discussion of “credit ratings and taxes: the effect of book–tax differences on ratings...

Discussion of ‘‘Credit Ratings and Taxes: The Effect

of Book–Tax Differences on Ratings Changes’’*

RYAN WILSON, University of Iowa

1. Introduction

Do tax-based performance measures provide useful information to users offinancial information outside of the equity markets? Ayers, Laplante, andMcGuire (2010; hereafter ALM) attempt to answer this question by examin-ing whether credit analysts use the difference between a firm’s pre-tax bookincome and taxable income (BTDs) in assessing creditworthiness. ALMnote that prior research suggests BTDs can provide a useful signal aboutthe quality of a firm’s earnings and ⁄or the extent of a firm’s off–balance-sheet financing activities. Both signals may be useful to analysts evaluatingcredit risk. ALM document a significant association between large positiveand large negative changes in BTDs and changes in credit ratings after con-trolling for known determinants of credit rating changes.1 ALM (2010, 359)interpret their results as being ‘‘consistent with book-tax changes signalingnegative information to credit rating agencies’’.

ALM also find the association between changes in credit ratings andlarge changes in BTDs is attenuated in high tax-planning firms. They arguethat, for high tax-planning firms, large changes in BTDs are more likely aresult of tax-planning strategies than changes in earnings quality, and wouldtherefore be of less use to credit analysts in assessing credit risk. Based onthis analysis, ALM conclude credit analysts are able to identify the sourceof BTDs.

In this discussion I focus on three points related to ALM’s analysis andcontribution. First, I discuss the potential information signaled by largechanges in BTDs and the contribution of ALM’s study to existing researchexamining BTDs as a measure of earnings quality. Second, I discuss theextent to which conclusions can be drawn from their analysis about whethercredit analysts directly examine BTDs. Third, I propose additional direc-tions for future research.

* Accepted by Lillian Mills. An earlier version of this paper was presented at the 2008

Contemporary Accounting Research Conference, generously supported by the Canadian

Institute of Chartered Accountants. This paper reflects my discussion remarks at the 2008

Contemporary Accounting Research Conference. I thank Paul Hribar, Bruce Johnson,

Terry Shevlin, and conference participants for their thoughtful comments.

1. ALM rank changes in BTDs yearly into deciles for both positive and negative changes.

They then regress rating changes that occur between the end of fiscal year t and the end

of fiscal year t+1 on their decile ranking of positive changes in BTDs, the decile rank

of the absolute value of negative changes in BTDs, and control variables.

Contemporary Accounting Research Vol. 27 No. 2 (Summer 2010) pp. 403–411 � CAAA

doi:10.1111/j.1911-3846.2010.01012.x

2. What do large changes in BTDs signal?

Firms raise significant funds each year through debt issuances, and creditratings have important implications for bond yields and bank capitalrequirements. Financial reports provide analysts with a starting point forassessing credit ratings. An erosion of firm performance can result in liquid-ity problems for the firm, ultimately leading to an inability of the firm toservice its outstanding debts. Credit analysts rely on financial statementinformation to forecast future cash flow amounts, volatility, and sources.Credit analysts also rely on financial reports for leverage analysis includingadjustments for their estimate of a firm’s off-balance-sheet liabilities (Stan-dard and Poor’s Corporate Rating Criteria 2008, 43). To the extent changesin BTDs provide relevant information about future earnings, cash flowperformance, or off-balance sheet liabilities, this would be useful to creditanalysts.

Because financial reports serve as the starting point for assessments ofcredit risk, concerns about the quality of the information in those reportscan be expected to affect credit ratings. In Standard and Poor’s corporatecredit rating criteria the firm notes that to the extent they believe informa-tion risk exists, it will influence their decision to maintain a certain creditrating. Consistent with this assertion, Francis, LaFond, Olsson, andSchipper (2005) find accrual quality is positively associated with credit rat-ings. Ashbaugh-Skaife, Collins, and LaFond (2006) also find accrual qualityand earnings timeliness are both positively associated with credit ratings.ALM extend this analysis by focusing on an alternative measure of earningsquality in BTDs.

Recent research suggests large BTDs are a useful signal of low qualityearnings. Phillips, Pincus, and Rego (2003) conjecture that because tax lawallows less discretion in accounting choices than generally accepted account-ing principles (GAAP), large positive differences between book and taxableincome can be informative about earnings management. Consistent withmanagers at firms with large BTDs exercising more discretion over theaccruals process, Hanlon (2005) finds that firm-years with large temporaryBTDs have less persistent earnings than firm-years with small temporaryBTDs. Also consistent with BTDs being a signal of earnings quality, Levand Nissim (2004) calculate a ratio of tax-to-book income, reflecting bothpermanent and temporary BTDs, and find the ratio predicts subsequentfive-year earnings changes. Taken together the results from these studiessuggest large BTDs are a useful signal of low-quality earnings.

Based on this evidence, ALM argue that large changes in BTDs are asignal of low-quality earnings, which inhibit credit analysts’ abilities to mea-sure a company’s performance. Several accounting textbooks (includingRevsine, Collins, and Johnson 2005) point out that increases in the deferredtax expense could be an indication of deteriorating earnings quality. There-fore, it is not unreasonable to assume that credit analysts rely on significant

404 Contemporary Accounting Research

CAR Vol. 27 No. 2 (Summer 2010)

changes in BTDs as a signal of information risk. The results reported byALM are consistent with this assumption and help triangulate the results ofprior studies examining BTDs as a measure of earnings quality. Specifically,this study provides support for BTDs as a measure of earnings quality byexamining the implications of BTDs in a setting outside of the equitymarkets.

Large changes in BTDs could also be of interest to credit analystsbecause this signals changes in a firm’s off–balance-sheet financing activity.Consistent with this idea, Mills and Newberry (2005) find that firms withlower credit ratings report greater interest expense on their tax returns thantheir financial statements. This finding suggests these firms are using off–balance-sheet financing that results in a tax deduction for interest, but nocorresponding interest expense on the financial statements, which wouldincrease BTDs. Maydew (2005) notes that the findings by Mills andNewberry 2005 are consistent with credit analysts discerning to some extentthe degree of off–balance-sheet financing and adjusting their credit ratingsaccordingly. Extensive off–balance-sheet financing would have clear implica-tions for the probability of future default. Consequently, ALM argue thatto the extent changes in BTDs reflect changes in off–balance-sheet financ-ing, this will be associated with changes in credit risk.

ALM point out that in some cases large changes in BTDs could also bethe result of extensive tax-planning activity and not a change in either earn-ings quality or off-balance-sheet financing.2 They predict that changes inBTDs resulting from tax planning will be less useful to credit analysts inassessing credit risk. However, recent research suggests that aggressive taxplanning can be associated with aggressive financial reporting and manage-rial opportunism, both of which would have implications for credit risk.Desai and Dharmapala (2006) argue tax shelters are intentionally designedto obscure the economic substance of a transaction and therefore provide ashield for managers to engage in opportunistic behavior. For example, forfirms such as Enron that engaged in extensive tax shelter activity, it mightbe difficult for credit analysts to evaluate firm performance because of thecomplex nature of these transactions.3

Frank, Lynch, and Rego (2009) hypothesize that some firms have a ten-dency toward aggressive corporate behavior, which simultaneously affectstheir financial and tax reporting systems. They find results consistent withfirms choosing to report aggressively for book purposes also reportingaggressively for tax purposes. If aggressive tax reporting is associated with

2. It is worth noting that a significant portion of BTDs are likely unrelated to either earn-

ings management or aggressive tax reporting strategies. Consistent with this, Seidman

(2008) shows that changes in GAAP accounting and general business conditions explain

a significant portion of BTDs.

3. The 12 tax-avoidance transactions that Enron did from 1995 to 2001 produced $2.02

billion in tax savings and resulted in $2.079 billion in current income for financial state-

ment purposes (France 2003).

Discussion of ‘‘Credit Ratings and Taxes’’ 405


either managerial opportunism or aggressive financial reporting, this wouldsuggest that even large changes in BTDs resulting from tax planning wouldbe of interest to credit analysts. However, the results for the test of the sec-ond hypothesis in ALM are inconsistent with analysts viewing changes inBTDs resulting from tax planning as relevant to their assessment of creditrisk. These results suggest credit analysts may not see a direct connectionbetween aggressive tax reporting and the quality of financial information.Nonetheless, it would be interesting to examine a subset of the mostextreme cases of tax planning (tax shelters or some set of predicted tax shel-ter firms) to see whether these cases of very aggressive tax planning areassociated with credit ratings.

To summarize, large changes in BTDs could be viewed as a signal ofchanges in a firm’s earnings quality, off–balance-sheet financing activity, ortax reporting aggressiveness. Before researchers can begin to include a mea-sure of changes in BTDs into a model of the determinants of credit ratingchanges it is critical to understand what is driving the observed associationbetween changes in BTDs and changes in credit ratings.

ALM begin this process by examining whether the association betweenchanges in BTDs and changes in credit ratings is attenuated for high taxplanning firms. Despite this analysis, additional work needs to be done tomore clearly determine what is driving this observed association. Forexample, this analysis could be extended by also examining whether theassociation between BTDs and credit ratings increases in the presence ofearnings management. A measure of discretionary accruals could be usedto sort firms into industry-year quintiles based on the level of managementdiscretion over the accruals process. ALM could then create an indicatorvariable set equal to one for observations in the top industry-year quintileof the discretionary accrual measure (low earnings quality firms) and inter-act that variable with their measures of large BTDs. If the associationbetween changes in credit ratings and changes in BTDs is a result ofBTDs being a signal of low-quality earnings, then this association shouldincrease in the presence of earnings management as measured by discre-tionary accruals.4 Such an analysis would help clarify what is causing theobserved association between changes in credit ratings and changes inBTDs.

3. Interpretation of results

One of the issues raised at the conference was whether the paper providesevidence that credit analysts actually use BTDs in their assessment of creditrisk. It is not clear this conclusion can be drawn from the current analysis.A positive association between changes in BTDs and changes in credit

4. Blaylock, Shevlin, and Wilson (2008) find that firms with large positive BTD arising

from upward earnings management exhibit lower earnings and accruals persistence than

other firms with large positive BTDs.



ratings does not provide evidence that credit analysts directly examineBTDs. In fact, one of four specialist groups at Moody’s is their off–balance-sheet structures group. It seems reasonable to assume this group does amore detailed analysis of a firm’s off–balance-sheet financing activities thansimply calculating a measure of BTDs. However, as ALM note, to the extentthat BTDs are associated with off–balance-sheet financing activity, BTDs doprovide researchers (who unfortunately lack their own off–balance-sheetstructures group) with a parsimonious measure of off–balance-sheet financ-ing that can be used in a model of the determinants of credit ratings.

ALM also conclude that because credit rating changes are negativelyassociated with both large positive and large negative changes in BTDs,their results are consistent with large changes in BTDs being a signal tocredit analysts of changes in earnings quality rather than changes in off–balance-sheet financing. The significant negative association between largenegative changes in BTDs and credit rating changes was surprising. Myexpectation was that negative changes in BTDs would signal a reduction ina firm’s off-balance-sheet financing activity or possibly a reduction in theextent of upward earnings management. In either case, I would expect apositive (or perhaps insignificant) association between large negativechanges in BTDs and changes in credit ratings. Hanlon (2005) does findthat firms with large negative BTDs have lower earnings persistence thanfirms with small BTDs, but it is not necessarily the case that firms withlarge negative changes in their BTDs would exhibit large negative BTDs ina levels analysis. In fact, a firm with a small level of BTDs could exhibit alarge negative change in BTDs if the firm had large positive BTDs in theprior period. Of course, this same limitation applies to observations withlarge positive changes in BTDs.

Related to this concern, a conference participant suggested ALM con-sider whether BTDs are normal ⁄abnormal relative to the standard deviationof past BTDs. For example, if BTDs for a given year are within one stan-dard deviation of past BTDs, it may just be a normal change. Abnormalchanges may better capture the type of signal that would be of interest tocredit analysts. This concern is mitigated by the supplemental analysis con-ducted by ALM. Specifically, the authors test if the association betweenchanges in BTDs and changes in credit ratings varies depending on whetherthe change in BTDs moves the firm closer to the industry median for BTDs.They find that changes in BTDs that move a firm further from the industrymedian for the level of BTDs in either direction have negative implicationsfor credit ratings.

Despite the extensive supplemental analysis conducted by ALM, Iwould suggest caution in interpreting their results as evidence consistentwith credit analysts using changes in BTDs primarily as a signal of changesearnings quality. Future research could provide insight into this issue byexamining the association between changes in BTDs and changes in theextent of off–balance-sheet financing. Operating leases alone are associated



with undiscounted total noncancelable future cash flow obligations of $1.25trillion for U.S. companies (Ge 2006). Such future cash flow obligationswould have clear implications for any assessment of credit worthiness.Many firms structure their leases to be treated as an operating lease forfinancial reporting purposes and as a capital lease for tax purposes. Oftenreferred to as synthetic leases, these types of leases can result in significantincreases in BTDs. However, the importance of off–balance-sheet finan-cing in explaining cross-sectional variation in BTDs remains an empiricalquestion.

ALM focus their primary analysis on changes in total BTDs. I wouldencourage them to include separate measures of changes in both the tempo-rary and permanent components of BTDs in their main analysis. PermanentBTDs are associated with increases ⁄decreases in a firm’s effective tax rates.Prior research suggests managers use discretion in accounting for effectivetax rates to meet key earnings targets (Dhaliwal, Gleason, and Mills 2004;Krull 2004). In other words, permanent BTDs provide insight into manage-rial discretion over one particular account (the tax expense). Further, theU.S. Congress Joint Committee on Taxation (1999), Weisbach (2002), andShevlin (2002) describe the ideal tax shelter as creating permanent, ratherthan temporary, BTDs. As a result, permanent BTDs might provide moreinformation about a firm’s tax planning practices than financial reportingchoices. In contrast, temporary BTDs have been hypothesized to signalinformation about managerial discretion over accruals more generally (e.g.,Phillips et al. 2003; Hanlon 2005). In supplemental analysis, ALM findchanges in the permanent component of BTDs are not associated withchanges in credit ratings. This result is not particularly surprising to theextent one believes permanent BTDs provide more information about taxreporting choices than earnings quality.

4. Suggestions for future research

Ashbaugh-Skaife et al. (2006) find credit ratings are negatively associatedwith the number of blockholders and CEO power and positively associatedwith ownership structure and influence, financial stakeholder rights andrelations, financial transparency, and board structure and process. Creditanalysts’ concerns regarding the quality of financial information could beheightened for firms with poor corporate governance. A possible associationbetween corporate governance and earnings quality highlights the impor-tance of controlling for governance characteristics when examining the asso-ciation between earnings quality and credit ratings. One potentially fruitfulavenue for future research would be to examine how the associationbetween measures of earnings quality and credit ratings changes as afunction of the quality of corporate governance.

On a related note, the quality of a firm’s corporate governance structurehas also been shown to play an important role in mitigating whether corpo-rate tax avoidance strategies are associated with managerial opportunism



(Desai and Dharmapala 2006). The results in ALM suggest the associationbetween changes in BTDs and changes in credit ratings is mitigated for hightax planning firms. However, it would be interesting to examine how corpo-rate governance affects this association. Do credit analysts view aggressivetax reporting combined with low-quality corporate governance structures as asignal that managers are behaving opportunistically and adjust their creditratings accordingly?

An alternative direction for future research would be to examinewhether credit analysts should be using BTDs in their assessment of creditrisk. This would require expanding existing models predicting financial dis-tress and ⁄or default to include measures of BTDs. I am unaware of anycurrent default prediction models that include measures of BTDs.5 Moregenerally, this type of analysis would require taking a step back fromresearch focused on identifying the factors that credit analysts do considerand instead attempting to model the determinants of default using acombination of accounting information and market data. The credit ratingagencies have come under criticism for their failure to respond in a timelyfashion during the high-profile failures of Enron and Worldcom (Hunt2002). To the extent these criticisms are valid, it suggests there is roomfor credit rating agencies to improve their approach to assessing creditworthiness. If future research can provide new insight into how to effec-tively predict default this would benefit both credit rating agencies andinvestors.

5. Conclusion

ALM’s study is well executed and addresses an interesting research ques-tion. The study contributes to research modeling the determinants of creditratings by establishing a strong association between changes in BTDs andchanges in credit ratings. The paper also raises a number of important ques-tions. For example, how does the observed association between BTDs andcredit ratings change in the presence of poor corporate governance? AreBTDs resulting from extremely aggressive tax reporting strategies such ascorporate tax shelters also associated with changes in credit ratings? As withmany studies in empirical accounting research, it is difficult to establish acausal link and it remains unclear whether credit analysts directly examineBTDs or whether BTDs are simply associated with other factors analystsconsider in their assessment of credit risk.

ALM conclude their results are generally consistent with credit analystsusing changes in BTDs as a signal of changes in earnings quality. However,the authors acknowledge the possibility that credit analysts may also usechanges in BTDs as a signal of changes in off–balance-sheet financing activ-ity. Future research can build on this study and examine directly whether

5. See Moody’s 2000 for a discussion of default prediction models developed in both

practice and research.



BTDs provide useful information about changes in off-balance-sheetfinancing activity.

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