Asset Write-Offs in the Absence of Agency Problems

Journal of Business Finance & Accounting, 35(3) & (4), 307–330, April/May 2008, 0306-686Xdoi: 10.1111/j.1468-5957.2008.02078.x

Asset Write-Offs in the Absence of AgencyProblems

Neil Garrod, Urska Kosi and Aljosa Valentincic∗

Abstract: Using a large sample of small private companies, we show incremental influenceof economic incentives over prescriptions from accounting standards by financial statementpreparers in a code-law setting with high alignment between financial and tax reporting andno agency problems. Contrary to predictions from standards, more profitable companies aremore likely to write-off and the write-off magnitude is greater, reflecting tax minimisation.Larger companies are more likely to write-off, but the magnitude decreases with size, reflectingincreasing political costs due to greater visibility to tax authorities. Previous write-off patternsand magnitudes are persistent, reflecting institutional learning linked to regulatory changes.

Keywords: asset impairment, asset write-offs, private firms, agency problems, economic incen-tives, political costs, accounting standards, regulation

1. INTRODUCTION

In this paper we investigate the factors that influence both the decision to decrease thebalance sheet value of an asset (asset write-offs or asset devaluations), and the magnitudeof any such write-off in an environment characterised by a high alignment betweenfinancial and tax reporting, codified legal environment (Ball et al., 2001; and Raonicet al., 2004) and no agency relationships (Ball and Shivakumar, 2005). By studyingwrite-offs of assets in this particular setting we are able to show the important roleof economic incentives of financial statement preparers over and above prescriptions

∗The first author is from Thames Valley University (UK), the second and third authors are from the Facultyof Economics, University of Ljubljana (Slovenia), the third author is also a visiting researcher at AmsterdamBusiness School (The Netherlands). Helpful comments from Peter F. Pope, Peter Easton, William Rees,Jeroen Suijs, Katherine Schipper, Steven Young, Branko Gorjan (General Tax Office of the Republic ofSlovenia), Erik Peek, Martin Walker (editor), an anonymous referee and participants at the EAA AnnualCongress 2005 in Goteborg and 2006 in Dublin, the AARN Conference 2005 at Erasmus University inRotterdam, the AAA Annual Meeting 2006 in Washington, DC, and the 1st CAIR Conference at the Universityof Manchester are gratefully acknowledged. The authors also wish to thank Bisnode, d.o.o., a commercialdatabase provider, for providing the data on ownership of companies in electronic form. This research ispart of the INTACCT programme - The European IFRS revolution (Contract No. MRTN-CT-2006-035850).(Paper received June 2006, revised version accepted June 2007. Online publication March 2008)

Address for correspondence: Urska Kosi, Faculty of Economics, University of Ljubljana, Kardeljeva. ploscad17, 1000 Ljubljana, Slovenia.e-mail: [email protected]

C© 2008 The AuthorsJournal compilation C© 2008 Blackwell Publishing Ltd, 9600 Garsington Road, Oxford OX4 2DQ, UKand 350 Main Street, Malden, MA 02148, USA. 307

308 GARROD, KOSI AND VALENTINCIC

derived from accounting standards in determining the content and quality of financialstatements (Ball et al., 2003).

Literature on factors that lead to changes in balance sheet values is dominatedby research on the choice drivers for fixed asset (upward) revaluations (increases inbalance sheet values) in large, publicly-quoted companies. Factors such as growth,leverage, underinvestment, debt covenant violation, size, likelihood of being a takeovertarget, auditors and independent appraisers estimates of revaluation, cash holdingsand industry influences have all been shown to be correlated with upward changes inthe book value of assets (Henderson and Goodwin, 1992; Whittred and Chan, 1992;Brown et al., 1992; Easton et al., 1993; Cotter and Zimmer, 1995; Barth and Clinch,1998; Gaeremynck and Veugelers, 1999; and Lin and Peasnell, 2000). However, large,publicly-quoted companies operate in environments in which agency, political andcontracting issues are especially influential, no more so than on accounting choice(Jensen and Meckling, 1976; and Watts and Zimmerman, 1986). Indeed these factorsoften make it difficult to uncover the underlying economic factors that accountingdisclosure attempts to reveal.

Asset revaluation represents a major departure from historical cost accounting andis at the discretion of management (Lin and Peasnell, 2000). Its application was limitedto only a few jurisdictions (e.g., the UK, the Netherlands, Ireland and Australia) andonly under close regulation. This has now been extended via International FinancialReporting Standards that have been endorsed by the EU member countries (RegulationEC No. 1606/2002) that permit upward revaluations of assets (e.g., IAS 16 – Property,Plant, and Equipment – IASB, 2003, pp. 16-3 – 16-22; Epstein and Mirza, 2005, p. 214),but the effects of these revaluations bypass immediate income-statement effects.

Decreases in the book value of balance sheet items, or write-offs, on the other hand,form part of the fabric of conservative, accrual accounting. Such conservatism leadsto an asymmetry in the timeliness of the recognition of economic gains (gradualrecognition) and losses (immediate, capitalised recognition) in financial statements(Basu, 1997; and Pope and Walker, 1999). In turn, we expect the influences that drivewrite-offs to be somewhat different to those that drive revaluations. Further, whilstthe change to any balance sheet value can be thought of as a continuous variable –negative, zero or positive – the actual reported amount of a write-off is a managementdecision which leads write-offs to be, potentially, quite different to a simple sign-reversedrevaluation (Lin and Peasnell, 2000). Recent evidence that working capital accrualsas well as ‘special’ items contribute to the ex-post conservatism of reported earnings(Garrod et al., 2005) suggests that current asset write-offs may play an important anddistinct role in the reporting process in addition to that of fixed asset write-offs.

The data source used in this study enables us to complement existing literature onfactors that affect changes in book values of assets. The study is based on comprehensivefinancial information about small private companies (SPCs) operating in Slovenia.The ownership structure of these companies, with almost half (47.09%) having but asingle owner, leads to no significant separation of ownership from management. As aconsequence, agency factors due to this separation are absent from accounting choiceand demand for financial reporting differs markedly from that of large, publicly-quotedcompanies, as:

Private companies are more likely to resolve information asymmetry by an ‘insider access’model. They are less likely to use public financial statements in contracting with lenders,managers and other parties, and in primary and secondary equity transactions. Their

C© 2008 The AuthorsJournal compilation C© Blackwell Publishing Ltd. 2008

ASSET WRITE-OFFS IN THE ABSENCE OF AGENCY PROBLEMS 309

financial reporting is correspondingly more likely to be influenced by taxation, dividendand other policies (Ball and Shivakumar, 2005, p. 84).

With very low levels of debt financing in our sample companies (and a significantnumber of companies using no external financial debt at all) there is but a singledominant economic information asymmetry, that between the company and the taxauthority (Garrod et al., 2007).

In such a setting it is possible to separate and analyse the factors that influence fixedand current asset write-offs directly. Specifically, after controlling for known contractualfactors from existing literature, we test for: the impact of potential economic incentives,related to tax minimisation; political costs, related to the possibility of a costly tax audit;and other contracting costs, related to regulatory change, compliance and institutionallearning on the accounting choices companies make in the process of preparing theirfinancial statements.

The remainder of the paper is organised as follows. Prior studies related to assetrevaluations and disclosure requirements in Slovenia form a backdrop to hypothesesdevelopment in Section 2. The test data is described in Section 3 followed by theempirical results and sensitivity checks. Concluding remarks form the final section.

2. HYPOTHESES DEVELOPMENT

Small private companies are characterised by the absence of agency relationshipsbetween owners and managers. Assuming, without loss of generality, that there is justa single owner of the company who is involved in the day-to-day management of thecompany, the owner does not rely primarily on published financial statements to revealthe true state of the company they own. In other words, the demand for financialreporting to resolve the information asymmetry between owners and managers doesnot exist in such circumstances. Further, assuming that companies do not use externalfinancial debt, the second important agency relationship – that between lenders andowners – does not exist and thus a second potentially important source of demand forfinancial statements is also absent.1

In such circumstances any observable discretion over accounting numbers cannot beattributed to opportunistic (contractual) motives of the owner-manager, but can only beattributed to rational (personal) value-maximizing decisions (Fields et al., 2001). Theseoriginate from the existence of a third source of demand for financial statements thatis not market-based, but government-mandated (regulated) – the demand to producefinancial statements for tax purposes.

If financial statements are used to determine the tax paid by a company, then owner-managers are faced with incentives to exercise the discretion over accounting numbersto minimise the present value of present and future taxes thereby maximising thepresent value of present and future cash flows. This is achieved by choosing appropriateaccounting procedures that delay tax payments as far into the future as possible.2 Any

1 Also, assuming the lender to SPCs is a bank, it is conceivable that the bank might have ‘preferential access’to inside information about the company, lessening thus the demand for financial reporting.2 The amount of corporate tax a company pays in nominal amounts over its life cannot be influenced bydifferent accounting procedures but its present value can be minimised by delaying tax payments as far intothe future as possible.



gains from such discretion are directly linked to the wealth (and changes in wealth) ofthe owner-manager.

A necessary condition for this is that financial and tax reporting is unitary. Generally,cost considerations are likely to push small companies towards preparing a single set ofaccounts for both financial and tax purposes (Ball and Shivakumar, 2005), so there is adirect link between the effects of discretion and the levels and changes in the wealth ofowners (in our empirical setting this link is even stronger as it is institutionalised – seebelow). It is important to note that in our setting the tax authorities represent a veryimportant (and often sole) source of ‘derived’ demand for financial statements throughdemand for tax reporting since tax and financial reporting are aligned. Moreover, theknowledge about the company is asymmetric – the owner-manager knows more aboutthe true state of the company than the tax authorities. It may thus be conceivable thatthe owner-manager would be able to convince tax authorities that a particular expenseis a justified, non-discretionary tax-deductible expense, when in fact it would be a purelydiscretionary expense used for no other purposes than to minimise tax.

Another condition for value-maximising discretion over accounting numbers is thatthe effects of this discretion cannot be undone completely by the user (Fields et al.,2001), either because the user cannot observe the effect of discretion or cannotreverse it or it is too costly to do so. In other words, market frictions allow for suchdiscretion to be profitable. However, owners-managers must be partially constrained intheir exercising of discretion to minimise taxes, as we would otherwise expect rationalmanagers to fully exercise their discretion and would observe companies paying noor very little tax. One such effective constraint is the existence of a powerful user offinancial statements who can in some circumstances undo the effects of discretion – thetax authorities and more specifically the tax auditor. Consistently, Garrod et al. (2007)find strong evidence to support the existence of earnings management to decrease, butnot entirely avoid corporate taxes due to the threat of a potentially costly tax audit whichwould effectively undo (part of) the effects of managers’ discretion over accountingnumbers.

In the absence of any market-based demand for financial reporting it is importantto consider cases where an observable accounting outcome (policy) can be attributedless to non-discretionary sources (e.g., the existence of a ‘normal’ receivable) thanto discretionary sources (e.g., to minimise tax). One particular set of accountingprocedures where this might become most apparent is the recognition of impairmentand consequent write-offs of fixed and current assets. Write-offs timely signal to outsideinvestors the falling expectations about future cash flows. The economic reality –diminished expected future cash flows – does not, however, depend on whether(or when) these expectations are reported in financial statements. Absent any ‘real’demand from outside investors for timely reporting of economic losses through write-offs, coupled together with a strong economic incentive (to minimise taxes in our case),the discretionary proportion of any observed write-offs is likely to be very high. It isthis accounting procedure that we use to show how economic incentives override theoriginal intent of accounting standards.3

3 The same logic applies equally to any other types of accruals, but using write-offs allows for a clearerspecification of our hypotheses and increases the power of our tests as the ratio of discretionary to non-discretionary accruals is likely to be much higher for write-offs than for other types of accruals.



Slovenian Accounting Standards (SAS) adopted in 2001, and to be used for financialyears on or after January 1, 2002, require fixed and current asset write-offs if recoverableamounts fall below their carrying amounts and separate disclosure of these write-offsin the income statement under operating expenses. In the case of fixed assets, animpairment loss is recognized as a write-off operating expense associated with fixedassets (SAS, 2001, p. 28). Write-offs of inventories of raw and other materials and smalltools are charged directly against the cost of materials, whilst write-offs of inventoriesof work in progress, finished goods and merchandise are charged against a write-offoperating expense associated with current assets (SAS, 2001, p. 52). In a similar manner,receivables must be written-off when their book value exceeds their collectible amountand the write-off is charged as a write-off operating expense associated with currentassets (SAS, 2001, p. 59).4

In a number of countries, including the UK and US, taxable income and accountingincome can differ markedly (Eberhartinger, 1999). In particular, many discretionaryaccrual adjustments, such as doubtful debt allowances, depreciation charges and assetwrite-offs, are ignored in the computation of taxable income, being replaced with actualbad debts, standard depreciation rates and losses when assets are actually disposed.However, the Corporate Profit Tax Act (Official Gazette of the Republic of Slovenia,14/2003, 2003) in Slovenia requires the use of financial statements prepared according tothe Slovenian Accounting Standards to determine the corporate tax basis of Sloveniancompanies. In order to limit the impact of the accounting discretion inherent inSAS, there are some restrictions in certain areas. For example, the Corporate ProfitTax Act (2003) sets maximum depreciation/amortisation rates and excludes somenon-operating expenses for tax purposes (e.g., limits expenses for supervisory andmanagement board). Additionally, it sets the below-the-line investment deductionsand tax relief: (i) a 30% investment tax deduction (and an additional 10% for certain‘desirable’ investments) and (ii) the creation of an investment reserve amounting upto 10% of the tax base that can be used for future investments if made in the followingtwo years. These deductions reduce the linear 25% tax rate (Corporate Profit TaxAct, 2003), to an effective tax rate for the SPCs in our sample to a mean (median) of17.1% (13.8%), with taxes representing 3.9% (0.2%) of net sales revenue. Thus, thereexists a direct institutional link between financial and tax reporting.5 While write-offoperating expenses have no direct effect on cash flows from operations they do, becauseof this link, directly affect the company’s tax base and, consequently, total cash flows.We expect managers to exercise their discretion through write-offs only after the twoallowances described above have been fully exhausted. After that, a 1-unit write-offcauses a 0.25-unit of reduction in current tax payment – a relatively large gain.

Whilst the write-off expenses related to fixed and current asset impairment wereintroduced in Slovenian Accounting Standards for financial years ending in 2002 andonwards, these were rescinded as of January 1, 2005, after which they were no longertax deductible. We thus have a very interesting window within which accounting andtaxable income are highly aligned and we are able to investigate the impact of economicincentives on accounting choice directly.

4 Slovenia is introducing new accounting standards effective January 1, 2006. At the time of writing, thesehave not yet been authorised by the Ministry of Economic Affairs, as required by Company Law. However,for our set of companies, such changes are likely not to be material.5 Taxation laws were modified several times up to March 30, 2004, but for our purposes these changes donot weaken the link between reported accounting earnings and taxable income.



Regulation regarding asset write-off is designed to reveal impairment in future cashflows generated by the asset. In order to obtain a clear link between write-offs andhypothesized factors determining the write-offs, we first identify, and then control for,other factors that may impact the write-off decision.

We use two conditioning variables to reflect normal (operating) impairment. First,the economic rationale for asset write-off lies in impairment that stems from fallingexpectations about future cash flows. Conservative accounting (e.g., Basu, 1997; andPope and Walker, 1999) requires immediate recognition of the full capitalised amountof these lower future cash flows in current-period earnings. One of the indicatorsthat assets might be impaired is a reported accounting loss. We thus use current yearlosses as a proxy for impairment and expect the likelihood and magnitude of write-offs for loss companies to be greater than for equivalent companies reporting profits.Second, recent work on accounting conservatism and the timeliness of earnings hasunderscored the impact of stocks of assets on the observed level of conservatism (e.g.,Beaver and Ryan, 2004; and Beaver et al., 2004). The potential for asset write-off isgreater if the opening book value of assets to be written-off is higher. Consequently,we use the opening balance sheet values of fixed and current assets as proxies of thepotential for asset write-off.

Influenced by the evidence available from the asset revaluation literature, weincorporate two additional control variables, the level of financial debt (Hendersonand Goodwin, 1992; Whittred and Chan, 1992; Brown et al., 1992; Cotter and Zimmer,1995; Gaeremynck and Veugelers, 1999; and Lin and Peasnell, 2000) and liquidity(Whittred and Chan, 1992; Brown et al., 1992; Cotter and Zimmer, 1995; and Linand Peasnell, 2000). The majority of the sample SPCs are equity financed, but thosethat use financial debt will, to some extent, be subject to debt covenants, which oftenprescribe a certain maximum debt-to-asset ratio. This would impose a constraint on theprobability and the magnitude of write-off which increases with the level of financialdebt. The second factor is liquidity. Write-off will reduce reported profit and thus taxespayable which will have a direct positive impact on cash flow. This may result in thepropensity to write-off and the magnitude of write-offs to be negatively associated withliquidity.

Having thus conditioned the write-off variable using the factors identified abovewe are in a position to test whether additional factors incrementally impact upon thewrite-off decision and magnitude. We postulate three such possible factors: potentialeconomic gains (the tax-minimisation factor), political costs and other contractingcosts (distinct from those captured by the conditioning variables above). Respectively,these generate the following testable hypotheses, stated in alternative form:

H1A: Higher levels of profitability will increase the probability and the magnitudeof a write-off.

In the absence of agency relationships owner-managers have no incentives to act otherthan to minimise current tax liabilities. As a consequence we expect more profitablecompanies to use write-offs to reduce taxable profit more heavily than less profitablecompanies. As reported operating profit will include the consequences of a write-offdecision in our empirical setting, we use an adjusted (i.e., pre-write-off) operating profitfigure to proxy for the underlying profitability.

H2A: Larger companies will be more likely to write-off assets than smaller companiesand the magnitude of this write-off will be inversely related to company size.



In existing research, size – often used as a proxy for political ‘visibility’ – is found to bean important factor affecting the revaluation decision, as larger companies are morelikely to revalue upwards (e.g., Brown et al., 1992; and Lin and Peasnell, 2000). Similarly,in our sample environment the political visibility of larger companies is greater thanfor smaller companies. The larger the company the greater the regulatory pressure toimplement the spirit, as well as the detail, of accounting regulations in general and assetwrite-offs in particular. On the other hand, there is anecdotal evidence that tax auditorsfocus their attention on larger SPCs that report low profitability as the potential tax gainfor the tax authorities resulting from a tax audit of larger companies is greater thansimilar audits of smaller companies or those reporting higher profits.6 Consequentlywe expect opposite influences on the likelihood of write-off and on the magnitude ofwrite-off. We hypothesise that larger companies will be more likely to write-off theirassets than smaller companies but that amongst those companies that do write-off themagnitude of that write-off will be inversely related to company size.

H3A: A write-off of assets in the previous year will increase the probability and themagnitude of a write-off in the current year.

Write-offs of assets only became mandatory in Slovenia with the adoption of the newSAS in 2001 for financial years beginning on or after January 1, 2002. Asset impairments(and consequent write-offs) emerging from purely operational reasons are expected tobe random and not correlated across years. Nonetheless, the concept of impairmentis still a fairly new one, particularly in a country without a tradition in user-drivenfinancial reporting. We expect, therefore, that it will take some time for write-offs to beembedded within the general financial reporting environment, particularly for smallcompanies. Reporting a write-off in the previous year would be an indication that thecompany involved had embraced this concept. In addition, tax benefits arising fromasset write-offs are likely to be learned across companies as this reporting regulationbecomes more embedded in reporting practice. We expect those companies that havegained lower tax payments resulting from write-offs to repeat this gain. Consequently,we hypothesise the companies that write-off assets in the previous year to be both morelikely to write-off in the current year and for those write-offs to be higher than for thosecompanies that did not write-off in the previous year.

3. EMPIRICAL RESULTS

(i) Sample Formation and Sample Description

We start with the initial sample of 37,962 small private companies (SPCs) operatingin the Republic of Slovenia in 2003 that submitted financial reports to the Agencyfor Public Records and Services, which collects them for statistical purposes and areaccessible to registered researchers. All companies operating in Slovenia are required bylaw to submit these financial statements.7 The same (but less detailed and condensed)

6 The latter presumes that more profitable companies have used less aggressive income-decreasingaccounting policies and thus the difference between ‘true’ and reported profitability is smaller.7 In this respect, the system of data collection resembles the Belgian system (e.g., Deloof and Jegers, 1999;and Vander Bauwhede et al., 2003), except that it is broader in scope as it applies to all companies. Theorigins of this system can be traced back to pre-transition times, where a predecessor of the Agency was thecentral organ governing inter-company payments and financial reports.



Table 1Sample Construction

Small private companies 37,962Less

Negative equity and no sales in 2002 and/or 2003 11,945Outliers 2,562

Final sample of small private companies 23,455Comprising

Companies writing-off fixed assets only 1,427Companies writing-off current assets only 4,403Companies writing-off fixed and current assets 1,048Non-writing-off companies 16,577

Notes:The write-off decision is analysed using the final sample, whilst factors impacting upon the magnitude of thewrite-offs are analysed using writing-off companies in the first three subsets (i.e., SPCs that write-off fixedassets only, SPCs that write-off current assets only, and SPCs that write-off both fixed and current assets).Companies in the total sample not included into one of these three subsets are non-writing-off companies.

accounting statements are then available for the general public, including the taxauthorities. In these condensed statements, both the current and fixed asset write-offexpenses are condensed to a single line together with the normal depreciation charge.An implication of this is that external users of these financial statements, includingpossibly the tax authorities, are not automatically alerted to the existence of these write-offs and may simply treat them as depreciation.8 Unless the tax authorities decide toconduct a tax audit, the assumptions that underlie these write-offs are not externally(objectively) checked and room for discretion is ample.

The criteria that denote the size of the company as ‘small’ is defined by theCompanies Act (Official Gazette of the Republic of Slovenia, 30/1993, 1993 and subsequentamendments) in terms of total assets, net sales revenue and number of employees and itfollows closely the quantitative criteria set by the EU regulations (4th Council Directive,2003).9

To be included in the sample, companies are further required to have positive netsales revenue and positive owners’ equity in both 2003 and 2002. With these restrictionswe aim to avoid including inactive companies or those that may have been financiallydistressed over a number of earlier periods.10 We also apply the conventional restrictionof trimming observations in the top/bottom 1% of the model variables.11 This yields afinal total sample of 23,455 small private companies. A summary of sample constructionand the composition of the sample in terms of companies writing-off assets is provided

8 The actual form submitted to the tax authorities is even more condensed. Any tax adjustments are madeto two aggregate categories – total revenue and total expense.9 Specifically, a company is defined to be ‘small’ if it fulfils two of the following three criteria: average numberof employees in the last fiscal year does not exceed 50, net turnover is less than EUR 4.34m, total assets atthe end of fiscal year do not exceed EUR 2.17m (Companies Act 2001 (amendment F), paragraph 52; actualfigures are in Slovenian tolars, converted to euros using the middle official exchange rate of the Bank ofSlovenia on December 31, 2002, at 230.2673 tolars/EUR).10 Mramor and Valentincic (2003) discuss the properties of financial statements of small private companiesoperating in Slovenia.11 For all variables with the exception of adjusted operating profit (ADJ OPt ) the restriction refers only tothe top 1%, given that these variables are bounded at zero.



in Table 1. Using the data provided by a commercial database provider, we are ableto determine the number of owners for 23,220 (99%) of our sample companies.Consistent with data on Slovenian companies reported earlier (e.g., Drnovsek, 2002),22,373 (95.39%) companies in our sample have 10 or fewer owners, giving us a samplethat conforms closely to our theoretical setting.

In this study we investigate two separate aspects of a write-off: the decision to write-offitself and the magnitude of any such write-off. The total sample is used to investigate thedecision to write-off assets. To investigate the factors impacting upon the magnitudeof write-offs, we study further only those companies that actually do write-off assets.Overall, 29.32% of the sample companies write-off fixed assets, current assets or both.Companies writing-off are further classified in four subsets: SPCs that write-off fixedassets only (20.75% of all writing-off companies); SPCs that write-off current assetsonly (64.02% of writing-off companies); SPCs that write-off both fixed and currentassets (15.24% of writing-off companies); and finally, SPCs that write-off either fixed orcurrent assets or both (100% of writing-off companies).

To test for the impact of our conditioning and hypothesized drivers on the write-off decision, we estimate four separate logistic regressions for the companies includedin the total sample. The dependent variable in these models is, respectively, a binaryindicator of whether the company has or has not written-off fixed assets only, currentassets only, both fixed and current assets, and fixed or current assets or both.

Explanatory variables used in logistic regression models are:12

ADJ OPt – operating profit before any write-off expenses, expressed as (deflatedwith) a proportion of opening total assets;St – company size measured as the natural log of year 2003 sales (as in Lin andPeasnell, 2000);D FAt −1, D CAt −1 – previous year write-off dummy defined as 1 if the company wrote-off fixed (current) assets in the previous year, and 0 otherwise;13

Lt – loss dummy defined as 1 if the company’s earnings before tax are less than orequal to zero, and 0 otherwise;FAt −1, CAt −1 – opening stock of fixed (current) assets, as a proportion of openingtotal assets;DEBTt – short- and long-term financial debt, as a proportion of opening total assets;CASHt – liquidity measured as cash holdings, as a proportion of opening total assets.

The conditioning variables FAt−1 and CAt−1 are used respectively in logistic regres-sions for those companies that write-off fixed assets only and for those companies thatwrite-off current assets only and are omitted from the remaining two logistic regressions.Previous year write-off dummies, D FAt −1 and D CAt −1, are used respectively in logisticregressions for those companies that write-off fixed assets only and for those companiesthat write-off current assets only. However, both indicator variables are included in thelogistic regressions for companies that write-off both fixed and current assets and eitherfixed or current assets or both.

Analogously to the logistic regressions used to study the decision to write-off, weestimate four separate linear regressions to test the hypotheses regarding the magnitude

12 For parsimony, the particular regression models used are detailed in notes to Tables 3 and 4.13 Because the variables listed here refer to the write-off decision (as distinct from magnitude), we definethe explanatory variables in the same manner as the dependent variable, i.e., as a binary variable. In addition,a continuous variable was also used, yielding similar results.



of such write-offs: one for those companies that write-off fixed assets only, a secondfor those companies that write-off current assets only, a third for those companiesthat write-off both fixed and current assets and a final regression for companies thatwrite-off fixed or current assets or both. In each case the dependent variable is themagnitude of the relevant write-off expense expressed as a proportion of opening totalassets. Explanatory variables are the same as in logistic regressions with one exception:the previous year write-off dummy is replaced by the value of the previous year write-off expense (WOFFFA,t −1, WOFFCA,t −1) as a proportion of opening total assets. Thevariables are therefore continuous and expressed in the same measurement scale asthe dependent variable.

Descriptive statistics of the dependent, explanatory and control variables for thethree subsets of writing-off companies and the subset of non-writing-off companiesare presented in Table 2. On average, companies that write-off are significantly moreprofitable, are larger and have less cash and more debt than non-writing-off companies.There are also notable differences between the subsets of writing-off companies. Thosethat write-off current assets only are the most profitable and those that write-offfixed assets only the least profitable. The reverse is true for the incidence of losses.Losses are more frequent in the group of companies that write-off fixed assets onlyand least frequent in the group of companies that write-off current assets only. Thissuggests that fixed and current asset write-offs may have different roles in the financialreporting process. Companies that write-off both fixed and current assets are larger,have higher levels of debt and the least cash. All these differences are statisticallysignificant at least at the 5% level of significance, with most being significant at 1% orbetter.

(ii) Results

(a) Decision to Write-Off

Empirical results of the four logistic regression models used to study the decision towrite-off/not to write-off fixed and/or current assets are presented in Table 3.

The results in the first column of the table refer to the decision to write-off fixedassets only. Both conditioning variables, the loss dummy and level of fixed assets, arestatistically significant. Companies that show a bottom-line loss are, on average, morelikely to write-off, as are companies with a higher stock of fixed assets. Neither of theconditioning variables from the revaluation literature, the level of debt and the liquidity,are significant. For the test variables, the potential economic gain proxy, the adjustedoperating profit, is not statistically significant, but both the political cost proxy (size),and the other contracting cost proxy (previous year write-off), are. Each significantvariable is signed as hypothesized.

The results for current asset-only write-offs are to be found in the second column ofthe results and reflect a quite different pattern. Here, the opening level of current assetsis significant, but the impairment loss dummy is not. Both conditioning variables fromthe revaluation literature, level of debt and liquidity, are significant. Notably, all threetest variables, potential economic gain, the political cost and the other contracting costs,are highly statistically significant and of expected sign. More profitable companies aremore likely to write-off current assets, as these companies are more likely to obtainan economic gain by doing so (less profitable companies have less to gain from tax-minimisation procedures), larger companies are more likely to write-off current assets,


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0.00

00.

000

Med

ian

0.00

50.

053

10.9

840.

000

0.00

00.

000

0.00

00.

000

0.41

10.

367

0.00

00.

033

Max

0.07

21.

032

13.6

661.

000

1.00

00.

064

0.14

41.

000

0.96

60.

984

0.88

31.

097

CA

subs

etM

ean

0.02

50.

097

11.0

170.

127

0.48

00.

001

0.01

20.

130

0.35

90.

464

0.08

00.

098

SD0.

033

0.13

61.

499

0.33

30.

500

0.00

60.

024

0.33

60.

267

0.26

30.

143

0.14

3M

in0.

000

−0.4

183.

045

0.00

00.

000

0.00

00.

000

0.00

00.

000

0.00

00.

000

0.00

0M

edia

n0.

011

0.07

611

.174

0.00

00.

000

0.00

00.

000

0.00

00.

328

0.44

80.

000

0.04

1M

ax0.

162

1.01

613

.666

1.00

01.

000

0.06

90.

145

1.00

00.

973

0.98

50.

930

1.11

1

FAan

dC

Asu

bset

Mea

n0.

007

0.02

00.

027

0.08

511

.792

0.42

50.

622

0.00

30.

012

0.17

10.

435

0.42

80.

105

0.06

7SD

0.01

30.

029

0.03

30.

131

1.28

80.

495

0.48

50.

009

0.02

20.

377

0.25

50.

246

0.16

20.

105

Min

0.00

00.

000

0.00

0−0

.406

6.90

60.

000

0.00

00.

000

0.00

00.

000

0.00

20.

001

0.00

00.

000

Med

ian

0.00

20.

007

0.01

50.

071

11.9

730.

000

1.00

00.

000

0.00

10.

000

0.42

70.

421

0.01

60.

028

Max

0.07

10.

162

0.17

40.

937

13.6

681.

000

1.00

00.

067

0.14

01.

000

0.97

20.

973

0.90

20.

977

Non

-wri

ting

-off

com

pani

esM

ean

0.05

79.

835

0.05

30.

115

0.00

10.

003

0.22

30.

345

0.42

20.

062

0.12

2SD

0.16

21.

728

0.22

40.

319

0.00

50.

013

0.41

60.

283

0.28

00.

141

0.17

9M

in−0

.426

1.38

60.

000

0.00

00.

000

0.00

00.

000

0.00

00.

000

0.00

00.

000

Med

ian

0.03

39.

936

0.00

00.

000

0.00

00.

000

0.00

00.

286

0.39

40.

000

0.04

9M

ax1.

078

13.6

681.

000

1.00

00.

070

0.14

61.

000

0.97

40.

985

0.94

81.

153

Not

es:

WO

FFFA

,tis

curr

ent

year

wri

te-o

ffex

pens

eas

soci

ated

with

fixed

asse

ts,W

OFF

CA,t

iscu

rren

tye

arw

rite

-off

expe

nse

asso

ciat

edw

ithcu

rren

tas

sets

,WO

FFFA

&C

A,t

isth

esu

mof

curr

ent

year

wri

te-o

ffex

pens

esas

soci

ated

with

fixed

and

curr

ent

asse

ts,A

DJ

OP

tis

oper

atin

gpr

ofit

adju

sted

for

wri

te-o

ffex

pens

es(a

ndre

port

edop

erat

ing

prof

itfo

rno

n-w

ritin

g-of

fco

mpa

nies

),S t

isco

mpa

nysi

zem

easu

red

asth

ena

tura

llog

ofye

ar20

03sa

les,

DFA

t−1

isdu

mm

yva

riab

lefo

rth

epr

evio

usye

arw

rite

-off

offix

edas

sets

,DC

At−

1is

dum

my

vari

able

for

the

prev

ious

year

wri

te-o

ffof

curr

ent

asse

ts,W

OFF

FA,t

−1is

prev

ious

year

wri

te-o

ffex

pens

eas

soci

ated

with

fixed

asse

ts,

WO

FFC

A,t

−1is

prev

ious

year

wri

te-o

ffex

pens

eas

soci

ated

with

curr

enta

sset

s,L

tis

loss

dum

my,

FAt−

1is

open

ing

stoc

kof

fixed

asse

ts,C

At−

1is

open

ing

stoc

kof

curr

ent

asse

ts,D

EB

Tt

isfin

anci

alde

btan

dC

ASH

tis

cash

and

near

-cas

h.A

llac

coun

ting

vari

able

sar

ede

flate

dby

the

open

ing

book

valu

eof

tota

lass

ets

TA

t−1.

Fixe

das

sets

subs

etin

clud

es1,

427

com

pani

es,c

urre

ntas

sets

subs

et4,

403

com

pani

es,f

ixed

and

curr

enta

sset

ssu

bset

1,04

8co

mpa

nies

and

non-

wri

ting-

offc

ompa

nies

subs

et16

,577

com

pani

es.



Tab

le3

Log

istic

Reg

ress

ion

Mod

els

–D

ecis

ion

toW

rite

-off

Coe

ffici

ents

for

Mod

els

(p-v

alue

sin

pare

nthe

ses)

Expl

anat

ory

Vari

able

sEx

pect

edSi

gnL

ogit

Mod

el1

Log

itM

odel

2L

ogit

Mod

el3

Log

itM

odel

4(W

rite

-off

FAon

lyye

s/no

)(W

rite

-off

CA

only

yes/

no)

(Wri

te-o

ffFA

and

CA

yes/

no)

(Wri

te-o

ffFA

orC

Aye

s/no

)

Con

stan

t−

5.34

5−

4.52

2−

9.65

0−

5.38

2(0

.000

)(0

.000

)(0

.000

)(0

.000

)Te

stva

riab

les:

AD

JO

Pt

+−0

.006

1.07

20.

652

0.97

7(0

.979

)(0

.000

)(0

.019

)(0

.000

)S t

+0.

203

0.24

20.

524

0.38

1(0

.000

)(0

.000

)(0

.000

)(0

.000

)D

FAt−

1+

1.10

81.

412

0.98

7(0

.000

)(0

.000

)(0

.000

)D

CA

t−1

+1.

412

1.23

41.

479

(0.0

00)

(0.0

00)

(0.0

00)

Con

trol

vari

able

s:L

t+

0.16

0−0

.099

0.51

90.

150

(0.0

49)

(0.0

78)

(0.0

00)

(0.0

02)

FAt−

1+

0.63

1(0

.000

)C

At−

1+

0.22

8(0

.001

)



Tab

le3

(Con

tinu

ed)

Coe

ffici

ents

for

Mod

els

(p-v

alue

sin

pare

nthe

ses)

Expl

anat

ory

Vari

able

sEx

pect

edSi

gnL

ogit

Mod

el1

Log

itM

odel

2L

ogit

Mod

el3

Log

itM

odel

4(W

rite

-off

FAon

lyye

s/no

)(W

rite

-off

CA

only

yes/

no)

(Wri

te-o

ffFA

and

CA

yes/

no)

(Wri

te-o

ffFA

orC

Aye

s/no

)

DE

BT

t−

0.15

7−

0.39

3−0

.076

−0.

265

(0.3

95)

(0.0

02)

(0.7

35)

(0.0

20)

CA

SHt

−0.

005

−0.

441

−1.

387

−0.

641

(0.9

81)

(0.0

00)

(0.0

00)

(0.0

00)

−2L

L10

,195

.087

19,9

53.6

926,

659.

371

23,2

16.3

53N

agel

kerk

eR

20.

064

0.17

60.

255

0.28

2%

Cor

rect

93.9

%81

.4%

95.6

%77

.6%

Not

es:

Est

imat

edm

odel

spr

esen

ted

inth

eta

ble

abov

ear

eof

the

form

:L

ogit

mod

el1:

LO

GIT

1=

f(A

DJ

OP

t,S t

,DFA

t−1,

Lt,

FAt−

1,D

EB

Tt,

CA

SHt)

,L

ogit

mod

el2:

LO

GIT

2=

f(A

DJ

OP

t,S t

,DC

At−

1,L

t,C

At−

1,D

EB

Tt,

CA

SHt)

,L

ogit

mod

el3:

LO

GIT

3=

f(A

DJ

OP

t,S t

,DFA

t−1,

DC

At−

1,L

t,D

EB

Tt,

CA

SHt)

,L

ogit

mod

el4:

LO

GIT

4=

f(A

DJ

OP

t,S t

,DFA

t−1,

DC

At−

1,L

t,D

EB

Tt,

CA

SHt)

,w

here

the

depe

nden

tva

riab

leL

OG

IT1

refe

rsto

deci

sion

onw

heth

erco

mpa

nies

wri

te-o

ffon

lyfix

edas

sets

orno

t,L

OG

IT2

refe

rsto

deci

sion

onw

heth

erco

mpa

nies

wri

te-o

ffon

lycu

rren

tas

sets

orno

t,L

OG

IT3

refe

rsto

deci

sion

onw

heth

erco

mpa

nies

wri

te-o

fffix

edan

dcu

rren

tas

sets

orno

t,an

dL

OG

IT4

refe

rsto

deci

sion

onw

heth

erco

mpa

nies

wri

te-o

ff(e

ither

fixed

asse

ts,

curr

ent

asse

tsor

both

)or

not

(1if

asse

tsar

ew

ritt

en-o

ff,

othe

rwis

e0)

,A

DJ

OP

tis

oper

atin

gpr

ofit

adju

sted

for

wri

te-o

ffex

pens

es,S

tis

com

pany

size

mea

sure

das

the

natu

ral

log

ofye

ar20

03sa

les,

DFA

t−1

isdu

mm

yva

riab

lefo

rth

epr

evio

usye

arw

rite

-off

offix

edas

sets

,D

CA

t−1

isdu

mm

yva

riab

lefo

rth

epr

evio

usye

arw

rite

-off

ofcu

rren

tas

sets

,L

tis

loss

dum

my,

FAt−

1is

open

ing

stoc

kof

fixed

asse

ts,

CA

t−1

isop

enin

gst

ock

ofcu

rren

tas

sets

,DE

BT

tis

finan

cial

debt

,and

CA

SHt

isca

shan

dne

ar-c

ash.

All

acco

untin

gva

riab

les

are

defla

ted

byth

eop

enin

gbo

okva

lue

ofto

tal

asse

tsT

At−

1.B

oldf

aced

estim

ates

are

sign

ifica

ntat

5%or

bett

er.E

xact

leve

lsof

sign

ifica

nce

are

show

nbe

low

each

estim

ated

coef

ficie

nt.S

ampl

esi

zeis

23,4

55co

mpa

nies

.



and companies that have written-off current assets in the previous year are also morelikely to write-off current assets this year, thereby repeating the economic gain.

The differences between the results for fixed asset write-offs and current asset write-offs are not totally unexpected. As prescribed in SAS (2001, p. 28), companies must writefixed assets off to their recoverable amount if the book value exceeds their recoverableamount. The recoverable amount is the higher of the net realisable value and the valuein use. The value in use is determined by discounting future net cash flows expectedfrom the asset by applying the appropriate discount rate, implying that companies mustmake a relatively complex analysis of fixed assets, involving all elements of a typicalcapital budgeting process (amount and timing of future expected net cash flows andan estimate of the riskiness of these cash flows). They may employ an external appraiserto provide these analyses. For current assets, on the other hand, the recoverable amountis based much more on a company’s judgment, including past experience in the caseof receivables (SAS, 2001, p. 59). Thus, the decision to write-off fixed assets involvesa much more detailed procedure of asset valuation, additional cost and relatively lessdiscretion. Descriptive statistics of our sample companies support this notion with bothmore companies writing-off current assets than fixed assets and the magnitude of thosewrite-offs being greater.

Taken together our results indicate that whilst fixed asset write-off decisions aredriven by regulatory and accounting process issues linked to impairment, it is thepotential economic gain resulting from a write-off that is more influential in the decisionto write-off current assets – more profitable companies are more likely to write-offcurrent assets. Incremental to this, and to other conditioning variables, are the politicalcosts and other contracting costs for both types of assets. This contention is furthersupported by the results for those companies that write-off both fixed and current assets(third column) with all variables significant except for debt, and for all companies thatwrite-off (fourth column) with all variables significant and signed as expected.

It is also interesting to note that with this latter model 77.6% of companies arecorrectly classified whilst a ‘naı̈ve’ decision rule of classifying all companies as non-writing-off would correctly classify only 71% of companies. This result is achieved witha non-optimising estimation technique – the logistic regression. The percentage ofcorrectly classified companies using the logistic regression models could be improvedsignificantly, had the cost of each type of error of classification been known or analternative optimising regression technique adopted. We have no priors regardingappropriate cost weights and simply report the non-optimised results.

These results indicate that the decision to write-off assets is not limited to accountingregulation and practice (impairment) and contracting factors known from the existingliterature. Having controlled for these factors there are economic gains, learning andpolitical factors that impact on the write-off decision. Our results are consistent withfindings that the system of economic and political incentives is an important andpotentially overriding determinant of the quality of financial statements (e.g., Ballet al., 2003) over and above accounting regulation.

(b) Magnitude of Write-Offs

To investigate the impact of these factors further we address next the drivers of themagnitude of write-off by regressing the magnitude of write-off for those companiesthat do write-off against the explanatory variables. The results of these regressionsare reported in Table 4, again separately for companies writing-off fixed assets only,



Tab

le4

Lin

ear

Reg

ress

ion

Mod

els

–M

agni

tude

ofW

rite

-off

s

Coe

ffici

ents

for

Mod

els

(p-v

alue

sin

pare

nthe

ses)

Expl

anat

ory

Vari

able

sEx

pect

edM

odel

1M

odel

2M

odel

3M

odel

4Si

gn(F

Aw

rite

-offs

only

)(C

Aw

rite

-offs

only

)(F

Aan

dC

Aw

rite

-offs

)(F

Aor

CA

wri

te-o

ffs)

Con

stan

t0.

037

0.05

60.

078

0.05

1(0

.000

)(0

.000

)(0

.000

)(0

.000

)Te

stva

riab

les:

AD

JO

Pt

+0.

021

0.07

50.

073

0.06

5(0

.000

)(0

.000

)(0

.000

)(0

.000

)S t

−−

0.00

3−

0.00

5−

0.00

5−

0.00

3(0

.000

)(0

.000

)(0

.000

)(0

.000

)W

OFF

FA,t

−1+

0.17

40.

136

0.10

5(0

.001

)(0

.188

)(0

.035

)W

OFF

CA,t

−1+

0.17

90.

268

0.23

0(0

.000

)(0

.000

)(0

.000

)C

ontr

olva

riab

les:

Lt

+0.

004

0.00

70.

012

0.00

8(0

.003

)(0

.000

)(0

.000

)(0

.000

)FA

t−1

+0.

003

(0.0

90)

CA

t−1

+0.

024

(0.0

00)



Tab

le4

(Con

tinu

ed)

Coe

ffici

ents

for

Mod

els

(p-v

alue

sin

pare

nthe

ses)

Expl

anat

ory

Vari

able

sEx

pect

edM

odel

1M

odel

2M

odel

3M

odel

4Si

gn(F

Aw

rite

-offs

only

)(C

Aw

rite

-offs

only

)(F

Aan

dC

Aw

rite

-offs

)(F

Aor

CA

wri

te-o

ffs)

DE

BT

t−

0.00

0−

0.00

8−0

.011

−0.

009

(0.8

81)

(0.0

14)

(0.0

77)

(0.0

00)

CA

SHt

−0.

002

0.00

30.

019

0.00

2(0

.588

)(0

.293

)(0

.046

)(0

.371

)A

djus

ted

R2

0.08

40.

173

0.15

70.

128

F19

.715

132.

823

28.9

4414

4.59

3Si

gnif

ican

ce0.

000

0.00

00.

000

0.00

0

Not

es:

Est

imat

edm

odel

spr

esen

ted

inth

eta

ble

abov

ear

eof

the

form

:M

odel

1:W

OFF

FA,t

=f

(AD

JO

Pt,

S t,W

OFF

FA,t

−1,L

t,FA

t−1,

DE

BT

t,C

ASH

t),

Mod

el2:

WO

FFC

A,t

=f

(AD

JO

Pt,

S t,W

OFF

CA,t

−1,L

t,C

At−

1,D

EB

Tt,

CA

SHt)

,M

odel

3:W

OFF

FA&

CA,t

=f

(AD

JO

Pt,

S t,W

OFF

FA,t

−1,W

OFF

CA,t

−1,L

t,D

EB

Tt,

CA

SHt)

,M

odel

4:W

OFF

FA+C

A,t

=f

(AD

JO

Pt,

S t,W

OFF

FA,t

−1,W

OFF

CA,t

−1,L

t,D

EB

Tt,

CA

SHt)

,w

here

WO

FFFA

,tis

curr

enty

ear

wri

te-o

ffex

pens

eas

soci

ated

with

fixed

asse

ts,W

OFF

CA,t

iscu

rren

tyea

rw

rite

-off

expe

nse

asso

ciat

edw

ithcu

rren

tass

ets,

WO

FFFA

&C

A,t

isth

esu

mof

curr

ent

year

wri

te-o

ffex

pens

esas

soci

ated

with

fixed

and

curr

ent

asse

tsif

both

type

sof

asse

tsar

ew

ritt

en-o

ff,W

OFF

FA+C

A,t

isth

esu

mof

curr

ent

year

wri

te-o

ffex

pens

esas

soci

ated

with

fixed

and

curr

enta

sset

s,A

DJ

OP

tis

oper

atin

gpr

ofit

adju

sted

for

wri

te-o

ffex

pens

es,S

tis

com

pany

size

mea

sure

das

the

natu

rall

ogof

year

2003

sale

s,W

OFF

FA,t

−1is

prev

ious

year

wri

te-o

ffex

pens

eas

soci

ated

with

fixed

asse

ts,W

OFF

CA,t

−1is

prev

ious

year

wri

te-o

ffex

pens

eas

soci

ated

with

curr

ent

asse

ts,L

tis

loss

dum

my,

FAt−

1is

open

ing

stoc

kof

fixed

asse

ts,C

At−

1is

open

ing

stoc

kof

curr

enta

sset

s,D

EB

Tt

isfin

anci

alde

bt,a

ndC

ASH

tis

cash

and

near

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current assets only, both fixed and current assets and either fixed or current assets orboth.

As for the write-off decision, the loss indicator is significant in the fixed assetregression (first column), suggesting that loss companies write-off more on average.Interestingly, the stock of fixed assets does not appear to determine the relativemagnitude of fixed assets write-offs. Also, neither of the conditioning variables from therevaluation literature (level of debt and liquidity) is significant, supporting the view thatthe factors driving revaluation and write-off are somewhat different. Most importantly,the results lend support to our three main hypotheses. More profitable companieswrite-off more on average, once the write-off decision has been taken. Consistent withavoiding undue political visibility to tax authorities, larger companies write-off relativelyless, once the write-off decision has been taken, and previous write-off experienceincreases the magnitude of current write-offs of fixed assets.

A similar picture is revealed for those companies that write-off current assets only(second column), except that the debt variable is now significant as is the opening levelof current assets. More debt implies less, and a higher opening stock of current assetsmore, write-off of current assets, consistent with expectations from existing literature.In addition, it is interesting to note that the coefficient on the profitability variablein the current asset regression is more than three times the value in the fixed assetregression, consistent with potential economic gains due to tax minimisation being amore important determinant of current asset write-off than for fixed asset write-off.

For those companies that write-off both fixed and current assets (third column) allvariables are significant, except for the debt variable and the level of fixed asset write-offs in the previous year. The liquidity variable is marginally statistically significant,but contrary to our expectations the sign is positive.14 A similar result is obtained forcompanies writing-off either type of assets (fourth column), except that previous yearwrite-off of fixed assets now becomes significant, as does debt, whilst liquidity loses itssignificance.

In summary, of the two conditioning variables found significant in previous studiesof revaluations in widely held, publicly-quoted companies, neither is consistentlysignificant with the level of debt being significant in 2 of the 4 regressions and liquidityonly significant in one. This finding supports our prior that the system of incentives ofeconomic agents in SPCs is very different from large quoted companies and that thedrivers of write-offs are somewhat different to the drivers of revaluations.

All three of the test variables are generally statistically significant with the hypoth-esized signs. The magnitudes of write-off are positively associated with the underlyingprofitability of the companies, whilst accounting standards would suggest the reverse.This is consistent with the system of incentives and institutional properties being veryimportant in determining the outcome of the financial reporting process in thesecompanies summarised in accounting earnings. The relation of the write-off amountwith size is negative and is, in some ways, consistent with findings that larger companiesare more likely to revalue their assets upwards (e.g., Brown et al., 1992; and Linand Peasnell, 2000) and with anecdotal evidence that tax authorities prefer – ceterisparibus – to tax-audit larger companies as the possible gains to the tax authorities

14 This result is examined further in the sensitivity analyses as this finding has an alternative explanation.



(and possibly the tax inspectors themselves) are larger.15 The estimated regressioncoefficients on previous year write-offs are positive and significant, consistent withour expectation that learning across time plays a role in the write-off decision inthe particular empirical setting we employ. Again, accounting systems and regulationassume appropriate implementation without the need for learning across time. Thecorrelation in write-off of current assets across years is particularly interesting, as, bydefinition, current assets decay within one reporting period and any effects should becaptured within that year’s financial statements, once controlled for growth in size (bydeflation) and industry-wide effects.

(iii) Sensitivity and Robustness Checks

Whilst the sample is relatively homogenous from an ownership perspective with 95.39%of our sample companies having 10 or fewer owners, it is still possible that our results aredriven by different contracting demands from active and passive owners. For example,passive owners may prefer higher dividend payouts whilst active owners may place moreweight on growth or be better placed to extract private benefits for themselves. Sucha scenario could also lead to the positive relationship between write-offs and earningsthat we have identified.

We therefore extract the 11,046 SPCs with but a single natural person owner to forma pure and extreme sub-sample where owner contracting differences cannot exist. Were-run all four logit and all four regression models using this refined sub-sample. For thelogit models – the decision to write-off/not to write-off assets – results are qualitativelyidentical to those reported above, except that the loss dummy is no longer significant inany of the models. All other explanatory variables are (in)significant as before, signedas before and coefficients are of similar magnitude. The loss of significance of the lossdummy only supports further our conclusion that write-offs are much more heavilydriven by economic and political incentives of owner-managers than by accountingregulation and substance.

Similar conclusions hold for the four regression models – reflecting the magnitude ofwrite-offs – except that the loss dummy loses significance only for the fixed assets write-offs. Additionally, previous write-offs of fixed assets become statistically insignificant. Insummary, all our main findings are confirmed in the absence of differing ownershipcontracting demands. If anything, the results are strengthened and our conclusion that,in the absence of agency conflicts, economic incentives dominate accounting standardsis reaffirmed.

Taking a related but different approach we investigate the relationship between themagnitude of write-off and the pre-write-off effective tax rate and expect a positiverelationship between the two. Consistent with our earlier findings, the estimatedcoefficient is significantly positive for current assets and insignificant for fixed assets.

Our models depend on concurrent data and we find a high correlation betweenwrite-offs and profitability. It is possible that the write-off is a signal of poor futureprofitability. We therefore regress the change in net income from this year to thenext on current year write-off expenses. If write-offs do offer a signal of weakening

15 Neither the criteria by which companies are selected for tax audits nor possible incentives for tax auditorsthemselves are publicly known in Slovenia.



future performance we would expect a negative correlation. Finding in fact insignificantcoefficients, our original conclusions are further corroborated.

Our sample companies are drawn from a wide range of 29 different industries,spanning both manufacturing and services sectors with different properties in termsof composition of assets (e.g., inventory is unlikely to be important in size in servicesindustries). We, therefore, carry out sensitivity analyses on both the logistic and linearregression models by incorporating industry dummy variables. Of the 28 dummies, sixare significant in one of the logistic regressions whilst in the remaining three logistic andall four linear regression models no more than four industry dummies are significant.None of the significant industry dummies recur throughout different models and wetake these results to confirm that industry factors are not significant drivers in thewrite-off decision.16

We also run all logistic and linear models separately for each of the 29 industries,obtaining similar results as in our main analyses overall. Condensed results of estimatingthe linear regressions for the magnitude of write-off are presented in Table 5. These aregenerally consistent with our main results. One result that is perhaps worth stressing isthe pervasiveness of the profitability (ADJ OPt) variable in current asset regressions,indicating the importance of economic gains rather than losses in influencing themagnitude of current asset write-offs.

The analysis of the magnitude of write-offs supports further the view that write-offsand upward asset revaluations are two distinct phenomena. It is difficult to envisage,in our setting, any benefits resulting from revaluations (e.g., due to signalling) overand above potential contractual benefits already controlled for. On the other hand, taxbenefits from write-offs are immediate and obvious. Moreover, accounting principles,notably conservatism, require an asymmetric treatment of write-offs and revaluations.If, however, asset write-offs and revaluations are thought of as a continuous variable (asnoted by Lin and Peasnell, 2000), then the method of empirical estimation of linearmodels in Table 4 is potentially flawed. Our dependent variable records a non-zerovalue where write-offs actually occur and a zero value is recorded when no write-off ora write-up occurs. We thus have a censored sample and the estimated parameters inTable 4 might be biased as well as inconsistent (e.g., Maddala, 1983, pp. 149–62; andGreene, 2000, pp. 905–26).

To account for this, we re-estimate the magnitude models using the Heckmanmaximum-likelihood procedure – the tobit regression. We find that all estimatedregression coefficients remain of the same sign (albeit, predictably, of differentmagnitudes), with the exception of the size variable, which changes sign to positive– larger companies are expected to write-off relatively more. Thus, in our total sampleof small companies, the tax benefits from write-off offset perceived potential costsresulting from increased political exposure. This is not inconsistent with our previousfinding. Once the write-off decision has been taken and the attention of tax authoritiespotentially drawn to the company, this is not further exacerbated by writing-off excessiveamounts of assets and so the magnitude of write-off is decreasing with size for writing-off companies only. In the overall sample that includes non-writing-off companies,however, we have shown that larger companies are more likely to write-off.

16 We would expect that the opening stocks of fixed and/or current assets would capture a significant partof any industry effects.



Table 5Signs of Significant Regression Coefficients in Linear Regression Models

(Magnitude) Estimated for Each Industry Separately

Expected Sign Significant and Positive Significant and Negative

FA subsetSignificant F -statistic 8ADJ OPt + 5St − 12WOFFFA,t −1 + 3 1Lt + 2FAt −1 + 1 1DEBTt − 1CASHt − 3

CA subsetSignificant F -statistic 24ADJ OPt + 16St − 17WOFFCA,t −1 + 9Lt + 3CAt −1 + 16DEBTt −CASHt − 3 2

CA and FA subsetSignificant F -statistic 9ADJ OPt + 6St − 5WOFFFA,t −1 + 2WOFFCA,t −1 + 4Lt + 2DEBTt − 1CASHt − 1

CA or FA subsetSignificant F -statistic 25ADJ OPt + 20St − 16WOFFFA,t −1 + 3WOFFCA,t −1 + 15Lt + 6DEBTt − 4CASHt − 1 2

Notes:Estimated models presented in the table above are of the form:Model 1: WOFFFA,t = f (ADJ OPt , St , WOFFFA,t −1, Lt , FAt −1, DEBTt , CASHt ),Model 2: WOFFCA,t = f (ADJ OPt , St , WOFFCA,t −1, Lt , CAt −1, DEBTt , CASHt ),Model 3: WOFFFA&CA,t = f (ADJ OPt , St , WOFFFA,t −1, WOFFCA,t −1, Lt , DEBTt , CASHt ),Model 4: WOFFFA+CA,t = f (ADJ OPt , St , WOFFFA,t −1, WOFFCA,t −1, Lt , DEBTt , CASHt ),where WOFFFA,t is current year write-off expense associated with fixed assets, WOFFCA,t is current yearwrite-off expense associated with current assets, WOFFFA&CA,t is the sum of current year write-off expensesassociated with fixed and current assets if both types of assets are write-offd, WOFFFA+CA,t is the sum ofcurrent year write-off expenses associated with fixed and current assets, ADJ OPt is operating profit adjustedfor write-off expenses, St is company size, WOFFFA,t −1 is previous year write-off expense associated withfixed assets, WOFFCA,t −1 is previous year write-off expense associated with current assets, Lt is loss dummy,FAt −1 is opening stock of fixed assets, CAt −1 is opening stock of current assets, DEBTt is financial debt andCASHt is cash and near-cash. All accounting variables are deflated by the opening book value of total assetsTAt −1. All models are estimated for each industry separately (29 separate industry groups are identified).



We perform a number of additional sensitivity analyses. First, because the cashvariable is clearly not independent from the write-off amount, we remove the cashvariable and re-estimate all the models. Second, we include the number of employees(both un-deflated and deflated by total assets), because the number of employeesmight motivate the owner-manager to reduce ‘visible’ operating profit to decreasethe likelihood of higher wage demands (a positive coefficient) and because higherwages would imply less need for tax-reducing write-off (a negative coefficient). Third,we include previous year operating profit (and in a separate regression, net income)as a proxy for current year tax-loss carry forward – the larger the last year’s loss, themore likely it is that part of this loss has been taken forward for tax purposes, therebyreducing the need for further write-offs in the current year. Potential non-linearitiesin the relation between profit and write-offs are accounted via a loss dummy variable.Fourth, we have tried different outlier deletion rules. In all these cases, our conclusionsfrom the main analyses remain qualitatively unchanged. For parsimony, we do notinclude them in our main results’ tables.

4. CONCLUDING REMARKS

In this paper we investigate the factors that influence the decision to write-off thebalance sheet value of an asset and the magnitude of any such write-off. We enrichthe literature by investigating asset write-offs rather than revaluations, by investigatingwrite-off decisions for both fixed and current assets and by investigating these decisionsin small private companies, thereby removing a range of agency-related issues.

We view our results as extending current research in three important areas. Firstly,and, we believe, most importantly, in the area of the interaction between financialreporting and institutional determinants of the environment in which a companyoperates and reports. In our case, the crucial distinction from existing literature isthe absence of agency issues between owners and managers which, coupled with aninstitutional link between financial and tax reporting, enables us to study directly theimpact of incentives faced by preparers of financial statements relative to intendedprescriptions of accounting standards. In this framework where financial and taxreporting are closely aligned, owners-managers of SPCs are exposed to pure incentivesto rationally minimise the present value of present and future tax payments. In thisthey are unencumbered by signalling and agency issues, but are subject to political andcontracting constraints, including a particular type of institutional learning in adaptingto a ‘new’ accounting regulation with the introduction of ‘new’ accounting standards.

Write-offs of current and fixed assets are shown to be used incrementally, if notmainly, as an earnings- and tax-reducing accounting practice, rather than beingexclusively an immediate consequence of asset impairment. This finding is robust tocontrolling for regulated (or operating or intended) impairment-induced write-offsthat are also identified in our sample. Write-offs represent one specific type of accrualswhere it is possible to formulate relatively strong expectations under the null hypothesisof no discretion and interpret the results as underscoring the importance of economicincentives over and above prescriptions of accounting standards. However, the findingscan likely be generalised to other types of accruals, too, and are not necessarily uniqueto write-offs.

We analyse empirically the decision and the extent of asset write-off using four subsetsof our total sample of small private companies operating in the Republic of Slovenia,



following the introduction of new accounting standards, representing an importantstructural break in financial reporting practice. We show that operating profit and prioryear write-off positively affect the choice and the magnitude of asset write-off. Theseresults confirm our main hypothesis that write-off serves as an important earningsand consequently tax-reducing practice. Positive association of company size with theprobability to write-off and negative association with its magnitude is consistent withlarger companies complying more quickly and more easily with new regulation butbeing constrained in their tax-reducing practices by political visibility. As expectedfrom existing literature, we find financial debt to be negatively associated to write-off.Asset write-off reduces the debt-to-assets ratio, thus increasing the chance of violatingdebt covenants and implying more costly external debt financing. Moreover, interestexpenses themselves reduce the need to decrease earnings with other types of expenses(e.g., write-off expenses). Consistent with the conservative accounting principle weidentify that asset write-offs do occur with asset impairment. Our findings above arerobust to controlling for such impairment (operating) write-off. In addition, thefindings are robust across industries and thus incremental to industry-wide factors.With these findings, we add, secondly, to existing revaluation/write-off literature that,hitherto, has focused on fixed asset revaluations in large, publicly-quoted companies.

Thirdly, our paper contributes to the current debate on regulation of small andmedium entities (SMEs) reporting, given that the incentives of preparers and the needsof users in the case of SMEs may differ substantially from those in large, publicly-quoted companies. Our paper exposes such differences ad extremum and providesinsights into the interaction between incentives and standards in an environment whereincentives of preparers are clear. The exceptional institutional requirement enforcedin Slovenia that requires all companies to report detailed financial statements allowsus to study asset write-off in an environment that conforms closely to a pure theoreticalsetting. Moreover, our paper also contributes to the growing literature on propertiesof accounting in privately-held companies and SMEs in particular, a relatively under-researched area in the accounting literature.

As an endnote, we reiterate that one aspect of institutional learning by thetax authorities has been completed. From 1 January, 2005, asset write-offs are notrecognised as a tax-deductible expense any longer (Corporate Income Tax Act, OfficialGazette of the Republic of Slovenia, 40/2004, 2004 and subsequent amendments).

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Asset Write-Offs in the Absence of Agency Problems

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