Does implementation guidance affect opportunistic reporting and value relevance of earnings?

Journal of Accounting and Public Policy 26 (2007) 160–192

www.elsevier.com/locate/jaccpubpol

Journal of Accounting and Public Policy 26 (2007) 160–192

www.elsevier.com/locate/jaccpubpol

Does implementation guidance affectopportunistic reporting andvalue relevance of earnings?

Jeff P. Boone a, K.K. Raman b,*

a Department of Accounting, College of Business Administration,

University of Texas at San Antonio, USAb Department of Accounting, College of Business Administration, University of North Texas,

P.O. Box 305219, Denton, TX 76203, USA

Abstract

In recent years, both the SEC (2003) and the FASB (2004) [Securities and ExchangeCommission, 2003. Study Pursuant to Section 108(d) of the Sarbanes-Oxley Act of 2002on the Adoption by the United States Financial Reporting System of a Principles-BasedAccounting System. Securities and Exchange Commission, Washington, DC; the Finan-cial Accounting Standards Board, 2004. On the road to an objectives-oriented account-ing system. Financial Accounting Series: The FASB Report (August 31), 1–5.] haveindicated a need for accounting standards where principles are balanced by implemen-tation guidance (i.e., a framework for exercising professional judgment). In this study,we take advantage of a jurisdictional split during 1996–2001 whereby the same eco-nomic event (i.e., an impairment in oil and gas assets) in the extractive petroleum indus-try was accounted for by ‘‘full cost’’ firms under a SEC standard (Regulation SX 4-10)which provides extensive implementation guidance, and by ‘‘successful efforts’’ firmsunder a FASB standard (SFAS No. 121) that provided relatively little guidance forimplementing the standard.

0278-4254/$ - see front matter � 2007 Elsevier Inc. All rights reserved.doi:10.1016/j.jaccpubpol.2007.02.004

* Corresponding author. Tel.: +1 940 565 3089; fax: +1 940 565 3803.E-mail addresses: [email protected] (J.P. Boone), [email protected] (K.K. Raman).

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J.P. Boone, K.K. Raman / Journal of Accounting and Public Policy 26 (2007) 160–192 161

We utilize this jurisdictional split (which provides a natural quasi-experiment) toevaluate whether the differential guidance for recognizing impairment losses providedby Reg. SX (for ‘‘full cost’’ firms) and SFAS No. 121 (for ‘‘successful efforts’’ firms)is associated with differences in opportunistic reporting (as proxied by an associationbetween the reported write-downs and managerial incentives to report opportunisti-cally) and differences in the value relevance of the write-downs (as proxied by their asso-ciation with stock returns). Our findings are inconclusive as to whether implementationguidance limits opportunistic reporting, but are broadly consistent with the notion thatsuch guidance potentially undermines the value relevance of accounting information.Collectively, our findings provide accounting policy makers with an additional pieceof evidence with which to evaluate the role of implementation guidance in standardsetting.� 2007 Elsevier Inc. All rights reserved.

Keywords: Rules vs. principles; Implementation guidance; Opportunistic reporting; Value rele-vance; Impairment loss (write-down)

1. Introduction

In recent years, both the Securities and Exchange Commission SEC (2003)and the Financial Accounting Standards Board (FASB, 2004) have indicated aneed for accounting standards where principles are balanced by implementa-tion guidance (i.e., a framework for the application of professional judgment).Although there has been much discussion of the issue of rules- versus princi-ples-based accounting standards and the need for implementation guidance(FASB, 2002, 2004; Schipper, 2003; SEC, 2003), there appears to be relativelylittle in the way of empirical evidence.1

In this study, we take advantage of a jurisdictional split (which provides anatural quasi-experiment) during 1996–2001 whereby the same economic event(i.e., an impairment in oil and gas assets) in the extractive petroleum industrywas accounted for by ‘‘full cost’’ firms under a SEC standard (Regulation SX4-10) which provides extensive implementation guidance and by ‘‘successfulefforts’’ firms under a FASB standard (SFAS No. 121) that provided relatively

1 Jopson (2005) notes that the issue of rules- vs. principles and the need for implementationguidance continues to be of current interest both in the US and abroad. Although internationalfinancial reporting standards (IFRS) are viewed as more principles-based (relative to US GAAP),Jopson (2005) reports that European Union (EU) accountants have been asking for more guidancefrom the International Accounting Standards Board (IASB) in the interests of more consistentimplementation across EU countries. Separately, as pointed out by Nobes (2005, p. 32), in the endwhat is better information for investors remains an empirical question.

162 J.P. Boone, K.K. Raman / Journal of Accounting and Public Policy 26 (2007) 160–192

little implementation guidance.2 Specifically, we examine whether the differen-tial implementation guidance is associated with differences in opportunisticreporting (as proxied by an association between the reported write-downsand managerial incentives to report opportunistically) and value relevance(as proxied by the association between the reported write-downs and stockreturns).

To our knowledge, there is no generally accepted definition of rules-basedand principles-based standards. Still, the basic idea is that both rules- and prin-ciples-based standards may be grounded on the same concept but vary in termsof implementation guidance. The SEC (2003, p. 17) and the FASB (2004) sug-gest that rules- and principles-based standards lie along a spectrum, and agreethat the optimal point may lie in what they call ‘‘objectives-oriented stan-dards’’, i.e., standards where principles are balanced by guidance that provides‘‘sufficient detail and structure so that the standard can be operationalized andapplied on a consistent basis’’ (SEC, 2003, p. 5).3 Potentially, the implementa-tion guidance may be useful in limiting managerial opportunism, i.e., in con-straining managers from opportunistically biasing financial reports toachieve self-serving ends (Schipper, 2003). However, as discussed below, tothe extent that the implementation guidance limits accounting discretion as ameans of communicating managers’ insights into the firm’s economics, theguidance could potentially affect the value relevance of the reportedinformation.

Specifically, in the context of accounting for the impairment of long-livedassets, the SEC (2003, p. 25) is critical of Statement of Financial AccountingStandards (SFAS) No. 121 (FASB, 1995) in that it cites it as an example ofa standard that establishes ‘‘the basic principle but (does) not provide sufficientguidance for implementation’’.4 In the same vein, Riedl (2004) suggests that theimplementation of SFAS No. 121 requires inherently subjective estimates andassumptions with little objective guidance. Riedl (2004) examines the charac-teristics of impairment write-downs reported prior and subsequent to the

2 The ‘‘full cost’’ and ‘‘successful efforts’’ methods of accounting are discussed in Section 2 below.Separately, although now superceded by SFAS No. 144 (for accounting periods beginning afterDecember 15, 2001), SFAS No. 121was the applicable standard during the 1996–2001 time periodexamined in our study. Note that although SFAS No. 144 replaces SFAS No. 121, it ‘‘does notchange the latter standard’s general provisions’’ (Riedl, 2004, p. 825).

3 The FASB (2004, p. 5) notes that ‘‘an approach to setting standards that places more emphasison principles will not eliminate the need to provide . . . implementation guidance for applying thesestandards. Thus, we agree with the SEC staff that some amount of implementation guidance isneeded for entities to apply objectives-oriented standards in a consistent manner’’.

4 Still, as noted by the SEC (2003, p. 25), ‘‘prior to the issuance of SFAS No. 121, there was noguidance for [determining the impairment of long-lived assets]’’. Alciatore et al. (1998, p. 4) make asimilar point when they state that ‘‘Until the issuance of SFAS No. 121, there was no specificrequirement for firms to reduce the carrying value of long-term assets that had become impaired’’.


issuance of SFAS No. 121. He finds a stronger association between the write-downs and ‘‘big bath’’ reporting behavior after the implementation of the stan-dard, and suggests that the ‘‘big bath’’ behavior is more likely a reflection ofmanagerial opportunism rather than improved communication of managers’private information.5 Although Riedl (2004) does not test for value relevance,he implies that SFAS No. 121 resulted in a decrease in the value relevance ofthe reported write-downs by suggesting that ‘‘the reporting of write-offsunder SFAS No. 121 has decreased in quality relative to before the standard’’(p. 849).6

However, as noted by Dye and Verrecchia (1995, p. 95), managerial oppor-tunism per se does not destroy the case for accounting discretion. Rather, therelevant question is whether the effects of managerial opportunism more thanoffset the prospects for improved communication of managers’ insights into thefirm’s underlying economic conditions.7 Thus, Riedl’s (2004) finding that theimpairment write-downs under SFAS No. 121 are associated with opportunis-tic reporting incentives provides an incomplete picture since it yields no insightinto the question of whether the write-downs also improved communication ofmanagers’ private information about the firm’s underlying economics. Put dif-ferently, since theoretical arguments alone cannot unambiguously predict therelation between accounting discretion and the usefulness of reported earningsfor investors, the value relevance of the impairment write-downs is an empiricalissue. Our study helps complete the picture by examining whether implementa-tion guidance impacts the value relevance of the reported impairment write-downs.

Our study also contributes by examining the impact on opportunisticreporting and value relevance of impairment write-downs reported underSFAS No. 121 as compared to those reported under the SEC standard (Reg.SX) that, unlike SFAS No. 121, provides managers with implementation guid-ance. Thus, by examining the opportunistic reporting and value relevance

5 Similarly, Turner (2001) – a former SEC Chief Accountant – is also critical of the discretionpermitted by SFAS No. 121 and notes that ‘‘Today’s US impairment standards are resulting innothing more than one-time ‘‘big bath’’ charges that lack relevance or economic reality’’ (p. 6).

6 As noted previously, prior to SFAS No. 121 accounting standards did not specifically addressthe reporting of long-lived asset impairments. Still, Riedl (2004) suggests that reporting discretionover write-offs may have increased after the adoption of SFAS No. 121, ‘‘as the standard’ssubjective (but now explicit) criteria may enable managers to more easily justify their reportingchoices relative to before the standard. Restated, . . . (SFAS No. 121) may afford managers ajustification to take (or not take) write-offs that was unavailable prior to the standard’’ (p. 824).

7 As noted by Beaver (2002), managers can use the accounting discretion inherent in the currentreporting system to conceal as well as to reveal information, i.e., managers can use accountingdiscretion to report opportunistically as well as to communicate value relevant information toinvestors. Beaver (2002) suggests that limiting accounting discretion may reduce opportunisticreporting, but at the potential cost of also limiting the communication of value relevantinformation to investors.


effects of asset impairment write-downs reported by ‘‘full cost’’ firms comparedto ‘‘successful efforts’’ firms, we are able to provide insight into the Dye andVerrecchia (1995) question of whether the effects of managerial opportunismarising from the lack of accounting guidance more than offset the prospectsfor improved communication of managers’ insights into the firm’s underlyingeconomic conditions.8

We operationalize value relevance as the contemporaneous associationbetween the reported write-downs and stock returns. Both SFAS No. 121and Reg. SX specify expected future cash flows (relative to book values) asthe measure triggering oil and gas asset impairment write-downs. A write-downthus communicates management’s expectations of lower future cash flows.Since the stock market is forward looking and the stock price is expected tocapture all publicly available information about a firm’s expected future cashflows, we expect a reported write-down to be value relevant, i.e., to be associ-ated with contemporaneous stock returns, controlling for the amount of earn-ings before the write-down.

Relative to prior research on asset impairment (discussed below), our studyfeatures more refined tests due to (1) the quasi-experimental nature of the oiland gas setting, and (2) our ability to utilize SFAS No. 69 (FASB, 1982) oiland gas supplemental disclosures to construct direct indicators of the extentof impairment. Further, our objective is to examine whether managers’response to implementation guidance (or lack thereof) affects the value rele-vance of the reported write-down. By contrast, prior studies were focused ondetermining whether impairment (based on indirect indicators) or managerialopportunism explained asset write-downs. Moreover, prior studies (exceptfor Riedl, 2004) were based on pre-SFAS No. 121 data while our study utilizesSFAS No. 121 data.

Our findings are inconclusive as to whether the implementation guidanceprovided by Reg. SX constrained managerial opportunism, in the sense thatthe write-downs were unrelated to opportunistic reporting incentives. How-ever, the implementation guidance appears to have lowered the valuerelevance of the impairment write-downs for full cost firms since the reportedwrite-downs had a smaller response coefficient. By contrast, write-downs bysuccessful efforts firms were associated with opportunistic reporting incentives(consistent with Riedl, 2004), albeit without affecting the value relevance ofthe reported write-downs.

Thus, we find that write-downs arising from a standard (SFAS No. 121) thatprovides little implementation guidance are associated with opportunisticreporting incentives, but are also value relevant. By contrast, the write-downs

8 Schipper (1989, p. 91) notes that ‘‘research results to date have not shed any light on the issue ofwhether some change in the amount of managerial discretion might even add to the informativenessof accounting earnings’’. Our study essentially provides evidence on this issue.


arising from a standard (Reg. SX) providing significant implementation guid-ance are less value relevant than the SFAS No. 121 write-downs, but tests pro-vide inconclusive evidence as to whether the Reg. SX write-downs areassociated with opportunistic reporting incentives. Collectively, our findingssuggest that implementation guidance, i.e., detail and structure for applyinga standard, may constrain opportunism (as suggested by Schipper, 2003),but potentially also entail a cost in terms of lower value relevance by imposinga one-size-fits-all measurement and recognition regime that (in our oil and gascontext) prevents managers in full cost firms from using their judgment andprivate information in deciding the timing and amount of the write-downs.These findings are broadly consistent with the notion that judgment (account-ing discretion) is essential to the practice of accrual accounting. In other words,discretion allows managers to communicate their insights (private information)about the value of the firm’s assets. By contrast, extensive implementationguidance may limit opportunistic reporting, but at the potential cost of dimin-ishing the usefulness of the information provided to investors.9

The remainder of the paper is organized as follows. Section 2 discusses theaccounting background and related research. Section 3 describes our researchdesign, while Section 4 discusses the results of our tests. Section 5 offers con-cluding comments.

2. Accounting background and related research

2.1. Accounting background

Firms engaged in oil and gas exploration and production may use either thefull cost method or the successful efforts method of accounting. The two meth-ods differ in how they account for the cost of drilling nonproductive wells. Thesuccessful efforts method expenses these costs when the well is deemed nonpro-ductive, whereas the full cost method capitalizes and amortizes these costsunder the rationale that the cost incurred to discover producing wells necessar-ily includes the cost of drilling nonproductive wells.

9 A recent study by Wyatt (2005) also suggests that although discretion opens the door toaccounting manipulation, it also improves the quality of reported accounting information. In herstudy, Wyatt (2005) examines the accounting recognition of intangible assets in Australia where,unlike the US, firms can capitalize R&D spending. Her findings suggest that ‘‘limitingmanagement’s choices to record intangible assets tends to reduce, rather than improve, the qualityof the . . . investors’ information set’’ (p. 967). Similarly, Altamuro et al. (2005) document thataggressive revenue recognition practices targeted by SEC Staff Accounting Bulletin (SAB) 101 weredriven by earnings manipulation considerations yet also yielded earnings numbers that were morevalue relevant.


Because full cost accounting capitalizes the cost of drilling nonproductivewells, the net book value of oil and gas assets over time could easily grow largerthan the underlying value of oil and gas assets. This possibility led the SEC in1978 to require that full cost firms recognize an impairment loss if the bookvalue of oil and gas assets exceeds a ‘‘cost ceiling’’, which proxies for the mar-ket value of the oil and gas assets.10 Under Regulation SX 4-10, a principalcomponent of the cost ceiling is the value of the producing reserves, which ismeasured as the present value of the future net revenues from ‘‘proved’’ oiland gas reserves based on oil and gas spot prices prevailing on the balancesheet date and discounted using a uniform 10% interest rate.

While full cost firms recognize impairment losses as prescribed by Reg. SX,successful efforts firms recognize oil and gas impairment losses pursuant toSFAS No. 121 (FASB, 1995).11 In contrast to the SEC’s full cost impairmenttest, SFAS No. 121 (para. 7) provides little objective guidance in determiningthe market value of assets, sanctioning such valuation techniques as theexchange price, discounted future expected cash flows, option-pricing models,matrix pricing, option-adjusted spread models, and fundamental analysis.Moreover, SFAS No. 121 allows firms to assign value to significantly moreuncertain categories of reserves (i.e., ‘‘probable’’ and ‘‘possible’’ reserves) whileReg. SX (for the full cost firms) explicitly requires that only ‘‘proved’’ reservesbe valued.12 Effectively, SFAS No. 121 enunciates a principle (i.e., an impair-ment loss ‘‘shall be measured as the amount by which the carrying amount ofthe asset exceeds the fair value of the asset’’) with little implementation guid-ance while leaving it to the discretion of management to determine the mostappropriate means of determining fair value. Not surprisingly, the SEC(2003) criticizes SFAS No. 121 as an accounting standard that does ‘‘not pro-vide sufficient framework for the application of judgment’’ (p. 25). Thus, oiland gas impairment losses recognized by full cost firms are derived from a stan-dard that provides significant implementation guidance tied to oil and gas spotprices on a specific (the balance sheet) date, whereas similar losses recognized

10 Per Reg. SX 4-10(i)(4), ‘‘For each cost center, capitalized costs, less accumulated amortizationand related deferred income taxes, shall not exceed an amount (the cost center ceiling) equal to thesum of: (A) the present value of future net revenues from estimated production of proved oil andgas reserves . . .; plus (B) the cost of properties not being amortized . . .; plus (C) the lower of cost orestimated fair value of unproved properties . . .; less (D) income tax effects related to differencesbetween the book and tax basis of the properties involved’’.11 As noted previously, SFAS No. 121 was the applicable standard during the time period

examined in our study. Also as noted previously, although SFAS No. 144 has replaced SFAS No.121, it ‘‘does not change the latter standard’s general provisions’’ (Riedl, 2004, p. 825).12 As discussed by Arps (1962), petroleum engineers classify oil and gas reserves as either

‘‘proved’’, ‘‘probable’’, or ‘‘possible’’ depending upon the probability that the reserves ultimatelywill be extractable. Proved, probable, and possible reserves are reserves for which there is at least a95%, at least a 50%, or less than a 50% probability of extraction, respectively.


by successful efforts firms are derived from a much more flexible accountingstandard.

The greater flexibility in SFAS No. 121 (relative to Reg. SX) potentiallyfacilitates opportunistic reporting, but also enables managers to better revealtheir private information about the economics of the firm. By contrast, themechanical aspect of Reg. SX (relative to SFAS No. 121) potentially constrainsopportunistic reporting but prevents managers from using write-downs toreveal their insights. For example, a precipitous fall in oil and gas prices onthe balance sheet date often will mechanically trigger an impairment loss underReg SX (since write-downs are based on oil and gas spot prices on the balancesheet date), but such a price decline need not necessarily trigger a write-downunder SFAS No. 121 if managers’ insights suggest that cash flows from futureexpected oil and gas production will remain strong (e.g., managers believe thatthe price decline is temporary, or that there are sufficient ‘‘probable’’ and/or‘‘possible’’ reserves to compensate for the loss in the value of ‘‘proved’’reserves).13 Thus, Reg. SX imposes a one-size-fits-all recognition and measure-ment regime that risks imposing similar accounting on economically dissimilarevents.

2.2. Prior research

Alciatore et al. (1998) provide a comprehensive review of the prior literaturerelating to asset write-downs. Although these write-downs can be economicallysignificant, they suggest that the flexibility permitted by GAAP (with respect tothe magnitude and timing of the write-downs) has raised questions about theirpotential value relevance due to the common perception that asset impairmentlosses are largely used to manipulate reported earnings. Indeed, Francis et al.(1996), Rees et al. (1996), and Zucca and Campbell (1992) document thatimpairment losses appear to be influenced in part by managerial incentivesto report opportunistically as well as by the extent of bona fide impairment.Further, they suggest that managers tend to put a positive spin on reportedwrite-downs by implying that these are one-time (transitory) events intendedto clear the deck for future earnings growth. In any event, prior research(e.g., Elliott and Hanna, 1996; Elliott and Shaw, 1988; Francis et al., 1996;Rees et al., 1996) indicates that the stock market’s reaction to asset write-downs is negative, i.e., that reported write-downs are value relevant and thatinvestors view these losses as an indicator of asset impairment rather than asa signal of an expected improvement in future earnings.

In the specific context of the oil and gas industry, Alciatore et al. (2000),Chen and Lee (1995), and Frost and Bernard (1989) examine impairment losses

13 Probable, possible, and proved reserves were discussed previously in ‘Footnote 12’.


reported by oil and gas firms during the oil price free-fall that occurred in early1986. Frost and Bernard (1989) examined whether debt-based contracting costsinfluenced the signed magnitude of the stock price response to reported impair-ment losses. They were unable to detect the posited effect, a finding they attri-bute to the predominant industry practice of specifying financial covenants interms of physical reserve quantities rather than accounting-based metrics.Chen and Lee (1995) find that full cost firms with accounting-based bonusplans switched from full cost to successful efforts accounting to avoid reportingfull cost impairment losses. Alciatore et al. (2000) document that these impair-ment losses increased the alignment between book values and equity values.Taken together, these three studies suggest that the 1986 full cost write-downswere reasonably timely, relevant, and were viewed sufficiently costly that somefirms changed accounting methods to avoid reporting an impairment loss.

Finally, as discussed previously, Riedl (2004) contrasts the characteristics ofwrite-downs reported before and after the issuance of SFAS No. 121 for abroad range of firms (i.e., not just oil and gas firms), and suggests that theresult of the greater discretion provided by SFAS No. 121 is an increase inopportunistic reporting (although he does not test the effects of the accountingdiscretion provided by SFAS No. 121 on the value relevance of the reportedwrite-downs). Note that Riedl (2004) focuses on SFAS No. 121 and thusexcludes ‘‘full cost’’ oil and gas firms from his study. Also, Riedl (2004) focusesexclusively on the opportunistic reporting effects associated with SFAS No.121. By contrast, we examine both the opportunistic reporting and value rele-vance effects associated with SFAS No. 121 and Reg. SX for oil and gas firms.Specifically, we take advantage of the unique jurisdictional split that exists inthe oil and gas industry to examine whether managers’ response to the differ-ential implementation guidance provided by Reg. SX and SFAS No. 121 affectsopportunistic reporting and the value relevance of the reported write-downs.

3. Research design

3.1. Opportunistic reporting

In this section, we examine the association between the reported impairmentwrite-downs and incentives for managers to report opportunistically. Specifi-cally, we specify a firm’s write-down decision as a Tobit function of the eco-nomic determinants of impairment plus various proxies for opportunisticreporting. We use a Tobit rather than an OLS model since the dependent var-iable (impairment write-downs) is censored at zero (because firms cannot write-up their assets).

However, since firms self-select into full cost or successful efforts accountingmethods, we first use Heckman’s (1979) two-step approach as a control for


potential selection bias in the opportunistic reporting model (discussed below)that examines the association between the reported write-downs and managers’incentives to manipulate earnings.14 The approach unfolds by first estimating aProbit accounting choice model (model 1 below), retaining the parameters, andusing these parameters to construct the so-called ‘‘inverse Mills ratio’’ (IMR),which is calculated as the ratio of the standard normal density to the cumula-tive probability distribution function (both evaluated at the fitted value of theProbit model). The IMR appears as an added regressor in the second stageopportunistic reporting model (model 2 below) to control for selection bias(we adjust the second stage standard errors whenever IMR is a regressor sinceit is a ‘‘generated regressor’’). See Maddala (1991) for more detail on the use ofthis technique as a control for self-selection bias.

SEit ¼ a0 þ a1EXPLit þ a2REPLACEit þ a3LnðSIZEitÞ

þXxx¼00

xx¼96

axxYEARxxþ e1it ð1Þ

where SEit, 1 for successful efforts firms, and 0 otherwise; EXPLit, explorationintensity of the firm, defined as total exploration expenditures of firm i duringyear t, scaled by total oil and gas revenues; REPLACEit, reserve replacementratio of the firm, defined as the present value of reserves discovered by explo-ration during the current year, scaled by total oil and gas revenues; Ln(SIZEit),natural log of firm size, measured as total oil and gas revenues; YEARxx, dum-my variables representing the years 1996 through 2000, with 2001 as the omit-ted category.

The explanatory variables in the accounting choice model (1) are motivatedby findings reported in Deakin (1979) and Malmquist (1990), who show thatchoice of the successful efforts accounting method is increasing in firm sizeand decreasing in the exploration intensity of the firm. We operationalize firmsize (SIZE) as total annual oil and gas sales revenues. We use total revenuesrather than total assets as the size proxy since revenues are exogenous whileassets are endogenous to the accounting method chosen. Consistent with theprior literature, SIZE enters the accounting choice model in log-transformedform. Exploration intensity is operationalized as variables EXPL andREPLACE. Variable EXPL, defined as exploration spending divided by total

14 Note that the problem of self-selection bias in the context of impairment losses should be muchless severe during the period of our study as compared to the pre-SFAS No. 121 period. Pre-SFASNo. 121, full cost firms could avoid impairment losses altogether by changing to successful effortsaccounting (see for example the evidence in Chen and Lee, 1995). Clearly self-selection was aneclipsing issue in any study of write-offs prior to SFAS No. 121. However during the period of ourstudy, full cost firms could no longer avoid impairment loss recognition merely by switching tosuccessful efforts accounting. Thus, the issue of self-selection, while still potentially relevant, is nolonger the eclipsing issue that it once was with respect to write-downs.


oil and gas revenues, measures the fraction of each dollar of oil and gas salesthat is expended in an effort to discover new oil and gas reserves. VariableREPLACE, defined as the present value of oil and gas discoveries during thecurrent year divided by total oil and gas revenues, measures the fraction ofeach dollar of oil and gas sales that is replaced in the current year by the pres-ent value of newly discovered reserves. Larger values of EXPL and REPLACEdenote greater exploration intensity. Consistent with the prior literature, wepredict a1 < 0, a2 < 0, and a3 > 0.

As noted previously, we use the above Heckman’s (1979) approach as a con-trol for potential self-selection bias in the Tobit write-down model (2) below,which is estimated by maximum likelihood with fixed time effects and randomfirm effects.

WOTAit ¼ b0 þ b1SFAS69it þ b2DMGMTit þ b3BATHit

þ b4SMOOTHit þ b5DEBTit þ b6IMRit

þXxx¼00

xx¼96

bxxYEARxxþ e2it ð2Þ

where WOTA is the aftertax amount of the impairment write-down deflated byending assets (before write-down); SFAS69 is the ending historical cost of oiland gas assets (before the write-down) less the ending present value of oiland gas assets deflated by ending assets (before the write-down). The historicalcost and present value measure of oil gas assets are obtained from footnote dis-closures pursuant to paragraphs 18 and 30 of SFAS No. 69, respectively;DMGMT is a dummy variable = 1 if the firm’s CEO changed during the cur-rent or preceding fiscal year, 0 otherwise; BATH is the change in annual earn-ings (before the write-down) from year t � 1 to t deflated by fiscal year-endassets (before the write-down) when this change is below the median of non-zero negative values for this metric, and 0 otherwise; SMOOTH is the changein annual earnings (before the write-down) from year t � 1 to t deflated by fis-cal year-end assets (before the write-down) when this change is above the med-ian of non-zero positive values for this metric, and 0 otherwise; DEBT is adummy variable = 1 if the firm’s debt is private (i.e., not publicly rated byStandard & Poor’s), and 0 otherwise; IMR is the inverse Mill’s ratio (obtainedfrom model 1) to correct for selection bias; YEARxx are dummy variables rep-resenting the years 1996–2001, with 2001 as the omitted category.

In model (2), note that although the write-downs (as represented by thedependent variable WOTA) decrease reported earnings, they are reflected inthe regressions as a positive number. As discussed below, we include in oursample all oil and gas firms for which complete data are available.

The reporting of write-downs is conceptually a function of economic factorsas well as opportunistic reporting incentives. Thus, managers are expected to


record a write-down if the firm’s oil and gas assets are impaired. At the sametime, in the absence of enforceable guidelines over the recording of the write-downs, the reported amounts may be influenced both by opportunistic report-ing incentives as well as managerial insights into the value of the firm.

The purpose of our analysis is to contrast the determinants of the reportedwrite-downs for full cost and successful efforts firms, i.e., the relative associa-tions across the Reg. SX and SFAS No. 121 regimes, respectively. Hence, weestimate the write-down model (2) for full cost and successful efforts firms sep-arately. Consistent with Riedl (2004), we expect to see an association betweenthe reported write-downs and opportunistic reporting incentives for the suc-cessful efforts (i.e., SFAS No. 121) firms. By contrast, given the greater imple-mentation guidance provided by Reg. SX, economic factors (as captured bySFAS No. 69 disclosures based on oil and gas spot prices on the balance sheetdate) may be expected to have a greater association with the reported write-downs for full cost (i.e., Reg SX) firms, although this is an empirical questionthat we address in our study.

3.1.1. Economic factors

Prior studies on impairment losses (discussed previously) have been largelyinter-industry in nature, and were compelled to use indirect asset impairmentindicators (such as changes in sales, earnings, or cash flows) that were measur-able across all industries. By contrast, our study focuses on a single industry inwhich a direct indicator of asset impairment (based on the SFAS No. 69 foot-note disclosures, described below) is available.

SFAS No. 69 (paragraphs 18 and 30) requires that oil and gas firms discloseboth a historical cost and a present value measure of their oil and gas assets,with the latter measure based on expected future cash flows (discounted at auniform 10% discount rate) determined using proved reserve quantities andoil and gas spot prices on the balance sheet date. For the full cost firms,Reg. SX explicitly mandates use of the SFAS No. 69 present value measureas a proxy for market value in assessing and measuring the impairment inoil and gas assets. By contrast, for the successful efforts firms, SFAS No.121 identifies an array of acceptable proxies for market value from which man-agement can choose. Survey evidence (Coe et al., 2001) indicates that in assess-ing impairment losses, most successful efforts firms proxy for market valueusing a present value measure of oil and gas assets based on managers’ expec-tation of future oil and gas prices/extraction costs, a firm-specific (rather thanan uniform 10%) discount rate, and a reserve base defined to include both‘‘proved’’ as well as ‘‘probable/possible’’ reserves.15

15 By contrast, as noted previously, Reg. SX constrains the full cost firms to use the oil and gasspot price on the balance sheet date, a standard 10% discount rate, and ‘‘proved’’ reserves only.


In our model (2), the explanatory variable SFAS69 is defined as the differ-ence between the historical cost and the present value of oil and gas assets, withthe difference deflated by end-of-year total assets (before the write-down). Asnoted above, the historical cost and present value amounts for the oil andgas assets are obtained from the footnote disclosures made pursuant to SFASNo. 69. Since the dependent variable WOTA (the write-down) in the regres-sions is reflected as a positive number, the predicted sign for variable SFAS69in the regressions is positive, i.e., the higher the historical cost of oil and gasassets relative to their present value, the greater the magnitude of the write-down.16

3.1.2. Incentive factors

Consistent with Riedl (2004) we include four explanatory variables to cap-ture managers’ incentives to report opportunistically. Variable DMGMT is adummy equal to 1 if the firm’s CEO changed during the current or precedingfiscal year, and 0 otherwise. A new CEO can be expected to change the firm’sstrategic focus or exercise greater scrutiny over existing assets, resulting in animpairment write-off. Also, a new CEO may be tempted to take all potentialcharges to earnings and attributing them to the previous administration withthe intent of improving the firm’s reported performance going forward. Forthis reason, the predicted sign for variable DMGMT is positive.

Variables BATH and SMOOTH are proxies for situations where reportedearnings are ‘‘unexpected’’ low or ‘‘unexpectedly’’ high, respectively. As dis-cussed by Riedl (2004), managers may use accounting discretion opportunisti-cally to either take ‘‘big bath’’ charges and/or smooth earnings to achieve adesired financial reporting outcome. Consistent with Riedl (2004), variableBATH is defined as the change in earnings (before the write-down) from yeart � 1 to t deflated by ending assets (before the write-down) when the change isbelow the median of non-zero negative values for this metric, and 0 otherwise.Since the BATH variable takes on negative values (when it is not equal to 0)

16 For completeness, we note that Riedl (2004) included the following variables to control foreconomic factors: change in GDP, change in industry return on assets (ROA), change in sales,change in earnings, and change in operating cash flows. In our study, we include dummy variablesfor years which effectively control for changes in GDP, i.e., change in GDP is perfectly correlatedwith the year dummies. Similarly, since our study is restricted to one (the oil and gas) industry, thechange in industry ROA is perfectly correlated with the year dummies already included in ourmodel. Finally, in comparison to the variables change in sales, change in earnings, and change inoperating cash flows, our variable SFAS69 (as noted previously) is more appropriate as aneconomic factor since it is a direct indicator of impairment constructed from SFAS No. 69 oil andgas supplemental disclosures. As discussed later in the paper, variable SFAS69 was highlysignificant in our regressions. By contrast, the variables change in sales, change in earnings, andchange in operating cash flows were never significant in Riedl’s (2004) regressions during the SFASNo. 121 regime.


and the dependent variable WOTA enters the regressions only as a positivenumber (when it is not equal to 0), the predicted sign for variable BATH is neg-ative (consistent with the notion that firms take write-downs as part of a ‘‘bigbath’’).

Along the same lines, variable SMOOTH is defined as the change in earn-ings (before the write-down) from year t � 1 to t deflated by ending assets(before the write-down) when the change is above the median of non-zero posi-

tive values, and 0 otherwise. Since variable SMOOTH takes on positive values(when it is not equal to 0) and the dependent variable WOTA enters the regres-sions only as a positive number (when it is not equal to 0), the predicted signfor variable SMOOTH is positive (consistent with the notion that firms takewrite-downs as part of an effort to smooth, i.e., offset an otherwise much largerrise in earnings). Put differently, the variables BATH and SMOOTH ‘‘arecoded to turn on when below/above their respective medians to focus on rangeswherein managers are more likely to have incentives to engage in ‘big bath’ or‘smoothing’ reporting behavior’’ (Riedl, 2004, p. 833).

Finally, consistent with Riedl (2004), variable DEBT is a dummy variableequal to 1 if the firm has private debt (i.e., debt not publicly rated by the ratingagencies), and 0 otherwise. Riedl (2004) argues that because private debt ismore likely to have covenants affected by the write-down (such as the magni-tude of net worth or the debt to equity ratio), the predicted sign for variableDEBT is negative. However, as noted by Frost and Bernard (1989), account-ing-based debt covenants may be less applicable in the oil and gas industrysince the predominant industry practice is to specify financial covenants interms of physical reserve quantities rather than accounting-based metrics. Sep-arately, one could argue that covenants on private debt (whether accounting-based or based on physical reserve quantities) can be more easily re-negotiatedwith lenders than covenants on public debt, since in the event of covenant vio-lations it would likely be easier to re-negotiate the terms of the debt with a fewprivate lenders than with a much larger number of public debt holders. Thus,to the extent that write-downs are utilized to report opportunistically, thesewrite-downs could be more likely in the context of private (rather than public)debt. For this reason, we do not predict the sign of variable DEBT in theregressions.

3.2. Value relevance

We assess the value relevance of the reported impairment write-downs usingthe model specified in the following equation:

Rit ¼ b0 þ b1DNIit þ b2NIit þ b3WDit þ b4IMRit þ e3it ð3ÞThe variables in model (3) are defined as follows: R is the annual market-ad-justed return calculated over the period �9 to +3 months around fiscal


year-end; DNI is the change in annual earnings (before the write-down) fromyear t � 1 to year t, scaled by the market value of equity at the beginning ofthe return calculation period; NI is the level of annual earnings (before thewrite-down) for year t, scaled by the market value of equity at the beginningof the return calculation period; WD is the aftertax amount of the annualimpairment write-down, also scaled by the market value of equity at the begin-ning of the return calculation period; IMR, inverse Mill’s ratio.

In this model, the dependent variable Rit represents the market-adjustedannual stock return measured over the period �9 to +3 months around the fis-cal year-end. As noted by Ali and Zarowin (1992) and Easton and Harris(1991), both earnings changes and earnings levels (scaled by the market valueof equity at the beginning of the return period) have explanatory power in aregression of annual returns on earnings. Hence, our model (3) includes bothearnings changes and levels (before the write-down) – DNI and NI (both scaledby the market value of equity at the beginning of the return period) – as explan-atory variables. Consistent with Ali and Zarowin (1992), we estimate the earn-ings response coefficient (ERC) as the sum of the coefficients (b1 and b2) on theearnings change and level variables (DNI and NI). The model also includes var-iable IMR (the inverse Mill’s ratio) to correct for selection bias as discussedpreviously. The test variable in model (3) is WD, i.e., the reported after-taxwrite-down (also scaled by the market value of equity at the beginning ofthe return period). Unlike model (2), model (3) omits year-dummies since thedependent variable Rit is a market-adjusted return measure that effectively con-trols for time-specific fixed effects.

We estimate model (3) for the full cost and successful efforts firms sepa-rately, and assess the value relevance of the reported write-downs based onthe significance and magnitude of the coefficient for variable WD, i.e., thewrite-down response coefficient (WDRC). Further, as discussed below, wecompare the earnings response coefficient (ERC) and the write-down responsecoefficient (WDRC) across the two firm-groups (i.e., the full cost and successfulefforts firms), to gauge whether the greater implementation guidance providedby Reg. SX for full cost firms affects the value relevance of the reported write-downs for these firms.

4. Data and findings

4.1. Sample selection

We focus on firms with SIC code 1311 (i.e., firms with core operations in oiland gas discovery and extraction) and reported in Research Insight during1996–2001. The sample period begins in 1996 since SFAS No. 121 was effectivefor fiscal years beginning after December 15, 1995, and ends in 2001 since


SFAS No. 121 was superceded by SFAS no. 144 for fiscal years beginning afterDecember 15, 2001.

As indicated in Table 1, the initial screen identified 891 firm-years for whichcomplete data for the variables in our study were available.17 From these, weeliminated 14 firm-years in which firms changed their oil and gas accountingmethod (from full cost to successful efforts, or vice versa), 68 firm-years inwhich financial statement comparability was impaired by a change in account-ing period or a change in accounting entity, and 244 firm-years in which oil andgas supplementary footnote disclosures were unavailable, leaving a sample of565 firm-years that was fairly evenly distributed across years and fairly evenlydistributed between the two accounting methods. We reviewed each of theannual reports to identify firm-years reporting a write-down of oil and gasassets. As shown in panel B, full cost and successful efforts firms reported 94and 161 write-downs, respectively. In total, 255 of the 565 firm-years reportedoil and gas asset impairment write-downs.

4.2. Characteristics of the sample

Table 2 provides descriptive statistics and correlation coefficients for thevariables in our study. With respect to the dependent variables in our threeregression models, panel A shows that successful efforts firms comprisedapproximately 54% of the sample (mean value of SE is 0.5416). The average(mean) reported impairment write-down (variable WOTA) was approximately6.4% of the end-of-year total assets (before the write-down). Finally, for oursample, the mean annual market-adjusted return (variable R) calculated overthe period �9 to +3 months around fiscal year-end was approximately 6%.

With respect to the explanatory variables, panel A shows that for our sam-ple observations, the mean exploration intensity (variable EXPL), i.e., explora-tion expenditures scaled by oil and gas revenues, was approximately 31%.Further, the mean reserve replacement ratio (variable REPLACE), i.e., thepresent value of new reserve discoveries scaled by oil and gas revenues forthe current period, was approximately 99%. Also, the mean firm size (variable

17 Much of the data used in our study had to be hand-collected, since Compustat does not providethe supplementary SFAS No. 69 disclosure data for oil and gas firms. Also, we found Compustat’spolicy with regard to reporting impairment losses for oil and gas assets to be ambiguous.Specifically, the documentation for Compustat claims to record impairment losses in the ‘‘specialitems’’ variable as well as the ‘‘cost of goods sold’’ variable. We hand-collected relevant data fromannual reports for oil and gas firms. Subsequently, we cross-checked known instances of oil and gasimpairment losses with Compustat data, and found that indeed some write-offs were reported byCompustat as part of ‘‘special items’’ while others appeared to be included in ‘‘cost of goods sold’’.For our overall sample, the correlation between our hand-collected measure of impairment lossesand the Compustat ‘‘special-item’’ variable was only 0.21. For the sub-sample of firm-years withknown impairment losses, the correlation was only 0.07.

Table 1Sample selection

Panel A – Sample selection

Population of SIC 1311 firm-years reported in Research Insight 1996–2001with complete data

891

Change from full cost to successful efforts accounting method (or viceversa)

�14

Change in accounting period or change in reporting entity �68Oil and gas reserve disclosure data unavailable �244

Total firm-year observations 565

Year Full cost (FC) Successful efforts (SE) Totals

Write-down Non-write-down Write-down Non-write-down

Panel B – Firm-years partitioned by presence/absence of write-down, year, and accounting method

1996 3 33 18 35 891997 13 32 24 33 1021998 45 6 44 14 1091999 8 34 28 22 922000 8 39 20 27 942001 17 21 27 14 79

94 165 161 145 565


Ln(SIZE)) measured as the natural log of the firm’s oil and gas revenues (mea-sured in millions of dollars) was about 3.71 (or approximately $40.85 million,before the log transformation).

As the economic factor underlying oil and gas asset impairments, the differ-ence between the historical cost and the present value of oil and gas assetsdeflated by year-end assets (variable SFAS69), had a mean value of negative

14% indicating that, on average, the present value of oil and gas assets wereabove the historical cost of those assets during the period of our study forthe sample firms. Approximately 16.8% of our sample firm-years experienceda change in CEO (variable DMGMT). Variable BATH which represents thechange in annual earnings deflated by year-end assets – when the change isbelow the median of non-zero negative values – had a mean value of approxi-mately negative 2%. By the same token, variable SMOOTH which representsthe change in annual earnings deflated by year-end assets – when the changeis above the median of non-zero positive values – had a mean value of approx-imately 6%. Approximately 67.8% of our sample observations had private debt(variable DEBT).

Separately, the change in annual pre-write-down earnings scaled by thebeginning market value of equity (variable DNI) had a mean value of approx-imately 4.5% for our sample observations. By contrast, the level of the annualpre-write-down earnings scaled by the beginning market value of equity

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(variable NI) had a mean value of approximately 1.6%. Finally, variable WD,the amount of the reported impairment write-down (also scaled by the begin-ning market value of equity) had a mean value of approximately 6.8%.

Table 2(panel B) reports the correlations among the various dependent andindependent variables. As expected, the bivariate correlations between vari-ables SFAS69 and WOTA, and between variables WOTA and R are positiveand negative, respectively. Further, the various independent variables exhibitonly modest bivariate correlations suggesting a low potential for collinearityin the multivariate regression analyses. Subsequent examination of standardcollinearity diagnostics, i.e., variance inflation factors (VIFs) and data matrixcondition indices, for our various regressions (described below) confirmed thisassessment. In no instance did these collinearity diagnostics approach thethreshold values that would indicate a collinearity ‘‘problem’’.

4.3. Tests of opportunistic reporting

As discussed previously, in our tests we control for self-selection bias. Thus,Table 3 reports the maximum likelihood estimates for our accounting choicemodel (model 1). This Probit model exhibits good overall fit, with a v2 statistic(=27.83) that soundly rejects the null hypothesis that all coefficients in themodel are equal to zero (p = 0.0005). As predicted, the probability of choosingthe successful efforts method of accounting (1) decreases as firms become moreexploration-intensive (EXPL and REPLACE both negative and significant),and (2) increases as firms become larger in size (Ln(SIZE) positive and signif-icant). The probability of choosing successful efforts accounting appears unas-sociated with time-specific factors as none of the year-dummies were significant.

Table 4 summarizes the maximum likelihood estimates for our impairmentwrite-down Tobit model (model 2) for the full cost and successful efforts firmsseparately. This model also includes variable IMR (the inverse Mill’s ratio) tocorrect for selection bias, as well as yearly dummies. As reported in Table 4, themodel exhibits strong explanatory power for both full cost and successfulefforts firms (significant at the p < 0.0001 level for both sets of firms).18 Consis-tent with expectations, variable SFAS69 (which is a direct proxy for the impair-ment in oil and gas assets) is significant with the expected positive sign for bothfull cost and successful efforts firms.

With respect to the variables in our model that proxy for opportunisticreporting incentives, i.e., variables DMGMT, BATH, SMOOTH, and DEBT,the null hypothesis (specified as H1 in Table 4) that all four coefficients are

18 Consistent with prior research (e.g., Francis et al., 1996), the significant and negative interceptsreported in Table 4 imply that when all the explanatory variables are assigned zero values, thefirm’s asset values exceed book values. Recall that the dependent variable WOTA enters theregression as a positive number even though a write-down lowers earnings.

Table 3Probit accounting choice model

SEit ¼ a0 þ a1EXPLit þ a2REPLACEit þ a3LnðSIZEÞ þXxx¼00

xx¼96

axxYEARxxþ e1it ð1Þ

Expected sign Coefficient Standard error t-Statistic

INTERCEPT ? �0.0248 0.18111 �0.14EXPL – �0.3078 0.12012 �2.56***

REPLACE – �0.0797 0.03976 �2.00**

Ln(SIZE) + 0.0459 0.02552 1.80**

YEAR96 ? 0.2678 0.19962 1.34YEAR97 ? 0.2219 0.19306 1.15YEAR98 ? 0.1171 0.18903 0.62YEAR99 ? 0.1400 0.19686 0.71YEAR00 ? 0.0037 0.19781 0.02

Nobs 565Model Chi-square 27.83Overall model significance p = 0.0005

Notes: Model (1) above – the accounting choice model – is estimated as a Probit model based onannual observations pooled across the years 1996–2001 with control for time fixed effects. Thesubscripts i and t denote firm and year, respectively. SE = 1 for successful efforts firms, and 0otherwise. EXPL is the exploration intensity of the firm, defined as total exploration expendituresof the firm scaled by total oil and gas revenues. REPLACE is the reserve replacement ratio of thefirm, defined as the present value of reserve discoveries scaled by total oil and gas revenues.Ln(SIZE) is the natural log of firm size, measured as total oil and gas revenues. YEARxx aredummy variables representing the years 1996–2001, with 2001 as the omitted category.*,**,*** denote significance levels of 0.10, 0.05, and 0.01 respectively. Significance levels are based onone-tailed tests when a directional hypothesis is specified; two-tailed otherwise.


jointly equal to zero was rejected for the successful efforts firms (F = 2.85 sig-nificant at the 0.02 level) but not for the full cost firms (F = 1.17 not significantat conventional levels of significance). The rejection of the null for successfulefforts firms indicate that opportunistic reporting incentives are associated withreported impairment losses for these firms.

Consistent with the joint test for all four coefficients discussed above, wefind the individual variables to be significant – with the predicted signs –for successful efforts firms but not for full cost firms. Thus, for successfulefforts firms, we find that reported impairment losses are larger for firms witha CEO change during the current or preceding year, i.e., variable DMGMT issignificant with a positive sign. Similarly, variable BATH is significant with anegative sign indicating that when the change in the annual pre-write-downearnings is below the median of non-zero negative values for this metric,the reported write-down is larger, indicating that managers may be usingtheir accounting discretion to take a write-down and report a larger loss than

Table 4Tobit write-down model with control for self-selection bias

WOTAit ¼ b0 þ b1SFAS69it þ b2DMGMTit þ b3BATHit þ b4SMOOTHit

þ b5DEBTit þ b6IMRit þXxx¼00

xx¼96

bxxYEARxxþ e2it ð2Þ

Expectedsign

Full cost Successful efforts

Coefficient Standarderror

t-Statistic Coefficient Standarderror

t-Statistic

INTERCEPT ? �0.2326 0.0523 �4.45*** �0.1348 0.0317 �4.26***

SFAS69 + 0.3393 0.0243 13.94*** 0.0949 0.0115 8.22***

DMGMT + 0.0424 0.0379 1.12 0.0295 0.0194 1.52*

BATH – 0.0032 0.1721 0.02 �0.1948 0.0963 �2.02**

SMOOTH + 0.1281 0.1124 1.14 0.1574 0.0977 1.61*

DEBT ? �0.0020 0.0295 �0.07 0.0382 0.0202 1.89*

IMR ? 0.0653 0.0377 1.73* 0.0893 0.0396 2.26**

YEAR96 ? �0.0609 0.0756 �0.81 �0.0053 0.0392 �0.13YEAR97 ? �0.0133 0.0533 �0.25 �0.0041 0.0352 �0.12YEAR98 ? 0.1429 0.0465 3.07*** 0.0543 0.0338 1.61YEAR99 ? �0.0149 0.0549 �0.27 0.0064 0.0364 0.18YEAR00 ? 0.1363 0.0601 2.27** 0.0231 0.0381 0.61

OLS Rsq 70.45% 28.44%Nobs 259 306Overall modelsignificance

p < 0.0001 p < 0.0001

Comparison tests. H1(FC)0: b2(FC) = b3(FC) = b4(FC) = b5(FC) = 0, not rejected (F = 1.17,p = 0.32). H1(SE)0: b2(SE) = b3(SE) = b4(SE) = b5(SE) = 0, rejected (F = 2.85, p = 0.02). H20:b2(FC) = b2(SE) and b3(FC) = b3(SE) and b4(FC) = b4(SE) and b5(FC) = b5(SE) not rejected(F = 0.61, p = 0.66).Notes: Model (2) above – the impairment write-down model – is estimated as a Tobit model basedon annual observations pooled across the years 1996–2001 with control for time fixed effects andselection bias. The subscripts i and t denote firm and year, respectively.WOTA is the aftertax amount of the impairment write-down deflated by ending assets (before write-down). SFAS69 is the ending historical cost of oil and gas assets (before the write-down) less theending present value of oil and gas assets deflated by ending assets (before the write-down). Thehistorical cost and present value measure of oil gas assets are obtained from footnote disclosurespursuant to paragraphs 18 and 30 of SFAS No. 69, respectively. DMGMT is a dummy variable = 1if the firm’s CEO changed during the current or preceding fiscal year, 0 otherwise. BATH is thechange in annual earnings (before the write-down) from year t � 1 to t deflated by fiscal year-endassets (before the write-down) when this change is below the median of non-zero negative values forthis metric, and 0 otherwise. SMOOTH is the change in annual earnings (before the write-down)from year t � 1 to t deflated by fiscal year-end assets (before the write-down) when this change isabove the median of non-zero positive values for this metric, and 0 otherwise. DEBT is a dummyvariable = 1 if the firm’s debt is private (i.e., not publicly rated by Standard & Poor’s), and 0otherwise. IMR is the inverse Mill’s ratio (obtained from model 1) to correct for selection bias.YEARxx are dummy variables representing the years 1996–2001, with 2001 as the omitted category.*,**,*** denote significance levels of 0.10, 0.05, and 0.01 respectively. Significance levels are based onone-tailed tests when a directional hypothesis is specified; two-tailed otherwise.



otherwise, i.e., take a bath. Along the same lines, variable SMOOTH is sig-nificant with a positive sign indicating that when the change in the annualpre-write-down earnings is above the median of non-zero positive values forthis metric, the reported write-down is larger, indicating that managersmay be using their accounting discretion to take a write-down and report asmaller increase in earnings than otherwise, i.e., smooth earnings. Finally,variable DEBT is significant with a positive sign indicating that, other thingsbeing equal, write-downs are more likely when the firm has private debt. Asdiscussed previously, to the extent that managers in the oil and gas industryhave an incentive to report impairment write-downs, these losses may be eas-ier to live with in the context of private (rather than public) debt since cov-enant violations may be easier to re-negotiate with a few private lenders thanwith a much larger number of public debt holders. Finally, the reader shouldview the individual coefficient tests with a degree of caution, however, as thet-statistics in some cases border on marginal significance.19 Still, the strongresults obtained from the joint coefficient test allow us to infer that write-downs reported by successful efforts firms (under SFAS No. 121) reflectopportunistic reporting – a finding consistent with Riedl (2004) – althoughthe weak t-statistics may preclude us from confidently pointing to any oneincentive as being the driving factor.

By contrast, for full cost firms we find no evidence of opportunistic report-ing behavior. Specifically, none of the opportunistic reporting incentive testvariables (either individually or as a group) are significant for the full costfirms. While this result (i.e., the insignificance of the opportunism incentivevariables in the full cost group) is illuminating, it provides only weak evidencein support of the idea that full cost firms do not use impairment losses as anopportunistic reporting tool since the inability to reject the null does not implythat the null hypothesis is true.

To more directly speak to the question of whether there is a difference betweenfull cost and successful efforts firms in the opportunistic use of impairment losses,we structured pair-wise comparison tests of the coefficients between the full costand successful efforts firms. These coefficient comparisons test the null hypothesis(specified as H2 in Table 4) that the vector of coefficients for the opportunistic

19 For the successful efforts firms, only one of the opportunistic reporting test variables (BATH) issignificant at the 5% level while the others are significant at the 10% level. Still, collectively, theevidence suggests that the reported write-downs are associated with opportunistic reportingincentives for the successful efforts firms. Also, as discussed in the Additional Analysis sectionbelow, for a sub-sample (n = 526) of our sample firms with oil and gas assets equal to at least 75%of total assets, the opportunistic reporting test variables (for the successful efforts firms) weresignificant at the 1% and 5% levels but the pairwise coefficient comparison tests, discussed below,remaining insignificant.


reporting incentive variables for the full cost firms is no different from the corre-sponding vector for the successful efforts firms. Rejection of the null would sug-gest that the vector of incentive variables influence asset impairment losses in fullcost firms differently than in successful efforts firms. By contrast, failure to rejectthe null would mean that the evidence is inconclusive as to whether the vector ofincentive variables influence asset impairment losses differently in full cost firmsthan in successful efforts firms. As noted in Table 4, we are unable to reject the null(F = 0.61, p = 0.66).20

Thus, while we find evidence of an association between impairment lossesand opportunism incentives for successful efforts firms but not for full costfirms, we cannot rule out the possibility that the opportunistic reporting incen-tive variables impact reported impairment losses similarly in full cost and suc-cessful efforts firms. On balance, these results provide inconclusive evidence onthe issue of whether implementation guidance curtails the use of impairmentlosses as an opportunistic reporting tool by full cost firms.

4.4. Tests of value relevance

Table 5 summarizes the parameter estimates for our value relevance model(model 3). In this model, the dependent variable R is the annual market-adjusted return calculated over the period �9 to +3 months around fiscalyear-end. Consistent with prior research (Ali and Zarowin, 1992; Easton andHarris, 1991), we include both earnings changes and earnings levels (beforethe impairment write-down), i.e., DNI and NI (both scaled by the market valueof equity at the beginning of the return period) as explanatory variables. Alsoconsistent with prior research, we estimate the earnings response coefficient(ERC) as the sum of the coefficients (b1 and b2) on both the earnings changeand level variables (DNI and NI). The model also includes variable IMR(the inverse Mill’s ratio) – obtained from model (1) discussed previously – tocorrect for selection bias. The test variable in model (3) is WD, i.e., thereported impairment write-down (also scaled by the market value of equityat the beginning of the return period).

In Table 5, model (3) is estimated for full cost and successful efforts firmsseparately. The ERC estimates obtained by summing the coefficients b1 andb2 are 0.8296 (t-stat = 3.46) and 0.7781 (t-stat = 3.72) for the full cost and

20 We also conducted individual pair-wise coefficient comparisons (untabulated) for each of thefour incentive variables and in each case the results were similar, the null hypothesis that thecoefficients are equal could not be rejected.

Table 5Association between annual write-downs and contemporaneous stock returns

Rit ¼ b0 þ b1DNIit þ b2NIit þ b3WDit þ b4IMRit þ e3it ð3ÞExpected sign Full cost Successful efforts

Coefficient Standard error t-Statistic Coefficient Standard error t-Statistic

INTERCEPT ? 0.3976 0.2302 1.73* �0.1178 0.1616 �0.73DNI + 0.2695 0.1641 1.64** 0.7975 0.1348 5.92***

NI + 0.5601 0.1746 3.21*** �0.0194 0.1599 �0.12WD – �0.2148 0.0770 �2.79*** �0.8257 0.3073 �2.69***

IMR ? 0.3750 0.2703 1.39 0.2508 0.2220 1.13ERC 0.8296 0.2396 3.46*** 0.7781 0.2091 3.72***

Rsq 12.72% 23.49%Nobs 259 306Overall model significance p < 0.0001 p < 0.0001

Comparison tests.

H10: ERC(FC) = ERC(SE) not rejected (F = 0.03, p = 0.87)H20: WDRC(FC) = WDRC(SE) rejected (F = 3.72, p = 0.05)H30: WDRC(FC) = �ERC(FC) rejected (F = 5.96, p = 0.01)H40: WDRC(SE) = �ERC(SE) not rejected (F = 0.02, p = 0.90)

Notes: Model (3) above – the value relevance model – is estimated as an OLS model based on annual observations pooled across the years 1996–2001with control for self-selection bias. The subscripts i and t denote firm and year, respectively.R is the annual market-adjusted return calculated over the period �9 to +3 months around fiscal year-end. DNI is the change in annual earnings (beforethe write-down) from year t � 1 to year t, scaled by the market value of equity at the beginning of the return calculation period. NI is the level of annualearnings (before the write-down) for year t, scaled by the market value of equity at the beginning of the return calculation period. WD is the aftertaxamount of the annual impairment write-down, also scaled by the market value of equity at the beginning of the return calculation period. IMR is theinverse Mill’s ratio (from model 1) to correct for selection bias.Consistent with Ali and Zarowin (1992), ERC is the earnings response coefficient calculated by summing the slope coefficients (b1 and b2) on DNI andNI, i.e., ERC = b1 + b2. WDRC is the write-down response coefficient (slope coefficient on WD), i.e., WDRC = b3.

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successful firms, respectively. Separately, the write-down response coefficient(WDRC) estimates for the impairment write-down test variable WD is�0.2148 (t-stat = �2.79) and �0.8257 (t-stat = �2.69) for the full cost and suc-cessful efforts firms, respectively.21 These negative estimates can be explainedby the fact that although the effect of the write-downs is to lower earnings,these write-downs enter the regressions (as discussed previously) as a positivenumber.

The null hypothesis that the ERCs (0.8296 and 0.7781) for the full cost andsuccessful efforts firms are equal to each other could not be rejected (H1 inTable 5, F = 0.03).22 By contrast, the null hypothesis that the WDRCs forthe same two group of firms (�0.2148 and �0.8267) are equal was rejectedat the 0.05 level (H2 in Table 5, F = 3.72). In other comparison tests, the nullhypothesis that the ERC and the absolute value of the WDRC for the fullcost firms (0.8296 and 0.2148) are equal was rejected at the 0.01 level (H3in Table 5, F = 5.96). Not surprisingly, the null hypothesis that the ERCand the absolute value of the WDRC for the successful efforts firms (0.7781and 0.8257) are equal could not be rejected (H4 in Table 5, F = 0.90). Thesefindings collectively suggest that as measured by the ERCs, the value rele-vance of the reported pre-write-down earnings is similar for the full cost

21 Our finding that the write-down response coefficients (WDRCs) are statistically significant isconsistent with prior research. Specifically, Alciatore et al. (2000) and Rees et al. (1996) areassociation studies similar to ours, and both report WDRCs that are significantly negative and nodifferent in absolute magnitude from ERCs. By contrast, Elliott and Hanna (1996) and Elliott andShaw (1988) are narrow (two-day) window event studies surrounding the write-down announce-ment, and both report absolute WDRCs that are significantly negative but smaller in absolutemagnitude than ERCs. Finally, Francis et al. (1996) is also a narrow window event study butreports WDRCs significantly negative and larger in absolute magnitude than ERCs. In any event,all of these prior studies report that write-downs are value relevant, i.e., that WDRCs aresignificantly different from zero and negative in sign. Thus, our findings are consistent with priorresearch.22 Our finding that the ERCs for the full cost and successful efforts firms are equal (i.e., not

different from each other) is consistent with the most recent empirical evidence (Bryant, 2003, basedon 1994–1996 data). Separately, Kothari (2001, p. 128) reports that empirical estimates of ERCmagnitudes obtained in prior research range from 1 to 3. A test of the null hypothesis that our ERCestimates (0.8296 and 0.7781) are not different from 1 could not be rejected (F equal to 0.506 and1.13, respectively). Hence, our ERC estimates appear to be consistent with estimates reported inprior research. Relatedly, Kothari (2001, p. 143) notes that although ERC research has madesignificant progress in the last decade, ‘‘the best a researcher can do currently is to test whether acoefficient is statistically significant (i.e., different from 0) or whether it is significantly greater thanthe coefficient on another variable (e.g., coefficient on earnings versus on cash flow fromoperations)’’. In our study, we test whether the coefficients on pre-write-down earnings and on thereported write-downs are statistically significant (i.e., different from 0), and whether the coefficientsare significantly different from each other.


and successful efforts firms. By contrast, as measured by the WDRCs, thevalue relevance of the reported write-downs for full cost firms appears tobe lower relative to the value relevance of the reported write-downs for suc-cessful efforts firms.23

Separately, prior research (e.g., Collins and Kothari, 1989; Easton and Zmi-jewski, 1989; Kormendi and Lipe, 1987) documents that ERCs may vary as afunction of factors such as persistence, interest rates, growth, and risk (beta).Potentially, differences in these factors between the full cost and successfulefforts firms could account for the findings we document. To probe the sensi-tivity of our inferences to these factors, we re-estimated model (3) after addinginteraction variables that allowed the ERCs (and WDRCs) to vary across firmsas a function of interest rates, growth, and beta. However, the vector of inter-action terms induced severe collinearity rendering the model unstable. Alterna-tively, we tested for differences in interest rates, growth, and beta across oursample of full cost and successful efforts firms.24 In each case, the null hypoth-esis that interest rates, growth, and beta were equal across our sample of fullcost and successful efforts firms could not be rejected (p-values of 0.2516,0.4244, and 0.8647, respectively). These findings suggest that our findings withrespect to the ERCs and WDRCs for the full cost and successful efforts firms

23 To test for influential observations we did the following: first, we repeated our analysis 1000times using a randomly selected sample (with replacement) of 100 full cost observations and 100successful efforts observations. We then used these 1000 bootstrap estimates to construct a 95%confidence interval based on the percentile method described in Mooney and Duval (1993). Ourinference – that the WDRC coefficient for successful efforts firms is larger in absolute magnitudethan the WDRC coefficient for full cost firms – was supported by the bootstrap analysis. Morespecifically, the upper and lower 95% confidence bounds of the WDRC coefficient were negative forboth successful efforts and full cost firms, and both the upper and lower bounds for the successfulefforts firms were larger in magnitude (i.e., more negative in value) than the upper and lowerbounds for the full cost firms. Second, we repeated the analyses after eliminating observations witha studentized residual absolute value greater than 3 and our inferences remained unchanged.Hence, based on the results of bootstrapping and ‘‘trimming’’ of observations with large absolutestudentized residual values, we conclude that our inferences are not ‘‘driven’’ by influentialobservations and outliers.24 We were not able to test for differences in persistence across the two firm-groups, since

operationalizing persistence requires sufficient time-series data which were unavailable due to thefact that SFAS No. 121 goes back only to 1996. Moreover, note that prior research (e.g., Schipperand Vincent, 2003, p. 99) identifies persistence as an earnings quality construct. Further, priorresearch (Collins and Kothari, 1989; Easton and Zmijewski, 1989; Kormendi and Lipe, 1987;Schipper and Vincent, 2003) suggests that investors attach a higher valuation multiple (i.e., a higherresponse coefficient) to more persistent (i.e., more sustainable) earnings. Hence, to the extent thatthe response coefficient and persistence are capturing the same underlying earnings qualityconstruct, it would not be meaningful in our analysis to attempt to control for persistence (even ifthe necessary data to do so were available) since doing so would essentially nullify the treatmenteffect we hope to observe.


cannot be attributed to differences in interest rates, growth, and beta across thetwo firm-groups. Rather, our findings suggest that across the two firm-groups(and, by implication, across the two accounting regimes Reg. SX and SFASNo. 121, respectively), the value relevance of pre-write down earnings (as prox-ied by the ERCs) is similar. By the same token, our findings also suggest thatacross the two accounting regimes (Reg. SX and SFAS No. 121), the value rel-evance of the reported impairment write downs (as proxied by the WDRCs) isdifferent.

An alternative explanation for our findings (that the absolute size of theWRDCs for the full cost firms is smaller relative to those of the successfulefforts firms) may simply be that the market reasonably expects that some ofthe costs that are being capitalized by the full cost firms will not actually pro-vide future economic benefits and therefore, when a write-down is recognized,the association with price is not as pronounced. In other words, our findingsmay have less to do with implementation guidance and more to do with theoriginal accounting for exploration costs.

However, note that Bryant (2003) finds no significant difference betweenfull cost and successful efforts firms in the valuation of reported oil and gasassets (her Table 2), and no significant difference between full cost and suc-cessful efforts firms in the valuation of reported earnings (i.e., the ERCsreported in her Table 4). Also, she finds that proforma full cost numberscalculated for successful efforts firms have more explanatory power forstock prices than their actual reported successful efforts numbers. Con-versely, proforma successful efforts numbers calculated for full cost firmshave less explanatory power for stock prices than their actual reported fullcost numbers. In other words, her findings suggest that investors viewunsuccessful exploration costs as a necessary component of discovering oiland gas reserves, and that the full cost method measures accounting assetsand earnings more consistent with economic earnings and assets. Thus, she(p. 23) concludes that ‘‘full capitalization of expenditures with uncertainfuture economic benefits [i.e., full cost accounting] better summarizes infor-mation relevant to investors relative to a policy of partial capitalization[i.e., successful efforts accounting]’’. Stated differently, her findings suggestthat full cost accounting does not provide an inferior asset measure, andthere is no reason to expect a muted response to a write-down of full costassets relative to a write-down of assets based on successful efforts account-ing. Furthermore, we estimated an imputed value model (untabulated) sim-ilar to that used in prior literature (e.g., Harris and Ohlson, 1987; Magliolo,1986) to test whether the market capitalization of oil and gas assets underfull cost accounting differs from that under successful efforts accounting forthe firms in our sample. Consistent with Bryant (2003), we found no statis-tically significant difference in the valuation of these assets for our samplefirms.


4.5. Additional analysis

Alciatore et al. (2000) document that investors anticipated (by up to 3months) the write-downs made by full cost firms during the 1986 oil and gasprice decline, raising the specter that our focus on the contemporaneous stockreturn/write-down association may understate the value relevance of the fullcost write-downs. To assess this possibility, we implemented tests (untabulated)similar to those in Alciatore et al. (2000) by examining the association betweenlagged (prior year) stock returns and current year write-downs, controlling forcurrent and prior year earnings. The tests revealed no association betweenlagged stock returns and current period write-downs, suggesting that the mar-ket did not anticipate the next period’s write-downs during the time period ofour study (1996–2001), i.e., the write-downs provided timely information forboth full cost and successful efforts firms, and that the value relevance of thefull cost write-downs examined in our study (and discussed previously) arenot understated.

Also, we examined the sensitivity of our findings by focusing on a smallersample of firms for which oil and gas assets constituted at least 75% of totalassets. While this partition is admittedly ad hoc, we pursue it to lend insightinto the sensitivity of our results to the presence of firms in our sample withproportionately large investments in non-oil and gas assets. For this reducedsample, the number of observations was 526.25 For the opportunistic report-ing tests, the findings for the SFAS69 variable were similar to thosereported previously in Table 4. Also, for the full cost firms, none of theopportunistic reporting incentive variables (DMGMT, BATH, SMOOTH,and DEBT) were significant. However, for the successful efforts firms, theincentive variables DMGMT, BATH, SMOOTH, and DEBT were signifi-cant at the 0.05, 0.01, 0.05, and 0.05 levels, respectively, with signs similarto those reported previously in Table 4. Still, the results for the coefficientcomparison tests H1 and H2 were similar to those reported in Table 4.Thus, for our reduced sample of firms with oil and gas assets constitutinga large majority (at least 75%) of total assets, the opportunistic reportingincentives appeared to be more strongly associated with the impairmentwrite-downs reported by successful efforts firms. For the value relevancetests, the findings were similar to those reported previously in Table 5,i.e., the write-down response coefficients (but not the earnings response coef-ficients) were lower for the full cost firms relative to the successful effortsfirms, suggesting that the reported impairment losses for the full cost firmshad lower value relevance.

25 In other words, from our original sample (n = 565), we dropped the 39 observations for whichoil and gas assets constituted less than 75% of total assets, reducing the sample to 526 observations.


5. Concluding remarks

The extractive petroleum industry is characterized by a unique jurisdic-tional split in which the same economic event (i.e., an impairment in oiland gas assets) is accounted for by full cost firms under a SEC standard(Reg. SX 4-10) that provides detailed implementation guidance, and bysuccessful efforts firms under a FASB standard (SFAS No. 121) that pro-vides relatively little guidance.26 We utilize this jurisdictional split to exam-ine whether the differential implementation guidance for recognizing oil andgas asset impairment losses is associated with differences in opportunisticreporting (as proxied by the association between the reported write-downsand managerial incentives to report opportunistically) and value relevance(as proxied by the association between the reported write-downs and stockreturns). Our findings are potentially relevant in the context of the ongoingdiscussion over the role of implementation guidance in standard setting.Both the FASB (2004, p. 5) and the SEC (2003, p. 5) have indicated thatan emphasis on principles in developing accounting standards does noteliminate the need for implementation guidance as a mechanism forensuring that standards are operationalized and applied in a consistentmanner.

As noted previously, prior research (Dye and Verrecchia, 1995; Dechow andSkinner, 2000; Schipper, 1989) suggests that both opportunistic reporting andvalue relevance are rooted in accounting discretion. Moreover, given the fun-damental role of judgments and estimates in the practice of accrual accounting,it is difficult to distinguish opportunistic reporting from the legitimate exerciseof accounting discretion. Thus, Riedl’s (2004) finding that the impairmentwrite-downs under SFAS No. 121 are associated with incentives to reportopportunistically provides only a partial picture since it does not address theimportant question of whether the write-downs affected the usefulness of thereported information to investors. Since theory provides relatively little help,the value relevance of the reported impairment write-downs is an empiricalissue.

Our analysis controls for self-selection bias that can arise because firmsself-select into Reg. SX or SFAS No. 121 by virtue of their choice of oil

26 Specifically, as discussed previously, Reg. SX ties the impairment write-down to the presentvalue of future cash flows based on ‘‘proved’’ reserve quantities, the oil and gas spot price on asingle (the balance sheet) date, and a uniform discount rate of 10%. By contrast, SFAS No.121 permits managers to utilize private forecasts of oil and gas prices, a firm-specific discountrate, and include in their calculations not only ‘‘proved’’ but also ‘‘probable/possible’’ reserves.Thus, relative to Reg. SX, SFAS No. 121 allows managers much more discretion incommunicating to investors their private insights about the underlying value of the firm’s oiland gas assets.


and gas accounting methods. Still, our study is a joint test of Reg SX versusSFAS 121 write-downs and our ability to control for self-selection bias. Westructure our tests to evaluate whether and to what extent various incentivesfor opportunistic reporting explain firms’ impairment write-down decisions(after controlling for selection bias). Also, as noted previously, we operation-alize value relevance as the association between the reported write-down andthe contemporaneous stock return. Specifically, the coefficient of the write-down variable in our regression model (controlling for the amount of pre-write-down earnings) serves as our measure of value relevance, and we assessthe effect on this metric (the write-down response coefficient) of write-downsdetermined under Reg. SX as compared to those determined under SFASNo. 121.27

Our findings suggest that the write-downs reported by successful effortsfirms under SFAS No. 121 are associated with opportunistic reporting incen-tives (consistent with Riedl, 2004). By contrast, our findings are inconclusiveas to whether the write-downs reported by full cost firms under Reg. SX areassociated with such incentives. Separately, we find the value relevance of thepre-write-down earnings for both full cost and successful efforts firms to besimilar in terms of their earnings response coefficients. However, the value rel-evance of the write-downs reported by full cost firms appears to be lower rela-tive to the value relevance of the write-downs reported by the successful effortsfirms. These findings are broadly consistent with the notion that accountingdiscretion permits managers to communicate their private insights into thefirm’s underlying economics, avoids imposing similar accounting on economi-cally dissimilar events, and that providing extensive implementation guidancemay lower value relevance. We also find that limited implementation guidanceis associated with opportunistic reporting, but we cannot eliminate the possibil-ity that the level of opportunistic reporting is no different between regimes withextensive guidance (i.e., Reg. SX) and those with limited guidance (i.e., SFAS121).

Although our paper is focused on a specific (extractive petroleum industry)context, we believe the results are generalizable since the study broadly exam-ines managers’ response to implementation guidance and the value relevanceof the information provided to investors. Collectively, our findings provide reg-ulators and accounting policy makers with an additional piece of evidence withwhich to evaluate the role of implementation guidance in the standard settingprocess.

27 Our focus on the response coefficient is consistent with prior research (e.g., Teoh and Wong,1993) that assesses the value relevance of reported earnings information using this metric. Similarly,Barth et al. (2001) interpret the coefficients as capturing the relevance of earnings information.


Acknowledgement

Authors’ names are in alphabetical order. We appreciate the helpful com-ments and suggestions of the two reviewers and the editor. Professor Boonegratefully acknowledges research funding provided in part by the Institute ofPetroleum Accounting at the University of North Texas.

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Does implementation guidance affect opportunistic reporting and value relevance of earnings?