WORKING CAPITAL ACCRUALS AND EARNINGS MANAGEMENT 1

Transcription

1 Invesmen Managemen and Financial Innovaions, Volume 4, Issue 2, WORKING CAPITAL ACCRUALS AND EARNINGS MANAGEMENT Joseph Kersein *, Aul Rai ** Absrac We reexamine marke reacions o large and small working capial accruals and predic ha he marke is more likely o discoun unexpeced earnings when posiive or negaive large working capial accruals (LWCAs) lead o small increases in earnings. We find ha he earnings response coefficien (ERC) is lower when small earnings increases are accompanied by LWCAs of eiher sign, bu no in oher cases. Resuls are robus o alernae definiions of working capial accruals and he inclusion of ERC conrol variables. The sudy conribues o exan lieraure by idenifying specific siuaions where he marke views LWCAs as earnings managemen. Key words: Earnings managemen; large discreionary working capial accruals; earnings response coefficien; earnings qualiy. JEL Classificaion: M4; L4; C89.. Inroducion The accrual mehod of accouning has been widely criicized as allowing managers oo many opporuniies o use discreionary accouning choices o manage earnings. The pracice of alering earnings o mislead sakeholders or achieve conracual oucomes is earnings managemen (Schipper, 989). Earnings managemen has enabled firms o be profiable, achieve posiive earnings surprises and smooh earnings growh (Carslaw, 988; Bursahler and Dichev, 997; Degeorge e al., 999; Barh e al., 999; Masumoo, 2002). Prior research suggess ha he marke relies on working capial accruals o miigae iming and maching problems inheren in cash flows (Dechow, 994). This implies eiher ha working capial accruals are no generally managed, or ha he marke does no recognize (or ignores) earnings managemen. If he marke is unable o deec earnings managemen, quesions can be raised abou he effeciveness of audiors/accouning regulaions in idenifying earnings managemen, and/or he marke s efficiency in recognizing managerial moivaions behind accouning choices. The lieraure provides mixed evidence abou he marke s abiliy o see hrough earnings managemen. Sloan (996) finds evidence ha he marke misudges he ime series properies of accruals. He suggess ha he marke overesimaes he persisence of low qualiy (high accrual) earnings and underesimaes he persisence of high qualiy (low accrual) earnings. Dechow and Skinner (2000) (DS) sugges ha he marke is inefficien in deecing earnings managemen o reach simple earnings arges. DS argue ha exreme reacions o small deviaions from simple benchmarks such as analyss earnings predicions indicae ha he marke uses overly simple heurisics o measure economic performance forecass. On he oher hand, focusing on non-linear relaions beween reurns and large absolue discreionary working capial accruals, Ali (994) finds ha he marke disinguishes beween he persisence of unexpeced accruals ha are large compared o hose ha are small in absolue value 2. He suggess ha he marke expecs eiher large posiive or large negaive discreionary working capial accruals o be more ransiory han smaller amouns. Ali, * Baruch College, Ciy Universiy of New York, USA. ** Wichia Sae Universiy, USA. We graefully acknowledge commens from Masako Darrough, John Ellio, Aloke Ghosh, Suresh Govindara, Anhony Kozberg, Seve Lilien, Rick Moron, Bill Ruland, Seve Ryan, Bhara Sarah, and seminar paricipans in Universiy of Alabama, Universiy of Florida, and Florida Sae Universiy. Any errors ha remain are our own. 2 Defond and Park (200) also examine he marke s reacion o unexpeced working capial accruals bu in conras o Ali (994) do no concenrae on annual earnings changes and he marke s reacion o large versus small working capial accruals and earnings surprises. Joseph Kersein, Aul Rai, 2007.

2 34 Invesmen Managemen and Financial Innovaions, Volume 4, Issue 2, 2007 however, does no consider he overall relaion beween large discreionary working capial accruals (LWCAs), earnings managemen and earnings response coefficiens (ERCs). We examine he marke s reacion o posiive and negaive earnings changes influenced by LWCAs and predic circumsances where LWCAs lead o varying marke expecaions of earnings qualiy, which has neiher been suggesed nor esed in earlier work. We argue ha annual earnings changes associaed wih eiher posiive or negaive LWCAs are more likely o be viewed by he marke as being managed and, herefore, being of lower qualiy when hey are associaed wih small earnings changes. On he oher hand, we anicipae ha he exisence of LWCAs does no, in and of iself, necessarily connoe earnings managemen o he marke. For example, large posiive earnings surprises having posiive LWCAs are inconsisen wih he bonus hypohesis (Healy, 985). Managers are normally expeced o reserve accruals for use in fuure earnings managemen raher han grealy overshoo bonus earnings arges. The exisence of posiive LWCAs along wih small earnings declines is also inconsisen wih likely managerial incenives, which, according o he lieraure, encourage managers o increase accruals a bi more o achieve posiive earnings growh. Possible alernaive explanaions for LWCAs include value-increasing acions (i.e., posiive signals), aemps o miigae iming problems, or errors in he measure ( Kohari, Leone and Wasley, 2004). We expec conflicing differences in he reasons why LWCAs exis o lead o diverse invesor opinions, resuling in a less predicable marke reacion. In general, we expec he marke o characerize discreionary working capial accruals as follows:. Posiive or negaive LWCAs associaed wih small earnings increases are likely o be perceived as earnings managemen; 2. Small posiive or negaive discreionary working capial accruals are more likely o represen non-discreionary accruals or measuremen error and less likely o be viewed as earnings managemen; 3. Posiive or negaive LWCAs lead o more disagreemens abou managerial moivaions among marke paricipans excep when hey resul in small earnings increases. We focus on annual earnings changes (similar o Ali, 994) because here is widespread ineres by invesors, analyss and compensaion commiees in annual earnings rends, which is likely o affec managerial incenives o manage earnings. In addiion, here is more deailed informaion available in annual filings from which he marke can assess earnings managemen. In designing our ess, we focus on working capial accruals raher han oal accruals because working capial accruals have been found o be especially imporan in helping he marke resolve problems inheren in cash flows from operaions (Dechow, 994). In addiion, we avoid poenial noise in our measure given he mixed evidence surrounding he use of large negaive non-working capial accruals o ake big bahs (Whie, Sondhi and Fried, 2003, p. 60). We concenrae on earnings before exraordinary and special iems as our primary measure of earnings. We exclude loss firms from our analysis since earnings managemen has been found o be less imporan when earnings are negaive (Degeorge e al., 999) 2. Similar o Ali (994), we allow for separae valuaion of small and large absolue earnings changes 3. In addiion, we conrol for facors ha have been found in previous work o affec he ERC including growh, persisence, and risk (Collins and Kohari, 989), so ha ERC differences aribuable o LWCAs are more likely o be relaed o lower earnings qualiy han be surrogaes for hose oher facors. Also, consisen wih exan research, we expec large posiive or negaive unexpeced working capial accruals o involve a greaer degree of discreionary accouning choices han small negaive or posiive unexpeced working capial accruals. Since non-discreionary accruals are unobserved variables, an exac measure of discreionary accruals is ypically no likely o occur. 2 In our sensiiviy analysis, however, he resuls are qualiaively similar when losses are included. 3 Ali (994) finds ha he ERCs are lower under hese circumsances, consisen wih Brooks and Buckmaser (976) and Freeman, Ohlson, and Penman (982) who find ha when he absolue change in earnings is small, a random-walk model is a good approximaion for annual earnings ime-series properies, while a mean-revering model is a beer one for large absolue changes in earnings.

3 Invesmen Managemen and Financial Innovaions, Volume 4, Issue 2, Our sample is divided ino four muually exclusive groups: (a) posiive small earnings changes, (b) negaive small earnings changes, (c) posiive large earnings changes, and (d) negaive large earnings changes. We separaely analyze he effecs of posiive or negaive LWCAs on he ERCs wihin each group (he cases idenified by he marke as being of lower qualiy earnings are expeced o be found in caegory a ). We divide our earnings surprises and discreionary working capial accruals ino large (small) caegories based on wheher he magniudes exceed (are less han or equal o) he annual median of he firm s indusry. Our working capial accruals expecaion model relies on he hisoric relaionship beween sales and working capial (Defond and Park, 200). Our main finding suggess ha he marke discoun earnings surprises wih LWCAs in he small earnings increase group bu no in he oher groups. The remainder of his paper is organized as follows. Secion 2 describes hypoheses developmen. Secion 3 describes he research design. Secion 4 idenifies sample selecion and daa. Secion 5 discusses resuls, and secion 6 concludes he paper. 2. Hypoheses Developmen As noed previously, he magniude of absolue unexpeced working capial accruals is anicipaed o be posiively associaed wih he degree of managerial discreion. This suggess ha LWCAs are more likely han smaller unexpeced working capial accruals o signify earnings managemen and he exisence of lower earnings qualiy o he marke. The fac ha LWCAs exis does imply, however, ha he marke idenifies managerial inenions behind accouning choices. We predic ha he marke is more likely o anicipae managerial moivaions when hey are consisen wih esablished managerial incenives. For example, managers may use negaive LWCAs o avoid large earnings shocks, ending up wih small earnings increases and he impression of smooher earnings growh. Alhough he marke normally prefers (i.e., pus a premium on) smooher earnings, he use of exraordinary means such as LWCAs o mask earnings variance is likely o sugges lower earnings qualiy once he marke sees hrough he manager s aemps. In addiion, managers may use posiive LWCAs o ransform earnings declines ino posiive (bu no excessive) earnings growh, a desirable oucome for achieving bonuses. Wheher firms mask much higher variance or he exisence of earnings declines, he marke is anicipaed o discoun he value of earnings ha i perceives as being of lower qualiy. This leads o he firs hypohesis saed in boh he null and he alernae forms: H,0 : Negaive or posiive LWCAs have no impac on he ERCs of firms reporing posiive small earnings surprises. H,A : Negaive or posiive LWCAs reduce he ERCs of firms wih posiive small earnings surprises. When earnings surprises are negaive bu small in magniude, he managerial moivaions surrounding posiive or negaive LWCAs are no clearly eviden o he marke. For example, when firms use large posiive LWCAs o repor small earning declines, by no using a lile exra working capial accruals hey appear o wase an opporuniy o repor earnings increases which are highly desirable earnings arges. If i was no possible o increase working capial accruals furher, hen accruals could be saved for flexibiliy in reporing earnings in fuure periods. Similarly, he exisence of negaive LWCAs in he presence of earnings below las year s levels is unlikely o be he resul of earnings managemen and, herefore, he marke is more likely o view LWCAs as being credible. In he absence of clear moivaions behind managerial choices, here is more diversiy of views among invesors abou he firm s prospecs compared o cases involving more ransparen earnings managemen, he implicaion being ha marke reacions are likely o be mixed. This suggess he second hypohesis, boh in he null and he alernae forms: H 2,0 : Posiive or negaive LWCAs have no impac on ERCs of firms reporing small earnings declines. We use he median of he indusry raher han he sample median as he demarcaion poin given our decision o runcae loss firms.

4 36 Invesmen Managemen and Financial Innovaions, Volume 4, Issue 2, 2007 H 2,A : Posiive or negaive LWCAs reduce ERCs of firms reporing small earnings declines. The exisence of posiive or negaive LWCAs in large posiive or negaive earnings surprises also obfuscaes managerial inenions because an earnings managemen sraegy is expeced o be a muli-period one ha reains fuure flexibiliy. This suggess ha he managerial moivaion behind posiive LWCAs ha occur along wih large posiive earnings surprises is no clearly eviden o he marke. The exisence of negaive LWCAs and large posiive earnings surprises also raises quesions abou managerial moivaions, i.e., why didn managers achieve smooher earnings growh and, in he absence of being able o do so, save negaive discreionary accruals for a differen ime. The exisence of posiive LWCAs and negaive earnings shocks is also inconsisen wih he big bah. Finally, he exisence of negaive LWCAs and negaive earnings shocks is consisen wih a big bah, bu working capial accruals have no been idenified as he usual vehicle for achieving big bahs. The lieraure normally poins o he disposal of bad long-erm invesmens as a way for firms o clear he deck. This leads o he hird hypohesis, boh in he null and he alernae forms: H 3,0 : Posiive or negaive LWCAs have no impac on ERCs of firms reporing large earnings increases or declines. H 3,A : Posiive on negaive LWCAs reduce ERCs of firms reporing large earnings increases or declines. 3. Research Design We assume a random walk model for annual earnings and use annual earnings changes as a proxy for unexpeced earnings or earnings surprises. We examine ERCs for he following four muually exclusive groups ha correspond o our four regression ables: (a) posiive earnings surprises of small magniude, (b) negaive earnings surprises of small magniude, (c) posiive earnings surprises of large magniude, and (d) negaive earnings surprises of large magniude. To es our hypoheses, we use dummy variables wihin each group represening he exisence of eiher posiive or negaive LWCAs. In addiion, we conrol for variables ha prior research has idenified o be deerminans of cross-secional differences in ERCs. Thus, ERC differences aribuable o LWCAs are more likely o be relaed o lower earnings qualiy han be viewed as surrogaes for hose oher facors. Consisen wih prior work (e.g., Ali, 994), we use a long-window associaion sudy. Annual reurn (RET) We use raw reurns compued as he compounded monhly reurns from nine monhs prior o he fiscal year-end o hree monhs afer he fiscal year-end as he dependen variable. Unexpeced working capial accruals (WC ) and absolue unexpeced working capial accruals ( WC ): Working capial from operaions for period is defined as curren asses (ne of cash and shor-erm invesmens) minus curren liabiliies (ne of shor-erm debs) : WC = (Daa 4 Daa ) (Daa 5 Daa 04 ) 2. There have been differen measures of unexpeced working capial accruals in he lieraure. Ali (994) and Dechow (994) use a random-walk expecaion model o capure annual surprises in working capial accruals. They boh examine cases involving differen rankings of absolue values of working capial surprises. Defond and Park (200) (DP) base heir working capial accrual expecaions model on how much working capial is normally needed o suppor curren Unless oherwise specified, all daa are obained from Year 200 Annual Compusa daase a Wharon Research Daa Sysem. Daa numbers refer o COMPUSTAT daa iem numbers. Firm subscrip is omied for sake of breviy. 2 If shor erm deb (Daa 04 ) was missing hen i was replaced by zero.

5 Invesmen Managemen and Financial Innovaions, Volume 4, Issue 2, sales. Our approach is similar o DP (alhough we es he oher model in our sensiiviy analysis) where we define expeced working capial as: E(WC ) = WC - x Sales / Sales - = WC - x (Daa 2 /Daa 2 - ) We define unexpeced working capial (WC ) as he difference beween he acual working capial WC, and he expeced working capial, E(WC ), scaled by he beginning period marke value. WC = [WC - WC - x (Daa 2 /Daa 2 - )]/ (Daa99 - x Daa 25 - ). Our measure of large working capial accruals (LWCA) is consisen wih he ones used in earlier sudies. We firs rank all observaions of WC in one of fifeen indusrial secors. Indusrial secors are defined according o he definiion used in Barh, Beaver and Landsman (998). Variable LWCA for a firm equals if WC is above he median for he indusry of firm in year (zero, oherwise). Afer creaing he variable LWCA o classify wheher unexpeced working capial accruals are large or small, we hen define dummy variables RWP and RWN based on wheher unexpeced working capial accruals are posiive or negaive as follows: RWP = if LWCA = and WC is posiive, RWP equals 0 oherwise. RWN = if LWCA = and WC is negaive. RWN equals 0 oherwise. Earnings changes (NI ) and absolue changes in earnings ( NI ) We use earnings before exraordinary iems and special iems. By excluding exraordinary iems and special iems, we reduce he likelihood ha our resuls are driven by he marke s response o one-ime evens. We use changes in annual earnings (scaled by beginning of he period marke value) as a proxy for unexpeced earnings under he assumpion ha annual earnings follow a random walk process. NI, = unexpeced earnings = Change in Earnings before exraordinary iems and special iems, divided by marke value a he beginning of he period. = [(Daa 8 Daa 7 ) (Daa 8 - Daa 7 - )] /(Daa99 - x Daa 25 - ). We define dummy variable RE o idenify firm-years wih large magniude of unexpeced earnings. Analogous o LWCA, RE is defined by ranking firms according o NI wihin each indusry group. Conrol Variables (X, = o ) Prior research has idenified conrol variables ha are relaed o he cross-secional differences in ERCs. We include a oal of eleven conrol variables in our marke reurns regressions. They include size, book-o-marke, and deb o equiy as risk proxies (Fama and French, 992); separae proxies for growh, persisence, and change in book value (Barh e al., 999); and ineracions beween all of hese variables (excep he change in book value) and earnings surprises. Conrol variables are described in Appendix A. We esimae equaion () below separaely for each of our four regression ables (i.e., one each for small posiive earnings changes, small negaive earnings changes, large posiive earnings changes, and large negaive earnings changes). To es hypohesis, we examine regression coefficiens in an esimaion using only hose observaions ha have small and posiive earnings surprises, i.e., he dummy variable for large absolue unexpeced earnings (RE ) = 0 and NI > 0. To es hypohesis 2, we use observaions wih small and negaive earnings surprises, i.e., RE = 0 and NI < 0. To es hypohesis 3, we use observaions wih large and posiive earnings surprises, i.e., RE = and NI > 0. We also es i separaely for observaions wih large and negaive earnings surprises, i.e., RE = and NI < 0.: RET a a NI a RWP NI a RWN NI a RWP a RWN a X () 0,, 2, 3, 4, 5, 5,,

6 38 Invesmen Managemen and Financial Innovaions, Volume 4, Issue 2, 2007 The marginal price response o unexpeced earnings is a, for firms wih small accruals. I is (a, +a 2, ) for firms wih posiive LWCAs. I is (a, + a 3, ) for firms wih negaive LWCAs. A negaive value of a 2, (a 3, ) indicaes ha he marginal price response o earnings is lower for firms wih posiive (negaive) LWCAs. Tess of he hree hypoheses of he sudy are conduced by examining wheher coefficien a 2,, < 0 and a 3, < 0. We esimae each of hese equaions separaely for each year and use Fama and Macbeh (973) ess on our coefficiens. To conrol for exreme observaions affecing cross-secional resuls, we use he DFFITS crieria (Belsley e al., 980, pp ), which enables us o idenify and hen delee observaions ha have a large influence on parameer esimaes. In addiion o esimaing he equaions for each year separaely, we also esimae each equaion using pooled regressions afer adding year dummy variables o allow for year-wise variaion in he inercep. Similar o individual year regressions, we use he DFFITS procedure o ensure ha our resuls are no unduly influenced by exreme observaions. To conrol for heeroscedasiciy in he pooled sample, we examine consisen esimaes of he covariance marix using he Whie (980) procedure. Finally, we conduc sensiiviy analysis o check he robusness of our resuls. 4. Sample Selecion We use financial saemen daa for he period of from Year 200 COMPUSTAT annual daase ha includes indusrial, full coverage, and research files. We obain sock reurn daa from Year 200 CRSP daase. Calculaions of earnings variance and earnings growh require four prior years of daa. Thus he firs year of esimaion is 986. This sample consiss of 4,936 firm-year observaions for a sixeen-year period from 986 o 200. In he full sample, 2,4 firm-year observaions are ranked as small NI firm-years and 20,822 firm-years as large NI firm-years. Of all small NI firm-years, 8,942 (89.7%) firm-years repored profi. Of all large NI firm-years, 2,952 (62.2%) firm-years repored profi. Afer calculaing annual indusry ranks based on he full sample, we selec only hose firms ha repored profis before exra-ordinary iems and special iems 2. The final sample for regressions and ess of hypoheses consiss of firm-years wih posiive ne income, consising of 3,894 firm-year observaions (8,942 small NI and 2,952 large NI firm-years). 5. Resuls Table repors he frequency of small accruals, posiive LWCAs and negaive LWCAs for small and large NI firms in he sample. For firms reporing small increase in earnings (RE = 0 and NI > 0), 8439 firm-years (67%) used small accruals, 944 firm-years (5.5%) used posiive LWCAs and he remaining 295 firm-years (7.5%) used negaive LWCAs. Approximaely equal frequency of posiive and negaive LWCAs suggess ha earnings smoohing (masking he variance) and earnings managemen o repor small increase in earnings (masking he level) are equally likely. For firms reporing a small decrease in earnings (RE = 0 and NI < 0), 395 firmyears (62.%) had small discreionary accruals, 99 firms (8.8%) had posiive LWCAs and he remaining 24 firm-years (9.%) had negaive LWCAs. For firms reporing large increase in earnings (RE = and NI > 0), 342 firm-years (36.5%) had small accruals, 2698 firm-years (28.9%) had posiive LWCAs, and he remaining 3239 firm-years (34.6%) had negaive LWCAs. For firms reporing large decrease in earnings (RE = and NI < 0) 598 firm-years (44.4%) had small accruals, 052 firm-years (29.2%) had posiive LWCAs and he remaining 953 firm-years (26.4%) had negaive LWCAs. The fac ha nearly hree quarers of he firms did no use negaive LWCAs in his las group ends o sugges ha oher means were being used o obain big bahs. The main reason ha small and large NI groups do no have equal number of observaions is because he ranking akes place each year for each indusry. To he exen ha indusry-year groups have odd-numbered firms, inequaliy in he wo groups may resul. 2 As explained earlier, he ranking of firms prior o deleing loss firms is done o ensure ha he abnormal performance is measured relaive o he enire indusry raher han relaive o only profiable firms.

7 Invesmen Managemen and Financial Innovaions, Volume 4, Issue 2, Classificaion of Earnings Changes and Unexpeced Working Capial Accruals Table Magniude of absolue changes in earnings ( NI ) of profi firms Small magniude of NI (8,942 firm-years) Large magniude of NI (2,952 firm-years) Increase/Decrease in earnings Unexpeced Accrual Classificaion Firm- Years Increase in Normal (LWCA = 0) 8,439 earnings (2,578 Large and Posiive (RWP = ),944 firm-years) Large and Negaive (RWN = ) 2,95 Decrease in Normal (LWCA = 0) 3,95 earnings (6,364 Large and Posiive (RWP = ),99 firm-years): Large and Negaive (RWN = ),24 Increase in Normal (LWCA = 0) 3,42 earnings (9,349 Large and Posiive (RWP = ) 2,698 firm-years) Large and Negaive (RWN = ) 3,239 Decrease in Normal (LWCA = 0),598 earnings (3,603 Large and Posiive (RWP = ),052 firm-years) Large and Negaive (RWN = ) 953 Toal Firm-Years 3,894 Noes:. NI = (Change in firm s earnings before exraordinary iems and special iems for fiscal year )/ (marke value of he firm) -. Subscrip is omied everywhere for sake of breviy. 2. Each year firms are ranked according o heir NI wihin heir respecive indusry. Indusries are classified according o Barh e al. (998). NI above (below) he indusry median are classified as large (small) change in earnings. 3. WC = Working capial accrual for firm for fiscal-year = Curren asses ne of cash - curren liabiliies ne of shor erm deb. E(WC ) = Expeced working accrual for firm for fiscal-year = WC - x (Sales / Sales - ) WC = Unexpeced working capial accrual = [WC - E(WC )] / (marke value of he firm) - 4. Each year, firms are ranked according o heir WC wihin heir respecive indusry. Indusries are classified according o Barh e al. (998). Dummy variable LWCA equals when WC is above he indusry median, and zero oherwise. 5. RWP (RWN ) = when LWCA = and WC is posiive (negaive). RWP (RWN ) = 0 oherwise. 6. Afer he ranking, only hose firms ha repored profi were included in he sample. The sample consiss of 3,894 firm-year observaions. To es he firs hypohesis of his sudy, we esimae equaion () using only hose observaions ha have annual profis, small increases in earnings, i.e., small NI and a posiive change in earnings. This resuls in 2,578 firm-year observaions. Table 2 repors he regression esimaes of equaion () for his group. The mean of yearly coefficiens on NI wih small accruals (a ) is 5.6 ( =7.9). The coefficien on RWP *NI, a 2,, is 3.02 ( = 2.36). A negaive and significan coefficien on RWP *NI shows ha he marginal response o unexpeced earnings is significanly lower for firms wih posiive LWCAs (RWP = ) han for firms wih small accruals. The mean of yearly ERCs for he posiive LWCA firms (a, +a 2, ) is 2.59 and is significan ( = 6.37, no repored). This indicaes a 9% decline in he ERC of firms wih posiive LWCAs in comparison o firms wih small accruals. The coefficien on RWN *NI, a 2,, is 3.59 ( = 3.43), suggesing ha he marginal response o unexpeced earnings is smaller for firms wih negaive LWCAs (RWN = ) han for firms wih small accruals. The mean of yearly ERCs for he negaive LWCA firms (a, +a 3, ) is 2.02 and is significan ( = 4.6, no repored). This indicaes a 23% decline in he ERC of firms wih small negaive accruals in comparison o firms wih small discreionary accruals. Thus, LWCAs of eiher posiive or negaive signs are associaed wih reduced ERCs when earnings changes are small increases. Acual number of observaions used in each regression is differen due o eliminaion of influenial observaions hrough he procedure of Belsley e al. described in secion 3 of his paper.

8 40 Invesmen Managemen and Financial Innovaions, Volume 4, Issue 2, 2007 Table 2 Impac of AWCAs on informaion conen of small increase in earnings RET a 0, a, NI a 2, RWP NI a 3, RWN NI a 4, RWP a 5, RWN a 5, X Year-wise Pooled Year Coeff. Mean -saisic Coeff. Whie - saisic Inercep NI RWP NI RWN NI Oher variables RWP RWN x, x, x x, x, x x x, x, x, x, Observaions Ad-Rsq See Noes hrough 6 of Table for definiions of NI, RWP and RWN. 2. Sample in his able consiss of firms ha have (i) profi, i.e NI > 0, (ii) increase in earnings, i.e. NI > 0, and (iii) he increase is small, i.e. NI indusry median. 2,578 firm-years spanning a sixeen-year period from 986 o 200 me hese crieria. 3. RET = Annual reurn of firm for fiscal year, calculaed by compounding monhly reurns from nine monhs before he end of fiscal year, o hree monhs afer he end of fiscal year. 4. Conrol variables for each firm, for fiscal year (Xi,,, i = o ) are defined in Appendix A.. 5. Year-wise regression mean is he mean of annual regression coefficiens over 6 annual regressions. Year-wise regression -saisic is calculaed as he mean of he year-wise coefficien divided by is sandard error, similar o Fama and MacBeh (973). Each regression uses Belsley e al. (980) diagnosic DFFITS o idenify and delee influenial observaions, hence he acual number of observaions used is less han he number of observaions menioned in Noe Pooled regression coefficien esimaes are based on consisen esimaes of he covariance marix using Whie (980) procedure. The regression uses Belsley e al. (980) diagnosic DFFITS o idenify and delee influenial observaions, hence he acual number of observaions used is less han he number of observaions menioned in Noe 2.,

9 Invesmen Managemen and Financial Innovaions, Volume 4, Issue 2, Impac of AWCAs on informaion conen of small decrease in earnings Table 3 Year 986 RET a 0, a, NI a 2, RWP NI a 3, RWN NI a 4, RWP a 5, RWN a 5, X Coeff. Mean Year-wise Pooled -saisic Coeff. Whie - saisic Inercep NI RWP NI RWN NI Oher variables RWP RWN x, x, x x, x, x x, x x, x, x, Observaions Ad-Rsq See Noes hrough 6 of Table for definiions of NI, RWP and RWN. 2. Sample in his able consiss of firms ha have (i) profi, i.e NI > 0, (ii) decrease in earnings, i.e. NI < 0, and (iii) he decrease is small, i.e. NI indusry median. 6,364 firm-years spanning a sixeen-year period from 986 o 200 me hese crieria. 3. RET = Annual reurn of firm for fiscal year, calculaed by compounding monhly reurns from nine monhs before he end of fiscal year, o hree monhs afer he end of fiscal year. 4. Conrol variables for each firm, for fiscal year (Xi,,, i = o ) are defined in Appendix A. 5. Year-wise regression mean is he mean of annual regression coefficiens over 6 annual regressions. Year-wise regression -saisic is calculaed as he mean of he year-wise coefficien divided by is sandard error, similar o Fama and MacBeh (973). Each regression uses Belsley e al. (980) diagnosic DFFITS o idenify and delee influenial observaions, hence he acual number of observaions used is less han he number of observaions menioned in Noe Pooled regression coefficien esimaes are based on consisen esimaes of he covariance marix using Whie (980) procedure. The regression uses Belsley e al. (980) diagnosic DFFITS o idenify and delee influenial observaions, hence he acual number of observaions used is less han he number of observaions menioned in Noe 2.,

10 42 Invesmen Managemen and Financial Innovaions, Volume 4, Issue 2, 2007 Pooled regression resuls repored in he las wo columns of Table 2 provide evidence similar o he separae year regression resuls. We use Whie s mehod for consisen esimae of variance-covariance marix for calculaing -saisics in all of he pooled regressions. The ERC for firms wih small increase in earnings and small discreionary accruals is 2.47 (Whie s = 9.50). Coefficien a 2, is 3.35 (Whie s = 3.88) which suggess a 27% decline in ERCs for posiive LWCAs. Coefficien a 3, is 3.24 (Whie s = 4.5) which indicaes a 26% decline in ERCs for negaive LWCAs. Negaive and significan values of coefficiens a 2, and a 3, imply a reecion of he null of he firs hypohesis, H,0 in favor of is alernaive, H,A. Overall, he resuls of Table 2 sugges ha firms ha repor small increases in earnings bu have large discreionary accruals ha are eiher posiive or negaive are viewed negaively by he marke. The size of discreionary working capial accruals significanly moderaes marke responses. To es he second hypohesis, we selec profi firms ha repored a small decrease in earnings (RE = 0, NI <0). There were 6,364 firm-year observaions ha me his crierion. Resuls of year-wise regressions, repored in Table 3, show ha he mean value of annual ERCs for profiable firms ha repored small decrease in earnings using small accruals (coefficien a )is 4.3, compared o 5.6 wih small earnings increases, and i is marginally significan ( =.84). The coefficien a 2, is.22 ( = 0.95) indicaing ha here is no decline in ERCs of firms wih posiive LWCAs. The coefficien a 3, is.5, and is no significan, (=0.87) indicaing ha here is no decline in ERCs of firms wih negaive LWCAs. Resuls of pooled regressions show ha he coefficien on NI is 4.02 and is significan (Whie s = 2.82), bu he coefficiens on RWP *NI or RWN *NI are no significan. These resuls indicae ha he use of large accruals, eiher income increasing or income decreasing, does no cause a furher decline in he ERC of profi firms ha repored a small decrease in earnings. Thus, he overall resuls in Table 3 for boh year-wise regressions and he pooled regression resuls fail o reec he null of he second hypohesis H 2,0 in favor of is alernaive, H 2,A. To es he hird hypohesis of his sudy, we selec profi firms ha had large increases (Table 4) or decreases (Table 5) in earnings. Resuls of Table 4 are based on 9,349 firm-year observaions. Table 4 shows ha he mean coefficien on NI(a ) from annual regressions is 0.97 and is significanly differen from zero ( = 2.5). In he pooled regression, he coefficien on NI is.04 and also significan (Whie s = 6.8). The coefficien a 2,, is 0.27 ( =.03) suggesing ha here is no significan decline in ERCs for firms wih posiive LWCA. The coefficien a 3, is -0.7 ( = 0.7) suggesing ha here is no significan decline in ERCs for firms wih negaive LWCAs. Pooled regression resuls also show ha coefficiens on RWP *NI and RWN *NI respecively are negligible and insignifican. Resuls of Table 5 are based on 3,603 firm-year observaions ha repored profi and had a large decrease in earnings. Table 5 shows ha he mean of coefficien on NI(a ) is 0.82 and is no significanly differen from zero ( = 0.98). In he pooled regression, he coefficien on NI is 0.82 and also no significanly differen from zero (Whie s =.5). These resuls show ha when firms repor large decreases in earnings, he informaion conen of earnings (as measured by he saisical significance of he corresponding ERCs) is negligible. Neing he wo coefficiens above for he separae year regressions, he ERC for firms wih large posiive accruals is 0.5 and saisically insignifican ( = 0.8 no repored); he ERC for firms wih large negaive accruals he ERC is 0.4 and no significan eiher ( = 0.4). Ineresingly, he difference beween firms wih small accruals and posiive LWCA is saisically significan given he significance of coefficien on RWP for year-wise regressions as well as for pooled regression ( = 2.04 and Whie s = 2.05 respecively), while he difference beween firms wih small accruals and negaive LWCAs is saisically insignifican boh in year-wise as well as in pooled regressions. Overall, he resuls of Table 4 and Table 5 fail o reec he null of hypohesis 3, H 3,0 in favor of is alernaive, H 3,A. The low overall ERCs in Tables 4 and 5 are consisen wih Freeman and Tse (992) and Ali (994) who find ha earnings shocks are valued less by he marke.

11 Invesmen Managemen and Financial Innovaions, Volume 4, Issue 2, RET Impac of AWCAs on informaion conen of large increase in earnings a 0, a, NI a 2, RWP NI a 3, RWN NI a 4, RWP a 5, RWN a 5, X Year-wise Pooled Table 4 Year Coeff. Mean -saisic Coeff. Whie - saisic Inercep NI RWP NI RWN NI Oher variables RWP RWN x, x, x x, x, x x, x x, x, x, Observaions Ad-Rsq See Noes hrough 6 of Table for definiions of NI, RWP and RWN. 2. Sample in his able consiss of firms ha have (i) profi, i.e NI > 0, (ii) increase in earnings, i.e. NI > 0, and (iii) he increase is large, i.e. NI > indusry median. 9,349 firm-years spanning a sixeen-year period from 986 o 200 me hese crieria. 3. RET = Annual reurn of firm for fiscal year, calculaed by compounding monhly reurns from nine monhs before he end of fiscal year, o hree monhs afer he end of fiscal year. 4. Conrol variables for each firm, for fiscal year (Xi,,, i = o ) are defined in Appendix A. 5. Year-wise regression mean is he mean of annual regression coefficiens over 6 annual regressions. Year-wise regression -saisic is calculaed as he mean of he year-wise coefficien divided by is sandard error, similar o Fama and MacBeh (973). Each regression uses Belsley e al. (980) diagnosic DFFITS o idenify and delee influenial observaions, hence he acual number of observaions used is less han he number of observaions menioned in Noe Pooled regression coefficien esimaes are based on consisen esimaes of he covariance marix using Whie (980) procedure. The regression uses Belsley e al. (980) diagnosic DFFITS o idenify and delee influenial observaions, hence he acual number of observaions used is less han he number of observaions menioned in Noe 2.,

12 44 Invesmen Managemen and Financial Innovaions, Volume 4, Issue 2, 2007 Impac of AWCAs on informaion conen of large decrease in earnings Table 5 RET a 0, a, NI a 2, RWP NI a 3, RWN NI a 4, RWP a 5, RWN a 5, X Year-wise Pooled Year Coeff. Mean -saisic Coeff. Whie - saisic Inercep NI RWP NI RWN NI Oher variables RWP RWN x, x, x x, x, x x, x x, x, x, Observaions Ad-Rsq See Noes hrough 6 of Table for definiions of NI, RWP and RWN. 2. Sample in his able consiss of firms ha have (i) profi, i.e NI > 0, (ii) decrease in earnings, i.e. NI < 0, and (iii) he decrease is large, i.e. NI is above he indusry median. 3,603 firm-years spanning a sixeen-year period from 986 o 200 me hese crieria. 3. RET = Annual reurn of firm for fiscal year, calculaed by compounding monhly reurns from nine monhs before he end of fiscal year, o hree monhs afer he end of fiscal year. 4. Conrol variables for each firm, for fiscal year (Xi,,, i = o ) are defined in Appendix A. 5. Year-wise regression mean is he mean of annual regression coefficiens over 6 annual regressions. Year-wise regression -saisic is calculaed as he mean of he year-wise coefficien divided by is sandard error, similar o Fama and MacBeh (973). Each regression uses Belsley e al (980) diagnosic DFFITS o idenify and delee influenial observaions, hence he acual number of observaions used is less han he number of observaions menioned in Noe Pooled regression coefficien esimaes are based on consisen esimaes of he covariance marix using Whie (980) procedure. The regression uses Belsley e al (980) diagnosic DFFITS o idenify and delee influenial observaions, hence he acual number of observaions used is less han he number of observaions menioned in Noe 2.,

13 Invesmen Managemen and Financial Innovaions, Volume 4, Issue 2, Sensiiviy analysis () We repea our analysis using a random walk model for working capial accruals, insead of one based on he expeced relaion beween accruals and sales. We find ha he conclusions are unchanged. (2) We include earnings levels (scaled by marke value) as a subsiue variable for change in book value (Conrol variable X 6,, see Appendix for deails). Using earnings levels in lieu of change in book value makes no difference in our resuls. (3) We resored loss firms o our sample bu he resuls are qualiaively similar. 6. Conclusions We examine marke reacions o unexpeced earnings influenced by large unexpeced working capial accruals (LWCAs). Focusing on nonlinear relaions beween reurns and LWCA, prior work has found ha marke reacions are generally weaker for LWCA han for small discreionary working capial accruals. We exend he exan lieraure by examining he marke s reacion o posiive and negaive earnings changes influenced by LWCAs and predic circumsances where LWCAs lead o varying marke expecaions of earnings qualiy. Prior work generally assumes ha LWCAs have a uniform impac on marke expecaions. We examine eigh siuaions ha combine posiive or negaive LWCAs wih earnings changes ha are eiher posiive or negaive and are of eiher small or large absolue magniudes. We argue ha he marke is more likely o suspec earnings managemen and, herefore, view earnings as being of lower qualiy when firms repor small increases in earnings wih he help of posiive or negaive LWCAs. According o he lieraure, managers are srongly moivaed o produce small earnings increases insead of earnings declines (i.e., by using posiive LWCAs), or produce small earnings increases insead of posiive earnings shocks (i.e., by using negaive LWCAs). The remaining six siuaions are no consisen wih radiional managerial incenives suggesed by he lieraure and, herefore, do no necessarily imply earnings managemen. For example, when here are large increases in earnings using posiive LWCAs, managerial accouning choices are inconsisen wih he moivaion prediced by he bonus hypohesis and wih expecaions ha managers reain fuure flexibiliy o manage earnings. Similarly, when managers repor small decreases in earnings using posiive or negaive LWCAs, heir acions are inconsisen wih he expeced desire o repor increases in earnings. These apparen inconsisencies may be a resul of error in he LWCA measure or unobservable moivaions by managemen. Consisen wih our predicions, we find ha he marke discouns unexpeced earnings when here are small increases in earnings using negaive LWCA (i.e., masking earnings variance or smoohing) or posiive LWCA (i.e., masking lower earnings levels). We find lile or no evidence ha posiive or negaive LWCAs lead o lower ERCs in he remaining six siuaions. The failure of posiive or negaive LWCAs o reduce ERCs in hese oher cases may be due o an absence of earnings managemen, error in he measure, diversiy in opinions among invesors abou LWCAs being a manifesaion of earnings managemen, or failure of he marke o deec earnings managemen. References. Ali, A., 994, The incremenal informaion conen of earnings, working capial from operaions, and cash flows, Journal of Accouning Research 34, Barh, M.E., W.H. Beaver, and W.R. Landsman, 998, Relaive valuaion roles of equiy book value and ne income as a funcion of financial healh, Journal of Accouning and Economics 25, Barh, M.E., J. A.Ellio, and M.W. Finn, 999, Marke rewards associaed wih paerns of increasing earnings, Journal of Accouning Research 37, Belsley, D.A., E. Kuh, and R.E. Welsch, 980, diagnosics (John Wiley, New York).

14 46 Invesmen Managemen and Financial Innovaions, Volume 4, Issue 2, Brooks, L.D., Buckmaser, D.A., 976, Furher evidence of he ime series properies of accouning income, The Journal of Finance, 3, Burgsahler, D., and I. Dichev, 997, Earnings managemen o avoid earnings decreases and losses, Journal of Accouning and Economics 24, Carslaw, A., 988, Anomalies in income numbers, Evidence of goal oriened numbers, The Accouning Review 63, Collins, D.W., and S.P. Kohari, 989, A heoreical and empirical analysis of he deerminans of cross-secional and iner-emporal differences in earnings response coefficiens, Journal of Accouning and Economics, Dechow, P., 994, Accouning earnings and cash flows as measures of firm performance: he role of accouning accruals, Journal of Accouning and Economics 8, Dechow, P., and D. Skinner. 2000, Earnings managemen, Reconciling he views of accouning academics, praciioners, and, regulaors, Accouning Horizon 4, DeFond, M.L., and C.W. Park, 200, The reversal of abnormal accruals and marke valuaion of earnings surprises, The Accouning Review 76, Degeorge F., J. Pael and R. Zeckhauser, 999, Earnings managemen o exceed hresholds, Journal of Business 72, Fama, E.R., and K.R. French 992, The cross-secion of expeced reurns, Journal of Finance 47, Fama, E.R., and J.D. MacBeh,. 973, Risk reurn and equilibrium, Empirical ess. Journal of Poliical Economy 7, Freeman, R. N., Ohlson, J. A., Penman, S.H., Book rae-of-reurn and predicion of earnings changes: An empirical invesigaion, Journal of Accouning Research, 20, Freeman, R.N., and S.Y. Tse, 992, The muli-period informaion conen of accouning earnings: Confirmaions and conradicions of previous earnings repors. Journal of Accouning Research 27, Healy, P., 985, The effec of bonus schemes on accouning decisions, Journal of Accouning and Economics 7, Kohari, S.P., A.J. Leone, and C.E. Wasley, 2004, Performance mached discreionary accruals, Journal of Accouning and Economics 39, Masumoo, D.A. 2002, Manager s incenives o avoid negaive earnings surprises, The Accouning Review 77, Mendenhall, R.R., 2002, How naïve is he marke s use of firm-specific earnings informaion? Journal of Accouning Research 40, Sloan, R.G. 996, Do sock prices fully reflec informaion in cash flow and accruals abou fuure earnings? The Accouning Review 7, Schipper, K., 989, Commenary, Earnings managemen. Accouning Horizons 3, Whie G.I., A.C. Sondhi, and D. Fried, 2003, The analysis and use of financial saemens (John Wiley, New York). 24. Whie, H., 980, A heeroscedasiciy-consisen covariance marix esimaor and a direc es for heeroscedasiciy, Economerica 48,

15 Invesmen Managemen and Financial Innovaions, Volume 4, Issue 2, APPENDIX A. DESCRIPTION OF CONTROL VARIABLES Variables for proxies of risk Based on prior lieraure (Fama and French 992) we use hree proxies o conrol for risk characerisics of a firm. These are book-o-marke (X ), deb-o-equiy (X 2 ), and size a he beginning of he period (X 3 ). X = Book value of firm ()/Marke Value (-) = (Daa 27) /(Daa 99 - x Daa 25 - ) X 2 = Deb/Book Value of firm =(Daa 2 Daa 27 )/(Daa 27 ) X 3 = Size a he beginning of he period = log (Daa99 - x Daa 25 - ) Conrol for growh and variabiliy in earnings Prior research (Barh, Ellio and Finn, 999) has shown ha growh and variabiliy of earnings are deerminans of reurns-earnings relaionship. Barh e al (999) argue ha earnings variabiliy is a measure of operaing risk. Accordingly, we define he following wo conrol variables X 4, and X 5, respecively: X 4 = Growh in Book value over previous hree years BV 27 = 3 Daa 3 BV Daa 4 X 5 = Sandard deviaion of earnings change over previous hree years 3 2 = NIk NIk., where, 2 k NI k NI, = Change in Earnings before exraordinary iems and special iems, divided by marke value a he beginning of he period. = (Daa 8 Daa 7 ) (Daa 8 - Daa 7 - )] /(Daa99 - x Daa 25 - ). Conrol for change in book value Barh e al. (999) sugges ha change in book value has significan impac on ERCs. Correspondingly, we use change in book value scaled by he marke value as an addiional conrol variable. X 6, = Change in book value divided by marke value a he beginning of he period =(Daa 27 Daa 27 - )/(Daa99 - x Daa25 - ) Ineracion of conrol variables wih change in earnings We are also ineresed in each conrol variable s marginal response o change in earnings. Hence we inerac each conrol variable (excep change in book value, conrol variable X 6, ) wih change in earnings. Since change in book value is a proxy for earnings, we do no inerac i wih change in earnings. The ineracion erms creae he following addiional five conrol variables, X 7, hrough X,. X 7, = X, x NI X 8, = X 2, x NI X 9, = X 3, x NI X 0, = X 4, x NI X, = X 5, x NI 27 Laer in sensiiviy analysis, we replace change in book value wih earnings levels. Resuls are similar. 4