Embed Size (px)
Citation preview
This article was downloaded by: [University of Lethbridge]On: 03 October 2014, At: 06:39Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954 Registeredoffice: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK
The European Journal of FinancePublication details, including instructions for authors andsubscription information:http://www.tandfonline.com/loi/rejf20
The association between qualitativemanagement earnings forecastsand discretionary accounting in theNetherlandsAndré B. Dorsman a b , Henk P.A.J. Langendijk a c & Bart Van Praag ca Nyenrode University , Straatweg 25 , Breukelen , 3621 BG , TheNetherlandsb Free University of Amsterdamc University of AmsterdamPublished online: 19 Mar 2012.
To cite this article: André B. Dorsman , Henk P.A.J. Langendijk & Bart Van Praag (2003) Theassociation between qualitative management earnings forecasts and discretionary accounting in theNetherlands, The European Journal of Finance, 9:1, 19-40, DOI: 10.1080/13518470110099696
To link to this article: http://dx.doi.org/10.1080/13518470110099696
PLEASE SCROLL DOWN FOR ARTICLE
Taylor & Francis makes every effort to ensure the accuracy of all the information (the“Content”) contained in the publications on our platform. However, Taylor & Francis, ouragents, and our licensors make no representations or warranties whatsoever as to theaccuracy, completeness, or suitability for any purpose of the Content. Any opinions andviews expressed in this publication are the opinions and views of the authors, and arenot the views of or endorsed by Taylor & Francis. The accuracy of the Content should notbe relied upon and should be independently verified with primary sources of information.Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands,costs, expenses, damages, and other liabilities whatsoever or howsoever caused arisingdirectly or indirectly in connection with, in relation to or arising out of the use of theContent.
This article may be used for research, teaching, and private study purposes. Anysubstantial or systematic reproduction, redistribution, reselling, loan, sub-licensing,systematic supply, or distribution in any form to anyone is expressly forbidden. Terms &
Conditions of access and use can be found at http://www.tandfonline.com/page/terms-and-conditions
Dow
nloa
ded
by [
Uni
vers
ity o
f L
ethb
ridg
e] a
t 06:
40 0
3 O
ctob
er 2
014
The European Journal ofFinance 9, 19-40 (2003) I, Routledge~ '....."F'......"'-
The association between qualitativemanagement earnings forecasts anddiscretionary accounting in the NetherlandsANDRE B. DORSMAN1,2, HENK PA.J. LANGENDIJK1,3and BART VAN PRAAG3
fNyenrode University, Straatweg 25, 3621 BG Breukelen, The Netherlands2Free University of Amsterdam3University of Amsterdam
This paper examines whether there Is an association between discretionary accountingand the accuracy of long-run forecasts of annual earnings disclosed voluntarily by Dutchcompanies In the directors' report. In particular, Investigations were made of the consistency In the sign and direction of discretionary accounting techniques and qualitativeearnings forecasts. Long-run forecasts are defined, for the purposes of this paper, asforecasts made at least seven months before the year-end. Although not mandatory,qualitative forecasts are released by well over 60% of the listed companies in theNetherlands. Empirical results Indicate that there Is consistency in the sign and directionof qualitative earnings forecasts and discretionary accounting. After adopting discretionary accounting, the forecast errors are reduced if the company can reach themanagement earnings forecast (target). In the event that reserves are insufficient toaccomplish this goal, managers choose their next best option and take an earnings bathIn order to maximize reserves available for future use. By partitioning the sample invarious sub-sets It is shown that earnings management and forecast errors occur mostin the extreme ranges of financial performance. Overall, the study shows that management engages in discretionary accounting to present results in line with the disclosedqualitative earnings forecasts in their directors' reports. Whilst discretionary accountingmay clearly Improve the consistency of companies' earnings forecasts released via thedirectors' reports and the actual earnings, managers' earnings forecasts are sometimesdisclosed In anticipation of planned discretionary accounting actions.
Keywords: forecasting earnings, discretionary accounting and qualitative managementearnings forecasts .
1. INTRODUCTION
Publlcly disclosed management forecasts are Important sources of Informationto Investors. This is borne out by market reactions to disclosure of theseforecasts-see, for example, Waymire (1986), Jaggi and Sannella (1995), Mensahet al.. (1996) and Kasznlk (1999). Management often discloses their expectationsabout future earnings performance without projecting expllctt earnings orearnings per share numbers. Phrases used in the director's report (on the
The European Journal of FinanceISSN 1351-847X prlntllSSN 1466-4364 online © 2003 Taylor & Francis Ltd
hUp://www.landf.co.uk/journalsDOl: JO.1080/13518470110099696
Dow
nloa
ded
by [
Uni
vers
ity o
f L
ethb
ridg
e] a
t 06:
40 0
3 O
ctob
er 2
014
20 A Dorsman et at.
business outlook) are for Instance 'expect earnings to be well above last year'snet' or 'expect earnings to be substantially higher than last year's levels'.According to our definition a qualitative management earnings forecast sets outmanagement's expectations about the company's earnings for the next annualreporting date without estimating a specific amount or range. At the same time,the words ciearly Indicate whether management expects an Increase or adecrease In earnings from the previous year. Because earnings forecasts inDutch companies' directors' reports are not mandatory, it is possible that theywill only be given where managers are able to predict or control earnings (selfselection bias, Brown, 1988). Managers have control over numerous transactions and reporting decisions that affect reported earnings, for example,accounting changes, sale and lease back transactions, provisions, extraordinarygains and losses and pensions.
We define discretionary accounting as accounting based on these Irregulartransactions. The association between qualitative management projections anddiscretionary accounting techniques has not been' researched until now.However, since a large number of companies choose this form of forecastdisclosure In place of more specific proJections, qualitative forecasts and discretionary accounting techniques are relevant to the study of the range ofearnings forecasts In relation to discretionary accounting. Generally, theresearch In this field has been restricted to quantitative management earningsforecasts, exceptions being Foster (1973), Lev and Penman (1988) and Mensahet al. (1996). Mensah et al. (1996) proVided evidence on the predictive valueof qualitative management earnings forecasts and their effects on financialanalysts' expectations and stock prices, however, they did not examine dis_cretionary accounting. Prior research on quantitative management earningsforecasts and discretionary accounting documents an association between highpre-change forecast errors and the adoption of discretionary accountingchanges (Jaggi and Sanella, 1995) or the adoption of discretionary accruals(Kasznik, 1999).
Proxies for discretionary accounting can take two forms. Either specific lineitems of a discretionary nature are identified or benchmarks are used todetermine normal levels of variables. An example of the latter approach is thefamily of accrual models. The advantage of using line items is increased precisionwhereas benchmarking can yield a more encompassing but noisy measure. Inthis paper we will use line Items because it is the authors' opinion that the noisymeasure contains even less theoretical grounds In the Netherlands wheresample size Is relatively small and accrual accounting is implemented differentlyfrom the US. The highly Judgmental accounting system of the Netherlandsprovides many more opportunities to use discretionary line Items than theaccounting system of the US. As a consequence it Is expected that DutChmanagers will use discretionary line items much more than discretionaryaccruals than their US counterparts.
This study investigates whether managers who Issue qualitative earningsforecasts manage reported earnings in the direction of their forecasts or whenthey cannot reach the forecast by discretionary accounting techniques, theywill choose their next best option and take an earnings bath to maximize
Dow
nloa
ded
by [
Uni
vers
ity o
f L
ethb
ridg
e] a
t 06:
40 0
3 O
ctob
er 2
014
Discretionary accounting in the Netherlands 21
reserves available for future use (see Abarbanell, 1999, for this theoreticalconstruct). We hypothesize-under the condition that managers can reach theirforecast by discretionary accounting techniques-that managers make incomeincreasing (decreasing) accounting decisions when earnings would otherwisenot be of the sign and the direction of the qualitative forecasts and thatdiscretionary accounting activity is increasing in expected forecast error costs.These costs are likely higher for overestimates than for underestimates and areIncreasing in the magnitude of the forecast error. If managers cannot reach theirforecast, it is hypothesized that managers will take an earnings bath in order tomaximize reserves available for future use.
The discretionary accounting techniques were obtained from the notes ofthe annual reports. Then, the association between the forecasts and the discretionary accounting techniques was examined. There have been variouspieces of research focusing upon Dutch quantitative and qualitative forecastsreleased in directors' reports. In general, they have conciuded that mostvoluntarily released earnings forecasts are correct. Levy (1995) reports 66%making forecasts and 72% correct; Stolwerk et al. (1997) report 87% withforecasts and 62% correct. It appears that larger companies release earningsforecasts more often than small companies and large companies have smallerforecast errors than small firms-see Levy (1995). Management seems to releaseearnings forecasts more frequently when earnings are rising than when they arefalllng (see Levy, 1995). With the exception of Stolwerk et al. (1997) all empiricalwork In this direction is of a descriptive nature. Stolwerk et al. (1997) mentiondiscretionary accounting techniques as a possible explanation for the reductionof forecast errors. However, they have not investigated this possible explanationof the reduction of forecast errors. The contribution of this paper to themanagement earnings forecast literature In the Netherlands Is the Investigationof the relationship between management earnings forecasts and discretionaryaccounting techniques.
This study sheds light on the interaction between financial reporting discretion and voluntary disclosure in the Netherlands. It is the first paper thatinvestigates the association between qualitative management earnings forecastsand discretionary accounting techniques (Jaggi and Sanella, 1995; Kasznlk, 1999analysed the relationship between quantitative forecasts and discretionaryaccounting). Furthermore, it is the first paper that relates the exogenouslydefined rules for mapping pre-managed earnings to the reported earnings ofAbarbanell (1999) and qualitative management earnings forecasts. Abarbanelland Lehavy (1999) Investigated the association between discretionary accounting by management and quantitative analysts' forecasts. OUf results extend theresearch in the field of management earnings forecasts and discretionaryaccounting.
Finally, this study contributes to the qualitative management earnings forecasts literature by introducing the scale of Mock (1992) as a measurementdevice for the interpretation of qualitative forecasts. This scale is a better andmore refined scale than the scale used by Mensah et al. (1996). It is a 13-pointscale instead of a five-point scale and It is widely used in practice in the
Dow
nloa
ded
by [
Uni
vers
ity o
f L
ethb
ridg
e] a
t 06:
40 0
3 O
ctob
er 2
014
22 A Dorsman et at.
Netherlands by management of companies and financial analysts since Its firstpublication In 1984.
The paper Is organized as follows. Section 2 presents a brief discussion of theInstitutional background of the Netherlands. Section 3 provides an overview ofprevious research on the relationship between management earnings forecastsand discretionary accounting. Section 4 describes the empirical analysis withrespect to the association between discretionary accounting and management earnings forecasts. In the final section the results are summarized anddiscussed.
2. ACCOUNTING AND CAPITAL MARKET ENVIRONMENT FOR EARNINGSFORECASTS IN THE NETHERLANDS
Capstaff et al. (1996) made a comparative analysis of earnings forecasts InEurope. For fourteen countries (including the Netherlands) they comparedaccounting and the capital market environment under four headings-earningsbehaviour, frequency and timeliness and quality of accounting disclosure.influence of taxation, and securities markets. According to their analysis.earnings In the Netherlands have relatively low volatility and show smallpositive changes. Regarding frequency, timeliness and quality of accountingdisclosure, the Netherlands Is ranked as second best (after the UK) with respectto the quality of accounting disclosure. On taxation, the Netherlands has anaccounting system like Denmark, Ireland and the UK that is relatively free frornthe Influence of taxation. Therefore, Dutch management has no Incentive for t<Ucreasons, to depress reported earnings-unlike the systems In Germany andFrance. Turning to the effects of securities markets, Capstaff et al. (1996) suggestthat If value Is a function of earnings, the frequency and resources devoted toforecasting and to Improving the accuracy of forecasts Is likely to be significant.In the Netherlands Olke the UK), there seems to be a high degree of associationbetween earnings and share prices. Generally, the accounting and capitalmarket environment In the Netherlands Is reasonably comparable to the UK.According to the classification of Nobes and Parker (2000, p. 59) the Nether_lands has an accounting system which Is based In business economics (ampleroom for current cost and market value applications) and Is extreme Judgmental.The accounting system In the Netherlands gives managers much more 0ppor_.tunltles to use discretionary line items than In the US and other continentalEuropean countries. This abundant use of discretionary line items by man.agers In the Netherlands Is confirmed by studies of Hoogendoorn (1990) andOverboom and Vergoossen (1997). As a consequence of the large number ofopportunities provided by the accounting system In the Netherlands to USediscretionary line Items It Is expected that managers will use discretionary lineitems much more than discretionary accruals than their counterparts from theUS or other continental European countries. Since 1984 companies In theNetherlands have been obliged to provide Information on the business outlookIn the directors' report, paying attention, unless there are compelling reasonsfor not doing so, to Investment, financing and circumstances affecting futureturnover and profitability (Dutch accounting law, section 391, subsection 3),
Dow
nloa
ded
by [
Uni
vers
ity o
f L
ethb
ridg
e] a
t 06:
40 0
3 O
ctob
er 2
014
Discretionary accounting in the Netherlands 23
So, the company Is not obliged to give an earnings forecast, per se, for thenext period. But, the company must focus on circumstances affecting futureprofitability. .
The Dutch Council of Annual Reporting (CAR) refers In CAR section 400.108 toDutch accounting law, section 391, subsection 2. The CAR put forward that theprescription to pay special attention to Investment, financing and circumstancesaffecting future turnover and profitability Is Intended to prevent the authors ofdirectors' reports confining their remarks to generalizations and vague pronouncements (CAR 400.105). However, the CAR adds no further requirements toDutch accounting law in relation to the elements of directors' reports.
According to the results of Dutch accounting research there seems to be atradition to give voluntary management earnings forecasts In directors' reportsof listed companies In the Netherlands for decades (see Van der Meer, 1981;Levy, 1995 and Stolwerk et al., 1997). Generally, these forecasts are of a qualitativenature. Van der Meer (1981) finds that the primary motive for voluntarymanagement earnings forecasts Is the wish of management to cultivate areputation for reliable disclosure. Furthermore, voluntary management forecasts are used to confirm rather than correct analysts' forecasts. The reason isto avoid embarrassing their analysts by surprising them. The argument Is thatanalysts' III feelings and loss of confidence In management because of suchsurprises, particularly disappointments, Increases the firm's cost of capital. Thisargument has been confirmed by Dorsman et al. (1999) In an Investigation ofInvestor relations for Dutch companies.
3. PREVIOUS RESEARCH ON MANAGEMENT EARNINGS FORECASTSAND DISCRETIONARY ACCOUNTING
3.1 Motives for the disclosure of voluntary management earningsforecasts
Previous research Indicates a number of motives for the disclosure of voluntarymanagement earnings forecasts. Predominantly, management seems to use forecasts as a signalling deVice.
King et at.. (1990) provide evidence that managers disclose their earningsforecasts to correct unrealistic forecasts published by financial analysts. Rulandet al. (1990), on the other hand, have shown that management forecasts areused to confirm rather than correct analysts' forecasts. Skinner (1994) andKasznik and Lev (1995) Indicated another Important reason for disclosure ofearnings forecasts, namely to avoid embarrassing their analysts by surprisingthem. The argument Is the analysts' III feelings and loss of confidence Inmanagement because of such surprises, particularly disappointments, Increasesthe firm's cost of capital. Ruland et al. (1990) and Frankel et al. (1995) documenta positive relationship between companies' access to capital markets andvoluntary disclosure of earnings forecasts. The underlying reasons are theproblems of adverse selection and moral hazard associated with outsiders'reluctance to increase investment given that managers know more than outsidersdo. To some extent, this may be overcome by voluntary earnings forecasts.
Dow
nloa
ded
by [
Uni
vers
ity o
f L
ethb
ridg
e] a
t 06:
40 0
3 O
ctob
er 2
014
24 A Dorsman et at.
Finally, according to studies by Botosan (1997) and Healy et al. (1998)voluntary disclosure of management earnings forecasts seems to reduce thecost of capital of companies.
3.2 Qualitative earnings forecasts, forecast accuracy and discretionaryaccountingQualitative earnings forecasts are less precise than the various kinds of quantitative earnings (per share) projections, which have been studied in most pastresearch. This lack of precision would appear to reduce the predictive abilityand feedback value of qualitatively stated earnings projections, since it Isneither possible to Infer the exact percentage change in earnings predicted bymanagement, nor Is it easy to determine the extent to which management wasable to meet its own expectations ex post. Despite this, qualitative forecasts maybe informative about the expected direction of the change In the earnings (pershare). This was confirmed by the study of Mensah et al. (1996). They found nodifference in the reliability of quantitative and qualitative forecasts with respectto the signs of predicted earnings changes. Since the scale of Mock Is widelyused for many years both by management to phrase qualitative earnings fore_casts in the director's reports and by financlal analysts' to analyse these forecastswe expect that these forecasts are effectively used in the Netherlands.
The decision to disclose voluntarily qualitative rather than quantitativeforecasts may be related to a desire to avoid some of the potential costs ofproviding a more specific forecast, while successfully signalling management'splanning capabilities to investors and the labour market, and/or because the netearnings of these companies are Jess subject to accurate prediction. Trueman(1986) and Mensah et al. (1996) argue that management's ability to anticipateand tailor transactions to suit environmental changes may be successfullysignalled to investors by the forecast disclosure Itself, without regard to itscontent. While market reactions to such signals may be favourable, making aspecific forecast (in an amount) may entail risks that could be costly. Thesecosts may include litigation costs arising from inaccurate forecasts as well as'reputation' costs if management subsequently is viewed as unreliable (Kinget al., 1990; Kasznik, 1999). The popularity of qualitative management earningsforecasts could therefore be argued on the basis that it is a compromise for a lotof companies, between making a specific forecast (in an amount) and making noforecasts at all (Mensah et al., 1996, p. 1248).
Papers by Penman (1980), Jennings (1987) and Mensah et al. (1996) sug_gest that management's qualitative forecasts are more numerous than management's quantitative forecasts. Our study confirms this for the Netherlands; seesection 4.
We conjecture that the issue of a voluntary earnings forecast should minimizean earnings surprise when actual earnings are released. Moreover, managerswant to reduce the potential penalty resulting from high forecast errorsPotential penalties vary from one country to another and range from credibilityloss, negative impacts on share prices, adverse effects on managers' compensa_tion to legal liability resulting from large forecast errors. A rational managerwould only release a forecast if the expected benefits from the voluntary
Dow
nloa
ded
by [
Uni
vers
ity o
f L
ethb
ridg
e] a
t 06:
40 0
3 O
ctob
er 2
014
Discretionary accounting in the Netherlands 25
disclosure exceed its costs. This notion Is consistent with Brown's (1988) selfselection bias concept, which suggests that managers only release a forecast ifthey believe they can predict profit or have the abUlty to manage earningsthrough discretionary accounting techniques.
We assume that the aforementioned costs will increase with the magnitude ofthe forecast error and are higher for overestimates than for underestimates(Kasznlk, 1999). Lowering forecast errors might be achieved by discretionaryaccounting techniques and/or discretionary accruals. Contrary to Jaggl andSannella (1995), we do not restrict ourselves to the use of accounting policychanges. In our view, managers use both accounting policy changes and otherdiscretionary accounting techniques to reduce forecast errors and, in general,to manage their net actual earnings-see Healy (1985). Another differencebetween the research of Jaggi and Sane))a (1995) and our work is the fact thatthey investigated quantitative management earnings forecasts. We investigatedqualitative earnings forecasts. Other related work is from Kasznik (1999). Heinvestigated the association between quantitative management forecasts (andforecast errors) and the use of discretionary accruals to avoid forecast errorcosts. In line with Kasznik (1999) we also divided the full sample Into a subsample of overestlmators and underestimators.
Discretionary accounting techniques are used not because they are viewed asmore credible than the manipulation of discretionary accruals. Discretionaryaccounting techniques can be used to Improve forecast accuracy for thefollowing reasons. First, the existing forecast literature indicates that managershave a propensity to overpredlct in making their forecasts, resulting in negativeforecast errors (penman, 1980: Jaggi and Sanella, 1995; and Kasznik, 1999).
If discretionary accruals were used to reduce the forecast error, they wouldhave to be designed to increase reported earnings through capitalization ofexpenses or the accrual of additional revenues. However, because of auditors'conservatism and limited disclosure requirements relating to discretionaryaccruals and deferrals (in the Netherlands), managers would probably have anasymmetric ability to manage accruals significantly (With greater ablllty toreduce rather than to increase earnings). Consequently, managers may have torely on discretionary accounting techniques to improve forecast accuracy.Second, through the use of discretionary accounting techniques, managers mayachieve the objective of providing signals of their future cash flow expectations(I.e. signalling hypothesis), and at the same time Increase the company's marketvalue (and their own compensation). For example, changes in pension planassumptions can reduce pension expense, Increase reported earnings, andreduce future funding requirements (Healy and Palepu, 1990). Reduced futurefunding requirements will Increase future cash flow expectations, companymarket value (and managerial compensation). If a manager were concerned onlywith the adverse compensation effects of a forecast error and 'fooling' investors(i.e. the opportunistic behaviour hypothesis), then discretionary accrualswould be preferred because they are less visible and offer more future flexlbUltythan discretionary accounting techniques. Because of the inability to detectmost discretionary accruals, discretionary accounting techniques serve as a
Dow
nloa
ded
by [
Uni
vers
ity o
f L
ethb
ridg
e] a
t 06:
40 0
3 O
ctob
er 2
014
26 A Dorsmim et al.
better signalling mechanism (Jaggi and Sanella, 1995, p. 6-7). Third, It Is equallyplausible that discretionary accruals were used to adjust the forecast error butwere not sufficient to reduce the error to a level needed to signal InsideInformation to the market. Consequently, discretionary accounting techniqueswould also be required to reduce the forecast error to the level of accuracynecessary to signal the manager's future cash flow expectations.
There Is also another reason to use discretionary accounting techniquesInstead of discretionary accruals. This points on the reduced ability to detectmost discretionary accruals in empirical testing (Healy and Palepu, 1990). Anyproxy for discretionary accruals Is a noisy measure of discretionary accruals(Kasznlk, 1999, p. 67). Previous evidence of related studies suggests that theforecast errors are reduced by discretionary accounting changes (Jaggl andSanella, 1995). This was especially evident for the companies with negative prechange forecast errors. According to the findings of Kasznlk (1999) managersuse positive discretionary accruals to manage reported earnings (measured asoperating Income) upward when earnings would otherwise fall below management's earnings forecasts. Contrary to findings for companies whose managershave overestimated earnings, there Is no evidence that managers who haveunderestimated earnings manage reported earnings downward, or that proXiesfor litigation costs explain variation In the magnitude of their discretionaryaccruals. These managers are twice as likely to revise their forecasts as aremanagers who overestimate earnings, suggesting they may favour forecastrevision as a way to mitigate their forecasting errors (Kasznlk, 1999, p. 79-80).
Recently, Abarbanell (1999) suggested the following framework for analysingmanagement analysts' forecast errors based upon the Ideas of Healy (1985).When realized pre-managed earnings for the period are, below the managementearnings forecast, managers are assumed to have an Incentive to use reserves toInflate earnings to meet the forecast. So the forecast error wUl be reduced. In theevent that reserves are Insufficient to accomplish this goal, managers ar-eexpected to choose their next best option and take an earnings bath tomaximize reserves available for future use. This will result In an increase of theforecast error Instead of a decrease of the forecast error. If pre-managedearnings realization Is above the forecast, management will deflate earnings to areported level equal to the forecast, reserving a portion of current gOOdperformance for future use. We test the theoretical framework of Abarbanell(1999) for qualitative management earnings forecasts and discretionary accounting techniques. Abarbanell and Lehavy (1999) focused their empiricalanalysis on the association between quantitative analysts' earnings forecastsand the use of discretionary line Items and discretionary accruals. Theyconfirmed that managers attempted to reach the target set by analysts' as longas this target was within reach.
When these studies are taken Into account we expect qualitative forecasterrors to be large for companies with extreme financial performance and we alsoexpect earnings management to have negative components In these InstancesAn additional complexity in the analysis of line Item based earnings manage:ment in the Netherlands Is that the creation of accounting slack can be masked
Dow
nloa
ded
by [
Uni
vers
ity o
f L
ethb
ridg
e] a
t 06:
40 0
3 O
ctob
er 2
014
Discretionary accounting in the Netherlands 27
with the help of extraordinary gains. The net result is a negligible effect on netearnings and an Increase In slack for future periods.1
4. EMPIRICAL EVIDENCE
4.1 Hypotheses
We predict that a wish to avoid potential loss of reputation and potential legalliability provides the incentive for managers who issue an earnings forecastwhich later becomes Inaccurate to manage reported earnings towards theforecast. This prediction does not preclude other targets to manage earningssuch as bonus schemes or other implicit or explicit contracts. We assume thatmanagers benefit even from a partial reduction In forecast error. Specifically, wehypothesize that managers will make Income-increasing (decreasing) accountIng decisions when they expect earnings might fall below (above) their previously disclosed forecasts and that the magnitude of the earnings managementis Increasing In expected forecast error costs. The hypotheses. stated in alternative form, are:
HI: A manager who issues a qualitative earnings forecast in the directors'report reduces the forecast error by managing reported net earnings toward theforecasted number if he can reach the specific forecast.
H2: Aggregated discretionary items will decrease with an increase in' financialperformance.
H3: If a manager cannot reach his qualitative earnings forecast he will take anearnings bath and consequently will increase his forecast error.
4.2 Data collectionThe data used in this study are derived from annual reports of listed companies(excluding financial institutions) and from the accounting database REACH. Weused only those companies which had a listing for at least three years on theAmsterdam Stock Exchange for the period 1984 to 1994. A listing for threesuccessive years Is required because two years are needed for a propercomparison of the forecast and reported earnings. We started with the financialyear 1984 because Dutch companies from that year onwards were obliged topresent information In their directors' report with respect to the circumstancesaffecting future turnover and profitablllty.
All forecasts relate to net Income. This Is in line with the quantitative management forecast study of Jaggl and Sanella (1995) and the analysts' forecaststudy of Abarbanell and Lehavy (1999). Kasznik (1999) used managementforecasts of earnings from continuing operations in his accrual-based research.The business outlook paragraphs in the directors' reports can be divided Intofive categories with respect to earnings forecasts. These are:
I Big bath accounting In the literature often refers to taking large discretionary charges againstearnings. In this paper we allow for 'masked big baths' where the charges are offset by one-timegains. Thus, Increasing slack for future periods without shOWing a one-time loss.
Dow
nloa
ded
by [
Uni
vers
ity o
f L
ethb
ridg
e] a
t 06:
40 0
3 O
ctob
er 2
014
28 A Dorsman et at
A no forecast (251; 18%)B. only In vague wordings does management give an Impression of the future
(126; 9%)C. only an earnings forecast with respect to profit before extraordinary Items
(113; 8%)D. a qualitative forecast of earnings (867; 62%)E. a quantitative forecast of earnings (37: 3%)
Category D was used for the empirical analysis. The small number ofquantitative forecasts does not allow a comparison between categories 0 and E.The other three categories were not suitable for our research purposes. Further_more, the sample size was reduced because a particular year for a company canonly be Included If the prior year's earnings are available and comparable withthe reported figures. This means that the first year for every company was notused. Moreover, a number of companies merged or became bankrupt during theselected period. In addition, companies reporting losses In year t·l or year twere also excluded. The sample remaining consisted of 622 usable earningsforecasts. The final sample of Kasznlk (1999) was 499 management forecasts forthe years 1987-1991 and the sample of Jaggl and Sanella (1995) was 180management forecasts for the years 1979-1988.
Each business outlook paragraph In a company's report was carefully readusing the fonowlng criteria. The forecast must be a disclosure, In words, ofmanagement's expectations about the next annual earnings performance.without being specific about amounts or estimated percentage changes. Onlyannouncements that were exclusively qualitative were Included. To ensure thatan approach was used which was as unbiased and consistent as possible, wedrew upon the work of Mock (1992) who developed a scale for assessingqualitative earnings forecasts In the business outlook paragraph of the direc_tor's report of Dutch listed companies. The scale does not fully cover all theused adjectives and forms of expression, which were discovered In thedirectors' reports. Therefore, we extended the scale to facllltate the claSSifica_tion of all qualitative management forecasts.2 The resulting scale Is displayed inTable 1.
2 Mensah el al. (1996. p. 1252-1254) used a tw()-step procedure to classify qualitative managementearnings forecasts. In the first step. these authors arrived at a subjective consensus Interpretationof each statement on a five-point scale that Included the range points -2, -I. O. +1, and +2. Onthis scale a forecast was classified as -2 (+2) If a forecast was Interpreted as Implying a relatlvellarge anticIpated decline (Increase) In EPS. Forecasts classified as zero were those Interpreted ~predicting no significant change In EPS. If the level of change was not unusual or significant, It Wasclassified as relatively small change (+ 1. -I). In the second step, 13 MBA-students were asked Ina formal survey to classify a su~sample of the total sample used by Mensah el 01.. There wassignificant consistency between classification between Mensah el 01. and the 13 MBA-stUdents. Th:adjusted scale of Mock 15. In our opinion, a better and more refined scale for Interpretation Ofqualitative management earnings forecasts. It Is a 13-polnt scale Instead of a five-point scale. Thscale of Mock Is based on a careful Interpretation of Dutch adjectives according to the well-knoweDutch dictionary 'Groot Woordenboek der Nederlandse Taal' (1984). Further, the scale of Mock t1
widely used In the Netherlands by management of companies for writing their paragraph on thSbusiness outlook In the directors' report and by financial analysts for Interpretation since Its fir epublication In 1984. St
Dow
nloa
ded
by [
Uni
vers
ity o
f L
ethb
ridg
e] a
t 06:
40 0
3 O
ctob
er 2
014
Discretionary accounting in the Netherlands 29
Table 1. The adjusted Mock scale: the classification scheme for translating the qualitativemanagement earnings forecasts Into point estimatesa
o3.5
Mid-point(%)
o0-7
Increase/decreaseof the profit (%)
Equal, no deviation, same size, approximate equalFractional, slightly, small, a little bit, modest,
moderate, limited, someClearly, reasonable, sizable, satisfactory 7-12 9.5Important, large, significant 12-20 16Strong 20-30 25Considerable, substantial, appreciable 30-45 37.5Robust 45 or more 50
Description
• With the aid of 'Groot Woordenboek der Nederlandse Taal (Geerts and Heestermans, 1984) a wellknown Dutch dictionary we have grouped the different wordings to similar groups. In this process wehave adapted the Mock scale (1992). He published an overview which allowed for the translation ofadjectives Into percentages for changes In earnings forecasts by management in the business outlookparagraph of the directors' report of Dutch listed companies. This overview was published for the firsttime In 1984.
4.3 Calculation of forecast errors
Forecast accuracy Is measured by the difference between reported and proJected earnings. Data on reported earnings (N!) were obtained from annualreports. Information on projected earnings (management earnings forecasts)was extracted from directors' reports and is referred to as FORECAST. Theforecast error (F.,$RK) measure Is used to evaluate the forecast accuracy and iscalculated as:
F..£RR = NI - FORECAST
The F..£RR for all forecasts Is calculated based on net Income after tax. Fromdescriptive analysis (not included in the tables), we infer that there Is nodifference in the tendency to forecast over time nor is there a difference in theextent to which the specified discretionary Items are used by reporting entities.It can be seen In Table 2 that the order of magnitude for the earnings variablesIs about equal for the different measures. For all the earnings measures, it canalso be seen that the variable NI has the highest value. This results from theexclusion of losses in net income In the year in which the forecasts are made.The variable DA represents the aggregated discretionary accounting items. Themean of this variable has a small but positive value. Thus, the net income beforediscretionary accounting adjustment Is somewhat lower than reported Income.This finding is consistent with the use of discretionary accounting to increasereported earnings. Table 2 presents a summary of the statements for thecompanies In the final sample and their forecast disclosures. The most noticeable difference is between the reported numbers and the pre-adjustmentnumbers. The mean of the forecast error changes for the whole sample from
Dow
nloa
ded
by [
Uni
vers
ity o
f L
ethb
ridg
e] a
t 06:
40 0
3 O
ctob
er 2
014
30 A Dorsman et at
Table 2. Descriptive statistics for various measures of (forecasted) net income forecasterrors
Case Summaries
FORECAST
NUNUm1
F_ERRF~RR_PRE
DA
FORECASTNUNUm1F~RR
F~RR_PRE
DA
N Mean Median Minimum Maximum Std. Dev.
622 0.0651 0.0633 -0.0072 0.4208 0.0414
622 0.0681 0.0668 -0.2184 0.3215 0.0495622 0.0636 0.0611 0.0005 0.3737 0.0408
622 0.0030 0.0041 -0.2112 0.1401 0.0275622 -0.0019 0.0013 -0.2234 0.1133 0.0290622 0.0049 0.0000 -0.1606 0.2435 0.0205
Forecasted net IncomeNet Income In the forecasted yearNet Income In the year the forecast Is madeNet Income minus forecasted earningsNet Income before discretionary accounting minus forecastedearningsAggregated Discretionary Accounting corrected for double counts -Descriptive statistics for 622 cases over the period 1985-1994. All variables are beginning of periOd
total assets. For the variable NUm1 all negative cases have been excluded since the scale of MOCkis not suited for companies with losses
-0.0019 prior to discretionary accounting to 0.0030 after discretionary account_Ing. The change In mean shows an Increase In absolute forecast error.
4.4 Identification of discretionary accounting techniques
To obtain Information on discretionary accountlng, we consulted the annualreports of all 128 companies Issuing the 622 usable earnings forecasts over theperiod 1984 to 1994. We considered only the following categories of discretionary accounting: accounting changes, sale and lease-back transactions,provisions, pensions and other extraordinary gains and losses. These wereIdentified from the footnotes In the annual reports. Dutch accounting lawreqUires disclosure of these Items In footnotes. From Table 3 It can be seen thatthe most Important discretionary accounting areas are the extraordinary Items.This Is true both In terms of the frequency of occurrence and In the magnitudeof the amounts of extraordinary Items. Moreover, there seems to be moreextraordinary gains than extraordinary losses. In order to further examine theeffect of earnings management on forecast errors the sample was partitioned inunderestlmators and overestlmators. An underestlmator Is a company Wherethe actual net Income Is higher than the forecast net Income. Table 4 panel A.shows the results for the partitioning for the forecast error prior to the dis_cretionary accounting (F..fiRRYRE) and after discretionary accounting (F..fiRR).The grouping variable Is a binary dummy (FERR,JJMY) that Is set to 0 If theactual outcome Is below the forecast and 1 If the actual outcome Is above theforecast. Around 2/3 of the cases underestimate net Income. The actual netIncome Is higher then the forecast net Income. For the group overestlmators,
Dow
nloa
ded
by [
Uni
vers
ity o
f L
ethb
ridg
e] a
t 06:
40 0
3 O
ctob
er 2
014
Discretionary accounting in the Netherlands
Table 3. Descriptive statistics for discretionary accounting line items
31
Case Summaries
ACHGSLEASPROVEXGEXLPENSDA
ACHGSLEASPROVEXGEXLPENSDA
N Mean Median Minimum Maximum Std. Dev.
622 0.0004 0.000 -0.02370 0.05230 0.00390622 0.0004 0.000 0.00000 0.11680 0.00510622 0.0002 0.000 -0.06600 0.08200 0.00620622 0.0047 0.000 0.00000 0.24350 0.01820622 -0.0007 0.000 -0.22920 0.00000 0.01100622 0.0000 0.000 -0.01590 0.02330 0.00130622 0.0049 0.000 -0.16060 0.24350 0.02050
Net Income effect of accounting changes when quantifyableNet Income effect of sale and lease-back transactionsNet Income effect of changes In provisionsNet Income effect of extraordinary gainsNet Income effect of extraordinary lossesNet Income effect of pension holidaysDouble count corrected net Income effect of all discretionaryaccounting effects combined
Descriptive statistics for 622 cases over the period 1985-1994. All variables scaled to beginning ofperiod total assets. All discretionary accounting line items are shown as their effect on net incomescaled to beginning of the bookyear total assets. Aggregated discretionary items DA are corrected fordouble counts to avoid InclUding a discretionary Intervention more than once.
the forecast error Is reduced from -0.0225 to -0.0189. This means that due tothe use of discretionary Hne Items the estimate Is missed by a smaller amount.
This result Is in Hne with the study of Kasznlk (1999, p. 70-71) reporting thatmanagers who overestimate earnings use Income-Increasing discretionaryaccruals to mitigate their forecast errors. Jaggl and Sanella (1995, p. 14-15) alsoreport results In line with our results (and Kasznik, 1999): In the case ofoverestlmators management used discretionary accounting changes to reduceforecast errors.
For the group underestlmators (FERRJ)MY = 1) the forecast error increasesas a result of earnings management. In other words the target Is overshot by alarger degree then would be the case without discretionary accounting. Kasznlk(1999) and also Jaggl and SaneUa (1995) find no support for the prediction thatmanagers who underestimate earnings manage reported earnings downward.However, an Increase of the forecast error was not reported either by Kasznlk(1999) and Jaggl and SaneUa (1995). The overshooting result of our study couldbe caused by the qualitative (and so Imprecise) character of our Investigatedforecasts.
However, for the group that would not have met the forecast without earningsmanagement the discretionary accounting causes a larger increase in earningsthan for the group where the forecast is met. Panel B of Table 4 shows a similardivision of cases into a group of optimists where they expect net Income toincrease and a group of pessimists where they expect net Income to be lower orequal. Panel B of Table 4 shows that the change in forecast error resulting fromthe use of discretionary Une Items for the pessimists is very small. However, if
Dow
nloa
ded
by [
Uni
vers
ity o
f L
ethb
ridg
e] a
t 06:
40 0
3 O
ctob
er 2
014
Tab
le4.
For
ecas
ter
rors
for
sub-
sam
ples
CIo
)N
Pan
elA
:U
nder
estim
ator
svs
.O
vere
stim
ator
sN
Mea
nM
edia
nM
inim
umM
axi
mu
mS
td.
Dev
.
F_E
RR
_PR
EF
ER
R_
DM
Y=
O19
2-0
.02
25
-0.0
11
0-0
.223
40.
0052
0.03
32F
ER
R_
DM
Y=
143
00.
0072
0.00
56-0
.17
75
0.11
330.
0213
Tot
al62
2-0
.00
19
0.00
13-0
.22
34
0.11
330.
0290
F_E
RR
FE
RR
_D
MY
=O
192
-0.0
18
9-0
.00
69
-0.2
112
0.00
000.
0340
FE
RR
_D
MY
=1
430
0.01
280.
0082
0.00
000.
1401
0.01
64T
otal
622
0.00
300.
0041
-0.2
11
20.
1401
0.02
75
Pan
elB
:O
ptim
ists
vs.
Pes
sim
ists
NM
ean
Med
ian
Min
imum
Ma
xim
um
Std
.D
ev
F_E
RR
_PR
EO
PT
_D
MY
=0
152
-0.0
06
00.
0000
-0.2
23
40.
0699
0.03
17O
PT
_D
MY
=1
470
-0.0
00
60.
0018
-0.2
01
70.
1133
0.02
80T
otal
622
-0.0
01
90.
0013
-0.2
23
40.
1133
0.02
90
F_E
RR
OP
T_
DM
Y=
015
2-0
.00
57
0.00
12-0
.21
12
0.05
700.
0350
OP
T_
DM
Y=
147
00.
0058
0.00
48-0
.18
24
0.14
010.
0240
Tot
al62
20.
0030
0.00
41-0
.21
12
0.14
010.
0275
Pan
elC
:F
_ER
Rvs
.F
_ER
R_P
RE
Mea
nD
iff.
Std
.Dev
.t-
valu
e
Tot
al0.
0049
0.02
006.
0185
***
FE
RR
_D
MY
=0
0.00
360.
0180
2.76
66**
*F
ER
R_
DM
Y=
10.
0056
0.02
155.
3503
***
OP
T_
DM
Y=
O0.
0003
0.01
770.
1792
OP
T_
DM
Y=
10.
0065
0.02
116.
6350
***
F_E
RR
Net
inco
me
min
usfo
reca
sted
earn
ings
F_E
RR
_PR
EN
etin
com
ebe
fore
disc
retio
nary
acc
ou
ntin
gm
inu
sfo
reca
ste
dea
rnin
gsF
ER
R_D
MY
Dum
my
varia
ble
set
to0
for
over
estim
ator
s(f
orec
ast<
actu
al)
),.
OP
T_D
MY
Dum
my
varia
ble
set
to0
for
pess
imis
ts(f
orec
ast
islo
we
ro
req
ualt
hen
pri
or
year
sne
tin
com
e)0 o
Sam
ple
con
sist
so
f622
case
sfr
om
the
peri
od1
98
5-1
99
4.A
llva
riabl
ese
xce
pt
for
du
mm
ies
are
scal
edto
begi
nnin
go
fp
eri
od
tota
lass
ets.
Pan
elA
CAex
amin
esO
vere
stim
ator
sve
rsus
Und
erst
imat
ors.
Ove
rest
imat
ors
are
com
pa
nie
sth
at
have
an
eti
nco
me
tha
ttu
rns
ou
tlo
we
rth
an
the
fore
cast
.P
anel
:38
sho
ws
Op
timis
tsa
nd
Pes
sim
ists
for
diff
eren
ces
info
reca
ster
rors
.Op
timis
tsar
eco
mp
an
ies
tha
tpre
dic
tan
incr
ease
'inn
eti
nco
me
ove
rth
epr
evio
us§
year
.P
anel
Cte
sts
the
diff
eren
ces
info
reca
ster
rors
betw
een
Und
eres
timat
ors
an
dO
vere
stim
ator
sa
nd
the
diffe
renc
esin
fore
cast
erro
rsfo
rO
ptim
ists
('Tl
vers
usP
essi
mis
ts•
...i
ndic
ates
sign
ifica
nce
atp
<0.
01,
base
don
two-
taile
dte
sts.
Tes
tsfo
rdi
ffere
nces
inth
em
eans
are
base
don
t-sta
tistic
sfo
r;
cont
inuo
usva
riabl
es.
r-
Dow
nloa
ded
by [
Uni
vers
ity o
f L
ethb
ridg
e] a
t 06:
40 0
3 O
ctob
er 2
014
Discretionary accounting in the Netherlands 33.
management predicts Increases In net Income for the next period they fall shortprior to the discretionary accounting (F_ERRYRE = -0.0006) and exceed theforecast after earnings management (F..,$RR = 0.0058). In other words, the use ofdiscretionary line Items helps the optimists meet their forecast. This partition Inoptimists and pessimists was not Investigated In the related work of Kasznik(1999), Jaggl and Sanella (1995) and Abarbanell and Lehavy (1999). Panel Cshows significance tests for the differences in mean between the forecast errorprior to discretionary accounting and after discretionary accounting for the fullsample and the sub-sample for underestimators and overestlmators and thesub-sample for optimists and pessimists. As can be seen the change Is alwayssignificant except for the sub-sample of pessimists. The fact that pessimisticforecasters don't use discretionary accounting to meet the expectation In astatistically significant manner Is not surprising since they have less incentive tomeet expectations once bad news Is signalled.
As mentioned In the Introduction and the formulation of hypotheses weexpected earnings management to be more predominant In the tails of theperformance distribution since extreme financial performance changes theincentives to manage earnings. The simplest way to examine the differences isto group cases by financial performance. We created 20 groups of 31 cases withone extra case assigned to the 7th and 14th group. Figure 1 shows the separatediscretionary accounting components for the 20 groups when they are sortedfrom group 1 Oowest net Income In the year that is forecasted) to the highestgroup (20).
Figure 1 shows that. in line with the theoretical construct of Abarbanell(1999), the action Is mainly In the extremes. Group I, the lowest performing 5%
0021100 ,..--------------------------
OD1~1-11------------------------
.oooeoot--r---------------------~~
001000 +--\----------Jy.--------------_ACHG
o.oosoo ~-t-:__-_r_-~~:..--_\_--_f~r_+~------ _SlEAS
-"-PROV
1-7~~~_!~~~~~~~~!"_~?~~;;;~""'!'""'_EXGO.<nXlO I _ElCL-.-PENS
.o.D1~
All variable. are scaled 10 lagged tolai assets. ACHG. Accounting changes. SLEAS • sale and lease back transaction.PROV • changes In provisions. EXG • extraordinary gains, EXL. extraordinary losses and PENS. pension holiday.
Fig. 1. Earnings management across 5% groups of pre-managed earnings (1 = lowest).Sample consists of 622 cases from 1985-1994
Dow
nloa
ded
by [
Uni
vers
ity o
f L
ethb
ridg
e] a
t 06:
40 0
3 O
ctob
er 2
014
34 A Dorsman et al.
of the sample, displays relatively high levels of extraordinary losses, which aremasked by extraordinary gains and other discretionary accounting items. Whencases fall In the top 5% they show above average provisions. Presumably this Isdone to increase accounting slack and reduce reported net Income for theactual period. Figure 1 also shows that aggregated discretionary accountlngpartially conceals the action In the tails since items can have offsetting effects.Apart from the tails and group 9 discretionary accounting seems to be evenlydistributed across the performance spectrum. Group 9 displays a spike Inextraordinary items resulting from one single company in two subsequentreporting periods. The company Begemann reported an extraordinary gain of24% of total assets In 1988 and an extraordinary gain of 12% of total assets in theyear 1989. Begemann later lost credibility from financial market participants andhas become a textbook example of creative accounting. Figure 2 displays theaggregated discretionary accounting variable and the forecast errors.
Discretionary accounting Is most net income Increasing when aggregated forthe lowest pre-managed net Income and (even) negative for the highest premanaged net income. Forecast errors are negative for the low performinggroups. This means that when pre-managed earnings are low they don't meettheir forecast target.
Forecast errors are positive when they are in the higher pre-managed netIncome groups. When they are doing well they outperform their forecast. Theforecast error after discretionary accounting Is generally cioser to 0 than priOrto earnings management. To further analyse the graphical results from Figure 2the sample Is partitioned in the tails versus the middle of the distribution of th~
0.030
0020
0.0'0
0000
.0.010
.0.020
.0.030
.0.040
.0000
-0.000
-0.070
".~.
\,
A • /-
~~~,~ , .... ...•. ,,~ ", .'.., .",' .......- ,, .., ,{ ' .. /10 -- ;~ ' ... • T • 11 12 13 1. lS 11 17 18 18
,f' ....:_,, ' .. ,"
~ .:,: ,:!:,
, ,; ,-;,,I
-.-f_ERR_PRE..... "_ERR
--.OA
All cases are scaled to lagged total assets. F_ERRJ'RE Is a forecast error prior to discretionary accounting.F....ERR • forecast error for net Income and DA Is aggregated discretionary accounting,
Fig. 2. Forecast error and discretionary accounting across 5% groups of pre-managedearnings. Sample consists of 622 cases from 1985-1994
Dow
nloa
ded
by [
Uni
vers
ity o
f L
ethb
ridg
e] a
t 06:
40 0
3 O
ctob
er 2
014
Discretionary accounting in the Netherlands
Table 5. Partitioning the sample to exclude tails of performance
35
Panel A: tails 50%
ABSFER MeanStd. Dev.
ABSFERPR
Panel B: tails 20%
MeanStd. Dev.
MeanStd. Dev.
Tail Centre Total
0.0193 0.0109 0.01470.0306 0.0144 0.0234
0.0211 0.0116 0.01590.031 0.016 0.0244
0.0073 0.0063 0.00680.0201 0.0199 0.0200
Tail Centre Total
t-value
4.1796*-
4.6674***
0.6221
t-value
ABSFER Mean 0.0269 0.0116Std. Dev. 0.0408 0.0151
0.01470.0234
4.1173***
ABSFERPR Mean 0.0300 0.0124Std. Dev. 0.405 0.0166
Mean 0.0119 0.0055Std. Dev. 0.0277 0.0174
0.01590.0244
0.00680.0200
4.7456***
2.4613**
ABSFERABSFERPR
ABS_DAtails 50%
tails 20%
Absolute value of forecast error of net IncomeAbsolute value of forecast error of income prior to discretionaryaccountingAggregated discretionary accountingDummy variable partitioning the sample in the centre and tail 50% ofpre-adjusted net incomeDummy variable partitioning the sample in the centre 80% and tail20% of pre-adjusted net income .
Sample consists of 622 cases from the period 1985-1994. All variables except for dummies arescaled to beginning of period total assets. Panel A displays the data after partitioning the sample inthe middle 50% (centre) and outer 50% (tail) of pre-adjusted net income. For the three variablesABSFER, ABSFERPR and ABS_DA the means and standard deviations are shown for the two groupsand the full sample. Panel B shows the mean and standard deviation for the middle 80% (centre) andouter 20% (tail) and the full sample. ** and *** indicate significance at p < 0.05 and p < 0.01respectively, based on two-tailed tests. Tests for differences In the means are based on t-statistics forcontinuous variables.
pre-managed net Income. Since the magnitude rather then the sign of the erroris of interest here the absolute values of the forecast error (ABSFER) and theabsolute forecast error prIor to dIscretionary accounting (ABSFERPR) are used.Table 5 shows the results.
Panel A displays the partitioning for the centre 50% and the outside 50% (0 Isthe outer 50%). In the inner 50% the mean forecast error Is 0.0109 and in theouter 50% this Is almost double with a value of 0.0193. The forecast errorsbefore and after earnings management are significantly higher In the talls then Inthe centre with t-values of 4.6674 and 4.1796 respectively.
When the cut-off Is moved from the outer 25% on both sides to the outer 10%the difference becomes even more pronounced. The error more then doublesfrom 0.0116 to 0.0269. Discretionary accounting succeeds In reducing the
Dow
nloa
ded
by [
Uni
vers
ity o
f L
ethb
ridg
e] a
t 06:
40 0
3 O
ctob
er 2
014
36 A Dorsman et at.
forecast error In the tails and the middle part of the full sample. Again thedifferences In forecast error are significant. The difference In the absolute valueof the discretionary accounting (ABS..DA) Is significant as well with a I-value of2.4613. This Indicates that discretionary accounting Is used more often forcompanies In the tails. An Important Implication from the results presented hereand Abarbanell (1999) Is that means are shown to be not descriptive for forecastaccuracy since the errors are not normally distributed.
4.5 Summary of the resultsWe set out to examine the link between earnings management and forecasterrors. To examine this link we assumed that the effect would not be continuousacross levels of pre·managed performance. Prior research by Healy (1985) andAbarbanell (1999) has shown that It Is unlikely that incentives are constantacross the performance spectrum. Using a Mock scale to compute qualltatlveforecasts by management and several discretionary line Items as a proxy fordiscretionary accounting, the relationship between forecast errors and dis_cretionary accounting was examined.
Support was found for the first hypothesis that managers that Issue aqualitative forecast reduce their forecast error when they can attain the forecasttarget. For the total sample, It was shown that the forecast error decreases afterthe addition of discretionary accounting In the annual report.
Substantial differences between underestlmators and overestlmators as Wellas optimists and pessimists were found. The forecast error Is reduced for thesub-sample overestlmators. This Is In line with the results of Kasznlk (1999) andJaggl and Sanella (1995). For the sub-sample underestlmators the forecast errorIncreases as a result of discretionary accounting. The overshooting result of thisstudy could be caused by the qualltative (and so Imprecise) character of theInvestigated forecasts.
A similar division was made of the full sample Into optimistic managementand pessimistic management. The use of discretionary line Items helps theoptimists meeting their forecast. This was not the case for pessimists.
Our second hypotheses expected an Inverse relation between financial performance and positive discretionary act:;0untlng adjustments. The results sup..port this hypothesis.
The third hypothesis formulated was that when the target for the earningsbecomes unreachable the manager would take a bath. Findings here are mOrecomplex then hypothesized. There Is a strong Increase In the occurrence ofnegative adjustments when financial performance Is low. However, offsettingeffects of positive discretionary items are found that are larger then the negativediscretionary Items. The companies camouflage their baths. As a result of thiscombination of discretionary actions they both Increase their slack for futureperiods and avoid decreasing the reported earnings even further. Looking at theaggregated effect of discretionary Items does not tell the whole story. To furtherexamine the differences a graphical analysis of the discretionary accountingItems across the performance spectrum was shown. We sorted the full sampleInto 20 groups from lowest to highest net Income In the forecast year. In linewith the theoretical construct of Abarbanell (1999) the action Is mainly In the
Dow
nloa
ded
by [
Uni
vers
ity o
f L
ethb
ridg
e] a
t 06:
40 0
3 O
ctob
er 2
014
Discretionary accounting in the Netherlands 37
extremes. The lowest performing group displays high levels of extraordinarylosses masked by extraordinary gains and other extraordinary Items. Thehighest group shows above average provisions. Presumably this is done toIncrease accounting slack and reduce reported net income for the actual period.In general, it could be seen that the outer regions showed substantially morediscretionary activity. When the aggregated discretionary Items and forecasterrors were shown It became clear that activity In the discretionary accountingvariable occurs simultaneously with the presence of forecast errors. Finally, theresults were truncated to examine the effect of the forecast errors In the tails onthe accuracy of the forecast. The deletion of the tails of the performancespectrum showed a remarkable Increase In forecasting precision.
5. SUMMARY AND DISCUSSION
Many earnings forecast studies have been conducted for Anglo-Saxon countries,but to date very few have focused on continental Europe. This study hasexamined the association between discretionary accounting as measured byaggregating specific line Items and the accuracy of long-run qualitative forecastsof annual earnings voluntarily disclosed by managers in the directors' reports Inthe Netherlands.
The full sample was partitioned Into overestlmators and underestlmators toexamine the effect of discretionary accounting on forecast errors. The forecasterror Is reduced for the sub-sample overestlmators. For the sub-sample underestimators the forecast error Increases as a result of discretionary accounting.
A similar division of the full sample was made into optimistic managementand pessimistic management. The use of discretionary line Items helps theoptimists meeting their forecast. This was not the case for pessimists. Further,the full sample was sorted Into 20 groups from lowest to highest net Income Inthe forecast year. The action Is mainly In the extremes. The lowest performinggroup displays high levels of extraordinary losses masked by extraordinarygains and other extraordinary Items. The highest group shows above averageprovisions. Presumably this is done to Increase accounting slack and reducereported net income for the actual period.
These empirical results are a confirmation of the theoretical framework ofAbarbanell (1999). If realized pre-managed earnings are below the qualitativemanagement earnings, forecast managers use discretionary accounting techniques to Inflate earnings and reduce the forecast error If they can reach theforecast. In the event that discretionary accounting techniques are insufficientto accomplish this goal, managers take an earnings bath In order to maxfmlzereserves available for future use. Companies deflate their reported earnings to alevel equal to their qualitative earnings forecast and reduce the forecast error,reserving a portion of current good performance for future use. We argue thatthis is an Indication that the underlying phenomenon of target-based Incentivesto manage earnings results in non-eontinuous behaviour and consequently Innon-conUnuous occurrences of forecast errors and discretionary accounting. Animportant Implication from the results presented here and Abarbanell (1999) Is
Dow
nloa
ded
by [
Uni
vers
ity o
f L
ethb
ridg
e] a
t 06:
40 0
3 O
ctob
er 2
014
38 A Dorsman et at.
that means are shown to be not descriptive of forecast accuracy since the errorsare not normally distributed.
Despite the fact that our results are to a large extent In line with expectationswe cannot rule out measurement error. The use of the Mock scale to Inferproperties of management forecasts and their relatlon to discretionary accountIng techniques Introduces a Joint hypothesis problem. Results could be due toeither the properties of the measurement Instrument or the actual behaviour.
this study cannot be Interpreted to Indicate that the accuracy of all forecastsIs affected by the discretionary accounting techniques Investigated. The reSUltsdo, however, suggest that some discretionary accounting Is associated withmanagement's desire to Improve the accuracy of their forecasts.
These findings are suggestive of managers releasing voluntary forecasts Whenthey are able to control reported earnings through discretionary accountingtechniques. This provides some empirical support for Brown's (1988) argumentthat the release of a management forecast reflects the self-selection bias of theforecaster, Influenced by management's ability to control events that Impactreported earnings and affect the magnitude of the forecast error. A possiblelimitation of our study Is that we excluded company years with losses from thesample. Of course, the results are country-specific and time-specific. Oneshould, therefore, be cautious In generalizing the results to all managementforecasts and all discretionary accounting techniques.
ACKNOWLEDGEMENTSWe would like to thank Jeff Abarbanell, A. Buckley, M.N. Hoogendoorn, theparticipants of the 'finbel dag' congress Erasmus University Rotterdam, 1997the participants of the European Financial Management Association (Istanbul'1997) and especially R. Crespi, the discussant, the participants of the Easter~Finance Association (Wllllamsburg, 1998) and especially H. Saraoglu, thediscussant, and M. Kemper and A. Bon for helping with the data collection.
REFERENCESAbarbanell, J. (1999) Framework for analyzing earnings management:lmpllcatlons for
stock prices and analysts forecast errors. Working Paper, UNC.Abarbanell, J. and Lehavy, R. (1999) Can stock recommendations predict earningS
management and analysts' earnings forecast errors. Working Paper, UNC.Botosan, C.A. (1997) Disclosure levels and cost of equity capital, The Accounting ReView
72 (3), 323-49. 'Brown, L.O. (1988) Comparing Judgmental to extrapolative forecasts: It's time to ask Why
and when, International Journal of Forecasting, 171-3.Capstaff, l., Paudyal, K. and Rees, W. (1996) A comparatlve analysis of earnings In
Europe. Working Paper 96/1, Department of Accounting & Finance, UnIversIty ofGlasgow.
Council for Annual Reporting (2000) Guidelines for Annual Reporting in the Netherlandfrom 1990. Oeventer: Kluwer Bedrljfswetenschappen. S
Oorsman, A.B., van Dljk, H.LL and de Ruiter, AJ.C. (1999) An emplrlcallnvestlgatlon ofthe relevance of investor relations, Investment Analysts Journal, 50, 47-53.
Dutch Accounting Law (Burgerlljk Wetboek, Boek 2, Utel 9).
Dow
nloa
ded
by [
Uni
vers
ity o
f L
ethb
ridg
e] a
t 06:
40 0
3 O
ctob
er 2
014
Discretionary accounting in the Netherlands 39
Foster, G. (1973) Stock market reaction to estimates of earnings per share by companyofficials, Journal of Accounting Research, Spring, 25-37.
Frankel, R., McNichols, M. and Wilson, G.P. (1995) Discretionary disclosure and externalfinancing, The Accounting Review, 61, 135-50.
Geerts, G. and Heestermans, H. (1984) Groot woordenboek der Nederlandse taal, 11thedition. Utrecht: Van Dale.
Hoogendoorn, M.N. (1990) Stelselwijzigingen in de jaarrekening. Gronlngen: Wolters-Noordhoff.
Healy, P. M. (1985) The effect of bonus schemes on accounting decisions, Journal ofAccounting and Economics, 73-109.
Healy, P. and K.G. Palepu (1990) Effectiveness of accounting-based dividend covenants,Journal of Accounting and Economics, 97-123. .
Healy, P., Hutton, A. and Palepu, K. (1998) Stock performance and Intermediationchanges surrounding sustained Increases In disclosure. Working Paper, HarvardBusiness School.
Jaggl, B. and Sannella, A. (1995) The association between the accuracy of managementearnings forecasts and discretionary accounting changes, Journal of Accounting,Auditing & Finance, 1-21.
Jennings, R. (1987) Unsystematic security price movements, management earningsforecasts, and revisions In consensus analyst earnings forecasts, Journal ofAccounting Research, 25, 90-110.
Kasznlk, R. (1999) On the association between voluntary disclosure and earningsmanagement, Journal of Accounting Research, 37 (1), 57-81.
Kasznlk, R. and Lev, B. (1995) To warn or not to warn: management disclosures in theface of an earnings surprise, The Accounting Review, 113-34.
King, R., Pownall, G. and Waymire, G. (1990) Expectations adjustment via timelymanagement forecasts: Review, synthesis, and suggestions for future research, Journal of
Accounting Litemture, 9, 113-44.Lev, B. and Penman, S. (1988) Voluntary forecast disclosure, nondisclosure and stock
prices. Working paper, University of California, Berkeley.Levy, N. (1995) No one can predict the future, but Investors want forecasts. Een analyse
van de wlnstprognose In Jaarverslagen van Nederlandse beursgenoteerde ondernemlngen, VBA Journaal, 11 (4), 2-6.
Meer, R.A.H. van der (1981) Enige beschouwingen omtrent prognoses in hetjaarverslag ende certificeerbaarheid daarvan, Lelden, Stenfert Kroese.
Mensah, M.O., Nguyen. H.V. and Ryan. H.A. (1996) An empIrical analysis of qualitativemanagement forecasts, Journal of Business Finance & Accounting, 23 (9) & (10),December, 1245-65.
Mock, H. (1992) FinancUUe public relations/investor relations. Deventer: Kluwer BedrlJfswetenschappen.
Nobes, C. and R. Parker (2000) Comparative International Accounting. Harlow: FinancialTimes/Prentice Hall
Penman, S.H. (1980) An Empirical Investigation of the Voluntary Disclosure of CorporateEarnings Forecasts, Journal of Accounting Research, Spring, 132-60.
REACH-financial database ofDutch companies (1996). Brussel/Den Haag: Bureau Van DijkfDelwel UltgeverlJ.
Ruland, w., Tung, S. and N.E. George (1990) Factors associated with the Disclosure ofmanagers' forecasts, The Accounting Review, 710-21.
Skinner, D. (1994) Why firms voluntarily disclose bad news, Journal of AccountingResearch, 32, Spring, 38-60.
Dow
nloa
ded
by [
Uni
vers
ity o
f L
ethb
ridg
e] a
t 06:
40 0
3 O
ctob
er 2
014
40 A Dorsman et at.
Stolwerk, R.A.P.F., H.F.D. Hasslnk and G.M.H. Mertens (1997) Wlnstprognoses vanNederlandse beursgenoteerde ondernemlngen, Tijdschrift voor Bedrijfsadministratie.101,54-60.
Trueman, B. (1986) Why do managers voluntarily release earnings forecasts?, Journal ofAccounting and Economics, 8, 53-71.
Overboom, C.P.M. and R.G.A. Vergoossen (1997) Voorzlenlngen en Jaarrekenlngbeleld.Maandblad voor Accountancy en Bedrijfseconomie, 71 (6),405-416.
Waymire, G. (1986) Additional Evidence on the Accuracy of Analyst Forecasts Before andAfter Voluntary Management Earnings Forecasts, The Accounting Review, 129-141.
Dow
nloa
ded
by [
Uni
vers
ity o
f L
ethb
ridg
e] a
t 06:
40 0
3 O
ctob
er 2
014
