPOTHESES
The Securities Exchange Commission (SEC) and the Financial Accounting Standards
Board (FASB) promulgate the required disclosures of public companies. In particular, SEC
Regulation S-X, Rule 4-08(h) and FASB ASC 740-10-50-12 provide guidance on the required
disclosure of the income tax footnote, including the effective tax rate (ETR) reconciliation.
Mounting scrutiny of the corporate tax burden and social responsibility has increased the
attention and focus on the income tax footnote disclosure. For example, companies, such
as Apple Inc., Google Inc., and Starbucks have drawn extensive media attention and public
scrutiny for their very low tax rates (Duhigg and Kocieniewski 2012), as well as governmental
scrutiny as evidenced by the number of comment letters issued by the SEC related to income
tax disclosures. Despite being in the media spotlight, very little public information revealing
their true tax burden is available, aside from that presented in the income tax footnote of
the 10-K filings (Christians 2012; Donohoe, Gary, and Outslay 2012; Hanlon 2003; Lisowsky
2009).
At the 2014 AICPA National Conference on SEC and PCAOB Developments, the SEC
staff highlighted its attention to the topic of income taxes for year 2015. In particular, the
SEC staff noted that they have increased focus on the ETR reconciliation disclosure, valu-
ation allowance, unremitted foreign earnings, as well as areas that require the judgment of
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management. In fact, during 2015, 30 percent of the comment letters issued by the SEC
related to the ETR reconciliation (PwC 2015). Recently, as part of its broader disclosure
framework project, the FASB began reconsidering the income tax disclosure. Its stated ob-
jective was to improve the effectiveness of disclosures in the notes to financial statements
and to reduce complexity in the accounting standards by clearly communicating the infor-
mation that is most important to users of an entity’s financial statements. As part of this
project, the Board considered a number of changes to the existing income tax disclosure
requirements, including changes to the ETR reconciliation, valuation allowance, indefinitely
reinvested foreign earnings, and unrecognized tax benefits (FASB 2016). In recent years,
accounting and securities regulators seem to be increasingly concerned about, and paying
attention to, income tax disclosures.
Given the attention from the various constituents, companies could avoid scrutiny by
being transparent and reporting ETRs that seem equitable and fair. Consistent with the
political cost hypothesis (Watts and Zimmerman 1978), to reduce politically imposed wealth
transfers, companies may choose strategies that would decrease the expected likelihood of
wealth transfers. In recent years, firms’ tax rates have come under increased scrutiny from
a social equity perspective. Successful, highly profitable companies, like Apple, have come
under fire, both within the U.S. and in European countries for their tax-minimizing strategies.
For example, the EU recently imposed a $15 billion tax bill on Apple claiming that they were
not paying their fair share of taxes for business conducted in Europe. Profitable companies
that face high political costs for their seemingly low contributions by way of tax payments,
may seek to minimize attention to their low tax rates (as a percentage of pre-tax income) and
instead emphasize the dollar amount in taxes paid. Hite and Roberts (1991), for example,
examine the perception of subjects to individual income tax burdens expressed in dollars vs.
percentages (of income). Respondents seemed to assess higher tax burdens when assessing
taxes in percentages than when they were asked to assess taxes in dollars for hypothetical
taxpayers, suggesting that the dollar format may lead to a higher perception of tax burden
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than warranted by equivalent percentages. On the other hand, companies that pay a bigger
percentage of their income in taxes may wish to emphasize their ”good citizenship” by
presenting tax information in percentages (i.e., emphasizing that they pay a larger proportion
of their income in taxes).
Prior research in psychology and accounting has shown that numerical formats can in-
fluence individual judgments and decisions. In particular, numerical format can influence
individual’s perception of the size of an amount (Paivio 1991; Denes-Raj, Epstein, and Cole
1995), and investors’ assessment of risk (Nelson and Rupar 2014). Accordingly, we would
expect that manager’s decision to report in dollars or percentages could impact financial
statement users’ perceptions of the corporate tax burden.
As mentioned earlier, publicly traded companies are required to disclose an ETR recon-
ciliation in its financial statement footnotes using either a percentage or dollar format. The
ETR reconciliation serves to disclose the underlying causes of differences between the actual
total income tax expense (benefit) reported on the income statement and the expected fed-
eral tax (benefit) at the statutory tax rate (i.e., “hypothetical tax”). A reconciling item is
deemed significant and must be listed separately if it exceeds five percent of the hypothetical
tax. Components that cause the ETR to vary from the typical statutory rate of 35% are
items, such as state and local income taxes, taxes on income in foreign jurisdictions, and
permanent items (i.e., tax credits, tax-exempt income, and non-deductible expenses).
In Appendix A, we provide an example of an ETR reconciliation in each format, dollars
and percentages, for Google Inc. and Facebook Inc. Google reports its ETR reconciliation in
the dollar format, while Facebook reports in the percentage format. Facebook’s total pre-tax
book income (PTBI) and total tax expense for year ended December 31, 2015 was $6,194
million and $2,506 million, respectively. If all of its PTBI were taxable on its federal tax
return, its expected tax provision for 2015 would have been $2,167.9 million ($6,194 × 35%)
before any tax credits. However, its actual tax provision reported on its income statement
was $2,506 million, or an ETR of 40.4% ($2,506 / $6,194).
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Google, Inc. reported total PTBI and total tax expense for the year ended December 31,
2015 in the amounts of $19,651 million and $3,303 million, respectively. If all of its PTBI
were taxable on its federal tax return, its expected tax provision for 2015 would have been
$6,878 ($19,651 × 35%) before any tax credits. However, its actual tax provision reported
on its income statement was $3,303 million, or an ETR of 16.8% ($3,303 / $19,651).
Given the above information, it should be noted that regardless of format, one presen-
tation format can be converted into the other with minimal effort. As these two examples
above illustrate, the company that has the higher ETR (Facebook), would prefer to em-
phasize the fact that it is paying more per dollar of taxable income, whereas, the company
with the lower ETR (Google) would prefer to emphasize the larger dollar amount of its tax
burden.
Based on this political cost argument, we present our first hypothesis (in alternate form):
Hypothesis 1 Firms with lower (higher) ETRs are more likely to use dollar (percentage)
format in their ETR reconciliations.
We next examine the consequences of firms’ choice of a particular format of presenting
ETR reconciliation in their tax footnotes. Most financial statement textbooks advocate
forecasting line items on the income statement up to pre-tax income, and then applying
current (or some form of average) firm-specific ETR to compute tax expense, to finally
arrive at forecasted net income. When the ETR reconciliation is presented in the percentage
format, the final line of the reconciliation is the firm’s current ETR expressed as a percentage
of income, which can be readily used in making forecasts of future tax expense. While
converting a dollar format presentation to ETR is relatively straightforward, prior research in
psychology and consumer behavior document subjects’ inability to freely transition between
dollars and percentages even when the calculations are fairly simple (Krishna et al. 2002).
While one would expect sophisticated users, like financial analysts, to be less vulnerable to
these shortcomings, prior research demonstrates analysts’ failure to make seemingly easy
adjustments when the information is less readily available, for example included in footnotes
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(Johnston et al. 2012). Thus, we expect that analysts’ forecast of tax expense (ETR) will be
more accurate for firms that present information in percentage format rather than in dollar
format.
Hypothesis 2 Analyst ETR forecasts are more accurate for firms that present their ETR
reconciliation in percentage format.
III. DATA AND DESCRIPTIVE STATISTICS
We start by classifying firm ETR reconciliation reporting format found in the footnotes
to financial statements as either percentage or dollar. First, we download all 10-K filings
available at the SEC’s Electronic Data Gathering, Analysis, and Retrieval (EDGAR) system.
We require 10-K filings to be prepared in Hyper Text Markup Language (HTML) format
(as opposed to plain-text format) in order to be able to extract ETR reconciliation tables
found in tax footnotes.2 Although, the SEC started accepting 10-K filing in HTML format
on June 28, 1999, HTML reporting had not been widely adopted until the end of 2001. As
a result, we limit our sample to the 2002-2015 fiscal years.
Using an automated procedure, we are able to extract 58,794 tax footnotes from 115,286
10-K filings. The lower number of footnotes compared to the overall number of filings is
likely due to either 1) the 10-K being reported in a plain text format as opposed to HTML,
2) tax footnote not being reported in an exhibit (i.e., not in the main 10-K HTML file),
3) extracted tax footnote being too short (less than 100 words), 4) tax footnote not being
reported, or 5) automated algorithm not being able to reliably identify the tax footnote. We
randomly select 300 extracted footnotes to check the accuracy of the footnote tax extraction
process and find the extraction algorithm to be correct in 97% of all cases.3
We then employ another automated procedure to extract the ETR reconciliation table
2HTML requires a uniform syntax to represent tabular structures using HTML tags (such as <table>todenote a table, <tr>to denote a row, and <th>to indicate a column). We use this syntax to parse HTMLtables.
3The 3% error rate is unlikely to impact the accuracy of ETR reporting format classification since werequire a tax footnote to contain a tax reconciliation table.
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and classify the ETR reporting format as either percentage, dollar, or both (percentage and
dollar). Overall, we are able to classify 42,993 tax footnotes of 9,493 unique firms. Manual
verification of 300 extracted footnotes indicate that about 18% of tax footnotes in our sample
do not have a tax reconciliation table due to them being loss firms, exempt from tax, REIT,
etc.4 In around 8% of all cases, the algorithm was not able to reliably classify a tax footnote
due to inconsistency in reporting, and in 6% the classification was incorrect.
We define a firm-year observation as a “percentage” (“dollar”) observation for all firm-
years starting with the first year we can identify the firm as using percentage (dollar) format
and ending with the last year in which we can unambiguously verify that they still use the
percentage (dollar) format. In our main analysis, we classify firm-year observations that
disclose the ETR reconciliation in both percentages and dollars as “percentage” firms since
all our predictions related to “percentage” firms outlined in the previous section will apply to
firms that choose the “percentage and dollar” format as well.5 For example, in Hypothesis 1
(H1) we predict that firms with higher ETRs are more likely to disclose the higher percentage
of pre-tax income that they pay in taxes (i.e., are more likely to be a “percentage” firm);
firms that disclose both percentages and dollars, by way of disclosing the percentages, satisfy
our definition of a “percentage” firm for this hypothesis. In other words, whether to disclose
ETR percentages (or not) is the strategic decision. We do not expect firms to use both
dollars and percentages if they are trying to avoid scrutiny (i.e., low ETR firms); only firms
that are willing to let their ETRs be known in percentages (i.e., high ETR firms), are likely
to add the dollar presentation. The application of H2 to the “ percentage and dollar ” firms
are even clearer - once a firm reveals ETR percentages (as a “ percentage and dollar ” firm
does), we expect analysts to be more accurate in their ETR predictions (much like with pure
“percentage” firms).
The format choice is sticky with only 883 firms out of our total sample of 9,679 unique
4A loss firm may still have a tax reconciliation table with negative ETR (i.e., tax refund).5We do not find qualitatively different results when we repeat our analysis using only “percentage” and
“dollar” format observations (and excluding “percentage and dollar” observations).
8
firms switching their presentation method over the sample period. Our initial sample includes
48,974 firm-years. This sample reduces to 29,112 firm-year observations for 5,413 unique
firms after we impose Compustat data restrictions needed for our analyses. Furthermore,
only 7,445 firm-year observations (for 2,400 unique firms) have related analyst forecast data
in IBES. The sample attrition process is summarized in Panel A of Table 2.
For the analyst sample, we include all observations where there is at least one annual
forecast for year t + 1, of both pre- and post-tax income (Baik et al. 2016), made within
30 days after the 10-K filing date for year t. We also exclude observations where the IBES
reported actual pre-tax income is negative. Analysts do not make explicit ETR forecasts;
however, we can compute them based on their pre- and post-tax forecasts available on IBES:
Analyst ETR Forecasti,t =Pretax Income Forecasti,t − Posttax Income Forecasti,t
Pretax Income Forecasti,t
We compute analysts’ ETR forecast for a given firm-year made within 30 days after the
previous year’s 10-K filing date. We estimate analyst ETR forecast error as the absolute
value of the difference between actual ETR (computed similar to forecasted ETR, above, but
using “actuals” data from IBES) and forecasted ETR. AnalystETRError is then computed
as the median analyst ETR forecast error for a given firm-year. Precise definition and
measurement of all variables are provided in Table 1.
In Table 2 Panels B and C, we report the mean and median values for select variables
across the two samples (all continuous variables are winsorized at 1% and 99% of their val-
ues). In Panel B, consistent with our political cost argument and Hypothesis 1, we find
that the mean and median ETRs for the percentage sample are higher than the dollar sam-
ple (significant at the 1% level). The percentage firms also have lower variability of ETR
(ETRRange), are significantly larger (Log(Assets)), older (Log(Age)), operate in more lines
of business (NumBus), report more geographical segments (NumGeo), have less leverage
(Leverage), greater market-to-book ratio (MTB), and foreign operations (Foreign). Accord-
9
ingly, in our multivariate analysis of the relation between ETR and presentation format we
control for these significant differences in firm characteristics.
Panel C of Table 2 presents initial evidence in support of Hypothesis 2. Analysts’ ETR
forecast errors are smaller when companies present ETR reconciliation in the percentage
format, consistent with analysts finding the percentage format more useful in forecasting
future tax expense. However, analysts’ pre-tax earnings forecast error (AnalystPreTaxEarn-
Error) are also lower for the percentage sample, suggesting that these firms may be more
predictable, in general. Therefore, we control for the magnitude of the pre-tax earnings
forecast error (proxy for predictability) in multivariate tests of the association between ETR
presentation format and ETR forecast accuracy.
In Panel D of Table 2, we report the number and percentage (in parentheses) of firm-year
observations that use percentage and dollar ETR presentation format across different levels
of ETR. When ETR is low (below 15%), around 53% of observations use the dollar format.
Yet, as ETR increases to 25% and levels above, more firms (around 55%) tend to use the
percentage format. This pattern is consistent with our predictions.
Panel E of Table 2 reports the usage of percentage versus dollar format in ETR recon-
ciliation presentation across “Big Four” auditors. Consistent with the descriptive statistics
in Panel A, most clients of PwC and Deloitte tend to use the percentage format (62% and
60%, respectively), while most KPMG clients tend to use the dollar format (around 53%).
EY and other audit firms have a balanced distribution of percentage and dollar usage across
their clients.6
Table 3 presents the Spearman correlations between our main variables of interest as well
as control variables. In Panel A, ETRs are positively correlated with presentation format
(percentage format = 1, 0 otherwise). Further ETR forecast errors are negatively correlated
with ETR presentation format (Panel B), consistent with smaller forecast errors for firms
6The auditor-related figures in Panels B and E are different because Panel B reports the proportionof firm-year observations audited by a given auditor across all percentage (dollar) firm-year observations,whereas Panel E reports the relative proportion of firms using the percentage (dollar) format across allfirm-year observations audited by a given auditor.
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using the percentage format, documented in Table 2, Panel C. Correlations between other
variables are generally consistent with prior research.
IV. HYPOTHESES TEST AND RESULTS
ETR Reconciliation Presentation Formats and ETR levels
We first empirically test Hypothesis 1 that predicts a positive association between ETR
reconciliation presentation format and firm-year ETR level.
Table 4 shows results of logistic regression analysis with ETR presentation format (Per-
centageFormat) as a dependent variable and ETR level (ETR) as the primary independent
variable. PercentageFormat takes a value of one if the reconciliation is in percentages, and
zero if it is in dollars. In Column (1), we present the results of a simple logistic regression
with no control variables. Consistent with the prediction in H1, we find that ETR presenta-
tion format is positively associated with ETR levels (p < 0.01), confirming that firms with
higher (lower) ETRs tend to emphasize the proportion of income (amount in dollars) paid
in taxes.
In the second column of Table 4, we control for other possible determinants of presentation
format choice and cluster standard errors on firm and years. Consistent with the univariate
descriptive statistics in Table 2, we find that firms that are more likely to disclose using
the percentage format have smaller variation in ETR, are bigger, are less levered, are less
profitable, have higher market-to-book ratio, have foreign operations and tend to operate
in litigious industries. The evidence is also consistent with PwC and Deloitte favoring the
percentage format and KPMG favoring the dollar format, after controlling for these other
firm characteristics. More importantly, even after controlling for other possible determinants
of ETR reconciliation presentation choice, we find that firms with higher (lower) ETRs choose
to present their ETR reconciliation in the percentage (dollar) format (p < 0.01), which is
consistent with our political cost hypothesis (H1). The effect of ETR levels on presentation
choice is economically significant: one standard deviation increase in a firm’s ETR increases
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the likelihood of ETR presentation using the percentage format by 12.32%.
A possible concern is that our results are driven by an omitted endogenous variable that
might independently affect the ETR reconciliation presentation format and firm ETR levels.
To mitigate this concern we perform two additional analyses in addition to the main one
presented in Table 4.
First, we posit that for some firms political costs are likely higher than for other firms.
Specifically, we use two proxies for political cost discussed in the literature: firm size (Zim-
merman 1983) and media coverage (Wong 1988; Piotroski, Wong, and Zhang 2015). If the
conjecture in Hypothesis 1 is true, the choice of ETR reconciliation presentation format will
be more important for firms that face greater political costs. In other words, we expect the
association between ETR presentation format and ETR levels to be stronger for larger firms
and firms with greater media coverage. To test this prediction, we measure firm size in a
given fiscal year using its pre-tax income.7 We measure media coverage for a given firm in a
given fiscal year as the number of articles related to this firm that appeared in that year in
the top national news outlets, Wall Street Journal, New York Times, Washington Post, and
USA Today. The data on media articles is obtained from the RavenPack database.
Table 5 shows the results of cross-sectional analysis with ETR presentation format (Per-
centageFormat) regressed on ETR level (ETR), indicator variable for the highest quartile of
pre-tax income (HighPreTaxIncome), indicator variable for the highest quartile of firm’s me-
dia coverage (HighMediaCoverage), and their respective interactions (ETR×HighPreTaxIncome)
and ETR×HighMediaCoverage). We expect the coefficients of the interaction terms to be
positive and significant if the relationship between ETR reconciliation formats and ETR
levels is stronger for firms with the greatest visibility. In Column (1), the coefficient of
ETR×HighPreTaxIncome is 0.959 (p < 0.05), and in Column (2) the coefficient of ETR×HighMediaCoverage
is 1.266 (p < 0.01). These results provide further evidence in support of Hypothesis 1.
Finally, we also examine the sample of firms that switched their ETR reconciliation pre-
7We use pre-tax income since it is directly related to income taxes and ETR. We find similar results whenwe use sales as a proxy for size.
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sentation format from dollar to percentage format or vice versa. This is a sample comprising
of firm-year observations for 240 switches from dollar to percentage format and 179 switches
from percentage to dollar format (that have required Compustat data). The advantage of
using this sample is that an ETR format switch more accurately captures the active choice
of a firm to use percentage (or dollar) format rather than it being an inherent (or historical)
decision. If our political cost argument outlined in Hypothesis 1 is correct, we should observe
firms with relatively higher ETRs switching to the percentage format, and firms with lower
ETRs switching to the dollar format.
For every switch event in our sample, we take firm-year observations up to five years
following the switch and regress the switch format (SwitchToPercentageFormat) on ETR
level (ETR) and firm characteristics.8 Variable SwitchToPercentageFormat is equal to one if
the firm switched to percentage ETR reconciliation format, and zero otherwise. We report
the results in Table 6. Column (1) presents the results of a simple logistic regression where
the ETR presentation format (after the switch) is regressed on ETR. We find a significant
positive association between these two variables (p < 0.01). Column (2) reports the results
of a conditional logistic regression where a number of firm characteristics are included as
controls. Consistent with H1, we find that firms that switch to the percentage format have
higher ETRs, on average (p < 0.01). We also document that these firms tend to have
lower variability in ETR, are bigger, and have higher market-to-book ratio. In terms of
economic significance, we find that a one standard deviation increase in ETR increases the
likelihood of a firm switching to the percentage (as opposed to dollar) format by 66.74%.
This likelihood for the switch sample is much greater than the one we documented for the
full sample (12.32%) suggesting that the level of ETR is a very important factor affecting
the decision of a firm to switch to a different ETR reconciliation presentation format.
8We go five years out because the decision to switch is likely a long horizon decision (i.e., firms are morelikely to switch based on expectations of the long-run ETR). We repeat the analysis by using only oneobservation per firm (the year of the switch) and find similar results.
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Analyst Forecasts and ETR Presentation Formats
Next, we empirically examine Hypothesis 2 that predicts lower ETR forecast errors for
firms that present the ETR reconciliation in the percentage format.
In Table 7, we present the results of our tests of the impact of presentation format on
analysts’ ETR/tax expense forecasting accuracy. In the first column, we regress analysts’
ETR forecast errors (AnalystETRError) on solely the presentation format (PercentageFor-
mat), and find that the coefficient on PercentageFormat is significantly negative (p < 0.01),
suggesting that analyst forecasts of ETR are more (less) accurate when firms present ETR
reconciliations in the percentage (dollar) format. Consistent with H2, this evidence suggests
that analysts seem to better predict future tax expense when the previous year’s taxes are
readily available as a percentage of pre-tax income.
It is likely that the future performance of percentage (dollar) firms are generally more
(less) predictable on all dimensions, not just ETRs (i.e., other components of income are
also more (less) predictable). To control for this, in the second column of Table 7, we
include the variability in ETR over the last three years (ETRRange) and the error in an-
alysts’ pre-tax earnings forecasts (AnalystPreTaxEarnError) as proxies for predictability.9
Motivated by Ramnath, Rock, and Shane (2005), who show that analyst earnings forecast
accuracy is increasing in the number of analysts following the firm, we also control for the
number of analysts following the firm (NumAnalyst). We find that the ETR forecast er-
ror is negatively related to the number of analysts following the firm, positively related to
ETR variability (ETRRange), and positively related to earnings predictability proxied by
AnalystPreTaxEarnError. Even after controlling for these potential determinants of ETR
forecast accuracy, we find that the percentage format is negatively related to AnalystETR-
Error (p < 0.01), consistent with analysts making more accurate tax expense predictions for
firms that use the percentage format for their ETR reconciliations.
9The Spearman correlation between AnalystETRError and AnalystPreTaxEarnError is significantly pos-itive in Table 3, Panel B, confirming that the two variables are related.
14
In Column (3) of Table 7, we include additional controls, but still document similar effects
for our main variable of interest. The estimated coefficient of PercentageFormat variable is
-0.005 (p < 0.01), which translates to a $3.63 million decrease in analyst tax expense forecast
error when percentage format is used, given the average pre-tax income of $726.2 million in
our forecast analysis sample. Overall, our results in Table 7 provide strong support for the
percentage format being more user friendly than the dollar format in forecasting future tax
expense.
ETR Reconciliation Presentation Format and ETR Forecast Accuracy. Evidence
from an Experiment
Experimental Method
We conducted an experiment to isolate the presentation format effect, keeping all else
equal (i.e., financial statement information), and manipulating the ETR reconciliation format
presentation in dollars or percentages, as well as the ETR as low or high. The experiment
consists of a full-factorial 2×2 between-subjects design, with presentation format (dollars
or percentages) and effective tax rate (low or high) as manipulated variables (independent
variables described below).
Task and Procedures
Participants were given a link to access the experimental materials on Qualtrics, which
randomly assigned participants to one of the four experimental conditions. After reading
the consent form to participate, participants were advised that they would be reviewing
financial statement information in order to provide forecasts for the next year. Participants
were then provided consolidated statements of income for ABC Inc. and Subsidiaries and a
reconciliation of differences between the actual income tax expense and the expected income
tax expense at the federal statutory rate (i.e., ETR reconciliation) for the prior three years
15
(2014-2016).10 See Appendix B for the experimental materials.
Presentation Format and Effective Tax Rate Manipulation
We manipulate presentation format by presenting the ETR reconciliation in either dollars
or percentages. We manipulate the ETR as either low (29.2 percent) or high (40.8 percent),
from an expected 35 percent federal statutory rate. All income statement items, pre-tax
book income, and ETR reconciliation items were the same for all treatment groups, allowing
us to isolate the presentation format effect. In addition, in order to simplify the task and
eliminate year-to-year fluctuation in ETRs, the ETR reconciliation items and rates were kept
constant for the three prior years (i.e., 29.2 percent or 40.8 percent). After reviewing the
financial information, participants responded to a number of dependent measures and post
experimental questions as described in the next section.
Dependent Variables
Income Tax Expense Forecast and Net Income Forecast
Our second hypothesis focuses on analyst forecast accuracy, and posits that analyst ETR
forecasts are more accurate for firms that present the ETR reconciliation in the percentage
format. In our experiment, we ask participants to forecast income tax expense and net
income. As mentioned above, they are provided with three prior years of income statement
and ETR reconciliation. In addition they are informed that “Company management has
forecasted 2017 annual Income Before Income Taxes to be $155,000 (in thousands).” Using
this information, they are asked to provide a forecast for year ended 2017 for Income Taxes
and Net Income. Without any other company information, it is expected that the income tax
forecast would be computed by multiplying the Pre-Tax Book Income forecast ($155,000)
by the historical ETR. For those in the percentage format, this task should produce less
10Financial statement information for ABC Inc. was taken from the actual financial statements of BostonBeer Company.
16
error, since the ETR is provided and does not require computing. We also ask participants
to provide a forecast of net income as an attention and comprehension check. They should
correctly forecast net income by subtracting their income tax forecast from the pre-tax book
income forecast.
Fairness Perceptions
Given the political cost argument, we posit that firms with low (high) ETRs are more
likely to disclose the ETR reconciliation in dollars (percentages). To measure whether indi-
viduals perceive the same rate differently between the two formats, we asked participants to
indicate their level of agreement with the following statement: “Based on the tax information
disclosed by ABC, Inc., ABC Inc. is paying its fair share of taxes.” Participants responded
on 7-point scale with endpoints 1 (“Strongly Disagree”) and 7 (“Strongly Agree”). We also
asked them “What do you think is a fair corporate income tax rate?” Participants responded
on a scale between 0 and 100-percent.
Participants
One hundred twenty-nine individuals completed the experiment, of which 37 failed the
comprehension check mentioned above, resulting in 92 usable responses. As described in
Table 8, Panel A, they include 26 business school alumni from a private university, 33 ac-
counting professionals employed in public or corporate accounting, and 33 graduate students
in accounting from a private university. All participants would have taken a minimum of two
accounting courses. Participants completed the study via a web-administered instrument on
the Qualtrics platform.
Results
Participants took on average approximately 20 minutes to complete the task (Table 8,
Panel A). Distribution of participants across the four treatment groups is provided in Panel
17
B. In Panel C, we report the differences in forecast accuracy between the dollar and percent-
age formats. Both mean and median forecast errors are significantly higher for participants
in the dollar format group, confirming the archival-empirical evidence in support of Hypoth-
esis 2 presented earlier. The experiment holds constant extraneous factors that cannot be
controlled for in archival settings, while still confirming the effect of presentation format on
tax expense forecast accuracy.
In untabulated analyses, we do not find a difference in fairness perceptions across the
high and low ETR groups and presentation format. This non-result could be explained by
two factors. First, the difference in ETR between the high and low groups (29 percent vs
40 percent) may not have been substantial enough to elicit significant differences. In fact,
on average, participants believed that 28 percent was a ”fair corporate income tax rate,”
and therefore, even those in the low ETR group would have perceived 29 percent to be
a fair share of taxes paid by ABC Inc. Second, the question may not have been framed
appropriately. In other words, instead of asking participants to agree or disagree with the
statement ”ABC Inc. is paying its fair share of taxes”, a better response may have been
obtained if the statement had been framed as ”Do you believe ABC Inc. is paying ’less than
its fair share of taxes’ or ’more than its fair share of taxes’.”
V. CONCLUSION
In this paper we examine the determinants and consequences of the choice of ETR rec-
onciliation format adopted by companies in the footnotes to their financial statements. Con-
sistent with a political cost argument, we find that profitable firms that pay lower taxes in
terms of percentage of pre-tax income (i.e., low ETRs) choose to use the dollar format to
present their ETR reconciliations. In other words, these firms seem to emphasize the dollar
amount of their tax expense rather than the effective rate. In terms of consequences of the
presentation method choice, we explore the effect of the choice on analyst forecasts of future
ETRs. While either presentation can easily be transformed into the other, the percentage
18
format is more direct and therefore, more user friendly in determining future tax expense.
Consistent with this notion, we find that financial analysts seem to make more accurate pre-
dictions of future ETRs when companies present reconciliations in the percentage format.
Experimental results confirm our archival-experimental evidence with respect to the relation
between presentation format and forecast accuracy.
Our findings have policy implications and address an issue of contemporary regulatory
interest (i.e., SEC, FASB). Specifically, given the equivalence of information provided across
the two methods, the percentage format seems less likely to obfuscate public perception
regarding companies shouldering their “fair share,” and at the same time provides users
with a more direct measure that can be used to predict future tax expense. Our findings
also point to the overreliance of even sophisticated financial users on presentation formats
and a surprising lack of ability/effort on their part to recast presented information into more
usable forms.
19
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Duhigg, C., and D. Kocieniewski. 2012. How apple sidesteps billions in taxes. The New York
Times 28:1–5.
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taxes (topic 740). disclosure framework – changes to the disclosure requirements for
income taxes. http://www.fasb.org/jsp/FASB/Document_C/DocumentPage?cid=
1176168335332 (accessed Sept. 14, 2017).
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Johnston, R., A. J. Leone, S. Ramnath, and Y.-w. Yang. 2012. 14-week quarters. Journal of
Accounting and Economics 53 (1): 271–289.
Krishna, A., R. Briesch, D. R. Lehmann, and H. Yuan. 2002. A meta-analysis of the impact
of price presentation on perceived savings. Journal of Retailing 78 (2): 101–118.
A reconciliation of the U.S. federal statutory income tax rate of 35.0% to our effective
tax rate is as follows (in percentages):
Year Ended December 31,2015 2014 2013
U.S. federal statutory income tax rate 35.00% 35.00% 35.00%State income taxes, net of federal benefit 2.00 1.40 1.60Research tax credits (1.4) (1.10) (4.7)Share-based compensation 2.20 6.50 5.20Effect of non-U.S. operations (0.90) (3.60) 6.80Other 3.50 1.90 1.60
Effective tax rate 40.40% 40.10% 45.50%
Google, Inc.
The reconciliation of federal statutory income tax rate to our effective income tax rate is
as follows (in millions):
Year Ended December 31,2015 2014 2013
Expected provision at federal statutory taxrate (35%)
$6,878 $6,041 $5,567
State taxes, net of federal benefit (291) 132 133Change in valuation allowance (65) (164) (641)Foreign rate differential (2,624) (2,109) (2,482)Federal research credit (407) (318) (433)Basis difference in investment of Arris - - 644Other adjustments (188) 57 (49)
Provision for income taxes $3,303 $3,639 $2,739
22
Appendix B. Survey Instrument
[Income statement. High ETR version.]
On the following screen, you will be provided with financial information for ABC Inc.
You will be asked to provide forecasts for the next year.
THE ABC, INC. AND SUBSIDIARIESCONSOLIDATED STATEMENTS OF INCOME
Net revenue 903,007 739,053 580,222Cost of goods sold 437,996 354,131 265,012
Gross profit 465,011 384,922 315,210Operating expenses:Advertising, promotional and selling expenses 250,696 207,930 169,306General and administrative expenses 65,971 62,332 50,171Impairment of long-lived assets 1,777 1,567 149
Total operating expenses 318,444 271,829 219,626
Operating income 146,567 113,093 95,584Other income (expense), net:
Interest income 21 31 31Other expense, net (994) (583) (98)
Total other expense, net (973) (552) (67)
Income before income taxes 145,594 112,541 95,517Income taxes 59,402 45,692 39,066
Net income $ 86,192 66,849 56,451
[ETR Reconciliation using dollars. High ETR version.]
The following table summarizes (in thousands of dollars) the differences between the actual
income tax expense and the expected income tax expense at the federal statutory rate:
2016 2015 2014
Expected tax expense at federal statutory rate (35%) $ 50,958 39,389 33,431State income taxes, net of federal benefit 5,824 4,614 3,916Other 2,620 1,689 1,719
Income tax expense $ 59,402 45,692 39,066
23
[ETR Reconciliation using percentages. High ETR version.]
The following table summarizes (in percentages) the differences between the actual income
tax expense and the expected income tax expense at the federal statutory rate:
2016 2015 2014
Expected tax expense at federal statutory rate (35%) 35.0% 35.0% 35.0%State income taxes, net of federal benefit 4.0% 4.1% 4.1%Other 1.8% 1.5% 1.8%
Effective income tax rate 40.8% 40.6% 40.9%
[Income statement. Low ETR version.]
On the following screen, you will be provided with financial information for ABC Inc.
You will be asked to provide forecasts for the next year.
THE ABC, INC. AND SUBSIDIARIESCONSOLIDATED STATEMENTS OF INCOME
Net revenue 903,007 739,053 580,222Cost of goods sold 437,996 354,131 265,012
Gross profit 465,011 384,922 315,210Operating expenses:Advertising, promotional and selling expenses 250,696 207,930 169,306General and administrative expenses 65,971 62,332 50,171Impairment of long-lived assets 1,777 1,567 149
Total operating expenses 318,444 271,829 219,626
Operating income 146,567 113,093 95,584Other income (expense), net:
Interest income 21 31 31Other expense, net (994) (583) (98)
Total other expense, net (973) (552) (67)
Income before income taxes 145,594 112,541 95,517Income taxes 42,513 33,087 27,795
Net income $ 103,081 79,454 67,722
[ETR Reconciliation using dollars. Low ETR version.]
The following table summarizes (in thousands of dollars) the differences between the actual
income tax expense and the expected income tax expense at the federal statutory rate:
24
2016 2015 2014
Expected tax expense at federal statutory rate (35%) $ 50,958 39,389 33,431State income taxes, net of federal benefit (5,824) (4,614) (3,916)Other (2,621) (1,688) (1,720)
Income tax expense $ 42,513 33,087 27,795
[ETR Reconciliation using percentages. Low ETR version.]
The following table summarizes (in percentages) the differences between the actual income
tax expense and the expected income tax expense at the federal statutory rate:
2016 2015 2014
Expected tax expense at federal statutory rate (35%) 35.0% 35.0% 35.0%State income taxes, net of federal benefit (4.0)% (4.1)% (4.1)%Other (1.8)% (1.5)% (1.8)%
Effective income tax rate 29.2% 29.4% 29.1%
[Survey questions.]
Company management has forecasted 2017 annual Income Before Income Taxes to be
$155,000 (in thousands).
Provide a forecast (in thousands) for year ended 2017 for Income Taxes
Provide a forecast (in thousands) for year ended 2017 for Net Income
25
TABLES
Table 1: Variable Definitions and Data Sources
Variable Definition Source
PercentageFormat Indicator variable that equals one if ETR reconciliation in fi-nancial statement footnotes is reported using a percentage for-mat.
EDGAR
ETR Three-year average effective tax rate, calculated as the ratio oftax expense to pre-tax income, truncated at values of 0 and 1.
COMPUSTAT
ETRRange The difference between the highest and lowest ETR in the lastthree years, winsorized at 1% and 99%.
COMPUSTAT
Log(Assets) Natural logarithm of total assets, winsorized at 1% and 99%. COMPUSTAT
Leverage Current and long-term debt scaled by beginning-of-year totalassets, winsorized at 1% and 99%.
COMPUSTAT
ROA Earnings before extraordinary items scaled by beginning-of-year total assets, winsorized at 1% and 99%.
COMPUSTAT
MTB Market value of equity plus book value of liabilities divided bybeginning-of-year total assets, winsorized at 1% and 99%.
COMPUSTAT
Foreign Indicator variable that equals one if a company has foreignoperations.
COMPUSTAT
Litigious Indicator variable that equals one if a firm operates in a liti-gious industry (a firm with an SIC code either 1) between 2833and 2836, 2) between 3570 and 3577, 3) between 3600 and 3674,or 4) between 5200 and 5961, or 5) equal to 7370).
COMPUSTAT
PwC Indicator variable that equals one if company’s auditor is PwC. COMPUSTAT
Deloitte Indicator variable that equals one if company’s auditor is De-loitte.
COMPUSTAT
EY Indicator variable that equals one if company’s auditor is EY. COMPUSTAT
KPMG Indicator variable that equals one if company’s auditor isKPMG.
COMPUSTAT
Log(Age) Natural logarithm of the number of years a company has beencovered by COMPUSTAT.
COMPUSTAT
AnalystETRError Median implied analyst ETR error, where analyst ETR error iscalculated as the absolute difference between implied one-yearahead ETR forecast (pre-tax earnings forecast minus after-taxearnings forecast divided by pre-tax earnings forecast) and theactual ETR. Only the first forecast of each analyst for the nextfiscal year made within 30 days after the current 10-K filingdate is considered. The variable is winsorized at 1% and 99%.
IBES
NumAnalyst Number of analysts in IBES dataset that forecast pre-tax andafter-tax earnings needed to calculate implied ETR forecast.
IBES
AnalystPreTaxEarnError Median analyst pre-tax earnings forecast error, where analystpre-tax earnings error is calculated as the absolute differencebetween one-year ahead pre-tax earnings forecast and the ac-tual pre-tax earnings divided by firm’s market value. The vari-able is winsorized at 1% and 99%.
IBES
26
Table 2: Descriptive Statistics
Panel A: Sample Selection
Firm-years
Firm-year observations in fiscal years 2002-2015 with available data on ETR reportingformat.
48,974
Firm-year observations with required Compustat data. 29,112
Firm-year observations with required Compustat and IBES data for implied analystETR forecast analysis.
7,445
Panel B: Mean Values of Firm Characteristics by ETR Reporting Format
VariableFull Sample Percentage Sample Dollar Sample ETR Format
Auditor Percentage Format Dollar Format All Formats
PwC 2,973 (62 26%) 1,802 (37.74%) 4,775
Deloitte 2,542 (59 52%) 1,729 (40.48%) 4,271
EY 3,059 (50 24%) 3,030 (49.76%) 6,089
KPMG 2,184 (47 38%) 2,426 (52.62%) 4,610
Other 4,603 (49 14%) 4,764 (50.86%) 9,367
Total 15,361 (52 77%) 1,3751 (47.23%) 29,112
This table reports sample selection process (Panel A), the mean and median values of variables used inthis study for the full sample, sample with ETR reconciliation being reported using percentage format, andsample with ETR reconciliation being reported using dollar format (Panel B and Panel C), and the numberand percentage of firm-year observations using dollar and percentage format for different levels of ETR(Panel D) and by auditor (Panel E). Panel B includes firm characteristic variables, and Panel C includesanalyst-related variables. The last columns in Panel B and Panel C shows the differences in means betweenpercentage and dollar format samples. All variables are defined in Table 1.
28
Table 3: Correlation Statistics
Panel A: ETR Reporting Format and Firm Characteristics
This table shows Spearman correlations between ETR reporting format and firm characterizes (Panel A), and ETR reporting format and analystforecast characteristics (Panel B). All variables are defined in Table 1.
29
Table 4: Determinants of ETR Reporting Format
(1) (2)PercentageFormat PercentageFormat
ETR 0.638∗∗∗ 0.802∗∗∗
(7.850) (4.385)
ETRRange −0.607∗∗∗
(−6.277)
Log(Assets) 0.082∗∗∗
(4.425)
Log(Age) 0.026(0.563)
NumBus 0.003(0.113)
NumGeo 0.016(1.142)
Leverage −0.279∗∗∗
(−2.904)
ROA −0.127∗∗∗
(−3.041)
MTB 0.013∗∗∗
(3.448)
Foreign 0.171∗∗∗
(2.958)
PwC 0.358∗∗∗
(3.741)
Deloitte 0.240∗∗
(2.316)
EY −0.130(−1.518)
KPMG −0.233∗∗
(−2.504)
Litigious 0.072(0.920)
Year Fixed Effects No Yes
Observations 29,112 29,112R2 0.002 0.023
t statistics in parentheses∗ p < 0.10, ∗∗ p < 0.05, ∗∗∗ p < 0.01
This table shows the estimated coefficients of logistic regressions of ETR presentation format (PercentageFormat) on (1) the level of ETR (ETR) and (2) ETR and firm characteristics. Year fixed effects areincluded in column (2), but not reported. All variables are defined in Table 1. Reported statistics are basedon standard errors clustered both at the firm and year levels.
30
Table 5: Pre-Tax Income, Media Coverage, and ETR Presentation Format.
(1) (2)PercentageFormat PercentageFormat
ETR 0.641∗∗∗ 0.607∗∗∗
(3.374) (3.183)HighPreTaxIncome 0.122
(0.784)ETR×HighPreTaxIncome 0.959∗∗
(2.050)HighMediaCoverage 0.083∗
(1.722)ETR×HighMediaCoverage 1.266∗∗∗
(5.285)ETRRange −0.514∗∗∗ −0.513∗∗∗
(−5.113) (−5.087)
Log(Assets) 0.038∗ 0.036∗
(1.896) (1.785)
Log(Age) −0.002 −0.002(−0.040) (−0.051)
NumBus 0.001 0.001(0.034) (0.056)
NumGeo 0.013 0.013(0.965) (0.963)
Leverage −0.294∗∗∗ −0.292∗∗∗
(−3.120) (−3.106)ROA −0.131∗∗∗ −0.131∗∗∗
(−3.240) (−3.215)MTB 0.009∗∗∗ 0.009∗∗∗
(2.660) (2.623)Foreign 0.123∗∗ 0.122∗∗
(2.142) (2.113)PwC 0.345∗∗∗ 0.335∗∗∗
(3.581) (3.455)Deloitte 0.233∗∗ 0.225∗∗
(2.234) (2.145)EY −0.146∗ −0.157∗
(−1.709) (−1.828)KPMG −0.236∗∗ −0.243∗∗∗
(−2.531) (−2.609)Litigious 0.057 0.049
(0.734) (0.630)Year Fixed Effects Yes Yes
Observations 29,112 29,112R2 0.026 0.027
t statistics in parentheses∗ p < 0.10, ∗∗ p < 0.05, ∗∗∗ p < 0.01
This table shows the estimated coefficients of logistic regressions of ETR presentation format (PercentageFormat) on the level of ETR (ETR), indicator for high pre-tax income (HighPreTaxIncome, Column (1)),indicator for a firm having high media coverage (HighMediaCoverage, Column (2)), and their interactions(ETR×HighPreTaxIncome and ETR×HighMediaCoverage). Varible HighPreTaxIncome is one if firm-yearpre-tax income is in the fourth quartile of its distribution, and zero otherwise. Variable HighMediaCoverageis one if the total number of articles in Wall Street Journal, New York Times, Washington Post, and USAToday related to a firm in the current fiscal year is in the fourth quartile of its distribution, and zerootherwise. Year fixed effects are included, but not reported. All variables are defined in Table 1. Reportedstatistics are based on standard errors clustered both at the firm and year levels.
31
Table 6: Determinants of Switching ETR Reconciliation Format
t statistics in parentheses∗ p < 0.10, ∗∗ p < 0.05, ∗∗∗ p < 0.01
This table shows the estimated coefficients of logistic regressions of ETR presentation format (SwitchToP-ercentageFormat) on (1) the level of ETR (ETR) and (2) ETR and firm characteristics for firm-year ob-servations five years following firms switching their ETR reporting format from either dollar to percentageor percentage to dollar. Year fixed effects are included in column (2), but not reported. All variables aredefined in Table 1. Reported statistics are based on standard errors clustered both at the firm and yearlevels.
32
Table 7: ETR Reporting Format and Analyst ETR Forecast Error
t statistics in parentheses∗ p < 0.10, ∗∗ p < 0.05, ∗∗∗ p < 0.01
This table shows the estimated coefficients of OLS regressions of analyst implied ETR forecast error (Ana-lystETRError) on ETR reconciliation reporting format (PercentageFormat), number of analysts giving anETR forecast (NumAnalyst), analyst pre-tax earnings forecast error (AnalystPreTaxEarnError), and firmfundamentals. Year fixed effects are included in column (3), but not reported. All variables are defined inTable 1. Reported statistics are based on standard errors clustered both at the firm and year levels.
33
Table 8: ETR Reconciliation Presentation Format and Forecast Accuracy. Experimen-tal Evidence
Panel A: Time Taken to Complete Survey (in Seconds)
Group N Mean Low Median High
0 26 1,065 107 866 4,194
1 33 1,700 198 1,114 17,148
2 33 872 159 818 3,081
Overall 92 1,223 107 895 17,148
0 = alumni1 = employed in public or corporate accounting2 = graduate students in accounting
Panel B: Frequency Across Treatments
Group N Dollar Format (N) Percentage Format (N) Low ETR (N) High ETR (N)
0 26 14 12 14 12
1 33 15 18 18 15
2 33 22 11 17 16
Overall 92 51 41 49 43
Panel C: Test of Forecast Accuracy Across ETR Formats
Forecast Error
N Mean Median StdDev
Dollar Format 51 0.0360 0.0049 0.0839
Percentage Format 41 0.0091 0.0034 0.0315
Difference 0.0269
t-stat 2.11(p < 0.04)
z -stat −2.91(p < 0.004)
F -stat 7.70(p < 0.001)
This table summarizes the results of an experiment that examines the effects of ETR reconciliation presen-tation format on participants’ ability to forecast future ETR. Panel A shows summary statistics for surveycompletion times across three groups of participants. Panel B shows the frequency data across participantgroups and treatments. Panel C shows forecast error statistics (mean, median, and standard deviation)across dollar format and percentage format treatment groups as well as their differences. Mean, median,and standard deviation (variance) test statistics and their p-values are calculated using two-tailed t-test,Wilcoxon-Mann-Whitney test, and F -test, respectively.
