Disponíve* em: http://editora.unoesc.edu.br/i*dex.php/rac* Race, Joaçaba, v. 14, n. 1, p. 3*1-*8*, *an./abr. 2015 THE LIN* B*TW*EN EARNINGS MAN*GEMENT AN* DIGIT*L PATTERN O elo entre gerenciamento de res*ltado e *adrão digital Jennifer Martíne* F*rrero E-ma*l: j*nny_ma**e@usal.es Douto** pela Faculd*de de Econom*a e Em*r*sa da Univ*rsidade de Sa**manc*, Espanha; P*ofe*sora d* U*iversi*ade de Salamanca - Cam*us *iguel de Unamu- n*; **enida Fra*cisco Tomás y Va*iente, s/n, 3*007, Salaman*a. Beatriz Cuadra*o B*llesteros E-mai*: u77171@us*l.e* Doutora **la Facu*da*e de Economi* e **presa da *niversidade de S*l*manca, Esp*nha; Profess*ra da Universidad* de S*lamanca - Camp*s Mi*ue* de Un*mu- no; Aven*da *r*ncisco To*ás y *aliente, s/n, 370*7, Salamanca. Marco Antonio Figu*iredo Milani Fi*h* E-*a*l: m*rco.m*lan*@*ca.unicamp.br Pós-*o*tor p*la Faculda*e de Econ**i* e Empresa da Universida*e de Sa*a*an- ca, Espa**a; *out*r em Cont*oladoria e **ntabili*ade pel* Universi*ade d* São Paulo; *rofesso* do Cur*o de Admin**tração de *mpresas da Uni*ers*d*de Estadual de Campi*a*; Cidade *nivers**ária; R*a Pedro Zaccaria, 1300, *imeir*/ *P, 13484-350, Brasil. Artigo *ecebido *m 04 de novembro de 2013. Ac*ito em *7 *e novembr* de 2014 35* Jen*i*er M*rtínez Ferre*o, Beatriz Cuadrado Ba*lesteros, *arc* A*tonio *igueiredo Milani Fi*ho Abstrac* Ac**rding t* Decho* and Di*h*v (200*) and Lin and Wu (2014), * hig* degree of earni*gs management (EM) *s **so*iated wit* a poor quali*y of *nformation. *n this sens*, it is possible to assume that *he *in*ncial data of companies that *anage *arn*ngs can present different *atterns fr*m th*se with lo* degree of EM. The aim of this exp*oratory s**dy is to test whether a financi*l **ta *et (opera**ng e*pe*s**) of compan*es wit* high deg*ee of EM pres*n*s bias. F*r this analysis, we used th* m*d*l of Kothari *nd the modified *o**l *f **nes ("Dechow mo*el" hereafter) to es*im*te th* degree o* EM, and we u*ed the l*garithmic distribution of data predi**ed by the Benfor*\s Law to detect abnormal p*t*erns of d*gits in nu*b*r *ets. The sample was composed of *45 inter*a*ional listed non- fin*ncial c*m*anies for the year 2010. To *nal*ze the disc*ep*ncies betw*en the actu*l and ex*e*te* *req*e*c**s of the *ign*f**ant-*igi*, t*o sta*isti*s were calc*l**ed: Z-tes* and Pe*rson\s c**-s*uare test. T*e results show that, with a *onfidence level of 90%, the companie* with a high degree of EM acco*ding to the Kothari model present*d simi*ar distribution to th*t one pred*cte* by the *e*ford\* Law, suggesting that, in * *rel*minary ana*ysis, their fi*ancial data are free from bias. On the ot**r hand, the data set *f the organizations *hat ma*age earnings acco*ding to the Dechow model prese*ted abn*rma* patterns. The Benford´s *aw has b*en impleme*ted to succ*ssfu*ly de*ect ma*ipulated data. These re*ults offer insight* in*o the interac*ions between EM and p*tterns of fi*ancial data, an* stimulate new *omparative studie* *bout the accu*acy of models *o estimate EM. Keyword*: E*rning* m*nagement (EM). Financia* Reportin* Quality (FRQ). Benfo*d\s L*w. * *lo entre gerenc*ament* de result*do e pad*ão digital Resumo Conf*rm* D*cho* e Dichev (2*02) e Lin e Wu (2014), u* al*o gra* de gerencia*en*o de r*sultado* (GR) *stá associado a **a qualid**e informacion*l *obre. Nesse *ent*do, * *ossível assumir *u* os dados financeiros de e*presas que g*renciam resu*tados po*em apresen*ar *adr*es dif*rentes daque*as com *m baixo grau de GR. O o*jeti*o d*ste *studo explo*atório *oi te*t*r se um conju*t* de *a*os fi*anceiros (*espesas o*eracio*ais) de emp*esas com alto grau de GR *presentam *iés. Para *sta análise, utilizou-s* * modelo de Ko*hari e o m*delo modificado de Jones ("modelo Dec*ow") para est*mar o g**u d* GR e foi usada a *istrib***ão log*rítmica *e dados predita pe*a Lei *e *enford *a*a d*tec*ar pa*r*es digitais anormais em um conju*to numérico. A a**stra foi compost* por 845 empr*sas *ão fin**c*iras lista*as em bols*s de valores no a*o d* 2010. Para analisar as disc*epâ*cias en*re as frequê*cias atuai* * espera*as do díg*to cha*ado de significativo, dois test*s esta**sticos fora* reali*a***: o *e*te Z e * t*ste Qu*-Quadrado. Os *esu*ta**s mostrara* que, com um nível de confiança de *0%, a* em*resas com alto grau de GR conf*rme o modelo *e Kothari apresentar*m *is*rib*ição simil*r à*uel* p**dita pela Lei d* B*nford, sugerindo que, *m uma análise prelim*na*, e*ses dad*s nã* possuem v**s. P*r *utro lado, o *o*junto de dados das *rga*****ões que *erenciam resultados c*nforme o modelo Dechow apresentaram p**rões anorm**s. * Lei de B*nford te* si*o im*l**entad* c*m suces** para detec*ar dados manipulados. *sses resul**do* 3*2 Th* link between... ofer*cem novos *leme*tos sobre as **terações en*re GR e padrõ*s de dados f*nan*ei*o*, al*m de estimular n**o* estudos compa*a**vos sob*e a ac*rác*a de mod*los p**a *e estimar o **. Palav**s-chave: Gerenciamen*o de res*lt*dos (GR). Qua*idade dos Relat*rios Finan*eiros (QRF). Le* d* Be*for*. 1 INTROD*CTIO* Financial re**r** offer r*levant elements f*r the a*aly*is of compa*ies\ as*e*s a** econ*mic balance. The finan*ial *nformation di*c*ose* by en**ties of any *ature **st me** standar*s *f q*a*ity in order to meet t*e different expe**a*ions *f t*eir *se*s. Thus, the re*ia*il*ty of t*e fi***cial dat* is an impor*ant *actor for reducing the informational asymmet*y bet*een companies and their stak*holders. According to *echow and Dichev (2002), * high deg*ee of earnings man*ge**nt (EM) is *s*ociat*d with a *oor qual*ty *f *n*orma*ion, and t*ere*o*e it i* a relevant issue *or external us*rs of **coun**n* inf**mation. *c*ording*oLeclercetal.(19*6,p.*24),t*er*leof*ud*tingis"[]toaddcredibility to fin*nci** s*atements and to *n*ance the e**ectiveness of ac*ounting com*unication need** by our e*on*m*c sys*em." Unde* th*s *erspec*ive, the auditing c*n incre**e the co**iden*e level of i*f*rmation *isclosed. S*atistica* te*ts can be u*ed by aud*tors *s *n*lytical *rocedures *n the *lanning stages of the audit (NI*RINI; MITTER*AI*R, 19*7). Be*ford\s Law (*L) is a u*eful *ogarithmic distribution for dete*t*ng abnormal p*tterns in sets of *umber* *nd it *as been applied *n di*feren* *reas of knowledge *o an*lyze th* *requency of *ata sets. Wi*h the improvem*n* of computat*ona* r**ources, t*e BL had its use inc*easingly s*mpli*ie* and *ractices pre*imi**ry a*dit has shown a s*mple an* effe*tive t*o* *or detecting evidence of errors, illegal or *ntoward e*ents, suc* as fr*ud and man*g*ng f*r results (*IGRINI, *00*). The g**era* aim of this e*plor*to** study *s *o test whe*he* a financial variable (operating expenses) of c**p*nies with * h*gh de*ree of EM presents b*as according *he da*a *ist**b*tion predicted ** Be*ford\s Law. ** t*is *e*se, the re*ear*h *ues*ion o* this stu*y is: Do *he companies with a hi*h degree of ear*ings man*gement have b*as in thei* financi*l data? C**sidering that t*ere *s a gap in th* literature rega*ding the qua*ity of **nancial information and detection of bias in companie* *hat m*nag* ear*ings, it is expected that the r*sults *f this study contribute to this subj*ct a*d c*n fo*ter *ew inves*igations in diff**ent e***ties an* regions. 353 J**ni*er Martínez *errero, Beat*iz Cuadrado Bal*esteros, Marco A*tonio Figu*ired* Milani Filho 2 *HEORETIC*L FR*MEWORK: EARN*NGS MANAGE*ENT AND FINANCI*L REPORT*NG Q*ALITY 2.1 EARNINGS MA*AGEMEN* (EM) **co*nting s*an*als that have *it t*e headlines in the l**t decade (notably tho*e i*volving Enron, WorldCom, *erox a*d Merck) h*ve *enerated incr*as*ng mistrust among investors reg*rding *he r*l*vanc* *nd rel*a*il*ty of publis**d accounting informa*io*. In this respect, the ea*n*ngs management issue **s *e*ome a conc**n thro*ghout the worl* (IS*AM; ALI; AH*AD, 2011). Pre*isel*, the separation between ownership and control can be co*si*ered *he sta*t*ng point *f E*, which is viewed as * variet* *f agency cost (DAV*D*ON; XIE; *U, 2004). As Ball (*013) noted, g*ven th* conflic* of interest share*old*r *er*us manager, t*e *ost to be *orne by managers for m*nipulating the result i* le*s th*n t*e cost that *harehold*rs ha*e to bear for detectin* and *enalizing such man*ge*ent. Moreo*er, *ecause of agency conflict, *he exi*tence of asymmetric information m*kes it particu*a*ly *ifficult for inv*st*rs to know *he *eal situation *f com**n**s (LIN; WU, 2014). This problem is *ssociated with *he different availability of i*fo*mation b*tween diverse participants (AKE*LOF, 197*). In a*cordan** wit* them, com*a*y direc*or*, act*ng for thei* own ben*f*t, c*rry *ut actions aimed, *ot just against *hareholders\ interests, in *h* for* of non-o*tim*l inv*stment d*cisions, *u* also against those of other inte*es* g*oup*, in order to infl*ence contrac*ua* o*tc*mes (*EAL*; *AH*EN, 1999; SC*TT, 2*09). According to Gar*ía-Osma, Noguer e Clement* (*005), EM can *e defined as an* pra***ce carri*d o*t intentionally by *ompany *anagers, fo* opp*rtu*is*ic and/o* info*mation purposes, t* report accounting r*sults t*at do n*t correspond to those *eally achieved. These author* stress th*t such actions may *e either oppo*tun*sti* or i*formation-**lated, as propo*ed also by Schipper (1989), *ho remaine* *n th* sidelin*s of the deb*te *s to whe*her EM c*nstitutes exclusiv*ly practices th*t viol*t* *en*ral*y acc**ted accounting p*inc**les or whether managers may use their *iscretionary powe*s, overstati*g or unders*ating result*, w*thout vio*atin* *hese p*i*ciple*. In accordance with Gao (2*1*) m****ers c*uld engage in EM act*vities *o i*fluence the charac*eris*i*s of a transaction withou* im*roving i*s e**nom*c substance. But it is nec*ssar* t* note that this EM can d*stort *he 35* The link bet*e*n... f**anci*l pi*ture of the firm (, 2013). With increasing m*nage*ial discreti*n by EM *ctions, thus di**or*ing the signal *alue of earning*, the earnings quality and th*n, the **nancial reporting quality i* r*duc*d (NELS*N; SKINNER, 2013). Earnings *anagemen* practices are prox**d by manage*ent accruals (AEM) and real measures (RE*) in order to determine whet*er results vary dependi*g on earnings practice*. Altho*gh the choice *f *n* ** ins*rum*nt or ano*her depends on various factors - the aim pursued, th* ac*ounting rules applica*le *nd business-sector characte**stics, a**** o*hers (G*R*ÍA-O*MA; NOGUER; CLE**NTE, 2005; D*TTA; ISK*NDAR-DA*TA; *INGH, 2013) - mana*ers prefer instruments *hich a*e r*adily available *nd low co*t, *ike AE*, or, in contrast, s*lected REM instruments that are less *isib*e to i*vesto*s, th* market, audi*ors and o*he* stakeholders. EM via *iscretionary accruals i* a ma**gers instru*ent *or ch*ng*n* s*are*o*ders and stak*holders\ expe**ation* (Mar**jory et al., 20*3). Manager* can choose betw*en AEM a*d REM a*tions according to which on*s **e less cos*ly and *ess visi*le to *n*estors and to the market (KIM; L*SI*; **VZNER, 2011). Accordin* to Zang (2012), decisio*s *o manage *arning* throu*h "**al" *ctions p*ecede t*ose to manage *arni*** throug* accruals. REM could *e detrim*ntal to firms\ co*petit*v**ess and future va*ue (GAR*Í*- OSMA; NOGUER; CLE*ENTE, 20*5). However, *t has been suggest*d that the manipulation of r*al activities is also wides*read (GRAHAM; HAR*EY; RAJG*PAL, 200*) bec*use it is more d*ffic*l* for audi*ors and regulatory bo*i*s to det*ct RE* th*n AEM, because REM *s associated with o*erati*g, invest*ng *nd financing activiti*s (COHEN; Z*ROWI*, 2*10). Manag*rs hav* div*rse reasons for manipu*a*in* accounti*g res*lts. Th*s, according to Roychowdh*ry (*006), real act*v*ties *re misr*po*ted *n order to avoid rep*rting annual loss*s, while Gargou*i, Shabou and Fran*oeur (2010), in th*i* study of Canadi*n companies, *oun* that manag*rs ma* *eek to smooth out income f*ows, to mini*ise th* *ax bu*den, to effect c*anges in the co*trol of the company, to influence l*bour negotiati*ns or to respond to takeover bids. Moreover, in a**ord**ce with Hazarika, Karpo*fe* *nd Na*ata (2012), managers could be tending to distort their firms\ reported f*na*c*al p*rformance in o*d*r to incre*se t*eir compensation and gains throu*h stock sales (BURGSTAHLER; DIC*EV, 199*; G*N*Y, 2010). In or*er *o summarize these m*tivations, H**ly and Wa*l*n (1999) clas*ifie* *hese motivations as *o*tractual, political/gove*nme*tal and valuation-based. 35* Jenn*fer Mar*ínez Fe*rero, Beatriz Cuadrado Ballesteros, Marco Antonio Figueiredo Milani *ilho Firstly, in rel*tion to *on*ractu*l **ti*ati*ns, the higher the debt ratio of a co*pany, *he more lik*ly t*at *t* managers will select accoun*ing *r*ct*ces t**t t*ansfer futur* prof**s to the *resent (K*M; L*SIC; PE*ZNER, 2011). This tendenc* i* *eightened when m*nag*rs have sig*ed remuneration contrac*s r*la*ed to company results (H*ALY, 1985; H*LTHAUSEN; L*RCKERET; SLOAN, 1995). Moreover, as *ranz, *assab*lna*y and Lobo (201*) *xamined *nd f*und, firms show * positive corre*ation betwee* their i*centive* *o EM actio*s and the proximity t* debt *ov*n*nt vi*la*ion. Secondly, the g*eater t** poli*ical co**s facing a compa*y, t*e gr*at*r the *nce*tiv*s of manag*men* to artificial*y re*uce its profit, *n o*der to reduce th* potentia* costs of gove*n*ental actions *owards the company, *nd thu* to manipulate t*e image offered to th* *arket a*d to r**ulatory au*hori*ies (*ATTS; Z*MMERMAN, 19*6). Si*ila*ly, Monterre Mayoral *n* Sán*hez **gura (*00*) stu*ied how tax*s af*ect th* *ualit* of the accou*ting r*sult *n* *eported that in t** *ase o* companie* *hat are not *ighly indebted, ris*ng tax*s g*n*rate a t*n**ncy for pr*fits to be *assaged do*n. Meanwhile, Cahan (1992) exami*ed EM b*haviour b* *ompan*es *acing antitrust an* impo*t-rel*ef investiga*io*s, and found, empiri*ally, that manager* *ad incentives to us* account*ng pro*edures th*t reflected low*r levels of inco** than for the pe*iods *o* *ein* i*v**tig*ted. ***ever, managers ar* sensitive to future sto** performance an* those with hi*h equity i*centiv*s are less li*ely y to report large posi*ive earnings (**ENG; WARFIELD, 2005). And f*nally, related to asset va*uat**n, numer*us studies have high*ighted the existence of *M prior to trans*cti*ns in wh*ch valuation is * c**cial aspect. *s Cohen and Zarowin (20*0) report, firms use real and accrual-based EM activ*t*es around seaso*ed equity off**i*gs. *hus, P**ry and Williams (1994) o*se*ved that EM led to profits b*ing u*derstated i* period* p*ior to a management buyout. By c*nt*ast, Teoh, Welc* an* W*ng (1998) fo*nd that profi** were o**e* overstated d*ring periods of equity is*u*. Pau*o, Cava**ante and Lapa de Melo, 2012 found *hat *ccoun*ing n*mbers **e *ot significantly different in period* c*ose to the *ublic *s*ue of sha*e* and deben*ures, pointi*g that thi* fact does *ot affect the quality *f ac****ting inf*rmation. Anot*er q*es*ion of interest is tha* of man**ement changes. In this respec*, there are opportunistic **terest* both fo* *a*a*ers leaving a *ompany a*d for t*o*e j*i*ing it. As **own by DeAngelo (*98*), manager* who believe their position w*thi* the co*p*ny *s being challeng*d *ave an ince*tive to overs**te the a*countin* **sult, while th*s* *ho a** new*y arrived will se*k t* 356 The link *etween... unders*ate profits in their first **ar in or*e* to s*if* responsibility for this sit*ation to the former management a*d *o make sub*equent res*lts appear mor* impressive. **e consequences *f these manageme*t p*acti*es are beyond doubt detriment*l, *educing the value of the company, its as*ets, it* transactions, *t* *eputation and *or*orate **a*e (FOMBRUN; *ARDBERG; *ARNETT, 200*; ROYCHO**HUR*, 2*06). According *o Za*ra, *riem e Rasheed (2005), **e consequences of *hese discretion*ry practices *ffect i*ve*tors, employ*es, cu*tomers and the lo*al *ommunities, which is eventua*ly refl*cted in corporate reputation and, hence, the ma*ke* va*ue. Improvements in Earnings Quality lower *nformatio* asymme**y and affect the cost of cap*ta* (FRANCIS et al., 2*0*; BHAT*AC*ARYA; DAOU*; WELKER *003; BLANCO; GA*C*A; TRIBÓ, 20**). At th*s respect, a* Ferrero, Ba*e*jee an* Gar*ía-Sánchez (2013) a*d Martínez-*errero, Bane*jee *nd García-Sánchez (2014) report, EM practic*s le*ds to higher costs of capital and lower reput*tion, as re*u*t of the p*r*eived un*ertainty res*lting in a d**countin* o* the v*lue of the inf*rmation repo*ted by th* company engaging in EM prac*ices. At the same ti*e, pr*vo*ing a loss of support *mong sh*re*ol*er*, investors and other stakeho*d*rs, *nd incre*sing activism and surv*ill*nce *y *nterest grou*s a*d regula*ory aut**rities (Z*H*A; PRIEM; RASH*ED, 2005). 2.2 FINANCIAL R**ORTING QUAL*TY (FRQ) Due to th* marke*s an* business globalization, g*o*raphi*al e*pansion and th* gre*ter demand fo* infor**tio* a** *rans*are*c* amon* investors, stakeh*lders *nd society in general, market agents find the*r toe*ol* in the quality o* their f*nancia* rep*rt*ng and their main sou*ce of k*owledge on company strategy (MARTÍNEZ- F*RRERO, 2014). In relation to Finan*ial R**orting Quality (FRQ), let us first *ote that the goal of financial reporting is to provi*e useful infor*ation *or d*cisi**- ma*ing. **, accordi*g to Navar*o-Garcia and Madrid-Guijarro (2014), "[...] the main purpose of financ*al reporting ** to pr*vide informat*on that better reects the economi* posit**n and perfo*manc* of com**nies." *owever, even though *ompanies may *enerate financial statement* ** accordance **th generally accepted acc*u*ting p*inciple*, th*se statements may prese*t differing levels of quality (CHO*; PAE, 2011). N*neth**ess, companies t*nd to improve their accounting p*actices fr*m the moment that st*ndards can be vo*un**rily applied (N*VARRO- GARCIA; MADRID-G*IJARR*, 2014). *57 Jen*ifer Martínez Ferrero, B*a*riz Cuadrado Ballest*ros, Marco Antonio Figueiredo *il*ni Filho Pre*isely, a* FRQ can be defined as *he **ithfulne*s o* the inform*tion c*nveyed by the financial re*o*ti*g proc*ss. *his quality *ay be influenced b* *act*r* related to *axe*, dividends a*d objectives other th*n th*se regarding *he inf*r*ation needs of extern*l pr*viders of capital (BALL; SHIVAK*MAR, 2*05; *URGSTAH*ER; HAIL; LEUZ, *006). Reporting *s a *ina* output, but *he *u*lity *f the output depends on each o* th* par*s of t*e *rocess *y which it is *laborate*, includi*g *isclosure* *bout the compa*y\s transactions, th* selection *nd a**lication of accounting p*licies, t** judgment* i*vo*ved in t*i* res*ect and the esti*ates made (JONAS; BLANCHET, 2000). The fina*cia* report shows the econo*** and *inan*ial situation o* t*e c*mpany, in order to inform managers and shareho*d*rs (MATHEWS; PERERA, 1991; MONE*A; LLENA, 2000), *nd is *f cr*cial importance in decis*on mak*ng, wh*n the int*rests *f both shar*hol**rs an* credit*r* mu*t *e take* into *ccou*t. FRQ requires compani** to vol*n*arily expand *he scope *nd quality o* the inform*tion they report, to ensure *hat mar*et p*rticipa*ts are *ul*y informe* in order to make *ell-grounded decisio*s on i*vestme*t, credit, etc. Thi* high quality informatio* facili**tes g*eat*r transparency. T**reon, reporting quality is achi*ved wh*n *he information reporte* *o investors a*d to the market is credible and free of error *nd bias, whe**er they are int*nt**nal or not (LU; RICH*RDSON; SALTERI*, 2*11). *he**fo*e, the *cop* and *uality *f rep**ted infor*a*io* are expanded a*d m*rke* participant* are fully informed (HOPE; T*OMAS; VYAS, 20*3). Acco*ding to the l*a*ing aut*orities on the eva*u*tion of financial re*o*ting (su*h as the FA*B, the SEC o* the J**kin* co*mit*e*), *he main character*stics required ar* relevance, re*iabili*y, transpar**cy and clarity (JONAS; BLANC*ET, 20*0; LU; R*CHARD*ON; SA*TERIO, 2011). It has be*n *sserted that **gh quality *cc*unting infor*ati*n *s a v**uable *eans of counteracting informat*on asymmetry (*HEN et *l., *0*1). Numerous adva*tag** of *roviding high-quality informat*on have been cite*: FRQ reduces inf**matio* risk and liq*id*ty (Lambert et a*., 2007), *revent* managers from us*ng *iscretionary *ower* *or t*eir own b*nefit and *elps **em t*ke efficient in*estment decis**ns (CHEN; BOU*AIN, 2009). Lambert, Leuz e Verrec*hia (20*7) o*tain*d empirica* evi*ence that th* quality of a*counting informa*ion can i*fluen*e t** cost of capital, b*th **rect*y, by affecting **rket partici*ants\ perceptions abo*t the d*stribut*on of future *ash flows, *nd indire*tly, by affec*ing r*al *ecis*ons tha* alt** the *i*tr*bution of *utu*e cash flows a*ove. In 358 The link between... this sense, Bac*oo, Ta* and Wilson (2013) obtained evid*nce ***ch shows how t*e quality of reporting is negatively linked with cost of equ*ty capital, a*d pos*tive*y *in*ed with the exp*cted level *f futu** long-t*rm ear*ings. *hen and Bouvain (2009) found *hat F*Q positi**ly affects the invest*ent e*ficiency o* pr*vate firms in emergin* markets and t*at t*is ef*ect enhances bank *i*ancing and decreases *ncen*ives to mini*ise earnings **r tax avoidance purposes. T** ext*rnal indic*tor* of FRQ ar*: SEC Accoun*ing and Auditi*g *nforce*en* Releases (AAER*); Res*at*m*nt*; and finall*; internal *on*rol* (DECHO*; GE; *C*RAND, 2010). The two last indicators are *he **st i*p*rtant because th*y show inf*rmatio* about the quality of the financial statemen*s as a whole and not j*st as earnings. The *ain conseq*e*ces *f *hese alternati**s ar* th*ir e*fect on the co*t of *apital (**rket re**t*on to announcements of restatements and/ or AAERs is n**ative). Fran*is et *l. (2005), s*pporting this *oint of vi*w, r*por**d that fi*ms with a **gher earning quality have a l*wer cost of debt. 2.3 *ELIABILITY OF FINAN*IAL *N*ORMATIO* The four main attributes list** b* the In*erna**onal Acco*ntin* Standard Board ** *ak* financ*al *tatem*nts useful to u*ers a**: underst*ndability, rel*van**, com*a*abi*ity and reliability (INTERNATION*L AC*OU*TI*G STAND**D* *O*RD, 2011). The infor*ation that can in*l***c* t*e decis*ons of u*ers by helping them *o understand *he *perational and financial conte*t of the organizatio* and evaluate th* i*pa*t of previous, *urrent or future t*ansactions *nd eve*ts, must be **liable, i.e., it ha* t* be ve*ifi*ble and fre* *f *rrors and bi*ses (INTERN*TIO*A* AC*OUNTING S**NDARDS *OARD, 201*). Fr*m the perspec*ive of au*ito*s, re*iabilit* refers to the probabilit* of achievi*g the same res*lt* when an*lytical tests *re aga*n perf*rm*d o* when t*e same in**rmation *s obtained f*om different sources. Re*ia*le resul*s are t*us "[] con*ist*nt, and are *ini*ally affec*ed b* rand*m *rro*s ** me*sure*e**." (THE *ANADIAN A**IT*NG AND ASSURANCE STA*D*RDS BOAR*, *011, p. 2*). In ord** to verify the consis*ency and la*k of errors *nd bias of a data *et, s**tistical tests are used regularly b* au**tors and other a*alyst*. Digital *nalysis, whi*h is often used in the audi* *e*ting, allo*s finding abn*rmal patterns *f numb*rs, wrong digit combi*ations *n* rou*ding of numbers 359 Jenn*fer *artí*ez Ferre*o, Bea*riz *uadr*do Ballesteros, M*rco Antonio Fi*ueir*do Milani Fil*o *n fi*ancial infor*at*on. According to *urtsc**, H**lison and Pacini (20*4), one of the most ef*ecti*e too*s for digital analysis *s the *enford\s Law, which give* auditors the exp*c*ed frequen*ies *f digi*s in * given da*a set. The B*nford\s Law has bee* implemented to success*ully *etect manipulat*d data (RAUCH; GOETTSC*E; EL MOUAAOU*, 2*13; HENS*LMAN*; DITTER; S*HERR, 2*13). In recent s*udies, n*merous s*holars have emplo*ed Be*ford\s *aw to investigat* earnings mana**ment in enterpris*s. So, in accordance with *in an* Wu (2*14), Benford\s law has been widely employed in accounting audits and *hen exa*ining wh*t*er companies carry out E* ac*ions. In *his way, *igrin* a*d Mitte**aier (1997) ass*rt that, if *n *xamined *istribution o* data fitted well with t** BL, *ud*tors might con**ude that the re*pectiv* dat* passed * test of reasonableness. T*is f*ct do*s *ot me*n, *ec*ssarily, that al* the observed numbers are **rr*ct or auth*ntic, b*t ra*her that any bi*s or er*ors wer* not *igni*icant enoug* to *ffect the *ig*tal stan*ards exp*cted. A*cor*ing to Nigri*i (20*5) eve* i* auditors have to combine other *omplementary analyt*cal *rocedures and *ore accurate methods, BL co*st*tutes a powerful tool *n preliminary anal*sis to detect erro*s *nd other inco*si*tencies in da*a s*ts. Moreover, g*v*n t*e di*e**en*e betwe*n the *bserved first digits distrib*ti*n in annua* fi*ancial accounts, Am***m, **zani* a*d Rouen (*01*) evide*ced t*at when these **na*ci** st*tements are m*nage*, th*re is a *igh likelihood of an *ncrease i* the divergenc* from Benford\s Law. *o, these a*tho*s co*clude that Benford\s Law could be under*tood as a long-range tool to detec* fina*c*al reportin* irregu*ariti*s. 2.4 B*NFORD\S LAW **nford\s Law, also known *s Law of Anomal*us Numbe*s, Law of Significan* Digits or Newcomb-Benford\s L*w, is a log*r*t*mic distri*uti*n use*ul for detec*ing abnor*a* patterns in sets o* numbers. The d*viati*n in actual data *rom th*se *x*ec*ed f**q**ncies indicate* the presence of *anipul*tion (THO*A*, *012). The innovative paper, *ritten by Newcomb (1881), c*ntrib*te* to the theoretical explanation of Benford (1938) about the *i*st-digit d*str*but*on, whi*h *s b*sed on t*e probability of occurr*nce *f a gi**n initial d*git, e*pre*sed *y the followin* formula: (1) 360 The li*k *etween... Thus, the probabilit* of occurren*e of a spe*i**c numb*r in a *ata set, whose first *igit ** 1, is equa* ** 30.12%, consid*rin* Pe(1)=log102=0.*012. Similarly, the p*obability to find number* whose first digit i* 2, *s equal to 17.61%, consideri*g Pe(2)=log10(3/2)=0.1*61, an* so o*, until P*(9)=log10(10/9)=0.045*. Additionally, Hill (1995) pr**i*e* a *obust mathe*atic** *asis *or this d*stribu*ion. Fr*m the *econ* t* the *ift* digits, the logarithmic behavior o* *he predicted frequencie* *s reduced each time and the deviations from a linear distri*u*ion *end to disappear progressive*y after the s*cond *igit. T*e p**babili*y of occu*ren*e of * number bet*ee* 0 to 9 for the fi**h digit is equal *o 10%. An important property of BL, c*mmented b* Pinkham (1961), is scale i*vari*n**, *ince if a data set is *ultipli*d by a con*tant fact*r, t*e new dat* set a*so obey the law. F*r example, a shift from do*lar-de*ominat*d d*ta *o data *enom*nated *n other currenci*s does not c*a*ge the first-digit d**tribution predicted by BL. Benford\s L**, how*ver, is not a*pl**able to all da*a sets, s**h as those related to rando*l* *enerated *umbers wh*se probabi*i*y of occurrence of the digits is the sam* for the entire set. In addi*ion, d*tes or pr*-**fine* numbers, such as phone number*, bank a*count numbers or non-sequential reg*stries, also fail to sa*isfy BL. O* *he other hand, in all o*her cases w*en *he BL is applicable, the lack of conform*t* *etween t*e obser*e* *nd e*pected occ*rren*es suggests, in a preliminary *ay, abnor*al**ie* that s*ould be investigated to know *hether the **us* is relat*d to contextua* facto*s, u*intentio*a* or intent*o*a* actions. Hü*limann (2006) pointed ou* *hat *y the year 2006 there wer* 30* papers dir**t*y re**t*d to B* pub*ished *n *cientific journals, an* around 90 p*r ce*t *f these te*ts we*e written af*er 1990. De*pite this, th*re *re few papers in the literat*re about ** applied to org*n*zations of the health s*ctor, suc* *s the investiga*ion of Maher and Akers (2002) on fraud *n the insu*ance i**ustry an* the res*arch *f **seman (2011), to det*ct de*iat*ons *nd operatio*a* e*rors in hospital pr*cedur**. M*st of the papers related to the application of BL in f*rensic acc*unt*ng and auditing *e*e pu**is*e* after *he mid-1990s by authors suc* as Nigrini and Mittermaier (199*), Durts*hi, Hillis*n **d *ac*n* (2*04), Quick and Wolz (2005), Jo**son (*009) an* Geyer (20*0), among oth*rs. Basi*ally, a*thors emphasi*ed the relevance of the fi*st digit *n rela*ion to other digit*. Nigrini and M*tterm*i*r (1997) *tat** *hat the other d*gits can be a*alyzed to s*pport more specific *udit tes*s accord*ng to the designed *urposes, but the most sig*ifi*ant one is the *irst. *61 Jennif*r M*rt*ne* Ferrero, Beatriz Cuadrado B*lleste*os, Marco An*onio Fig*eiredo Mila*i Filho 3 RES*ARCH DESIGN AND DATA In *his study, we use* a qua*titative a*proach to ana*yze th* fina*cial data o* *elect*d companie*, particu*ar** those o*es that m*nage earn*ngs. The sample i* *onstituted of 845 in**rnational listed non-financial *ompa*ies for *he tax ye*r 2010. T*e r**pecti*e sample was o*t*in*d f**m the information ava*la*le in Tho*son One A*alytic da*abase for *ccounting and financial data related to 2* countri** (USA, United Kingdo*, Ir*land, Canad*, Austral*a, Germa*y, Net*erlands, Luxemb*rg, A**tria, *enm*rk, *orwa*, *inland, Sweden, Switze**and, France, Italy, Spain, *elgium, Po*tuga*, *reec*, Japan, C**na, N*w Zealand, Singapore and Ko**a) and the Adminis*rat*ve R*gio* of Hong Kong. Concretely, the financi*l informat**n correspon*s to co**ol*da*** data of the *nal*zed companies. More*v*r, the financial data **re d*rect** relat*d to the *p*rating account, which value* *nco*pass the total expenses for each in**it*ti*n. The i*form*t*on **ovided by *ho*son *ne Ana*yt*c databas* i* expre*sed i* millions of Eu**s. Therefo*e, there is n* conflict i* the valuatio* of each *tem caused by u*in* a sa*ple of international c*mpanies. Acc**ding to the Dec*** model, 208 companie* present*d a high degree ** earning m*n*g*m*nt in th* p*riod. Th* K*thari *odel, *nd its turn, detect*d th* *ame 20* plus 154 comp*nies, for a total of 362 compani*s with a high EM degree. We *ou*d 483 companies that *resente* * medi** or low EM degr*e accordi*g to *he both *odels applie*. 3.1 J*NES\ S**N*ARD MODE* Acc*rdin* to Jones (1991) a*d Dechow, Sloan and Sweeney (19*5), to*al ac*rual ad*ustments (TAA) ar* defined a*: (2) Wher* represent* the change ** cu*r*nt as*ets; refle*t* the *hang* in cash h*l* and sh*rt t*rm financial investme*ts; is the *hange in current li*bilities; *s *he change in recl**sif*ed l*ng term obl*gat*ons; is *he depreciation *nd amortization; i represents e*ch company and t re*resents the year. 362 The link between... On the basis *f Equ*tion 2, a*cruals are ca*cu*ated using an expla*atory *odel. The difference be**een p*esent and expec*ed accrual adj*s*ments (t*king into account *row*h, company assets a*d the ac*ounting result) represents the dis*retionary or ***xplained *omp*nent of accr*al adjustments (DAA) a*d **ts as a m*asure ** managem*nt discre*ion i* *he r*porting o* re**lts. The standard Jone* mode* uses the following pr*cedure t* separa*e th* discretionary from **e n*n-discretionary component: (3) Where are the total accrual adjustm*nts; represent* total assets of firm i i* period t-1 a*d this is used as * def*at*r to correct *ossible problems of heteroscedasticity; repr*sents the property, plant and equip**nt of firm i in p**iod *; *s t*e chang* in sales for firm * in *erio* *. Th* non- discre*ionary a**rual *dju*t*e*ts (N*AA) *re and *ep*e*ents t*e discretionary accrual adjustm*nts (DAA) for f*rm i in t*e year t. NDAA *re calcul*ted by replacing the coeffic*en*s in Equation 3 *ith *he v*l*es **tained b* Or*inary Lea*t Squar*s and DAA *re the residu*ls of thi* calcula*i*n. 3.2 MODIFIED *ONES MODEL (DECH*W; SLOA*; *WEENEY, 199*) In the m*dified Jones model (DECHOW; *L*A*; SWEENE*, 1995) (Equa*ion 4), the TAA use the **ri*tion i* sa*e* less accounts re*ei*able (u**d to m*as*re the g*owth of the c*mpa**, as its working cap*tal is closel* link*d to **les), and less *he item p*o*er*y, plant a*d e*u*pment, w*ich is us*d to mea*ure *he depr*ciation costs contained in the di*cre*ionary adj*stme*ts. *t *s assum*d *ha* not a*l sale* are necessarily non-discretionary and that this will depen* o* the it*m to be re*eived. (4) Wher* A*R repre*ents accounts receivable, and **e other *ariabl*s are as def***d *n Equat*on 3. 363 Jenn*fer Ma*tínez Ferrero, *eatriz Cu*drado Ballesteros, Ma*co Antoni* F*gueiredo Milani Filho No*e that in th*s mod*l, the coefficients are ca*cula*ed u*in* the original Jones model (1991) and that the *odifica**on *s made only for th* calcu*ation of th* non-di*c*etionary adjustme*ts. In *his stud*, we na*e th* modified Jone* *ode* as "*ech*w mode*". 3.3 KO*HA*I MO*EL Mo*eover, we alternative** employ the model prop*sed by *otha*i, Leone and **sley (200*). Thi* i* *hara*terised b* t*e **corpo*atio* *f a n*n-de*lated constant a*d the retu*n on ass*t*, or fina*cia* profita*i*ity. All vari**les (excep* t*e c*nst*nt) are deflated by the total a*s*ts *or *he pre*ious per*od a*d are calculated *y cross e*timatio*. This model pr*vide* in*reased reliabil*ty and higher qual**y re*ults, by resolving the quest*on ** whet*er differences in DAA may *eri** from differences *n performance. TA*i, t = 0 + 1, t 1 (Sale* A * R)i, t PPE*, t RO*i, t + *, * + 3, t + 4, t + * (5) Ai, t 1 Ai, t 1 A*, t 1 * Ai, t 1 A*, t 1 **e ND** are calculated by *eplaci*g th* coeffic*ents i* E*uation * ***h those obtain*d from Eq*atio* 5, *s in the **igina* modifie* Jones model. NDAAi, t = 0 + 1, t 1 (Sales A * R)i, t PP*i, t RO*i, t * * * + 2, * + 3, t + 4, t (6) Ai, t 1 * A*, t 1 Ai, t 1 Ai, t 1 The DAA are then obtained by subtracting the NDAA fr*m the *A* v*lue obt**n*d in Equa*io* 2, a* s*o*n in Equati*n 7. The DAA represent the unexpected or abnormal a*cruals *d*ustments that constitu*e the variabl* tak** a* a measure o* EM. D*Ai, t = TAAi, t NDA**, t (7) 36* T*e link between... 3.4 **A*U*ES OF *M AND FRQ EM is cons*dered *o be the inver*e of *RQ (DECHO*; DICHEV, *002); a highe* degree *f EM is as*ociated with lower quality of *nfor*ation (MARTÍN*Z- **RRERO, *ANERJEE, GARCÍA-S*NCHEZ, 2014). Ac*ording to García-Osma, Alb*rno* Noguer and Cleme*te (2*05), *M can be d*fined as "[...] any pra*tice carr*ed *ut i*tentiona*ly *y c*mpany managers, for opp*rtu*isti* and/or i*f*rmation purposes, to repor* account*ng *esul*s *hat do not corre*pond to th*se really achi*ved." T*e discretionary com*onent of accru*ls adjustme*t could *e used as a measur* of mana*emen* discret*on*rily, *nd therefore ** *ccounting m*nipul*tion. As *bserved by *arcía-Osma, Albornoz *ogue* and C**mente (200*), accr*als are not all discreti*nar*; hence it i* n*cessa*y to *e*ar*te the *iscretionary co*p*nent from the non-d*scret*onary one in order to det*rmi*e the pres*nce an* extent *f EM. The dis*retionar* accruals *djustment (DA*) is obtained by subtracting *he non-di*cr*tionary accr*als adjustmen* (NDAA) from the total accruals adjustment (TAA). The *AA represents the abnorma* accruals that constitut* the variable taken as a me*sure of EM. Fern*n*ez (2013), we us* t** modified Jones model (*ECHOW; Cu*dradoBallester*s (*013) **d Martín*z-Fe*rero, Pra*o-Lorenzo Fernánde*- In this study, *n a*cor**nce *i*h *a***nez-Ferrero, G**ciaSa*c*ez and SLOAN; SW*ENEY, 19*5) and *he Kothari *o*el (**T*ARI; LEONE; *ASLEY, 200*) t* s*para*e the *on-*iscre*ionary *ompo**nt o* accruals from the **s*re**onary one. De*pi*e th* *od**ied Jones model, *n Kothari mod*l, *t i* incl*de* lag*ed return on ass*ts (RO*) as an a*d*t*on*l regressor *o control for the effect of pe*for*ance on a firm\s *ccru*ls. 3.5 FIRST-DIGIT DISTRIBUTION I* order *o detect *bn*rmal digit frequencie* in *ccounting numbers, w* analyzed onl* the first-digit distri*ution, b*c*use it is considered * high-level te*t *f rea*onableness an* it is as**ciat* wi*h a larger *at*rial *a*ipu*at*on of earnings (R*U*H; G**TTSCHE; M**AAO**, 2013). Second an* other di*it* *ere not *ubjec* to ana*ysis for this study. The first digit of the financial data was *de*tif*** and or*anized, aiming to kn*w **e obs*r*e* freque*cy o* the spec*fic digit Po(d). Subsequent*y, *h* Po(*) was 365 Jen*ifer Martínez Ferrer*, *eat*i* Cuad*ado B*lleste*os, Mar*o Antonio Figueiredo Mila*i *ilho co*pare* to the expe*ted *rob*bil*ty of the same *ig*t Pe(*) predicte* by the B*, as *escribed prev*ously in the Equ*tion 1. The nul* *ypothesis (H0) *roposes that no statistical significance exists b**ween Po(d) and Pe(d), as shown in t*e Equ*ti*n 8: (8) We use* the Z-test to det*rmine wheth*r the differe*ces between the actual and ex*ected pr*port*ons are significant, in *rder to verify **e appropr*ate**ss of accep**ng or rejecting H0 w*th signific*nce l*vel () e*ual t* 5% and Zcritic*l *q*al t* 1.95*. The Equation 9 *resen*s the Z-test (*t), where n repr*sents t*e number of obse*vatio**. (9) According to Nigrini and **tt*rmaier (*99*), the co*rection term is appli*d in the Equation 3 when , a* sho*n in t*e Equat*on 10. (10) To test the null hy*ot*e*i* that the frequency distribution (Do) *bser*e* in the se*ecte* sample was consiste*t with t*e BL distribution (De), w* u*ed **e statis*ical test Chi-*quare (2), shown in **uation 11, with a si**i*icance level () equal to 10%, degree of free*om (df) equal *o 8, and the crit*cal value (2cri*ic*l) equal to 1*.362. (11) 36* The li*k betwee*... A**er t*e appropriate sta*ist*cal tests, it was **ssible to verify the confo*mit* ** the ob*e*ved distributions *o thos* expec*ed and to infer about the presence or absence of bias, by adopting the BL a* * proxy for reliabi*i*y. 4 EMPIRIC*L RESULTS In thi* se*tio*, we *resent the d*gital ana*ysis perf*rmed on the *alue* related to oper*ting expenses accounts of 845 observation* in *he p*riod. The results o* sta**sti*al tests verif* the r*liability of th* finan*ial data of the selected **mpan*es, usi*g the prob*bili*y distr*bution predicted by Ben**rd\s La* as a proxy of reliabi*ity. Hyp*thet*cally, t*e companies that manage earnings *ould be more propense t* pre*ent b*as in a digi*al ana*ysis than others. Sign*ficant differen**s be***en the predicted and observed data ar* relevant for t*e detectio* of no*-compliance, and may *oint out, *bjectivel*, t*e en*itie* that would need mo*e d*taile* analysis to clarify a*d expla*n some *ia* detec*ed. It is notewor*h* that a*y result* of non-*ompliance to B* not nece**ari*y mean that there are c*ses of fraud or ir*egularit**s, whi*h can on** be f*und *y an in-dept* *udit. Th* non-comp**ance d*ta, how**er, may be a *ood indicato* of attent*on an* *t can help to *d*n*ify r*lev*nt factors influen*ing the performan*e organization. *ompliance to BL, in turn, is not guarantee that *h*re is no risk of fraud or *r*ors in the data sets, but represents pr*limi*a**ly a *o*e *av*ra*le *ituation with absenc* o* bi*s and *ncreasing the degree of reliability o* th* analyzed data. 4.1 SELECTED COMPANI*S USING T** DECHOW MODEL **aphic 1 sho*s *he obse*ved (Po) and e*pec*ed (Pe) first-d*git freq*enci** of numbers *btain*d from th* oper*ti*g exp*nses *ccount of 2*8 compan**s with * high degree *f EM ac*o*ding to the Dechow mo*el. *he freq*encie* of digits 4 an* 5 *re higher than ex**ct*d *or the p*ri*d. *his fact *s associated with a re*uction in the fr**u*ncy ** o*her *igits, *ith emp**sis on the digit 7. 367 Jen*ifer Martíne* Fe*rero, Beatriz Cuadrado Bal*esteros, M*rc* Antonio Fig*ei*edo *ilani F*lho Gr*phic 1 - Digital distri*uti*n - Co*panies *ith h*gh EM accor*ing t* *echow *odel So*rce: th* auth*r*. Table 1 co*ta*ns the r*sults o* the Z-test (Zt), which verifies if there *s *ig**f*cant d*fferen*e between *he expected (Pe) and observed (Po) probabil*ty of occurr*n*e *f a g*ven initi*l digit (d) ** the revenue account values. The *ull hypot*es*s (H0) is tha* there is no signif*ca*t *if*erence betw*en ** a*d Po. After analy*ing the fr*quency of *ccurrence of d, the r*s*lts indi**ted *hat the *efere*ce *a**e (Zcr*tical = 1.959) was higher tha* *t in *ll the observations, *x*ep* for the di*its 7. This f*c* allows us to reject H0 for *he digi* 7 and classify the observed data wi*h "atte*tion" status, determinin* t*e pr*sence of bias. Ta*le 1 - Digital distr*bution d P* Po Po-Pe ** status 1 30,1% *7,9% -2,2*% 0,5* ok 2 17,6% 17,3% -0,30% - 0,*7 ok 3 12,5% 10,1% -2,40% 0,84 *k * 9,7% 13,9% *,25% 1,84 ok 5 7,9% 11,1% 3,14% 1,42 o* 6 6,7% 6,7% 0,04% 0,0* ok 7 5,8% 1,9% -3,88% 2,10 a*t*n*ion 8 5,1% 7,*% *,10% 1,06 ok 9 4,6% *,8% -0,73% 0,17 ok To t 100,0% 10*,0% Zcritical=1,*59 S*urce: th* authors. *68 The lin* bet*een... *a*le 2 sho*s t*e Chi-squa*e (2) test, calc*lat*d as shown in *qu*tion (11) f*r *ur *otal sampl*, in order to *e*ify whether observed (Do) a*d expe*ted (*e) dat* sets have significant **f*erences. The referen*e *al*e (*critical) is compare* to t*e calculated value (2cal*). D*e to 2critical<*2*alc in *he period, it is possible to reject the *ull hyp*the*is (Ho) that there is no si**i**ca*t difference between D* *nd De. T*is re*ult is a*so ex*ress*d in t*e relatio* Pvalue<0.1. Tabl* 2 - Test 2- Dechow\s model d Do *e *2calc 1 58 63 0,3400 2 *6 37 0,0107 3 21 26 0,957* 4 29 20 3,*792 5 2* 16 2,5*93 * 14 14 0,00*4 7 * 1* 5,3888 8 15 1* 1,7*6* 9 8 10 0,242* T*t *08 208 15,194 P value = 0,055 df=8 2*rit=13,**2 =0,1 Sour*e: the authors. Base* *n *bsolute v**u*s, t*e largest differences *n t*e ex*ected freque*c**s *ccurred in t**se numb*r* initiated by the digi*s 7, 4 and 5. The total dif*er*nc* is stati*ti*all* signi*i*ant. Thus, *dopt*ng the digital dis*ributio* pr*vided by BL as * pr*xy for r*liabilit*, statis*ical te*ts i*dicated that, prelimina*ily, there *s bias in the *perating expens*s data o* c**panies *ith a high deg*** of *M a*cording to Dec*ow M*de*. MartínezFerrero, Gar*iaSanchez and Cuadr*doBallestero* (20*3) and Martí*ez- This resul* is compatibl* wi*h the argument *f D*chow an* *i*hev (2002), Ferrero, Prad*-Lorenzo *ern*n**z-Fernández (2013), that a higher *egr*e o* EM is assoc*ated with lower qua*ity of information. *69 Jennifer Martínez F*rrero, Beatriz Cuadrad* Ba*les*eros, Marco Antonio Figueir*do Milani Filho 4.2 SELECTED C*MPANIES USING TH* *OTHARI MODEL Gr***ic 2 shows the observed (Po) and expecte* (Pe) first-digit frequencies of numbers *btained from the *perating ex*en*es a*count of 362 c*mpanies with a high d*gree of EM acco**ing to *h* *othari model. ** f*un* * reasonable fit of *o to the logarithm*c *urv* Pe. G*a*hic 2 - *igital distributio* - w*th hi*h E* acc*rding to K*thari Model *ource: the a*thors. The Zt value o* the *emaining d*gits in *oth years stu*ied w*s *ess than the Zcr*tica*, leading to the acceptance o* H*. Table 3 - Digital di*tribution - Kothar* d Pe Po P*-Pe Zt sta*** * 30,*% 34,3% 4,1*% *,61 ok * 17,6% 17,1% -*,48% 0,10 ok 3 12,*% 11,6% -0,89% 0,35 ok 4 9,*% 10,*% 0,*3% 0,16 o* 5 7,9% 8,*% 0,*7% 0,07 ok * 6,7% 6,1% -0,6*% 0,*6 ok 7 5,8% *,0% -0,83% 0,45 *k 8 *,1% 4,4% -0,*0% 0,*6 ok 9 4,6% 3,*% -1,54% 1,15 *k To t 100,0% 10*,0% Zcritical=*,*5* Sour*e: the authors. 3*0 T*e *ink b*tween... **e Chi-squar* (2) test, s*ow* in Table 4, all*w* ac*e*ting th* null *yp*thesis (Ho) *hat there is n* *i***fican* differe*c* **tween the obse*ved (Do) and expec*ed (De) data sets *f the *elect*d compa*ies in the *e*i*d. Th* r*fere**e value (*cri*ical) was highe* *han the ca*culated value (2calc) in both years, *s well as the P value was higher t*a* the significance level *f 1*%. *able 4 - Test 2- *x*enditures ON (2009-10) d Do De 2calc 1 124 109 2,0722 2 62 64 0,0478 * 42 45 0,2304 4 *7 *5 0,1049 5 30 2* *,0623 6 2* 24 0,2*6* * 18 21 0,4267 8 16 19 0,*422 9 11 *7 1,8691 Tot 3*2 *62 5,*617 P val*e = 0,*18 df=8 2crit=13,3*2 =0,1 *o**c*: the ****ors. Based on th* * test results, the *nalyzed data set* ca* be con*i*ered free of bias, *nd this sugge*ts **at the Kothari mod*l does not off*r, with a confi*ence level of 90%, * clear associati*n between com*anie* t*at man*ge earning* with lower qualit* of financial i**or*atio* (operational exp*nses). This may be relate* *o the fac* that th* group o* companies identified by t*e Kothari m*de* with a high degre* of ea*nings management is more c*m*re***sive th*n the *echow\s and hence th* Ko*hari\s could *o* point accurately to the re*ationshi* be**ee* E* and FRQ just as D*c*ow\*. H*wever, this result contrasts with th* apparent a*vantage ** Kothari mod*l ov*r the D*chow\s *egarding the reliability *f the in*or*ation generated, ac*ording to author* such as Jonas and Blanche* (2000). 4.3 SELECTED COMPANIES W*T* LOW EM DEGREE Graph*c * pr*sents *he observed (Po) and expect*d (Pe) frequencies of *i*st- di*i*s of the values *btained *rom the *perat*n* expenses acco*nt *f *ompa*ies that 371 Jen*ife* Martínez Fe*rero, Be*t*iz Cuad*ad* Ba*lesteros, M*r*o Anto*i* F*guei*edo M*lani F*lho p*esented a low EM *egre* acc*rding to *he b*th mod*ls: De*how **d Kothari o*e*. In 2010, despite the slig*t difference **r the digi*s "2" and "4", the*e i* a reasonable f*t *f Po (o*ser*ed frequency) t* the logari*h*ic cur*e Pe (**pec*ed frequency). Graphic 3 - Dig**al distri*u*io* - with low EM S*urce: the aut*or*. B**ed on t*e Z-te*t (Zt) presented *n Table 9, there is no signifi*ant diff*rence between the expected (Pe) and *bse*ved (Po) probabilit* of occ**ren** of a given initial digit (d) of th* reve*ue account values, whic* a*lows accep*ing H*. Ev*n consid*r*ng the diff*re*ces i* 2010, *e**ted to **e digits "2" and "4", the re*ere*ce value (Zcriti*al= 1.959) was higher tha* Zt. Thus, the observe* data in bot* year* rec*ived *he \ok\ sta*us, sug*est*ng t*e absence of b*as in **e dat* set*. Table 5 - Di*ita* *istribution - expendit*res - QC (2009-*0) d P* Po Po-P* Zt s*a*us * 30,1% 31,1% 0,95% 0,*6 ok 2 17,6% 15,*% -2,50% 1,3* ok 3 12,*% 11,6% -0,90% 0,46 ok 4 9,7% 11,6% 1,*0% 1,2* ok 5 7,9% 9,3% 1,40% 0,97 ok 6 6,7% 6,4% -0,*8% 0,*6 ok 7 *,8% 6,*% 0,41% 0,19 *k 8 5,1% 3,*% -1,39% *,18 ** 9 4,6% 5,0% 0,39% 0,20 ok To t 100,0% 10*,0% Zcri*i*a*=1,959 372 Sou*ce: the authors. The l*nk betwee*... The Chi-squ*re (2) t**t, show* in Ta*le 10, all*w a*cepting *he nul* hy***hesis (H*) that t*ere is no sig*ificant difference b*tween *he observed (*o) and expect*d (De) data sets of the selected c*mpa*ies. The referenc* value (2cr*tical) was h*gher than the *alculated val*e (2c*lc) in bot* years, as well as the P v*lue *as highe* than the significance level of 10%. Tab*e 6 - Test 2 - expenditur** - QC (*00*-10) d D* De 2calc 1 150 145 0,1457 2 73 85 1,7*78 3 56 6* 0,*129 4 56 47 1,*053 5 45 38 1,1933 6 31 32 0,055* 7 *0 28 0,1414 8 18 25 1,8205 9 24 22 0,163* Tot *83 4*3 7,3452 * value = 0,499 *f=8 2cr*t=13,3** =0,1 Source: the auth*rs. Adop*ing the di*ital dist*i*ut**n provi**d b* BL as * proxy fo* reliability, the Z-test *n*2test*esultsindicatedt*at,preliminarily,thereisnobi*si*therevenuedataofcompanies *ichev (2002) and *artínezFer*er*, Garci*Sanchez and CuadradoBalle*tero* (201*) and *ith low EM de*ree in 2010. This result is compati*le wit* the ar*ument o* D*chow *nd Martínez-Ferr*ro, P**do-L*renz* and Fernánd*z-F*rná*dez (2013). 5 CONCLUS*ON The aim of t*is *xploratory *tud* was *o test whether a financi*l data *et (oper*t*ng *xpenses) of companies that *anag* e*rni*gs *resent* bias. *e found that co*panies with high EM degree, **cordi** to *he Dec*ow model, have abnormal financial patte*ns bas*d o* the first-*igit analysi* and this *esult is *7* co*pa*ible with Decho* and Dic**v (2002) and M*rtín**Ferrero, GarciaS*n*hez Je**ifer Martínez *errero, Bea*riz *uadrado *allesteros, Marco Antonio Figu*iredo Milani Filh* the s*me te**, wi*h a co**id*nce level of 90%, w*en we consider*d comp*ni*s with and **ad*adoBa*l*st*ros (*013). Interestingly, we also found differen* results f*r high *M de*ree ca*cu*ated by the Ko*hari mod*l, and this fact contr*sts with *he appare*t ad*antage of *ot*ari model over the Dech*w\s regarding the reli*bi*ity of the *nformation generated. T*e com*anies *ith l** EM degree, a*cording to both mode*s, met t*e frequency expecta*io** predicted *y Benford\s La*. This fact sugg**ts that o*r initial h*pothesis about the existence of bias *n the fi*ancial data set (ope*ati*g expens*s) can be confirmed *sing t*e Dechow m*del, but not *h*n apply*n* the K**hari model. And it is p*s*ible to suppo*e that the Decho* mod*l (*r mod*fied Jones mo*el) can be mor* accu*ate than the K*thar* model i* order to select companies that man*g* e*rnings a*d whi*h *i**nci*l da** woul* be more pr**ense to present *ias a* we assumed in *ur hypothesis, based on *artínez-Ferrero, Pra*o-Lorenzo a*d Fer*ández-Fernández (2013). The *ur*ose o* t**s study *as **t t* point out any specifi* th*oretical im*rovement that could be *a** in the model*, but *o*tributes to the c*ncep*ual dis*ussion o* possible ad*antages and dis*d*a**age* o* the m*dels in ide*tif*ing c*mpani*s that m*n*ge ear*i*gs *nd br*ngs new questions abou* the lower adhe*ence of Ko*hari m*del t* Benford\s L*w than De*ho* **del. Any res*lts o* non-*o*pliance to *e**ord\s Law do not *ece*sarily mean that *here are cases of fraud or irregula*ities, but ***s f*ct might be * red fl*g and, therefore, * *ood indic*tor of at*en*ion. An in-*epth *ud*t *an ide**ify rele*ant fa*t*rs influ*nci*g the respect*ve *onconformit* t* B* and provide useful informatio* to t*e or*a*ization\s stakeho*ders. On the o*her hand, *ompliance to B* i* n*t gu*ran*e* t*at there is no risk of fr*ud or i**p*r*priat* **tions i* the data sets, bu* *t is a more f**or**l* condition with a*sence of **as and incr**ses the degre* of relia*ility of the analyzed data. 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