Capalbo_et Al_Accrual Based EM in State Owned Enterprise

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Accrual-based earningsmanagement in state

owned companiesImplications for transnational

accounting regulationFrancesco Capalbo

Seconda Università di Napoli, Naples, Italy

Alex Frino and Vito Mollica Macquarie Graduate School of Management, North Ryde, Australia, and

Riccardo Palumbo

Università “G. d’Annunzio”

di Chieti-Pescara, Pescara, Italy

Abstract

Purpose – Opposition to transnational calls for the adoption of accrual-based accounting in thepublic sector may stem from arguments that it is associated with poor earnings quality. The purposeof this paper is to determine whether state owned enterprises (SOEs) operating under accrual-basedaccounting manage their earnings, whether it is more prevalent vis-à -vis privately owned enterprises(POEs) and the conditions under which it is more likely to occur.Design/methodology/approach – This paper measures earnings management for a large sampleof unlisted Italian SOEs and POEs using a framework developed by Stubben (2010). The authors useregression analysis to estimate the variables which predict abnormal accruals including firm size,leverage and profitability.Findings – The authors find no evidence that the level of state ownership (SO) is positively correlated

with accrual-based earnings management. The authors also provide evidence that earningsmanagement by SOEs decreases with firm size and increases with profitability.Research limitations/implications – While the study is the first to examine earnings managementin a public sector accrual accounting environment for a sample of European firms, namely Italianfirms, the authors call for more research into this issue examining public entities in other EuropeanUnion (EU) member states or public entities other than SOEs.Practical implications – The EU recently introduced a new transnational accounting directive inwhich it prescribes the preparation of financial statements based on accrual accounting for allEuropean public sector entities, arguing that it reduces the window dressing that is allowed by cashaccounting. Since Italian SOEs already prepare their accounts on an accruals-basis, by analysing theiraccounting behaviour the authors are able to determine the variables which predict when earningmanagement is more likely to occur in a public sector accrual accounting environment, and thereforethe authors provide guidance which may be useful in shaping the transition process from cashaccounting to accrual accounting by identifying the types of entities whose accounts should be subjectto greater regulatory scrutiny. A better understanding of the relation between SO and earningsmanagement will provide insight into public sector corporate governance and aid in the acceptance of transnational regulation that would otherwise significantly alter current accounting practices andpossibly be opposed at a national level.

The current issue and full text archive of this journal is available at

www.emeraldinsight.com/0951-3574.htm

Accounting, Auditing &

Accountability Journal

Vol. 27 No. 6, 2014

pp. 1026-1040

r Emerald Group Publishing Limited

0951-3574

DOI 10.1108/AAAJ-06-2014-1744

The authors would like to thank seminar participants at the Macquarie Graduate School of Management, University of New England, Università Ca’ Foscari and Capital MarketsCooperative Research Centre, as well as a number of colleagues for useful comments.

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Originality/value – Earnings management in a public sector accrual accounting environment hadbeen analysed only for Chinese listed companies. The authors extend previous analysis to a sample of European (Italian) SOEs which are unlisted. The authors also extend previous work by determiningthe characteristics of firms which manage their earnings.

Keywords Earnings management, Italy, State owned enterprises,Transnational public sector accounting, Unlisted entities

Paper type Research paper

1. IntroductionThe globalisation of financial markets has challenged state based accountingregulators (Suddaby et al., 2009). In order to provide the market with timely, reliableand comparable financial information the European Union (EU) achieved transnationalharmonisation of private sector accounting through regulation 1606/2002 mandatingthe use of IAS/IFRS for all European listed companies. The EU recently releaseda directive in which it advocates the need for a similar transnational harmonisationof national government accounting standards. A key issue of that regulation is the

preparation of accruals-based financial statements for all European public sectorentities (European Council Directive, 2011/85). The transition to accruals-basedaccounting in the public sector has long been one of the main proposals of the socalled New Public Management Reform (NPMR) (Pallot, 1992). However, given theprominence of cash accounting in the sector (Jones et al., 2013) and views by publicsector accounting scholars that accrual-based accounting increases the scope formanipulation (Barton, 2004; Connolly and Hyndman, 2006), the benefits the EuropeanCommission expects from the transnational directive may be opposed given thesignificant impact on current practice and a conceivable deterioration in the qualityof financial reporting.

The European Commission believes a transition from cash to accruals-basedaccounting is necessary to “avoid some of the window-dressing that is allowed by cash

accounting, where a payment can be brought forward or postponed so as to berecorded in the period that the government chooses” (European Commission, 2013,Section 3). The adoption of an accrual-based accounting system implies that cashflow dates will cease to influence the allocation of revenues and expenses. However, theCommission’s view that accruals-based accounting will result in a general reductionin window dressing contradicts the evidence in previous accounting literature whichargues that it provides for greater subjectivity (Sloan, 1996; Xie, 2001), increasesmanagerial discretion and hence the opportunity to manage earnings (Healy andWahlen, 1999). Consequently guidance on whether the transnational processadvocated by the EU is associated with adverse effects and how the EU can bestmonitor or identify firms acting opportunistically from such changes is critical. Weexamine a sample of state owned enterprises (SOEs) in Italy that already use

accruals-based accounting to gauge whether earnings management is a problemfor a sample of European SOEs as mandated by the EU.

Previous literature theorises and provides empirical evidence which supports theexistence of a direct relationship between corporate governance and state ownership(SO) (Alchian and Demsetz, 1972; Shleifer and Vishny, 1997) and corporate governanceand earnings management (Dempsey et al., 1993, Beatty et al., 2002). Despite thesefindings and the significant number of SOEs operating in many countries and theirimpact on GDP (Goldeng et al., 2008; Christiansen, 2011)[1], the accounting literaturehas paid little attention to the impact that SO may have on earnings management

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(Wang and Yung, 2011). It is as if state owned companies fall within a twilight zonebetween the public and private sector (Collin et al., 2009), such that whether they aremore or less likely to manage their earnings, or the conditions under which theyare more likely to do so, remains an unresolved issue. Against this backdrop we

investigate the impact of SO on earnings management for 5,349 Italian unlistedcompanies. We also examine a number of variables which can predict earningsmanagement in entities with a significant level of SO.

There are a number of motivations for carrying out this research. Previous studiesthat have addressed a similar issue focus on Chinese companies and the authorsacknowledge the impact of country-specific factors on their conflicting results. Wangand Yung (2011) and Ding et al. (2007) find Chinese SOEs manage earnings lessvis-à-vis privately owned firms; conversely Aharony et al. (2000), Chen and Yuan (2004),and Liu and Lu (2007) find Chinese SOEs manage earnings more vis-à -visprivately owned firms. Aharony et al. (2000) believe their findings are affected bythe protective behaviour of the Chinese Government and by the peculiar circumstancessurrounding initial public offerings undertaken by SOEs. Ding et al. (2007) believe

their results reflect the specificity of Chinese capital markets, where privately ownedfirms are in a relatively weaker position because of political and historical factors.Moreover, Wang and Yung (2011) identify the intensive monitoring of managerialopportunism by the Chinese Government, while Liu and Lu (2007) highlight howearnings management is affected by the regulatory system in which the ChinaSecurities Regulatory Commission and other related authorities rely on accountinginformation to decide whether to de-list a public firm (Pistor and Xu, 2005).

Previous research has also provided evidence that “listing” is related to earningsmanagement (Penno and Simon, 1986; Beatty et al., 2002; Burgstahler et al., 2006;Givoly et al., 2010). Consequently the results of the only existing research on the impactof SO on earnings management, which only examines listed entities, cannot begeneralised to unlisted companies. OECD data demonstrates that SO is much more

common in unlisted than listed companies (Christiansen, 2011)[2]. Consistent withthis proposition, Wang and Yung (2011) call for further research addressing the topicof earnings management by SEOs in different economies and using “smallerstate-owned firms that are not publicly traded to determine the generalizability of theresults” (p. 810).

This study contributes to the extant literature in several other ways. First it detailsthe extent that managers of European public sector entities could make of thediscretion embedded in accruals-based accounting and its consequences onthe reliability of their financial reports, so to assist the EU in advocating andshaping the transnational change from cash accounting to accrual-based accounting.Second, it fills a gap in the literature by extending previous work on the effect of SOon earnings management to companies: outside China and unlisted entities. In doing

so, it responds to the call for such research by Wang and Yung (2011). Third, it shedslight on the reliability of comparisons between state and privately owned companiesaccounting data. These kinds of comparisons are widely used in assessing the impactof SO on corporate performance (Boardman and Vining, 1989; Dewenter andMalatesta, 2001). Fourth, we examine a number of variables which can explain thepropensity to manage earnings for unlisted public and privately owned enterprises(POEs), these include firm size, leverage and profitability. Previous literature hasidentified that the size of a firm may be related to its propensity to manage earnings.For example, Warfield et al. (1995) argue that executives of larger more politically

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sensitive firms are more likely to reduce political costs by managing their earnings.Sweeney (1994) also identified that a firm’s leverage may be related to its tendency tomanage earnings because the closer the firm is to breaching its debt covenants, themore likely it is to manage its earnings so as to avoid such a scenario. Finally,

Burgstahler and Dichev (1997) have identified that the profitability of a firm may berelated to its propensity to manage earnings because managers of profitable firms havea higher propensity to manipulate earnings to avoid losses. In this paper, we examinewhether these variables explain earnings management for a large sample of unlistedItalian state and POEs operating in an accrual-based accounting environment. Theresults of this analysis are important given the EUs recent and new transnationalregulation which advocates the preparation of accrual-based accounting financialstatements for all European public sector entities.

The findings of previous literature offer a number of reasons to expect that SOmight be positively related to earnings management in an accrual-based accountingenvironment, consequently arguing against the adoption of the European directive.These include: first, Shleifer (1998) who identifies that SO is likely to be associated

with poorer corporate governance; second, Warfield et al. (1995) who identify thatmanagerial ownership can reduce earnings management (in state owned companiesmanagerial ownership opportunities are limited); third, Laswad et al. (2005) whoidentify that politicians may put pressure on managers preparing financial statementsto manage their earnings; fourth, Jones (1991) who argues that earnings managementis more likely when there are a limited number of winners and a greater numberof losers that will share the cost (as is the case in public entities); and fifth, Koh (2003)and Rajgopai et al. (1997) who identify a negative relation between earningsmanagement and the level of financial skill of the shareholders that managers reportto (in most cases users of public sector entity financial statements are unsophisticatedand unfamiliar with accrual accounting).

In contrast, there are reasons to expect SO is negatively related to earnings

management including: first, SO increases the number of people and institutionsthat might have a legitimate interest in a company’s accounts and so it increases therisk of being detected (Burgstahler and Dichev, 1997); second, in state owned entities,the appointment of managers might be linked more to political connections than tofinancial results and this might reduce incentives to manage earnings to producefavourable results (Cristofoli et al., 2010); and third, the consequences of tamperingwith data for a public owned enterprise maybe more serious vis-à-vis POEs[3]. Giventhe conflicting predictions in relation to the impact of SO on earnings management, itremains an empirical issue as to whether SO is positively or negatively related toearnings management.

2. Institutional backgroundA survey published by the Italian Government (2013) reports that the number of companies owned (directly or indirectly) by an Italian public authority is 7,340, of which 349 were held by the central government or its agencies. In the last few decades,most Italian local governments, as well as the central government itself, have set uplimited liability companies, or acquired shares in them to operate the public servicesthat they are expected to provide local citizens, such as water supply, transportation,and garbage collection, amongst other services. Art 35 of Law 448/2001 mandated thatpublic authorities providing such services transform their legal form into corporations.In some cases private entities participate in ownership of these corporations but in

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companies that do not have a complete set of financial statements or considered asnon-operating (i.e. revenues oh100) which leaves a sample of 9,454. We then deletefrom our sample firms which have missing data for the period 2009 to 2012, leaving5,349 firms. The AIDA database permits the categorising of companies on the basis of

shareholder types. Specifically, it allows identification of companies owned by “states,governmental agencies, governmental departments, or local authorities”[6] (hereinaftersimply referred to as the “state”) either directly or through their associates or theassociates of their associates. Following previous literature we use the percentageof shares owned by public entities as a proxy for SO (Prowse, 1992) and define firmswith o30 per cent of shares held by the state as POEs (see Wang and Yung, 2011).A total of 3,892 POEs and 1,457 firms with more than 30 per cent of shares held by thestate are identified (i.e. SOEs).

In order to measure the extent of earnings management in our sample of firms werely on the work of Stubben (2010) who develops a model of changes in accountsreceivable to measure earnings management through revenue instead of earnings. Themain explanatory variable in the “conditional revenue model” developed by Stubben

(2010) to detect earnings management is total revenues. Other explanatory variablesare those which may explain the receivables policy of a firm including its financialstrength (proxied by size), stage in the business cycle (proxied by age) and operationalperformance (proxied by revenue growth rate and gross margin). The model can beused to estimate expected receivables and therefore unexpected or abnormal accountsreceivable, this being Stubben’s (2010) proxy for earnings management. Stubben(2010) provides evidence that this model is less biased and better specified than othercommonly used models based on aggregate accruals models, namely the Jones model(Jones, 1991), modified Jones model (Dechow et al., 1995) and the Dechow and Dichevmodel (Dechow and Dichev, 2002) to detect earnings management. The modeldeveloped by Stubben (2010) also has the added advantage in that is does not requirecash flow statement information, which our sample of firms are not required to

prepare, avoiding the use of proxies which may reduce the reliability of our results.We estimate for each industry category and year the Stubben (2010) conditional

revenue model of accounts receivable as follows:

D AR it ¼ aþ b1D R it þ b2D R it SIZE it

þ b3D R it AGE it þ b4D R it AGE SQ it þ b5D R it GRR pit þ b6D R it GRR N it þ b7D R it GRM it þ b8D R it GRM SQ it þ eit

ð1Þ

where D is the annual change; AR the accounts receivable (item C.II. in balance sheet inAIDA); R the total revenue (Item A.1. in profit and loss in AIDA plus Item A.5 in AIDA);

SIZE the the logarithm of total assets (totale attivo in AIDA); AGE the logarithm of the number of years since formation of the firm (anno di costituzione in AIDA); GRR P the industry median-adjusted change in revenues ( R ) multiplied by a dummy variablewhich is equal to 1 if the industry median-adjusted change in revenues in year t forfirm I40, otherwise 0; GRR N the industry median-adjusted change in revenues ( R )multiplied by a dummy variable which is equal to 1 if the industry median-adjustedchange in revenues in year t for firm i o0, otherwise 0; GRM the industrymedian-adjusted gross margin for firm; and AGE SQ and GRM SQ is the square of thevariables AGE and GRM , respectively[7].

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Following Stubben (2010) we estimate Equation (1) after deflating all revenue andaccrual variables by SIZE . We winsorize at 5 per cent each model input variable andeliminate sub-industries with fewer than ten firms[8]. We estimate hetroscedasticity-consistent standard errors as per White (1980) and use Fama and Macbeth (1973)

t -statistics to test whether the coefficients are statistically significant acrossestimates.

The absolute value of the residuals from the conditional earnings model aboveprovides an estimate of abnormal accounts receivable or discretionary accruals (whichwe label DAit ), the variable of primary interest in this study and proxy for earningsmanagement. We next utilise an approach similar to Wang and Yung (2011), andregress the absolute value of DAit against the proportion of issued shares owned by thestate (SO), as well as a number of control variables representing the size of the firm, itscapital structure and profitability[9]. The specific model that we estimate is as followsfor each industry-year:

j DAit j ¼ l0 þ l1SO it þ l2SIZE it þ l3 LEV it

þ l4 ROAit þ l5 NOI it þ eit ð2Þ

where all variables are as described above, and: SO is the the percentage of stateownership; LEV the debt/equity ratio; ROA the return on assets or redditività del totaleattivo; and NOI the non-operating income to sales[10].

We also estimate Equation (2) above separately for SOEs and POEs. FollowingWang and Yung (2011) we estimate the above model for each industry and year[11].

4. ResultsTable I provides descriptive statistics for each of the variables in Equations (1) and (2)for 5,349 firms, across three years of data and 16,047 observations. Panel A describes

data for all firm-years sampled, Panel B describes data for POEs ( o30 per cent of the firm’s shares owned by the state) while Panel C describes those firms with morethan 30 per cent of shares owned by the state (SOEs).

Panel A of Table I documents that the average change in accounts receivable andrevenue across all sampled firm-years (as a portion of total assets) is approximately3 and 5 per cent, respectively. This compares to 1 and 9 per cent, respectively, reportedby Stubben (2010) for his sample of US firms. Panels B and C report that SOEsexperienced significantly lower growth rates than POEs, reflecting perhaps a strongerimpact of the 2007-2009 financial crisis on SOEs relative to privately owned firms.Furthermore, the average (median) size of companies examined was h69.4 million( h3.6 million), with the mean and median size of state owned firms being slightly largerthan privately owned firms. The difference between the mean and median size reflects

the fact that there are a very small number of extremely large firms in the sample. Theaverage age of sampled firms is 15.7 years, and the gross margin is 1.4 per cent acrossall firms. Note, however, that the average margin is negative for state owned firmsand positive for privately owned firms. The ROA is 3.3 per cent across the entiresample, whereas the ROA of SOEs is substantially lower than that of privately ownedfirms. This again, seems to suggest that the global financial crisis in Italy hit publicentities stronger that it did privately owned entities. Finally, the median of the debtto equity ratio of all firms iso 2 per cent reflecting the very low reliance placed on debtby these companies.

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Table II documents the distribution of parameter estimates for Stubben’s (2010)conditional revenue model of accounts receivable. The coefficients across results onD R , on average, are positive and in aggregate are significant at the 0.01 level.Furthermore, the average coefficient across firms is 0.30 implying that, on average, 30per cent of non-discretionary revenues remain uncollected at year end for Italian firms.This is significantly higher than the US sample examined by Stubben (2010) whoreports a coefficient of 0.19. This is consistent with reports of a higher collection rateamongst US firms when compared with European firms (Ernst & Young, 2013). Thisis particularly true of Italian enterprises operating in public services, since most of

their revenues have to be collected from the public administrator which has beenshown to settle accounts, on average, after 185 days compared to a European averageof 65 days (Research Office of Mestre Chamber of Commerce, 2013). Table II alsodemonstrates that few of the other variables are significant in explaining the variationin accounts receivable, in contrast to Stubben (2010).

Table III documents the magnitude of earnings management in privately ownedand state owned firms using the absolute value of the residuals from the conditionalrevenue model for accounts receivable. Across all firms, the discretionary accrualsrepresent approximately 8.9 per cent of total assets. The absolute value of

DAR

(proportion of

total assets)

DR

(proportion of

total assets)

Size

( h mill.)

Age

(year)

Gross

margin

(per cent)

State

ownership

Debt/

equity

ratio ROA

Non-operating

income to

sales ratio

Panel A: unlisted utility firms (n¼16,047)Mean 0.033 0.047 69.4 15.7 0.014 0.237 0.016 0.033 0.049SD 0.148 0.254 892.4 14.6 0.331 0.384 0.039 0.074 0.195

Q1 0.032 0.039 0.8 6.8 0.000 0.000 0.000 0.000 0.063Median 0.012 0.009 3.6 11.0 0.033 0.000 0.002 0.023 0.026Q3 0.085 0.092 17.0 18.9 0.099 0.450 0.013 0.063 0.006

Panel B: privately owned util ity firms (n¼ 11,676)Mean 0.038 0.058 65.6 15.9 0.020 0.015 0.017 0.036 0.054SD 0.155 0.275 535.2 14.8 0.348 0.050 0.041 0.078 0.163

Q1 0.033 0.044 0.8 6.5 0.000 0.000 0.000 0.000 0.068Median 0.016 0.012 3.4 11.0 0.036 0.000 0.002 0.026 0.028Q3 0.097 0.114 15.2 20.6 0.115 0.000 0.014 0.070 0.006

Panel C: state owned util ity firms ( 430%, n¼ 4,371)

Mean 0.019 0.019 79.6 15.1 0.001 0.832 0.014 0 .025 0.037SD 0.129 0.185 1,469.2 14.1 0.280 0.221 0.032 0.064 0.260Q1 0.030 0.030 0.8 7.4 0.000 0.600 0.000 0.000 0.051Median 0.006 0.005 4.2 11.4 0.029 1.000 0.002 0.018 0.024Q3 0.056 0.051 21.5 16.8 0.072 1.000 0.012 0.046 0.006

Notes: This table reports descriptive statistics for three sets of firms. Panel A reports results for 16,047 firm/years,

Panel B reports results for 11,676 firm/years witho30 per cent state ownership and Panel C reports results for 4,371

firm/years with more than 30 per cent of shares owned by the state. The table reports the mean, standard deviation,

1st and 3rd quartiles and median for the following variables; the annual change in annual account receivables scaled

by total assets ( DAR), the annual change in revenues scaled by total assets ( DR), total asset (size), age determined as

numbers of years from the foundation (age), gross margin measured as operating income over revenues (GMR), state

ownership measured as percentage of shares owned by public entities (state ownership), debt to equity ratio (debt/

equity ratio), return on asset measured as operating income on total assets and non-operating income to sales ratio

(non-operating income to sales ratio)

TablDescriptive statis

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discretionary accruals across all years is lower for SOEs (7.7 per cent) than POEs(9.3 per cent), and a test of difference in means demonstrates that this is true at the1 per cent level of significance. Tests carried out for individual years provide similarresults. This is consistent with the findings of Wang and Yung (2011) who carry outvery similar tests on their sample of Chinese listed firms. Interestingly, discretionaryaccruals decrease from 2010 to 2012 suggesting that firms are reducing their earningsmanagement.

Table IV documents the relationship between the measure of earnings management,

the portion of SO – our primary variable of interest – as well as a number of othervariables. Table IV documents that the SO variable is negative and statisticallysignificant at all conventional levels of significance. This confirms the findingdocumented in Table III that SOEs manage their earnings less than privatelyowned firms, even after controlling for other known determinants of earningsmanagement. We find that the coefficients on SIZE and ROA are negative and positive,respectively. Furthermore, they are significant at the 0.01 level. This finding isconsistent with Wang and Yung (2011), and implies that larger firms manage theirearnings less while more profitable firms manage their earnings more.

Average coefficient Fama-McBeth t statistic

0.0163 4.83***D R 0.3010 2.39***D R Age 0.0347 0.29D R Age2 0.0032 0.13D R Size 0.0004 0.05D R GRR_P 0.0747 1.55D R GRR_N 0.0990 0.79D R GRM 0.3578 1.42D R GRM2 0.5285 0.44Adj average R 2 0.2072

Notes: This table reports results for analysis conducted on 5,349 Italian companies using data from2009 to 2012. Specifically, we estimate Stubben’s (2010) conditional revenue model of accountsreceivable as follows:

D AR it ¼ aþ b1D R it þ b2D R it SIZE it

þ b3D R it AGE it þ b4D R it AGE SQ it þ b5D R it GRR pit þ b6D R it GRR N it þ b7D R it GRM it þ b8D R it GRM SQ it þ eit

where AR is accounts receivable, R is total revenue, SIZE is the logarithm of total assets, AGE is thelogarithm of the number of years since formation of the firm, GRR P is the industry median-adjustedchange in revenues ( R ) multiplied by a dummy variable which is equal to 1 if the industry median-adjusted change in revenues in year t for firm i 40, otherwise 0, GRR N is the industry median-adjustedchange in revenues ( R ) multiplied by a dummy variable which is equal to 1 if the industry median-adjusted change in revenues in year t for firm i o0, otherwise 0, GRM is the industry median-adjustedgross margin for the firm, AGE SQ and GRM SQ is the square of the variables AGE and GRM ,respectively. D is the annual change. The conditional revenue model is estimated using data for each of the years 2010-2012. Following Stubben (2010) we estimate first, one model for each industry sector,

each year; second, after deflating D R and D AR by SIZE . Fama-Macbeth t -statistics is the Fama andMacbeth (1973) t-statistic to test whether a given coefficient is statistically significant across estimates.*,**,***Significance at 10, 5 and 1 per cent levels, respectively

Table II.Estimates of conditionalrevenue model

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Importantly, the separate regression results for SOEs and POEs reveal the conditionsunder which they are more likely to manage their earnings. All variables behavesimilarly across both state owned and privately owned firms and are significant,except for leverage for SOEs. This implies that size and profitability are significantdeterminants of earnings management for SOEs. Specifically, smaller firms and moreprofitable firms are more likely to manage their earnings.

All years 2010 2011 2012

Panel A: all firms|DA| 0.0888 0.0954 0.0874 0.0835

Panel B: private owned firms|DA| 0.09303 0.10002 0.09130 0.08777

Panel C: state owned firms|DA| 0.07746 0.08313 0.07700 0.07225

Panel D: tests of difference (state-private)Diff|DA| 0.01557 0.01689 0.01430 0.01553t-statistics 9.44*** 5.72*** 5.10*** 5.98***

Notes: This table reports results for analysis conducted on 5,349 Italian companies using data from2009 to 2012. Specifically, it reports the absolute value of residuals from the Stubben’s (2010) whichmeasures earnings management for all firms. The table the mean absolute discretionary accruals(| DA| ) for 3,892 unlisted and 1,457 firm with more than 30 per cent state ownership. We report resultsfor all firm/years as well as 2010-2012 separately. We carry out tests of different to determine if earnings management of the state owned firms is significantly different to earnings management

of publically owned firms. *,**,***Significance at 10, 5 and 1 per cent levels, respectively

TableEstimates of earni

managem

All firmsPrivately owned enterprises

o30% SOState owned enterprises

( 430% SO)

ParameterMean

coefficientFama-McBeth

t statisticMean


t statisticMean


t statistic

l 0.2006 13.81*** 0.18888 10.59*** 0.1982 9.19***SO 0.0110 3.25***Size 0.0076 7.79*** 0.00671 5.34*** 0.0081 5.63***

Leverage 0.1238 1.64* 0.17365 1.90* 0.1291 0.58ROA 0.0556 3.30*** 0.05812 2.81*** 0.1139 2.34***NOI 0.0712 2.76*** 0.10108 2.39*** 0.0803 1.66*Adj. R 2 0.1034 0.1159 0.1800

Notes: This table reports analysis conducted on 5,349 Italian companies using data from 2009 to 2012.The specific model that we estimate is as follows:

j DAit j ¼ l0 þ l1SO it þ l2SIZE it þ l3 LEV it þ l4 ROAit þ l5 NOI it þ eit

where |DA| is an estimate of discretionary accruals-based on Stubben (2010), SO is the proportion of issued shares held by the state, size is total assets, LEV is the debt/equity ratio, ROA is return onassets and NOI is non-operating income to sales. We estimate the model for each industry and yearusing OLS regression, and calculate white-adjusted t-statistics. We calculate Fama-Macbeth t-statisticsto test whether the t-statistic on a given coefficient is statistically significant across regression

coefficients estimated. *,**,***Significance at 10, 5 and 1 per cent levels, respectively

TableImpact of state owners

on earnings managem

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5. Summary and future research directionsIn this paper, we have examined the impact of SO on earnings management in anaccruals-based accounting environment. This enables us to assess whether, Ceteris paribus, in the public sector the “self-serving use” of accruals is greater vis-à-vis in the

private sector, thereby reducing the benefits of a transition from cash to accrual-basedaccounting. We have also examined a number of variables which can predict earningsmanagement by public entities. We find that unlisted Italian SOEs, despite the full andconsistent adoption of accrual-based accounting, still appear to significantly managetheir earnings, however, less so than privately owned firms.

Given the difficulties encountered by many EU national regulations trying toimplement accrual-based accounting at the public sector level, findings of a positiverelation between SO and earnings management could be used by those wanting tostifle transnational regulations trying to promote such a change. However, our resultsshow public entities do not exploit the discretions available in accrual based-accounting more so than any other entity preparing its financial statements on anaccrual-basis. Consequently, the benefits that many NPMR promoters and the EU

expect the public sector would obtain from a full and harmonised accrual accountingsystem cannot be denied on the basis of increased risk of earnings management.Furthermore, we find that the degree of earnings management is related to firm sizeand profitability. This provides insights relevant to regulators in targeting audit orother investigative efforts so as to improve the quality of public entities reportedfinancial position and performance in an accrual-based regime.

While we have examined a large sample of SOEs for a European country, itnevertheless is only one member state of the EU. Further work is required to probe thebroader generalisability of these findings to other countries. Furthermore, we havetested the relationship between earnings management and five independent variableswhich we can measure with our available data set and which have been examined inprevious research focused on private sector entities. We leave it to future research to

develop other variables which are unique to SOEs and which may explain earningsmanagement. These include the effect of impending government elections and thetargeting of industries or firms by regulatory organisations.

Notes

1. OECD has assessed SOEs’ contribution to GDP globally at 15 per cent (Christiansen, 2011).

2. Out of the 2085 companies analysed in the OECD report, 48 are listed, 1,764 are unlisted and273 are statutory corporations. Of course, listed companies are on average bigger, and hencethe report finds that, in terms of size and employment unlisted entities account for about half of all SOEs (Christiansen, 2011, p. 7).

3. In the case of private entities, the consequences of earnings manipulation can be mediatedamongst interested parties, whereas in public-owned companies there is a duty to reportearnings management to legal authorities.

4. A recent reform (law 42/2009, Leg. Decree 91/2011, Leg. Decree 118/201) is expected to makesome changes and to enhance their reporting obligations, but it is still at trial stage.

5. This is also consistent with the EU definition of public administration set out in EuropeanCouncil Directive (1992/50).

6. AIDA, shareholders section.

7. As a robustness check, the models are further estimated using fixed effects panel regression.The results are consistent with those reported in this paper.

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8. We eliminate the following three sectors: Organizzazioni ed organismi extraterritoriali,Estrazione di minerali da cave e miniere, Amministrazione pubblica e difesa, assicurazionesociale obbligatoria, due to small samples of firms in these sectors.

9. Wang and Yung (2011) explain that previous studies have demonstrated that these three

variables explain earnings management. They demonstrate that size and ROA are importantdeterminants of earnings management, and specifically that larger firms are less likely tomanipulate earnings while firms with higher ROAs are associated with higher managementof earnings. Wang and Yung (2011) highlight however that causality is unclear, as thesefirms may have higher ROAs because they are more likely to manipulate their accountingearnings.

10. Non-operating income is calculated as net income (Utile/perdita di esercizio: Item 23 in profitand loss in AIDA) less operating income (risultato operativo sourced directly from AIDA)where sales is R .

11. As a robustness check, the model is further estimated using fixed effects panel regression.The results are consistent with those reported in this paper.

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Corresponding authorProfessor Alex Frino can be contacted at: [email protected]

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Capalbo_et Al_Accrual Based EM in State Owned Enterprise

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