stable shareholdings, the decision horizon problem and earnings smoothing

Journal of Business Finance & Accounting

Journal of Business Finance & Accounting, 000, 1–31, XXX 2014, 0306-686Xdoi: 10.1111/jbfa.12091

Stable Shareholdings, the DecisionHorizon Problem and Earnings

Smoothing

AKINOBU SHUTO AND TAKUYA IWASAKI∗

Abstract: Prior studies argue that stable shareholders do not encourage firm managers tomanage their earnings to achieve short-term earnings goals. They also state that firm managerswith stable shareholders have an incentive to report smooth earnings to maintain long-termrelationships with such shareholders. We focus on cross-shareholdings and stable shareholdingsowned by financial institutions as stable shareholdings in Japan, and investigate the effect ofthese ownership structures on earnings management patterns. Specifically, we hypothesize thatstable shareholdings are positively associated with the informational components of earningssmoothing. Consistent with our hypothesis, we first find that as stable shareholdings increase,managers are more likely to conduct earnings smoothing that provides useful information tostable shareholders. Further, our additional analysis shows that stable shareholdings reduceincentives for managers to cut discretionary expenditures to meet short-term earnings bench-marks, implying that stable shareholdings could reduce the possibility of a myopic problem.These results suggest that managers with stable shareholdings tend to report smoother and lessvolatile earnings, and do not tend to pursue earnings management to attain short-term earningstargets.

Keywords: stable shareholdings, earnings smoothing, horizon problem, myopic problem

1. INTRODUCTION

Bushee (1998) provides evidence that institutional ownership with short-term invest-ment horizons induces managers to conduct earnings management to attain short-term earnings goals. Such management behavior is often called the myopic problemor the decision horizon problem (Smith and Watts, 1982; Narayanan, 1985; Stein, 1989;

∗The first author is at the Research Institute for Economics and Business Administration, Kobe University,Kobe, Hyogo, Japan. The second author is at the Faculty of Commerce, Kansai University, Suita, Osaka,Japan. The authors appreciate the helpful comments and suggestions received from Martin Walker (editor),an anonymous reviewer, Nobuhiro Asano, Masahiro Enomoto, Hiroyuki Ishikawa, Souichi Matsuura, Shin’yaOkuda, Koji Ota, Shota Otomasa, Fumihiko Kimura, Hiromi Wakabayashi, Tatsushi Yamamoto, HidetsuguUmehara, Atsushi Shiiba, Hironori Fukukawa, Takashi Yaekura, Takashi Obinata, Masaki Yoneyama, KeiichiOishi, and the participants of the workshops conducted at Osaka Gakuin University (Positive AccountingTheory Workshop), Tokyo University, and Chuo University. Shuto acknowledges the financial support fromthe Zengin Foundation for Studies on Economics and Finance. All errors are the responsibility of the authors.

Address for correspondence: Akinobu Shuto, Research Institute for Economics and Business Administra-tion, Kobe University 2-1, Rokkodaicho, Nadaku, Kobe 657-8501, Japan.e-mail: [email protected]

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2 SHUTO AND IWASAKI

Dechow and Sloan, 1991; Porter, 1992; Bushee, 2001; Cheng, 2004; Dikolli et al., 2009;Cadman and Sunder, 2014). In contrast, some studies and anecdotes argue that stableshareholdings with long-term investment horizons restrict managers from engaging insuch myopic behavior, and create incentives for these managers to pursue long-termstable earnings (Abegglen and Stalk, 1985; Porter, 1992; Jacobson and Aaker, 1993;Osano, 1996).

This study examines the implications of the aforementioned argument in relationto stable shareholdings from the viewpoint of earnings management. In particular,we focus on 1) cross-shareholdings, and 2) stable shareholdings owned by financialinstitutions in the Japanese equity market, and investigate the effect of these ownershipstructures on the major earnings management pattern, earnings smoothing. We focuson the corporate ownership structure of Japanese firms because it has features thatare more relevant to our investigation compared to the structures of US firms. Adistinctive feature of the Japanese stock market is that stable shareholdings with longinvestment horizons and foreign shareholdings with short investment horizons existsimultaneously. This unique ownership structure provides a useful research setting forstudying the relationship between earnings management and the decision horizonproblem.

In light of the theoretical argument of prior studies, we predict that stableshareholders with long-term investment horizons and firm managers have incentives toreport stable earnings strings through earnings management. First, from the perspec-tive of stable shareholders, we predict that stable shareholders do not encourage firmmanagers to pursue myopic behavior, and so firm managers do not have an incentiveto inflate their earnings to achieve their short-term earnings goals. In Japan, there arestable shareholders that are highly concentrated among the corporate stockholderswith financial institutions. In this case, firms are closely connected; they affect eachother through cross-holdings of equity ownership, and generally depend on a largecommercial bank (i.e., the main bank) for their primary banking needs (Hoshi et al.,1990, 1991; Aoki and Patrick, 1994; Douthett and Jung, 2001; Arikawa and Miyajima,2007; Shuto and Kitagawa, 2011).1

One of the important features about the stable shareholding arrangements madethrough cross-shareholdings and financial institutions is the implicit long-term contractsamong them. Sheard (1994, p. 318) defines “stable shareholding” as implicitly con-tracting away some of the property rights associated with shareholding; in particular,property rights pertaining to the transfer of shares or the exercise of corporatecontrol. In general, stable shareholders in Japan play the role of a “friendly” insider,sympathetic to incumbent managers and agreeing not to sell shares to third parties.Managers are able to develop operations according to a long-term perspective becausestable shareholdings decrease the threat of hostile takeovers and maintain long-termbusiness relationships (Abegglen and Stalk, 1985; Porter, 1992; Osano, 1996). Thus,firm managers do not have an incentive to inflate their earnings to achieve their short-term earnings goals because stable shareholders do not pressurize them to pursueshort-term earnings.

Second, from the perspective of managerial incentive, we predict that firm man-agers with stable shareholders are more likely to report stable earnings strings, therebyconveying credible information about themselves to stable shareholders in order to

1 It is widely known that the keiretsu system is the most typical form of organization in such corporate groups.

C© 2014 John Wiley & Sons Ltd

THE DECISION HORIZON PROBLEM AND EARNINGS SMOOTHING 3

maintain a long-term relationship with them. Because stable shareholders implicitlywaive the right to exercise corporate control, stable shareholdings could provide a cer-tain discretion to managers. This might encourage managers to pursue opportunisticbehavior to increase their private benefits, and by so doing, damage long-term firmvalue. However, it is unlikely that managers engage in such opportunistic behaviorbecause prior studies argue that passive monitoring behavior by stable shareholders(i.e., restrictions on the sale of shares or the exercise of corporate control) is state-contingent (Aoki, 1990; Sheard, 1994). In particular, prior studies provide evidencesuggesting that while stable shareholders never intervene in the management of firmsas long as performance is good, the reporting of extremely bad performance promptssuch shareholders to make various management interventions (Kaplan and Minton,1994; Kang and Shivdasani, 1995). Further, cross-shareholdings have been decliningamong Japanese firms, especially since the 1990s, because of changes to institutionalenvironments such as the introduction of mark-to-market accounting for marketablesecurities and the financial crisis.

The above argument suggests that the relationship between a firm’s futureperformance and stable shareholding will be one of equilibrium (Sheard, 1994,p. 411), meaning that stable shareholders might modify their stable relationship witha firm if they perceive a risk regarding the firm’s business prospects. Because ofan information asymmetry between stable shareholders and firm managers, stableshareholders cannot observe all of a firm’s private information, and thus cannot knowwhether firm managers are engaging in opportunistic behavior. In an informationenvironment, stable shareholders would consider their relationship with a firm tobe based on their perception of the firm’s business prospects and ability to fulfill itsobligations (Kreps et al., 1982; Raman and Shahrur, 2008; Dou et al., 2013). Therefore,if firm managers wish to maintain a long-term relationship with stable shareholders,managers must convey credible information about themselves to stable shareholders.

In order to convey credible information, earnings smoothing can be a usefulmethod for implicit contracting because managing accruals to smooth earnings lowersstable shareholders’ perceived variance of a firm’s underlying performance (Truemanand Titman, 1988). First, following the argument of Dou et al. (2013, p. 1,633), weexpect that a more stable earnings stream reduces the stable shareholders’ estimationof risk about a firm’s future cash flow, which helps to ensure a long-term relationshipbetween the firm and its stable shareholders. Second, we also expect that a smootherearnings stream in the current period reduces the stable shareholders’ perceived riskthat firm managers will engage in opportunistic behavior in the future. Consequently,smoother earnings in the current period increase stable shareholders’ willingness tomaintain a long-term relationship with a firm.

In accordance with the above arguments, the relationship between stable sharehold-ing and earnings management is summarized as follows: 1) stable shareholders do notencourage firm managers to inflate their earnings to achieve their short-term earningsgoals; and 2) firm managers who wish to maintain a long-term relationship withstable shareholders have an incentive to smooth earnings. Consequently, consideringthe above relationship, we hypothesize that firm managers with stable shareholders aremore likely to report stable earnings strings.

We predict that stable shareholdings are positively associated with earnings smooth-ing behavior because they decrease earnings volatility. In testing our hypothesis, weextract the informational component of earnings smoothing because our hypothesis


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development assumes that managers use earnings smoothing to convey credible infor-mation about the future viability of operations to stable shareholders. By employingthe method used by prior studies (Tucker and Zarowin, 2006; Dou et al., 2013), wedecompose income smoothing into “informational” and “garbling” components, andpredict that the relationship between stable shareholdings and earnings smoothingwill be explained primarily by the informational component of related incomesmoothing. This is because Demski (1998) argues that the informational role ofearnings smoothing refers to the efficient behavior of managers who signal privateinformation about future performance. Consistent with the hypothesis, we reveal thatstable shareholdings are positively associated with the informational component ofearnings smoothing.

Further, our additional analysis, which aims to replicate prior studies on discre-tionary expenditures, reveals that stable shareholdings reduce incentives for managersto cut discretionary expenditures, such as R&D and advertising expenses, to meetshort-term earnings benchmarks. In other words, stable shareholdings could reducethe possible occurrence of the myopic problem, thereby supporting our predictionthat stable shareholdings restrict managers from engaging in only myopic behavior.These results suggest that stable shareholdings in Japan create less volatile, andtherefore stable earnings strings through earnings management.

This study contributes to the literature and understanding of accounting practice.First, our study develops the findings of prior studies that examine the relationshipbetween ownership structure and earnings management by adding empirical evidenceon the investment horizon. Although many studies focus on the relationship betweenownership structure and discretionary accruals in US firms (Warfield et al., 1995;Chung et al., 2002; Cornett et al., 2008) and Japanese firms (Douthett and Jung, 2001;Teshima and Shuto, 2008), few examine the effect of ownership structure on earningsmanagement from the investment horizon perspective.2

Bushee (1998) is the only study to identify that institutional ownership with short-term decision horizons leads to earnings management aimed at achieving short-termearnings goals. Our study clearly differs from this prior study in several ways. To thebest of our knowledge, ours is the first study that examines the economic consequencesof stable shareholdings with long-term investment horizons and long-term businessprospects in the context of earnings management. Both Bushee (1998) and this studyanalyze the presence of institutional shareholdings; however, the two studies havecontrary results. Our results indicate that the effect of the investment horizon is criticalwhen discussing the effect of institutional ownership.

Further, we focus on earnings smoothing, especially the informational compo-nent of it, as a form of earnings management used by managers. Bushee (1998)assumed earnings management to be managerial opportunistic behavior and focusedon whether earnings management exists because of the differences in ownershipstructure. However, we reveal that informational earnings smoothing is allowed with

2 A few studies have examined the relationship between transitional institutional ownership and CEOcompensation contracting (Dikolli et al., 2009; Cadman and Sunder, 2014). Dikolli et al. (2009) providedevidence that firms with short-horizon incentives design compensation contracts to mitigate such decisionhorizon problems. In contrast, Cadman and Sunder (2014) showed that short-horizon, influential share-holders provide managers with explicit short-horizon incentives through compensation contracts in orderto sell their stocks. Further, in the earnings management context, Gopalan et al. (2013) indicated thatmanagers with shorter-duration pay contracts have a stronger tendency to use discretionary accruals toincrease short-term earnings.



institutional stable shareholdings, which advances our understanding of earningsmanagement patterns.

Second, we contribute to research on the informational versus garbling compo-nents of earnings smoothing by providing evidence that accounting information hasan important function in implicit long-term contracts with stable shareholders. We findthat firm managers use smoother earnings to maintain a long-term relationship withtheir stakeholders, which is consistent with the argument that earnings smoothing canplay an informational role by serving as an efficient form of communication regardingmanagers’ private beliefs about future earnings (Tucker and Zarowin, 2006; Dou et al.,2013).

The remainder of this paper is organized in the following manner. Section 2summarizes prior studies and develops the hypothesis. Section 3 explains the researchdesign for testing our hypothesis. Section 4 outlines the sample selection procedureand describes the variables used in this analysis. Section 5 reports the empirical resultson the relationship between stable shareholdings and earnings management. Section 6summarizes the results of additional analyses. Finally, section 7 concludes the studywith a summary.

2. PRIOR STUDIES AND HYPOTHESIS DEVELOPMENT

(i) The Decision Horizon Problem and Earnings Management

Prior studies provide evidence that the managerial decision horizon problem leadsto earnings management behavior. Dechow and Sloan (1991) indicate that managersreduce R&D spending to increase short-term earnings when they approach retirement.Baber et al. (1991) find that managers reduce R&D expenses to opportunistically boostearnings and avoid earnings decreases and losses. As aforementioned, such behavior isusually called the myopic problem or the decision horizon problem (Smith and Watts,1982; Narayanan, 1985; Stein, 1989; Dechow and Sloan, 1991; Porter, 1992; Cheng,2004).

Cheng (2004) examines whether compensation committees deter an opportunisticreduction in R&D expenses when facing decision horizon and myopic problems. Theresults show that the association between changes in R&D spending and changes inCEO compensation is significantly positive in the presence of these two problems,and is insignificant in their absence. This suggests that compensation committeesrespond to potential opportunistic reductions in R&D spending. Mande et al. (2000)reveal that Japanese managers in several industries adjust their R&D budgets accordingto short-term performance. Japanese managers are believed to differ from their UScounterparts in terms of R&D strategy; however, the results of Mande et al. show thatJapanese managers also have an incentive to engage in myopic behavior, as is the casewith US managers.

Further research reveals that ownership structure provides an opportunity forearnings management because it can affect firms’ decision horizons. Bushee (1998)indicates that concentrated ownership by “transient” institutions with short investmenthorizons significantly increases the likelihood that managers will cut R&D to meetearnings benchmarks. According to Bushee, concentrated institutional ownership,with heavy institutional trading based on current earnings, leads to myopic investment


6 SHUTO AND IWASAKI

behavior by managers (Bushee, 1998, p. 307). Bushee (2001) and Matsumoto (2002)also provide evidence suggesting that firms with higher transit institutional ownershipare more likely to meet or exceed expectation at the earnings announcement.Overall, the results suggest that decision horizon and myopic problems will lead toopportunistic discretionary behavior to meet short-term earnings goals rather than tothe maximization of long-term value.

(ii) Stable Shareholding, Investment Horizon and Stable Earnings String

Bushee’s (1998) analysis is closely related to our study because he investigates therelationship between ownership structure and discretionary behavior. While Bushee(1998) focuses on the relationship between shareholdings with short investment hori-zons and earnings management, this study examines the effect of stable shareholdingswith long, or no short-term, investment horizons on earnings management behavior. Aunique feature of Japanese ownership structure is that a large number of shareholdersin the Japanese equity market are dominated by stable shareholding, which comprises1) cross-shareholdings, and 2) stable shareholdings owned by financial institutions(Hoshi et al., 1990, 1991; Aoki and Patrick, 1994; Douthett and Jung, 2001; Shuto andKitagawa, 2011).3

Stable shareholding arrangements through cross-shareholdings and financial insti-tutions involve long-term contracts between firms and stable shareholders, but arebased on implicit arrangements. Because shareholders with cross-shareholdings arefirms’ trading partners, and these groups of firms maintain long-term relationships byexchanging equity stakes in each other, reciprocal voting rights are created (Osano,1996; Isagawa, 2007). The main banks are representative stable shareholders of finan-cial institutions and have a close relationship with firms as creditors and shareholders.In economic terms, “stable shareholding” can be interpreted as implicitly contractingaway some of the property rights associated with shareholding; in particular, propertyrights pertaining to the transfer of shares or the exercise of corporate control(Sheard, 1994, p. 318). Specifically, Sheard (1994) summarizes the behavior of stableshareholders as follows. First, stable shareholders hold shares as a “friendly” insider,sympathetic to incumbent management. Second, they agree not to sell shares tothird parties who are unsympathetic to incumbent management, particularly hostiletakeover bidders, or bidders trying to accumulate strategic parcels of shares. Finally,they agree, in the event that a disposal of shares is necessary, to consult the firms, or atleast to give notice of their intention to sell.

Because stable shareholdings strengthen the stability of firm management bydecreasing the threat of hostile takeovers and maintaining long-term business re-lationships, they permit managers to develop operations according to a long-termperspective. Studies argue that these stable shareholders can prevent managers fromengaging in opportunistic myopic behavior, and can encourage them to make long-term investments or financial decisions that focus on long-term firm value (Abegglen

3 In addition, some recent studies for examining firms in other Asian countries provide evidence thatunique ownership structures affect managers’ earnings management behaviors. For example, Wang andYung (2011) indicate that Chinese state-owned firms have lower levels of abnormal accruals and betteraccruals quality than privately owned firms. Further, Wang and Lin (2013) show that the availability ofinternal capital markets due to a pyramidal ownership structure in Taiwan reduces earnings managementresulting from higher leverage.



and Stalk, 1985; Porter, 1992; Osano, 1996). Jacobson and Aaker (1993) also contendthat because some prospective shareholders in Japan are business partners (often fromthe same industrial group) and related banks, these investors have better informationabout the long-term prospects of a business and can detect myopic managementbehavior and are therefore more willing to accept lower current-term earnings. Thus,stable shareholders do not encourage firm managers to pursue myopic behavior, andso firm managers do not have an incentive to inflate their earnings to achieve short-term earnings goals.

However, it is likely that stable shareholders delegate considerable discretion toincumbent management because they implicitly waive the right to exercise corporatecontrol. Firm managers might also act to increase their private benefits and therebydamage long-term firm value. Of course, stable shareholders do not allow managers toconduct such opportunistic behavior without limitation. In this context, it should benoted that the passive monitoring behavior of stable shareholders (i.e., restrictionson the sale of shares or the exercise of corporate control) is state-contingent. Inparticular, prior studies advocate that stable shareholders refrain from intervening infirm management or from arranging such intervention when a firm is performing well;however, if a firm is performing badly, the principal shareholders have the incentiveand means to exert influence on management (Aoki and Patrick, 1994; Sheard, 1994).For example, empirical evidence indicates that while the main banks never intervenein the management of borrowing firms as long as these firms are financially sound,the reporting of extremely bad performance prompts the banks to engage in variousmanagement interventions such as recontracting, changing the CEO, and installingdirectors chosen by them (Kaplan and Minton, 1994; Kang and Shivdasani, 1995). Inthe worst cases, the main banks might abandon any attempt to rescue their borrowingfirms and instead choose to liquidate them. This disciplinary mechanism differs fromthe Anglo-American (market-oriented) system based on takeovers and bankruptcyprocedures (Arikawa and Miyajima, 2007).

Furthermore, because of changes to the institutional environment such as theintroduction of mark-to-market accounting for marketable securities and the financialcrisis, cross-shareholdings have been declining among Japanese firms, especially sincethe 1990s. Sheard (1994, p. 411) suggests that good management performance andthe delegation of control by stable shareholders can be sustained as equilibriumbehavior, but such equilibrium is unlikely to be sustained if management abuses itsdiscretion. This means that stable shareholders have the option of changing theirstable relationship with a firm by selling their shares if they perceive a risk aboutthe firm’s business prospects. Thus, firm managers are required to convey credibleinformation about themselves to stable shareholders in order to maintain a long-termrelationship with them. Based on the above argument, the relationship between stableshareholding and earnings management is summarized as follows. First, shareholdersdo not induce firm managers to inflate their earnings to achieve short-term earningsgoals. Second, managers have an incentive to smooth earnings to maintain a long-termrelationship with stable shareholders.

(iii) Hypothesis Development

Because there is an information asymmetry between stable shareholders and firmmanagers, stable shareholders cannot observe all of a firm’s private information. Thus,


8 SHUTO AND IWASAKI

it becomes difficult for stable shareholders to know when and whether firm managersare engaging in opportunistic behavior. Thus, stable shareholders make a decisionabout their relationship with a firm based on their perception of the firm’s businessprospects and its ability to fulfill its obligations (Kreps et al., 1982; Raman and Shahrur,2008; Dou et al., 2013). In this circumstance, firm managers must continuously provideinformation about their performance in order to maintain a long-term relationshipwith their stable shareholders.

In such a context, accounting information plays an important role in implicitcontracting because managing accruals to smooth earnings lowers stable shareholders’perceived variance of a firm’s underlying performance (Trueman and Titman, 1988).Dou et al. (2013, p. 1,633) summarize the reasons why stakeholders’ perception abouta firm’s underlying performance is important for the relationship between the firmand its stakeholders from two perspectives. We use their argument for our hypothesisdevelopment because their study also analyzes the role of earnings smoothing inimplicit long-term contracts. First, a more stable earnings stream reduces the stableshareholders’ estimation of risk about a firm’s future cash flow, which helps to ensurea long-term relationship between the firm and its stable shareholders. Second, asmoother earnings stream in the current period, which holds the level of earningsconstant, reduces the stable shareholders’ perceived risk that firm managers willengage in opportunistic behavior in the future. Stable shareholders have to bearthe cost caused by managers’ opportunistic behavior. From the stable shareholders’perspective, risk arises to the extent that opportunistic behavior could occur inthe future, and the probability of observing opportunistic behavior increases as thevolatility of a firm’s earnings increases. By reporting a smoother earnings streamin the current period, a firm reduces the stable shareholders’ perception that inthe future, they will have to bear significant costs created by managers engaging inopportunistic behavior. As a result, smoother earnings in the current period increasestable shareholders’ willingness to maintain a long-term relationship with a firm.4

Finally, based on the above argument, we briefly summarize the relationshipbetween shareholdings, the decision horizon problem and patterns of earningsmanagement. As for the effect of shareholdings on managerial incentives, managerswith transient institutional ownership are encouraged to pursue short-term earningsto avoid earnings disappointment. Trading by institutional ownerships with short-termhorizons is sensitive to current earnings, and earnings disappointment can triggerlarge-scale institutional investor selling. Thus, such managers would have incentivesto achieve short-term earnings goals (i.e., myopic behavior).

On the other hand, managers with stable shareholdings are not encouraged topursue short-term earnings because the goal of stable shareholders is not to profit

4 Further, stable shareholdings, particularly shareholdings of financial institutions, are concerned withstable earnings because of their asymmetric pay-off function. Debt holders are less likely to be concernedabout the potential gains of a borrowing firm because they have a non-linear pay-off function that restrictstheir claims on the firm’s assets in relation to their promised payments (i.e., principal and interest). Debtholders have greater concerns about potential losses since they could lose their principal and interestpayments in the most serious cases (i.e., bankruptcy). Problems that arise from the existence of differenttypes of financial claim can be reduced by the shareholdings of financial institutions. One implication isthat the reduction of earnings volatility could be useful in reducing downside risk. This is because greateruncertainty about profits implies a greater risk that excess dividends based on temporarily inflated earningsmay be paid to shareholders (Watts, 1993; Ahmed et al., 2002). Thus, managers who want to maintain along-term relationship with financial institutions are likely to smooth earnings to send a signal about theirrisk-averse tendency.



from their short-term transactions. Additionally, managers have an incentive to reportstable earnings strings to maintain long-term relationships with stable shareholders. Inparticular, we predict that stable shareholdings are positively associated with earningssmoothing behavior, since this decreases earnings volatility.

Earnings smoothing is a typical earnings management pattern that seeks to reducethe variation in the reported income of firms over time. However, it is impor-tant to note that prior studies identify two types of role for earnings smoothing:“informational” and “garbling.” The garbling role of earnings smoothing refers tothe opportunistic behavior of managers who increase their private benefits, whilethe informational role refers to the efficient behavior of managers who signalprivate information about future performance (Demski, 1998). This implies that thereare two contradictory predictions about the relationship between stable shareholdingsand earnings smoothing, and that the net effect of these is an empirical question. How-ever, we predict that in our hypothesis development, the latter prediction based onthe efficient behavior view will be more pervasive than that based on the opportunisticbehavior view. Our hypothesis expects that earnings smoothing is used to convey usefulinformation to stable shareholders about the future viability of operations. In otherwords, managers use earnings smoothing as an informative signal to alter perceptionsabout the volatility of future earnings. Therefore, we predict that the relationshipbetween stable shareholdings and earnings smoothing will be explained primarilyby the informational component of related income smoothing.5 Thus, this argumentleads to our first hypothesis.

Hypothesis: Stable shareholdings are positively associated with the informationalcomponent of earnings smoothing.

In order to compare the results of stable shareholdings, we also examine the effectof foreign equity ownership. In the Japanese equity market, foreign shareholders arewidely known to have short-term investment horizons (Uno and Kamiyama, 2010),which is a comparable situation to institutional ownership in the US (Bushee, 1998);therefore, we can assume that foreign shareholders have similar effects on earningsmanagement behavior.6 Because foreign ownership is expected to require earningsmanagement to increase short-term earnings, and because it has a contrasting effectto that of stable shareholdings, we predict that foreign ownership decreases earningssmoothing behavior.

5 However, contrary to our proposal, if managers use their accounting flexibility under the passivemonitoring of stable shareholders for their private benefit, the garbling role of earnings smoothing willbe more pervasive.6 In addition to the analysis of stable shareholdings, the focus on foreign ownership in Japan is importantfor the following two reasons (Jiang and Kim, 2004). First, as noted by Kang and Stulz (1997), Japan is“the only large country that we know for which detailed data on [share] holding by foreign investors areavailable” (p. 4) from published annual reports or stock guides. Second, shareholdings by foreign investorsare, in general, restricted in Asian countries other than Japan (Jiang and Kim, 2004). In this regard, theJapanese equity market is well suited for addressing our research concern.


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3. RESEARCH DESIGN

(i) Earnings Smoothing Measures

In this section, we describe earnings management measures with respect to earningssmoothing in our empirical analyses. Specifically, following prior studies on earningsmanagement, we use three earnings management measures for earnings smoothing.

The first measure (ES1) captures the degree to which managers reduce thevariability of reported earnings by altering the accounting accruals; this is widely usedin prior studies (Leuz et al., 2003; Francis et al., 2004; LaFond et al., 2007; Lang et al.,2009; Grant et al., 2009; Perotti and Wagenhofer, 2014). Specifically, ES1 is defined asthe ratio of a firm’s standard deviation of net income (NI) to its standard deviation ofcash flow from operations (CFO) as follows:

E S1 = σ(N I )/σ(CF O),

where

NI = net income before extraordinary items, net income − extraordinary gains +extraordinary losses;

CFO = cash flow from operations, NI – ACC;ACC = (�current assets − �cash and cash equivalents) − (�current liabili-

ties − �financing item7) − �other allowance8 − depreciation.

NI and ACC are scaled by lagged total assets. We calculate the standard deviationsover rolling 5-year windows. The lower variability of earnings with respect to thevariability in cash flow indicates greater earnings smoothing; therefore, a lower valueof ES1 implies greater earnings smoothness.

Our second measure of earnings smoothing (ES2) is equal to the correlationbetween the changes in accounting accruals (ACC) and those in operating cash flows(Land and Lang, 2002; Bhattacharya et al., 2003; Leuz et al., 2003; LaFond et al., 2007;Myers et al., 2007; Grant et al., 2009; Lang et al., 2009; Perotti and Wagenhofer, 2014):

ES2 = ρ [�ACC,�CF O] .

We calculate ES2 over a period of 5 years. Even in the absence of earningsmanagement, the ES2 measure is expected to be negative on average because anegative correlation is a natural result of accrual accounting (Dechow, 1994). However,we expect that a greater negative value of ES2 will indicate the discretionary behavior ofearnings smoothing, which does not reflect a firm’s underlying economic performance(Bhattacharya et al., 2003; Leuz et al., 2003; Myers et al., 2007). Hence, a lower ES2value indicates a smoother earnings stream.

The third measure (ES3) extends the definition of ES2. Following Tucker andZarowin (2006) and Grant et al. (2009), we calculate ES3 as the correlation between

7 �financing item is the sum of the following items: change in short-term debt, change in commercialpaper and change in bonds and convertible bonds.8 �other allowance is the change in allowances classified as fixed assets.



the changes in discretionary accruals (DAC) and those in non-discretionary net income(NDNI):

E S3 = ρ [�DAC,�N DN I ]

where

DAC = discretionary accruals using the modified Jones model (Dechow et al., 1995);9

NDNI = non-discretionary net income; NI – DAC.

We again calculate the correlation over 5 years.10 Although we face difficultyin observing the discretionary portion of managerial earnings smoothing behavior,this measure has an advantage: it assumes that there is an underlying pre-managedearnings series and that managers use discretionary accruals to make the reportedseries smooth (Tucker and Zarowin, 2006; Grant et al., 2009). Consequently, a morenegative correlation on ES3 indicates greater earnings smoothing behavior.

Our next step is to decompose earnings smoothing into its informational andgarbling components. First, by using principal component analysis, we reduce ourthree earnings smoothing measures to a single index, that is, the aggregate earningssmoothing score (ES4).11,12 Second, following the estimation method of Dou et al.(2013), which modifies the method of Tucker and Zarowin (2006), we decomposeES4 into informational and garbling components. Tucker and Zarowin (2006) use aprices-leading-earnings framework to decompose earnings smoothing. This uses past,current, and future earnings to explain a current return. By examining the extent towhich prices lead earnings, Collins et al. (1994) assess whether income smoothingaffects the extent to which investors are able to predict future performance. Douet al. (2013) extend their basic model by considering the differential predictabilityof earnings for profitable and loss-making firms. This is because of the belief that theearnings of profitable firms are easier to predict. We follow their model to estimate theinformational component of earnings smoothing as follows:

Rt = a0 + ß1Xt−1 + ß2Xt + ß3Profit × Xt3 + ß4Loss × Xt3 + ß5Rt3 + εt (1)

where

Rt = annual stock returns for year t;Xt = income before extraordinary items scaled by lagged total assets for year t;

9 The detailed estimation method on the modified Jones model employed in this study is summarized inthe Appendix.10 The 5-year calculation period for earnings smoothing variables used in this study is the same calculationperiod used by Tucker and Zarowin (2006). Grant et al. (2009) use a 3-year period for the calculation.11 The detailed statistics of the principal component analysis show that the correlations among the threevariables are all positive and that all of the correlations are significant, as expected. Further, it reveals thatthe factor loadings all have positive signs, as expected. Finally, a single factor loaded by these three attributemeasures justifies around 58.1% of the cumulative variance. Overall, the results suggest that our factoranalysis provides useful composite measures for the degree of the aggregate earnings smoothing score.12 As Dou et al. (2013, p. 1,638) advocate, our earnings smoothing measure (ES4) has the advantage ofmeasuring the smoothness of accruals relative to underlying operating performance (i.e., operating cash flows),where smoothness of accruals reflects at least partially the managers’ choice, and cash flows are used as aproxy for the underlying fundamentals of the firm. This is important because it is possible that managers’investments smooth real operations, such as cutting long-term projects to meet short-term earnings targets.By calculating the ES4 variable, we can grasp the extent to which reported accruals are used to smoothearnings relative to any real smoothing effect.



Xt–1 = income before extraordinary items scaled by lagged total assets for year t − 1;Xt3 = the sum of Xt for years t + 1 to t + 3;Profit = indicator variables that take the value of one if Xt3 is positive, and zero

otherwise;Loss = indicator variables that take the value of one if Xt3 is negative, and zero

otherwise;Rt3 = the sum of Rt for years t+1 to t+3.

Rt is the annual stock return for year t, and Rt3 is the aggregate stock return in yearst + 1 to t + 3 with annual compounding (Tucker and Zarowin, 2006, p. 257). Xt–1 andXt are the return on assets (ROA) for years t − 1 and t, respectively, and Xt3 is the sumof ROA for years t + 1 to t + 3. Xt–1 and Xt are controlled for unexpected earningsin the current period (Lundholm and Myers, 2002). Rt3 is included in our model tocontrol for unexpected earnings realized in future periods, since our model relieson realizations of future earnings to measure future earnings expectations. FollowingDou et al. (2013), we separately estimate the predictability of earnings using indicatorvariables for positive (Profit) or negative (Loss) cumulative 3-year earnings.

Our concern is the coefficients on future earnings, β3 (FERC Profit) and β4

(FERC Loss), that capture revisions in investors’ expectations about such earnings. Toestimate the coefficients, β3 and β4, we run regression model (1) for each industry ina given year according to the Nikkei industry classification code (Nikkei gyousyu chu-bunrui).13 Finally, in order to decompose total income smoothing, we estimate thefollowing regression with FERC Profit and FERC Loss for ES4:

E S4t = a0 + ß1F E RC Pr o f i tt + ß2F E RC Losst + εt . (2)

The informational component (ES INFO) is calculated as the predicted value ofES4, and the residual, ε, proxies for the garbling component (ES GAR) of earningssmoothing. ES INFO captures the component of income smoothing that relatessystematically to investors’ ability to predict future earnings. ES GAR reflects theportion of income smoothing that does not provide information about future earnings(Dou et al., 2013).

(ii) Research Models

To test the hypothesis, we examine the association between stable shareholdings andearnings smoothing by estimating the following model:

ES = a + ß1STABLE + ß2FOREIGN + ß3MO + ß4ASSET + ß5CF O + ß6SALES

+ ß7CYCLE + ß8LOSS + ß9CINT + ß10MTB + ß11SO + ß12AF + ß13ZS

+ ß14 E V + industry dummy + ε (3)

13 Our regression result indicates that the averages of β3 (FERC Profit) and β4 (FERC Loss) are positive(1.007 and 0.805), and the paired t-test shows that β3 is significantly greater than β4 (t = 1.964). Theseresults are consistent with our expectation and the results reported in Dou et al. (2003), indicating thatfirms use income smoothing to share both positive as well as negative information in order to mitigateuncertainty for the stable shareholders.



ES = a + ß1CROSS + ß2F STABLE + ß3F OR E I GN + ß4MO + ß5ASS E T + ß6CF O

+ ß7SALE S + ß8CY CLE + ß9LOSS + ß10CI N T + ß11MTB + ß12SO + ß13AF

+ ß14ZS + ß15 E V + industry dummy + ε (4)

where

ES = earnings smoothing measures (ES INFO and ES GAR);STABLE = fraction of the shares owned by stable shareholders at the end of the fiscal

year;CROSS = fraction of the shares owned by cross-shareholders at the end of the fiscal

year;FSTABLE = fraction of the stable shareholdings owned by financial institutions at the

end of the fiscal year (i.e., FSTABLE is defined as STABLE minus CROSS);FOREIGN = fraction of the shares owned by foreign companies at the end of the fiscal

year;MO = fraction of the shares owned by directors at the end of the fiscal year;ASSET = log of total assets at the end of the fiscal year;CFO = standard deviation of a firm’s rolling 5-year cash flow from operations;SALES = standard deviation of a firm’s rolling 5-year sales revenue;CYCLE = log of the sum of a firm’s days accounts receivable ((yearly average accounts

receivable)/ (total revenue/360)) and days inventory ((yearly average inventory)/(cost of goods sold/360));

LOSS = proportion of losses over the last 5 years;CINT = ratio of the net book value of property, plant and equipment (PP&E) to total

assets at the end of the fiscal year;MTB = book-to-market ratio at the end of the fiscal year;SO = indicator variable that takes the value of one if the firm introduced stock options,

and zero otherwise;AF = the number of analyst followings;ZS = Z-score, computed using Altman’s (1968) model;EV = standard deviation of income before extraordinary items (scaled by lagged total

assets) for 3 years (t + 1 to t + 3);All variables are winsorized at 1% by year;Industry dummy = an indicator variable for the Nikkei industry classification code

(Nikkei gyousyu chu-bunrui).

As described in the subsection on earnings smoothing measures, we use twovariables (ES INFO and ES GAR) to measure earnings smoothing behavior. We focusmainly on the stable shareholdings variable (STABLE), which is classified into cross-shareholdings (CROSS) and stable shareholdings owned by financial institutions(FSTABLE). CROSS is defined as the fraction of shares that are owned by cross-shareholders at the end of the fiscal year. Cross-shareholders include all domesticcompanies listed on the Japanese stock markets at the end of the fiscal year. FSTABLEis calculated as the fraction of the shares owned by stable financial shareholders at the



end of the fiscal year.14 To compare the findings of stable shareholdings, we includeforeign shareholdings (FOREIGN) in the regression model.

Our hypothesis predicts that the relationship between stable shareholdings andearnings smoothing will be explained primarily by the informational component ofrelated income smoothing. Thus, if the relationship between stable shareholdingsand earnings smoothing is consistent with our hypothesis, the relationship betweenSTABLE and ES INFO is expected to be negative in regression model (1). We alsoexpect that FSTABLE and CROSS are negatively associated with ES INFO in regressionmodel (2). Further, foreign shareholdings are expected to have a positive relationshipto earnings smoothing variables, or have no impact on them.

Following Dechow and Dichev (2002) and Francis et al., (2004), we set the controlvariables for the earnings attributes that determine earnings volatility. Dechow andDichev (2002) identify the five factors that explain accruals’ quality: firm size (ASSET),cash flow variability (CFO), sales variability (SALES), operating cycle length (CYCLE),and incidence of negative earnings realizations (LOSS).

Firm size is expected to be negatively associated with earnings volatility sincelarge firms have more stable and predictable operations. Cash flow variability andsales variability are positively related to earnings volatility because uncertainty inthe operating environment increases as variability increases. Long operating cyclesinvolve high uncertainty, which increases earnings volatility. The incidence of negativeearnings realizations is expected to be positively associated with earnings volatilitysince reporting losses would indicate severe negative shocks in a firm’s operatingenvironment. Consequently, earnings volatility is expected to be negatively associatedwith ASSET and positively associated with CFO, SALES, CYCLE and LOSS.

In addition to these control variables, following the analysis of Francis et al. (2004),we use two additional variables: intangible intensity (MTB) and capital intensity(CINT).15 Prior studies reveal that intangible intensity is positively related to earningspersistence, thereby reducing earnings volatility (Baginski et al., 1999). Further, somestudies provide evidence suggesting that capital-intensive firms have greater earningsvolatility because of higher operating leverage (Lev, 1983; Baginski et al., 1999). Thus,earnings volatility is expected to be negatively related to MTB and positively associatedwith CINT.

Further, we use managerial ownership (MO) because prior studies show thatan entrenched CEO with greater managerial ownership tends to conduct earningsmanagement that is proxied by discretionary accruals (Warfield et al., 1995; Teshimaand Shuto, 2008). We cannot predict the expected sign of MO because it is unclearhow managerial ownership affects the earnings management pattern. The dummyvariable on the adoption of stock option (SO) is included since equity incentive islikely to increase earnings volatility. In accordance with Tucker and Zarowin (2006),we also add analyst following (AF) and future earnings volatility (EV). Tucker and

14 Financial institutions that own stable shareholdings include financial institutions, trust banks, otherfinancial institutions (i.e., brokerage companies and securities finance companies) and parent companies.The definitions of these stable ownership variables depend on those in the Data Package of Cross-Shareholdingand Stable Shareholding which is used in this study. For the details of databases used in the analyses, see thesection on sample selection.15 As the proxy for intangible intensity, Francis et al. (2004) use the variable based on R&D cost. However,we use the book-to-market ratio for the intangible intensity variable because systematic data for R&D cost isnot available until 2000 from the database used in this study. The reason for this limitation is summarizedin Footnote 23.



Table 1Sample Selection Procedures

Criteria Firm–years

Firm–years with data on cross-shareholdings and stable shareholdings 39,559for 1988–2006

Less:Banks, securities firms, insurance firms and other financial institutions (2,451)Fiscal year does not end in March (14,009)Change in accounting month within firm–years necessary for the analyses (7,336)Firm–year with negative total assets or book value of equity (52)Missing data for calculating independent variables (1,898)Missing data for calculating dependent variables (5,018)Final sample 8,795

Note:Cross-shareholdings data and stable shareholdings data necessary for the study are available from the DataPackage of Cross-shareholding and Stable Shareholding (Kabushiki mochiai zyoukyou tyousa no kiso data); Financialstatements data, managerial ownership data and share price data necessary for the study are available fromthe Nikkei NEEDS Financial QUEST; The industry is based on the Nikkei industry classification code (Nikkeigyousyu chu-bunrui); The financial statements data are based on consolidated financial statements.

Zarowin (2006) predict that a firm’s stock price probably impounds more informationabout future earnings when there are more private information search activities byanalysts. They also argue that if a firm’s future earnings are volatile, they are moredifficult to predict; thus, the amount of future earnings information impounded in thecurrent stock price is low. Consequently, these two variables are likely to be associatedwith earnings volatility. Finally, we control for bankruptcy risk using Altman’s (1968)Z-score (ZS) following Dou et al. (2013).

4. SAMPLE SELECTION AND DESCRIPTIVE STATISTICS

(i) Sample Selection

Our sample selection procedures are summarized in Table 1. We obtained our initialsample of 39,559 observations on stable shareholding from the Data Package of Cross-Shareholdings and Stable Shareholdings (Kabushiki mochiai zyoukyou tyousa no kiso data) for1988–2008. We excluded firms working in banking, securities and insurance, and otherfinancial institutions and firms whose fiscal year does not end in March; this resulted in23,099 observations.16 We also excluded 7,336 observations that changed accountingperiod during our analysis period. We then merged the financial statements andstock data from the Nikkei NEEDS Financial QUEST database, and eliminated thoseobservations with negative total assets, or negative book value of equity and missingdata in order to calculate independent variables. This resulted in a sample of 13,813

16 The reason why we use only observations of firms that have March as their fiscal year end is to ensurethe consistency of the data used in this analysis. The stable shareholdings variables, which are our mainconcern, are obtained from the Data Package of Cross-Shareholdings and Stable Shareholdings (Kabushikimochiai zyoukyou tyousa no kiso data). According to the database instructions, the package based its calculationof stable shareholdings on the number of shares at the end of March for each year and firm. We assume thisis because most Japanese firms have their fiscal year ends at the end of March. Therefore, we use only firmswhose fiscal year ends in March because we use the financial data at the end of March, which is consistentwith the calculation date of stable shareholdings.



observations. Finally, after deleting those observations with missing data in orderto calculate dependent variables (i.e., the informational component of earningssmoothing), we reduced our sample to 8,795 observations for earnings smoothinganalyses.

(ii) Descriptive Statistics

Table 2 presents descriptive statistics for the variables used in this study. It showsthat the average percentage of CROSS (FSTABLE) is 13.6% (17.%); this means thatthe average percentage of stable shareholdings (STABLE) in the Japanese market,which comprises cross-shareholdings and stable shareholdings owned by financialinstitutions, is 30.9%. The descriptive statistics of stable shareholdings are similar tothose of prior studies that examine the stable shareholdings of Japanese firms (Shutoand Kitagawa, 2011).

The table also indicates that the average percentage of FOREIGN is 7.7%, indicatingthat foreign ownership is less than stable shareholdings. Our untabulated analysis alsoindicates that while the value of stable shareholdings gradually decreases after the year2000, that of foreign ownership mainly increases during this period.

Table 3 presents the Pearson correlations matrix among the variables used in thisstudy’s regression models. We report the correlations matrix for variables in earningssmoothing analyses.

The Pearson correlations reveal that the STABLE variable is negatively correlatedwith ES4 (–0.06), ES INFO (–0.13), and ES GAR (–0.04). Both CROSS and FSTABLE arealso negatively correlated with the ES INFO. The results suggest that, as hypothesized,earnings smoothing behavior by managers, especially the informational component ofearnings smoothing, increases as stable shareholdings increase.

5. MAIN RESULTS

To test our hypothesis concerning the relationship between stable shareholdingsand earnings smoothing, we estimated regression models (3) and (4). We usedpooled regressions, and reported t-statistics based on standard errors clustered at firmand year levels following Petersen’s (2009) analyses.17 As described in section 3, weestimated two earnings smoothing variables, the information and garbling roles ofincome smoothing (i.e., ES INFO and ES GAR), and examined the effect of stableshareholdings (STABLE, CROSS and FSTABLE) on these. Table 4 summarizes theregression results.

In columns (3) and (4) of Table 4, the regression results of model (1) indicate thatonly the informational components of earnings smoothing are significantly associatedwith stable shareholdings in the predicted direction. In particular, the coefficient ofSTABLE in the third column, −0.055, is significantly associated with ES INFO at the

17 Petersen (2009) indicates that standard errors clustered by firm and time can be useful to control fortime-series correlation and heteroskedasticity simultaneously. Specifically, t-statistics are adjusted for cross-sectional and intertemporal dependence using two-way cluster-robust standard errors proposed by Petersen(2009). We also use this estimation method for all the following analyses in this paper. If clustering of thestandard errors does not allow for the inclusion of all of our currently included industry dummy variables,we combine at least two industry dummy variables into one industry dummy variable in order to estimatethe regression.



Table 2Descriptive Statistics

Mean Min Q1 Median Q3 Max SD N

ES4 −0.032 −1.423 −0.901 −0.435 0.395 5.923 1.253 8,795ES INFO 0.019 −1.331 −0.046 0.032 0.077 1.356 0.146 8,795ES GAP −0.050 −1.826 −0.908 −0.424 0.376 5.862 1.247 8,795STABLE 0.309 0.000 0.195 0.295 0.409 0.760 0.157 8,795CROSS 0.136 0.000 0.067 0.126 0.196 0.434 0.089 8,795FSTABLE 0.172 0.000 0.058 0.116 0.234 0.675 0.158 8,795FOREIGN 0.077 0.000 0.011 0.044 0.115 0.465 0.086 8,795MO 0.024 0.000 0.002 0.004 0.021 0.325 0.048 8,795ASSET 11.604 8.421 10.637 11.438 12.408 15.680 1.307 8,795CFO 0.047 0.008 0.027 0.040 0.059 0.210 0.029 8,795SALES 0.099 0.010 0.048 0.076 0.123 0.753 0.081 8,795CYCLE 4.955 2.760 4.729 5.057 5.294 6.186 0.550 8,795LOSS 0.219 0.000 0.000 0.200 0.400 1.000 0.257 8,795CINT 0.208 0.003 0.128 0.201 0.277 0.655 0.109 8,795MTB 1.533 0.203 0.793 1.226 1.883 15.217 1.204 8,795SO 0.155 0.000 0.000 0.000 0.000 1.000 0.362 8,795AF 3.275 0.000 0.000 1.000 5.000 21.000 4.310 8,795ZS 1.011 0.213 0.721 0.903 1.143 6.617 0.510 8,795EV 0.014 0.000 0.005 0.010 0.019 0.093 0.014 8,795

Note:ES4 = aggregate earnings smoothing score, computed using principal component analysis based onfollowing three variables (ES1, ES2 and ES3). ES1 = ratio of firm’s standard deviations of income beforeextraordinary items (scaled by lagged total assets) and operating cash flow (scaled by lagged total assets).Both variables are measured each year for each firm, using rolling 5-year windows. ES2 = the Spearmancorrelation between the change in accruals (scaled by lagged total assets) and the change in cash flowfrom operations (scaled by lagged total assets). Both variables are measured each year for each firm, usingrolling 5-year windows. ES3 = the Spearman correlation between the change in discretionary accruals (DA)and the change in non-discretionary income (NDNI). DA = discretionary accruals computed using themodified Jones model (Dechow et al., 1995). NDNI = income before extraordinary items (net income− extraordinary gains + extraordinary losses) minus DA. The Spearman correlation is measured eachyear for each firm, using rolling 5-year windows. ES INFO = the informative part of income smoothing,measured as the predicted value from regression result in model (2); ES GAR = the garbling part of incomesmoothing, measured as the residual value from regression result in model (2); STABLE = fraction of theshares owned by stable shareholders at the end of the fiscal year. Stable shareholdings are classified intothe cross-shareholdings (CROSS) and the stable shareholdings by financial institutions (FSTABLE); CROSS= fraction of the shares owned by cross-shareholders at the end of the fiscal year; FSTABLE = fraction ofthe stable shareholdings by financial institutions at the end of the fiscal year (i.e., FSTABLE is defined asSTABLE minus CROSS); FOREIGN = fraction of the shares owned by foreign companies at the end of thefiscal year; MO = fraction of the shares owned by directors at the end of the fiscal year; ASSET = log of totalassets at the end of the fiscal year; CFO = standard deviation of cash flows from operations (scaled by laggedtotal assets) for 5-year period (t to t–4); SALE = standard deviation of sales revenues (scaled by lagged totalassets) for 5-year period (t to t–4); CYCLE = log of the sum of the firm’s days accounts receivable (yearlyaverage accounts receivable)/(total revenue/360) and days inventory ((yearly average inventory)/(cost ofgoods sold/360)). If the cost of goods sold is not reported, we use the total revenue minus operating incomeinstead; LOSS = proportion of losses over the last 5 years; CINT = ratio of the net book value of PP&E tototal assets at the end of the fiscal year; MTB = book-to-market ratio at the end of the fiscal year; SO =indicator variable that takes the value of one if the firm introduced stock options, and zero otherwise; AF= the number of analyst followings; ZS = Z-score, computed using Altman’s (1968) model; EV = standarddeviation of income before extraordinary items (scaled by lagged total assets) for 3-year period (t + 1 tot + 3).



Tab

le3

Cor

rela

tion

sM

atri

x

ES4

ESIN

FOES

GA

RST

AB

LE

CR

OSS

FSTA

BL

EFO

REI

GN

MO

ASS

ETC

FOSA

LES

CYC

LE

LO

SSC

INT

MT

BSO

AF

ZSEV

ES4

1.00

ESIN

FO0.

09**

*1.

00ES

GA

R0.

99**

*−0

.03**

1.00

STA

BL

E−0

.05**

*−0

.07**

*−0

.04**

*1.

00C

RO

SS−0

.08**

*−0

.08**

*−0

.07**

*0.

28**

*1.

00FS

TAB

LE

0.00

−0.0

3**0.

000.

84**

*−0

.30**

*1.

00FO

REI

GN

0.02

0.05

***

0.01

−0.2

9***

−0.1

4***

−0.2

1***

1.00

MO

0.04

***

0.05

***

0.03

***

−0.3

9***

−0.1

8***

−0.2

9***

−0.0

6***

1.00

ASS

ET−0

.10**

*−0

.1**

*−0

.09**

*0.

010.

05**

*−0

.02*

0.45

***

−0.2

8***

1.00

CFO

−0.2

9***

0.03

**−0

.29**

*−0

.04**

*−0

.08**

*0.

010.

010.

03**

*−0

.13**

*1.

00SA

LES

0.06

***

0.00

0.06

***

0.05

***

−0.0

4***

0.08

***

−0.0

4***

0.03

***

−0.1

2***

0.25

***

1.00

CYC

LE

0.09

***

0.00

0.09

***

−0.0

3***

−0.0

4***

−0.0

10.

03**

−0.0

8***

0.05

***

0.01

−0.2

2***

1.00

LO

SS0.

27**

*0.

07**

*0.

27**

*−0

.04**

*−0

.07**

*0.

00−0

.24**

*−0

.05**

*−0

.14**

*0.

06**

*0.

02*

0.14

***

1.00

CIN

T0.

06**

*−0

.02*

0.07

***

0.11

***

0.01

0.11

***

−0.0

5***

−0.1

1***

0.11

***

−0.1

7***

−0.2

5***

−0.2

6***

−0.0

2*1.

00M

TB

0.08

***

−0.0

6***

0.09

***

0.04

***

−0.0

6***

0.08

***

0.16

***

−0.0

8***

0.19

***

0.02

*0.

06**

*0.

010.

02*

0.06

***

1.00

SO−0

.02*

0.09

***

−0.0

3***

−0.1

8***

−0.1

4***

−0.1

0***

0.21

***

0.11

***

0.00

0.08

***

0.06

***

−0.0

8***

−0.0

4***

−0.0

6***

−0.0

3***

1.00

AF

0.01

−0.0

3***

0.02

−0.1

0***

−0.0

5***

−0.0

7***

0.62

***

−0.1

2***

0.66

***

−0.0

4***

−0.1

0***

0.10

***

−0.2

1***

0.04

***

0.20

***

0.10

***

1.00

ZS−0

.08**

*−0

.03**

*−0

.08**

*0.

10**

*0.

04**

*0.

08**

*−0

.12**

*0.

05**

*−0

.12**

*0.

03**

*0.

54**

*−0

.48**

*−0

.07**

*−0

.28**

*−0

.05**

*0.

05**

*−0

.14**

*1.

00EV

0.22

***

0.08

***

0.21

***

−0.0

8***

−0.1

3***

0.00

0.07

***

0.04

***

−0.1

7***

0.13

***

0.10

***

0.10

***

0.17

***

−0.0

3***

0.07

***

0.04

***

0.00

−0.0

6***

1.00

(Con

tinue

d)



Tab

le3

Con

tin

ued

Not

e:ES

4=

aggr

egat

eea

rnin

gssm

ooth

ing

scor

e,co

mpu

ted

usin

gpr

inci

palc

ompo

nen

tan

alys

isba

sed

onfo

llow

ing

thre

eva

riab

les

(ES1

,ES2

and

ES3)

.ES1

=ra

tio

offi

rm’s

stan

dard

devi

atio

ns

ofin

com

ebe

fore

extr

aord

inar

yit

ems

(sca

led

byla

gged

tota

las

sets

)an

dop

erat

ing

cash

flow

(sca

led

byla

gged

tota

las

sets

).B

oth

vari

able

sar

em

easu

red

each

year

for

each

firm

,usi

ng

rolli

ng

5-ye

arw

indo

ws.

ES2

=th

eSp

earm

anco

rrel

atio

nbe

twee

nth

ech

ange

inac

crua

ls(s

cale

dby

lagg

edto

tala

sset

s)an

dth

ech

ange

inca

shfl

owfr

omop

erat

ion

s(s

cale

dby

lagg

edto

tala

sset

s).B

oth

vari

able

sar

em

easu

red

each

year

for

each

firm

,usi

ng

rolli

ng

5-ye

arw

indo

ws.

ES3

=th

eSp

earm

anco

rrel

atio

nbe

twee

nth

ech

ange

indi

scre

tion

ary

accr

uals

(DA

)an

dth

ech

ange

inn

on-d

iscr

etio

nar

yin

com

e(N

DN

I).D

A=

disc

reti

onar

yac

crua

lsco

mpu

ted

usin

gth

em

odif

ied

Jon

esm

odel

(Dec

how

etal

.,19

95).

ND

NI=

inco

me

befo

reex

trao

rdin

ary

item

s(n

etin

com

e−

extr

aord

inar

yga

ins+

extr

aord

inar

ylo

sses

)m

inus

DA

.Th

eSp

earm

anco

rrel

atio

nis

mea

sure

dea

chye

arfo

rea

chfi

rm,u

sin

gro

llin

g5-

year

win

dow

s.ES

INFO

=th

ein

form

ativ

epa

rtof

inco

me

smoo

thin

g,m

easu

red

asth

epr

edic

ted

valu

efr

omre

gres

sion

resu

ltin

mod

el(2

);ES

GA

R=

the

garb

ling

part

ofin

com

esm

ooth

ing,

mea

sure

das

the

resi

dual

valu

efr

omre

gres

sion

resu

ltin

mod

el(2

);ST

AB

LE

=fr

acti

onof

the

shar

esow

ned

byst

able

shar

ehol

ders

atth

een

dof

the

fisc

alye

ar.S

tabl

esh

areh

oldi

ngs

are

clas

sifi

edin

toth

ecr

oss-

shar

ehol

din

gs(C

RO

SS)

and

the

stab

lesh

areh

oldi

ngs

byfi

nan

cial

inst

itut

ion

s(F

STA

BL

E);C

RO

SS=

frac

tion

ofth

esh

ares

own

edby

cros

s-sh

areh

olde

rsat

the

end

ofth

efi

scal

year

;FS

TAB

LE

=fr

acti

onof

the

stab

lesh

areh

oldi

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Table 4Regression Results on the Relationship between Stable Shareholdings and

Earnings Smoothing

Model 1 Model 1 Model 2 Model 2ES INFO ES GAR ES INFO ES GAR

Independent Expected Coefficient Coefficient Coefficient CoefficientVariable Sign (t-value) (t-value) (t-value) (t-value)

Constant 0.170*** 1.207** 0.182*** 1.247***

(3.004) (2.532) (3.131) (2.599)STABLE − −0.055*** −0.170

(−6.777) (−0.970)CROSS − −0.114*** −0.379

(−5.003) (−1.511)FSTABLE − −0.049*** −0.141

(−6.834) (−0.779)FOREIGN + 0.130*** 0.746* 0.122*** 0.720*

(2.829) (1.913) (2.759) (1.848)MO +/− −0.046* 0.642 −0.056** 0.612

(−1.851) (1.059) (−2.305) (1.004)ASSET + −0.005** −0.142*** −0.005** −0.141***

(−2.433) (−5.588) (−2.356) (−5.498)CFO − −0.039 −16.258*** −0.048 −16.292***

(−0.470) (−22.894) (−0.593) (−22.694)SALES − −0.006 3.163*** −0.009 3.149***

(−0.158) (8.712) (−0.269) (8.688)CYCLE − −0.009*** 0.052 −0.010*** 0.050

(−4.349) (0.784) (−4.607) (0.745)LOSS − 0.026** 1.259*** 0.025** 1.254***

(2.416) (9.514) (2.337) (9.513)CINT − −0.043*** 0.595* −0.047*** 0.579*

(−2.962) (1.859) (−3.269) (1.810)MTB + −0.007** 0.059** −0.007** 0.058**

(−2.012) (2.541) (−2.096) (2.520)SO + 0.029*** −0.090 0.028*** −0.094

(3.575) (−1.530) (3.544) (−1.610)AF − −0.002 0.027*** −0.002 0.027***

(−1.377) (3.812) (−1.437) (3.789)ZS − −0.006 −0.206*** −0.007 −0.211***

(−0.837) (−2.616) (−1.043) (−2.667)EV + −0.063 10.959*** −0.080 10.900***

(−0.306) (6.703) (−0.398) (6.642)Industry dummy Yes Yes Yes YesAdj. R2 0.127 0.286 0.128 0.286N 8,795 8,795 8,795 8,795

(Continued)



Table 4Continued

Note:ES INFO = the informative part of income smoothing, measured as the predicted value from regressionresult in model (2); ES GAR = the garbling part of income smoothing, measured as the residual valuefrom regression result in model (2); STABLE = fraction of the shares owned by stable shareholders at theend of the fiscal year. Stable shareholdings are classified into the cross-shareholdings (CROSS) and thestable shareholdings by financial institutions (FSTABLE); CROSS = fraction of the shares owned by cross-shareholders at the end of the fiscal year; FSTABLE = fraction of the stable shareholdings by financialinstitutions at the end of the fiscal year (STABLE – CROSS); FOREIGN = fraction of the shares owned byforeign companies at the end of the fiscal year; MO = fraction of the shares owned by directors at theend of the fiscal year; ASSET = log of total assets at the end of the fiscal year; CFO = standard deviationof cash flows from operations (scaled by lagged total assets) for 5-year period (t to t–4); SALE = standarddeviation of sales revenues (scaled by lagged total assets) for 5-year period (t to t–4); CYCLE = log of the sumof the firm’s days accounts receivable (yearly average accounts receivable)/(total revenue/360)) and daysinventory ((yearly average inventory)/(cost of goods sold/360)). If the cost of goods sold is not reported,we use the total revenue minus operating income instead; LOSS = proportion of losses over the last 5years; CINT = ratio of the net book value of PP&E to total assets at the end of the fiscal year; MTB =book-to-market ratio at the end of the fiscal year; SO = indicator variable that takes the value of one if thefirm introduced stock option, and zero otherwise; AF = the number of analyst followings; ZS = Z-score,computed using Altman’s (1968) model; EV = standard deviation of income before extraordinary items(scaled by lagged total assets) for 3-year period (t+1 to t+3). All variables are winsorized at 1% by year.Industry dummy = an indicator variable for Nikkei industry classification code (Nikkei gyousyu chu-bunrui);t-statistics are corrected for heteroskedasticity, and cross-sectional and time-series correlation using a two-waycluster at the firm- and year-level proposed by Petersen (2009).*** Statistically significant at the 0.01 level of significance using a two-tailed t-test; ** Statistically significantat the 0.05 level of significance using a two-tailed t-test; * Statistically significant at the 0.1 level of significanceusing a two-tailed t-test.

less-than-0.01 level, as expected. On the other hand, in the fourth column, thecoefficient of STABLE, −0.170, is not significantly associated with ES GAR. In model(2), in order to conduct further analyses of stable shareholdings, we divide stableshareholdings into two ownership structures: cross-shareholdings (CROSS) and stableshareholdings owned by financial institutions (FSTABLE). The regression results arepresented in the last two columns of Table 5. The table shows that while the coefficientsof CROSS and FSTABLE are significantly negative at the less-than-0.01 level in theES INFO models, both coefficients are not significant in the ES GAR model. The resultsare consistent with our hypothesis and the theories advocating the informationalrole of earnings smoothing (Chaney and Lewis, 1995; Demski, 1998; Sankar andSubramanyam, 2001; Kirschenheiter and Melumad, 2002; Gu, 2005).

In contrast, the coefficients of FOREIGN are significantly and positively associatedwith the earnings smoothing variables across all models. The results suggest thatmanagers with greater foreign ownership tend to report more volatile earnings; thisis consistent with our prediction, which assumes that foreign shareholders inducemanagers to inflate their earnings to attain short-term earnings goals.

These results hold after controlling for other ownership structures, firm size, cashflow variability, sales variability, operating cycle length, incidence of negative earningsrealizations, intangible intensity, capital intensity, equity incentive, analyst following,future earnings volatility and bankruptcy risk. Among 13 control variables in ES INFOmodel (1), the coefficients of nine variables have expected signs. However, contrary



Table 5Regressions Results on the Relationship between Stable shareholdings and

Abnormal Discretionary expenses

Model 5 Model 6ADISEXP ADISEXP

Independent Variable Expected Sign Coefficient (t-value) Coefficient (t-value)

Constant 0.031 0.036(1.050) (1.211)

LOSSD − −0.019*** −0.022***

(−5.958) (−4.994)STABLE + −0.020*

(−1.835)CROSS + −0.054***

(−2.744)FSTABLE + −0.018

(−1.605)FOREIGN − 0.006 0.003

(0.300) (0.145)LOSSD* STABLE + 0.039***

(4.177)LOSSD* CROSS + 0.065***

(2.780)LOSSD* FSTABLE + 0.038***

(4.437)LOSSD* FOREIGN − 0.010 0.012

(0.555) (0.664)MO +/− 0.031 0.026

(1.077) (0.899)ASSET + −0.000 0.000

(−0.007) (0.162)CFO − 0.064* 0.058*

(1.827) (1.660)SALES − −0.068*** −0.071***

(−3.869) (−4.013)CYCLE − −0.006 −0.006

(−1.261) (−1.316)LOSS − −0.001 −0.002

(−0.242) (−0.295)CINT − −0.040*** −0.041***

(−2.800) (−2.876)MTB − 0.002 0.001

(1.497) (1.264)SO − 0.010*** 0.009***

(2.913) (2.846)AF − 0.001** 0.001**

(2.154) (2.016)ZS − 0.004 0.003

(0.704) (0.587)EV − −0.057 −0.060

(−0.879) (−0.911)(Continued)



Table 5Continued

Model 5 Model 6ADISEXP ADISEXP

Independent Variable Expected Sign Coefficient (t-value) Coefficient (t-value)

Industry dummy Yes YesAdj. R2 0.038 0.039N 7,784 7,784

Note:ADISEXP = the value of abnormal discretionary expense; LOSSD = an indicator variable that takes thevalues of one if the firm has scaled earnings in the interval between 0 (inclusive) and 0.0058 (exclusive),and zero otherwise; STABLE = fraction of the stable shareholdings by financial institutions and non-financialcompanies at the end of fiscal year; CROSS = fraction of the shares owned by cross-shareholders at the end offiscal year; STABLE = fraction of the shares owned by stable shareholders at the end of the fiscal year. Stableshareholdings are classified into the cross-shareholdings (CROSS) and the stable shareholdings by financialinstitutions (FSTABLE); FOREIGN = fraction of the shares owned by foreign companies at the end of thefiscal year; MO = fraction of the shares owned by directors at the end of the fiscal year; ASSET = log of totalassets at the end of the fiscal year; CFO = standard deviation of cash flows from operations (scaled by laggedtotal assets) for 5-year period (t to t–4); SALE = standard deviation of sales revenues (scaled by lagged totalassets) for 5-year period (t to t–4); CYCLE = log of the sum of the firm’s days accounts receivable (yearlyaverage accounts receivable)/(total revenue/360)) and days inventory ((yearly average inventory)/(costof goods sold/360)). If the cost of goods sold number is not reported, we use the total revenue minusoperating income instead; LOSS = proportion of losses over the last 5 years; CINT = ratio of the net bookvalue of PP&E to total assets at the end of the fiscal year; MTB = book-to-market ratio at the end of thefiscal year; SO = indicator variable that takes the value of one if the firm introduced stock option, and zerootherwise; AF = the number of analyst followings; ZS = Z-score, computed using Altman’s (1968)model;EV = standard deviation of income before extraordinary items (scaled by lagged total assets) for 3-yearperiod (t+1 to t+3); All variables are winsorized at 1% by year; Industry dummy = an indicator variable forNikkei industry classification code (Nikkei gyousyu chu-bunrui). t-statistics are corrected for heteroskedasticity,and cross-sectional and time-series correlation using a two-way cluster at the firm- and year-level proposedby Petersen (2009).*** Statistically significant at the 0.01 level of significance using a two-tailed t-test; ** Statistically significantat the 0.05 level of significance using a two-tailed t-test; * Statistically significant at the 0.1 level of significanceusing a two-tailed t-test.

to expectations, four variables, ASSET, LOSS, MTB and EV, have coefficients withunexpected signs.18

Further, we conducted an additional analysis to examine whether firms with stableshareholdings actually report stable earnings strings through earnings smoothing.Specifically, we classified our sample into two subsamples based on the value ofstable shareholdings and calculated the standard deviation of annual earnings overthe past 5 years for each observation. We then compared the results for the twosubsamples. Our untabulated results for the parametric and the non-parametric testsreveal that the standard deviation of earnings is significantly greater for the morestable shareholdings subsample.19 These results are consistent with our hypothesis

18 We might interpret these unexpected results as suggesting that large firms with more stable andpredictable operations have flexibility to conduct informational earnings smoothing. Further, assumingthat MTB reflects the growth opportunity of the firms, growth firms might signal their growth opportunitythrough earnings smoothing. Firms with losses might also have incentives to use earnings smoothing toconvey useful information to stakeholders and maintain a relationship with them. Finally, earnings withmore informational components through earnings smoothing might reduce future earnings volatility.19 We also examined whether firms with more stable shareholdings report longer strings of annual earningsincreases. Similar to the analysis of the standard deviation of earnings, we compared the length of the stringsof consecutive earnings increases of the two subsamples. Our results indicate that the length of the string of



that firms with more stable shareholdings tend to report more stable earnings strings,suggesting that earnings smoothing by firms with stable shareholders could createmore stable earnings strings.

The results suggest that firms’ managers smooth their earnings to convey moreprecise information about future earnings to stable shareholders in order to maintainlong-term relationships with them.

6. ADDITIONAL ANALYSES

(i) Real Discretionary Behavior to Meet Short-term Earnings Targets

In this section, we examine the relationship between stable shareholdings and one ofthe typical myopic behaviors: real discretionary behavior to meet short-term earningstargets. Prior studies provide evidence indicating that firm managers, rather thanmaximizing long-term value, manipulate real activities in order to meet short-termearnings goals, for example, by reducing R&D and advertising expenses (Dechow andSloan, 1991; Murphy and Zimmerman, 1993; Bushee, 1998; Lam et al., 2002; Cheng,2004).

Bushee’s (1998) analyses are similar to our study in that he focuses on therelationship between institutional ownership with short-term investment horizons andreal discretionary behavior (R&D). Specifically, he shows that concentrated ownershipby “transient” institutions significantly increases the probability that managers cut R&Dto meet earnings benchmarks.

Because stable shareholdings and Bushee’s (1998) institutional ownership areexpected to have contrary effects on discretionary behavior, we predict that stableshareholdings reduce incentives for managers to cut discretionary expenditures suchas R&D in order to achieve short-term earnings goals. Specifically, by employingthe following regression model, we investigate whether stable shareholdings restrictmanagers to reducing discretionary expenditures in order to avoid earnings losses.

ADISEXP = a + ß1LOSSD + ß2STABLE + ß3FOREIGN + ß4LOSSD ∗ STABLE

+ ß5LOSSD ∗ FOREIGN + ß6MO + ß7ASSET + ß8CFO + ß9SALES

+ ß10CYCLE + ß11LOSS + ß12CINT + ß13MTB + ß14SO + ß15AF

+ ß16ZS + ß17 E V + industry dummy + ε (5)

ADISEXP = a + ß1LOSSD + ß2CROSS + ß3FSTABLE + ß4FOREIGN

+ ß5LOSSD ∗ CROSS + ß6LOSSD ∗ FSTABLE + ß7LOSSD ∗ FOREIGN

+ ß8MO + ß9ASSET + ß10CFO + ß11SALES + ß12CYCLE + ß13LOSS

+ ß14CINT + ß15MTB + ß16SO + ß17AF + ß18ZS + ß19EV

+ industry dummy + ε (6)

consecutive earnings increases is significantly less for the more stable shareholdings subsample. This resultsuggests that stable shareholdings could reduce the possibility of a myopic problem, which is consistent withour hypothesis.



where

ADISEXP = the value of abnormal discretionary expense followingRoychowdhury’s (2006) model;LOSSD = an indicator variable that takes the value of one if reported earnings are

slightly greater than zero, and zero otherwise.

This study extends prior research by measuring discretionary expense in detail.Specifically, we estimate abnormal discretionary expense (ADISEXP) by using Roy-chowdhury’s (2006) model, which can capture abnormal discretionary expenditurescomprehensively, including R&D, advertising, promotion expenses and other sellingcosts.20 Here, we focus on loss avoidance as a form of earnings management to meetshort-term earnings goals.21 LOSSD is an indicator variable that takes the value of one ifreported earnings are slightly greater than zero, and zero otherwise.22 Thus, a negativecoefficient of LOSSD means that managers manipulate real earnings to avoid earningslosses.

Our primary concern is the coefficient of LOSSD*STABLE (LOSSD*CROSS andLOSSD*FSTABLE). If stable shareholdings prevent firm managers from reducingdiscretionary expenditures as predicted, the coefficient of LOSSD*STABLE is expectedto be positive, which is contrary to that of LOSSD.

The analysis in this section is restricted to firms sampled between 2000 and 2008,thereby reducing the sample size to 7,784. This is because detailed systematic data onresearch and development costs are not available for the period before the year 2000from the database used in this study.23

Table 5 presents the regression results. The negative coefficient of LOSSD meansthat managers are likely to reduce abnormal discretionary expenditures to meet short-term earnings targets (i.e., to avoid earnings losses). The table also indicates that thecoefficient of LOSSD*STABLE is significantly positive at the less-than-0.01 level. Wealso find that the coefficients of LOSSD*CROSS and LOSSD*FSTABLE are significantand have the expected sign.

Further, by using a regression model similar to model (5), we examined theeffect of stable shareholdings on the relationship between discretionary accruals,which reflect discretionary accounting behavior and loss avoidance. Untabulatedresults indicate that managers are less likely to manage earnings to avoid lossesby using discretionary accruals as stable shareholdings increase. These results areconsistent with our prediction and the results regarding the aforementioned abnormaldiscretionary expenditures.

20 The detailed estimation method of Roychowdhury (2006) is summarized in the Appendix.21 Bushee (1998) investigates earnings management used to avoid earnings decline. We focus on the lossavoidance situation because most studies on Japanese firms already provide evidence that while managershave less incentive to use real discretionary behaviors to avoid earnings decreases, they have strong incentivesto avoid earnings losses by using this method (Yamaguchi, 2009; Tazawa, 2010).22 We define firms reporting earnings that are slightly greater than zero as firms reporting earnings scaledby the total asset in the interval between 0 (inclusive) and 0.0058 (exclusive), which is the interval to theimmediate left of zero in the histogram of scaled earnings. This interval size of the histogram is based onthe method of Freedman and Diaconis (1981) used in Degeorge et al. (1999).23 In 1998, the Business Accounting Deliberation Council, which had set forth Japanese GAAP, issued anew accounting standard: The Accounting Standard for Research and Development Costs. This standard statesthat research and development costs should be charged to expenses immediately when they are paid; thistreatment is identical to that of US GAAP. Because this new standard on R&D was applicable from March2000, we restrict our sample period to this start date.C© 2014 John Wiley & Sons Ltd


Therefore, our results suggest that managers with stable shareholdings that usuallyhave long investment horizons do not tend to conduct myopic behavior and discre-tionary expenditures in order to meet short-term earnings goals.

(ii) Robustness of the Results

In this section, we describe an analysis conducted to verify the robustness of our results.In particular, we examine whether the results depend on the alternative definition ofSTABLE. Here, we use the mean value of the firm’s rolling 5-year stable shareholdings(STABLE5) instead of STABLE, since we also calculate the basic earnings smoothingvariables by using rolling 5-year windows. Our untabulated result reveals that thecoefficients of STABLE5 are significantly negative in the ES INFO models. On the otherhand, STABLE5 is not significantly associated with ES GAR. This is consistent with ourhypothesis. Therefore, according to the above robustness test, our study’s results arerobust.

7. CONCLUSION

A unique feature of the ownership structure in the Japanese stock market is theexistence of stable shareholdings such as cross-shareholdings and stable shareholdingsowned by financial institutions. Prior studies on economic and accounting theoryargue that stable shareholders do not encourage firm managers to inflate theirearnings to achieve short-term earnings goals (Abegglen and Stalk, 1985; Porter, 1992;Jacobson and Aaker, 1993; Osano, 1996). In addition, firm managers with stableshareholders have an incentive to report smoother earnings in order to maintain along-term relationship with stable shareholders (Dou et al., 2013).

To test the implications of the argument, we examined the effect of stableshareholdings on the earnings smoothing behaviors of Japanese firms. Specifically, wehypothesized that stable shareholdings are positively associated with the informationalcomponents of earnings smoothing. Consistent with our hypothesis, we found thatas stable shareholdings increase, managers are more likely to conduct earningssmoothing that provides useful information to stable shareholders. Further, ouradditional analysis showed that stable shareholdings reduce incentives for managers tocut discretionary expenditures, such as R&D and advertising expenses, to meet short-term earnings benchmarks, thereby implying that stable shareholdings could reducethe possible occurrence of a myopic problem. These results suggest that managerswith stable shareholdings tend to report smoother and less volatile earnings, and donot tend to pursue earnings management to reach short-term earnings targets.

This study contributes to the literature and understanding of accounting practice inseveral ways. First, we clarify how stable shareholdings with long-term decision horizonscreate an earnings management incentive. While the relationship between earningsmanagement behavior and an ownership structure with short-term decision horizonshas already been investigated (Bushee, 1998), few studies examine the effect of stableshareholdings with long-term decision horizons on earnings management behavior.Second, we contribute to research that examines the informational components ofearnings smoothing by providing evidence that firm managers use smoother earningsto maintain a long-term relationship with their stable shareholders.



It must be noted that this study has certain limitations. First, we cannot deny thepossibility that the earnings management measures used in this study have someestimation errors. Second, although our main concern is to examine the extent towhich reported accruals are used to smooth earnings relative to any real smoothingeffect, future research could examine the effect of stable shareholdings on real activitybehavior such as investment decision making. Finally, future research should addressthe problem of simultaneity. Although we assume that the shareholdings of stableshareholders affect the earnings management behavior of managers, we cannot ruleout the alternative hypothesis that stable shareholders simply invest in firms withsmoother earnings.

APPENDIX

Measurement of Discretionary Accruals and Abnormal Discretionary Expenses

Discretionary Accruals

We estimated discretionary accruals using the modified Jones model (Dechow et al.,1995). The model is a regression of total accruals (TAC) on the change in revenueadjusted for the change in receivables (�REV – �REC), the levels of property, plantand equipment (PPE).

TAC = a + ß1(�R E V –�R E C) + ß2PP E + ε,

where

TAC = [(�current assets − �cash and cash equivalents) − (�current liabilities −�financing item) − �other allowance – depreciation] divided by total assets at theprevious year;

�REV = change in sales revenues divided by total assets at the previous year;�REC = change in accounting receivables divided by total assets at the previous year;PPE = gross property, plant and equipment divided by total assets at the previous year.

The model is estimated cross-sectionally for each industry in a given year accordingto the Nikkei industry classification code (Nikkei gyousyu chu-bunrui). Using theestimated coefficients of the model, we measured non-discretionary accruals (NDA).The difference between total accruals and measured non-discretionary accruals is aproxy for discretionary accruals (DA).

Abnormal Discretionary Expense

We estimated abnormal discretionary expense using Roychowdhury‘s (2006) model.The model is a regression of discretionary expense (DISEXP) on the sales revenues(SALE). We set the missing data for the discretionary expense items equal to zero.

DISEXP = α + ß1A + ß2SALE + ε,

where



DISEXP = (research and development expenditure + advertising expense, promotionexpenses and other selling costs + labor cost and welfare expense + salary and bonusfor directors) divided by total assets at the previous year;

A = the value of one divided by total assets at the previous year;SALE = sales revenues at the previous year divided by total assets at the previous year.

The model is estimated cross-sectionally for each industry in a given year accordingto the Nikkei industry classification code (Nikkei gyousyu chu-bunrui). Similar to theNDA estimation, we measured the normal discretionary expense (NDISEXP) usingthe model‘s estimated coefficients. The difference between DISEXP and measuredNDISEXP is a proxy for abnormal discretionary expense (ADISEXP).

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stable shareholdings, the decision horizon problem and earnings smoothing

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