What Do Smoothed Earnings Tell Us about the Future?*
Yusuke Takasu†

Graduate School of Commerce and Management
Hitotsubashi University

Makoto Nakano

Graduate School of Commerce and Management
Hitotsubashi University

ABSTRACTThis study analyzes the information contents of income smoothing behavior, especiallythe role of income smoothing behavior as a signal of future performance. What dosmoothed earnings tell us about the future? To answer this research question, this paper
focuses on earnings persistence and dividend policy based on two prior survey papers.
These two issues (earnings persistence and dividend policy) are the foci of this study,
based on Japanese managers’ responses to questions regarding their motivation for incomesmoothing. This paper provides two new pieces of evidence. First, income smoothing in
the previous period relates positively to future earnings persistence. Second, firms thatengage in more smoothing tend to pay more stable dividends in the future, even when we
control for past dividend policy, fundamental factors, and corporate governance factors.
These results indicate that income smoothing behavior is likely to reflect future stability ofearnings performance. Income smoothing acts as a vehicle through which managers canreveal private information about future earnings persistence and future dividend policy. The
empirical evidence supports the information view rather than a garbling view of incomesmoothing, and sheds light on the bright side of smoothed earnings rather than its darkside.
JEL Classification: M41; G14; G35
Key Words: Income Smoothing; Private Information; Earnings Persistence; Dividened Policy* We wish to warmly thank the editor in chief (Hidetoshi Yamaji), two anonymous referees for many engaging comments andsome challenging requests. We have also benefited from discussions with participants at the European Accounting Association
35th Annual Congress in Ljubljana, Slovenia, 23rd Asian-Pacific Conference on International Accounting Issues in Beijing,
China, and TJAR Doctoral Workshop. The authors thank financial support from the GCOE program “Innovation in the JapaneseCorporation” at Hitotsubashi University. Final thanks go to our colleagues. All remaining errors are our own.
† Corresponding Author. Address Hitotsubashi University 2-1, Naka, Kunitachi-shi, Tokyo, JAPAN.
Telephone +81(42) 580-8745 E-mail cd121006@g.hit-u.ac.jp
Received November 1, 2011; accepted June 30, 2012
Copyright©2012 Research Institute for Economics & Business Administration – Kobe University.

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The Japanese Accounting Review, 2 (2012), 1-32

1. Introduction
Earnings quality is one of the most controversial issues, and a subject of growing concern infinancial accounting research and accounting-standards settings (Francis et al. 2004; Barth et al.
2008; Dechow et al. 2010). It has been examined from a number of perspectives. There exist several
concepts and measures of earnings quality; Francis et al. (2004), for example, present seven earnings
attributes: accrual quality, persistence, predictability, smoothness, value relevance, timeliness, andconservatism. Among these earnings attributes, this study sheds light on income smoothing. The
existence of income smoothing itself has long been discussed in practice and in academic literature,and some empirical and analytical studies focus on income smoothing. In particular, many researchers
have analyzed the relationship between income smoothing behavior and either stock returns or costof equity capital, e.g. (Hunt et al. 2000; Francis et al. 2004; Tucker and Zarowin 2006; McInnis
2010). These studies assume that income smoothing behavior reflects a manager’s private information
regarding future performance (Francis et al. 2004). There is, however, a counterargument that incomesmoothing behavior obfuscates earnings information (Bhattacharya et al. 2003; Leuz et al. 2003).
This study analyzes the information contents of income smoothing behavior, especially the role ofincome smoothing behavior as a signal of future performance. What do smoothed earnings tell us
about the future? To answer this research question, this paper focuses on earnings persistence anddividend policy, based on two survey papers by Graham et al. (2005) and Suda and Hanaeda (2008).
Top management has shown a clear preference for income smoothing. Graham et al. (2005,
p. 44) reported that “an overwhelming 96.9% of the survey respondents indicate that they prefera smooth earnings path,” as it keeps cash flow constant. Why do top managers prefer incomesmoothing? In a comparable survey undertaken in Japan, the two reasons most frequently cited were
(1) it enables stable dividends, and (2) it assures customers/suppliers that a business is stable (Sudaand Hanaeda 2008). Therefore, it seems that “stability” is a key word in understanding the motivation
for income smoothing. If income smoothing behavior reflects a manager’s private information about
future performance, the earnings of firms that engage in more smoothing are more informative. On
the other hand, if income smoothing reflects garbling (opportunistic) behavior, the earnings of firmsthat engage in more smoothing would not inform outsiders about any valuable information.
This study focuses on Japanese firms for two reasons. First, John et al. (2008) and Acharya etal. (2011) reported that the time-series volatility of return on assets in Japan is the lowest among
35 countries around the world. For example, although the average volatility of American, British,
German, and Australian firms is 8.8 percent, 7.1 percent, 5.7 percent, and 12.1 percent, respectively,
the average volatility of Japanese firms is only 2.2 percent. This evidence suggests there is a highpossibility that Japanese firms’ managers aggressively smooth earnings compared with managers inother countries. It is beneficial for us to test our hypotheses in the Japanese setting because we can
explore the unique earnings management behaviors that may be specific to Japanese firms.
Second, Denis and Osobov (2008) found that more Japanese firms pay dividends comparedwith firms in other countries. For example, although the proportion of dividend-paying firms in the
United States and Canada in 2002 was 19.0 percent and 19.9 percent, respectively, the proportion ofdividend-paying firms in Japan in 2002 is 83.8 percent. This fact may produce pressure on managers
to pay dividends. Because most Japanese firms pay dividends, we can use a large sample to test our
hypothesis. Moreover, during the sample period, approximately 40 percent of Japanese firms adopted
a stable dividend policy. This may produce pressure on managers to maintain stable dividends, thereby
encouraging managers to smooth earnings in order to maintain stable dividends. This pressure

Takasu and Nakano: What Do Smoothed Earnings Tell Us about the Future?

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might urge managers to engage in ad hoc income smoothing without ample consideration of future
performance.
This study provides two new empirical findings. First, income smoothing relates positively toearnings persistence. This implies that income smoothing behavior reflects high earnings persistencein the future. Second, firms those engage in more smoothing pay stable dividends in the future. There
are fewer non-dividend payers among firms that engage in more smoothing than among firms thatengage in less smoothing. Income smoothing is informative with respect to a firm’s future stabledividends, and functions as a signal even when we control for past dividend policy, fundamental
factors, and corporate governance factors. Given Lintner (1956)’s argument that the change in
dividend amount reflects the change in the level of long-term and persistent earnings, it would
appear that income smoothing behavior reflects long-term stability of firm performance.
Overall, the evidence shows that Japanese managers, on average, tend to smooth earnings with
future earnings performance in mind. The results are robust to the alternative definitions of incomesmoothing posited by Hunt et al. (2000), Leuz et al. (2003), Francis et al. (2004), and Tucker andZarowin (2006), and to varying model specifications.
This study makes several contributions to the literature and understanding of income smoothing
behavior. First, we build on recent advances in the literature vis-à-vis earnings quality, especially
income smoothing. Although most prior studies focus on the economic consequences of incomesmoothing—for example, Francis et al. (2004) found that firms that engage in more smoothing havelower cost of capital than firms that engage in less smoothing—few studies provide evidence as towhether or not income smoothing reflects future performance. The current study fills this gap.
Second, the empirical evidence supports the information view rather than a garbling viewof income smoothing. As mentioned above, few studies provide evidence as to whether incomesmoothing reflects future performance. The exception is Tucker and Zarowin (2006), who provided
evidence that income smoothing reflects future earnings persistence, although earnings persistence
may not fully stand as a proxy for future stability. Managers’ discretion may be included in bothcurrent and future net income. Furthermore, the earnings persistence coefficient estimated from thefirst-order auto-regressive calculation process might capture only the short-term stability of a firm’s
performance. The current study analyzes the information content of income smoothing from two
perspectives; short-term stability (earnings persistence) and long-term stability (dividend policy).
From these analyses, this study sheds light on the bright side of smoothed earnings rather than its
dark side.
The remainder of this paper is organized as follows. Section 2 reviews the literature and presents
the hypotheses. Section 3 provides details about the research design and sampling methodology.
Section 4 examines the relationship between income smoothing and future earnings persistence
and the relation between income smoothing and future dividend policy, to investigate the role ofsmoothed earnings paths as a signal about a firm’s future performance stability. Section 5 includes
robustness checks. Section 6 summarizes the paper and provides concluding remarks.

2. Prior Literature and Hypotheses
With respect to managers’ motivations vis-à-vis financial reporting, some influential survey
articles have come from the United States (Graham et al. 2005) and Japan (Suda and Hanaeda 2008).
In the United States, “an overwhelming 96.9% of the survey respondents indicate that they prefer a

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The Japanese Accounting Review, 2 (2012), 1-32

smooth earnings path” (Graham et al. 2005, p. 44), as it keeps cash flow constant. In Japan, 44 percentof the respondents in Suda and Hanaeda (2008)’s survey indicated that they might sacrifice corporate
value in order to report smoothed income. Managers have a high tendency to avoid a bumpy earnings
path, in both the United States and Japan.
Why do Japanese managers smooth earnings? What are their motivations for doing so?
According to Suda and Hanaeda (2008),1 the top two answers are that doing so (1) enables stabledividends (62.5 percent) and (2) assures customers/suppliers that the business is stable (55.2 percent).
This study investigates the link between income smoothing and the stability of Japanese firms, interms of these two managerial responses.2
Although managers have strong preference for income smoothing, there are two conflicting
viewpoints on income smoothing: (1) the information view and (2) the garbling view. First, theinformation view posits that managers can communicate private information about future earnings
through smoothing behavior, as well as mitigate any information asymmetry problems (Francis etal. 2004). Tucker and Zarowin (2006) found that the future earnings of firms that engage in moresmoothing are more likely to be impounded into their current stock returns than those of firms thatengage in less smoothing; they concluded that income smoothing improves the informativeness ofearnings.
Second, in contrast, smoothed income may include garbling information. Managers may
manipulate reported earnings for private reasons, including those related to their own compensation(Healy 1985) and career-related concerns in the manager labor market. Leuz et al. (2003) viewed
income smoothing as a device used by insiders to obfuscate their consumption of private-control
benefits, and Bhattacharya et al. (2003), in their international comparison study, contended thatsmoothing leads to greater earnings “opacity.” Which perspective is correct? This is still an open
question, and it seems to be an empirical issue.
While it is possible to categorize viewpoints conceptually as being in one of the two
aforementioned conflicting streams, it can be difficult to disentangle the actual smoothness of reported
earnings. Reported earnings may reflect the smoothness of (1) the fundamental earnings process, (2)financial accounting rules, or (3) managers’ intentional earnings manipulation (Dechow et al. 2010).
The current paper defines income smoothing as a manager’s tendency to exhibit accounting
behavior that decreases reported income volatility, compared to that of pre-discretionary income.
Cohen et al. (2008) found that firms have changed from accrued to real earnings management
following the implementation of the Sarbanes–Oxley Act (SOX); the reason is that SOX has madeaccrual-based earnings management more costly. Considering their finding, the current paper’s
definition of smoothing considers both accrual discretion and real discretion.
Using this definition, and given above managers’ preference for income smoothing, theirmotivation to smooth earnings, and the two conflicting perspectives, we investigate whether incomesmoothing behavior is informative or opportunistic. If income smoothing behavior reflects managers’
private information regarding future performance, which is consistent with Francis et al. (2004)’s
argument, then the earnings of firms that engage in more smoothing are more informative. In
When asked why they smooth income, the top three answers among managers in the United States were that doing so (1) leads toperceptions among investors that the firm is not risky, (2) makes it easier for analysts/investors to predict future earnings, and (3)assures customers/suppliers that the business is stable (Graham et al. 2005).
2
Shuto and Iwasaki (2012) found that a stable shareholder structure encourages managers to perform income smoothing in Japan.
They focused on the determinants of income smoothing. Our study, in contrast, investigates both the economic consequences andsignaling role of income smoothing.
1

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5

particular, if income smoothing behavior truly reflects future firm stability, which is what managers
want to convey to outsiders by smoothing earnings (Suda and Hanaeda 2008), then outsiders canrecognize the stability by observing the smoothed earnings path. On the other hand, if incomesmoothing reflects garbling (opportunistic) behavior, that is, managers’ behavior to deceive outsiders
and obfuscate their consumption of private-control benefits (Leuz et al. 2003), then the earnings offirms that engage in more smoothing would not offer outsiders any valuable information.
To investigate this effect of income smoothing behavior, we test two hypotheses. In thefirst hypothesis, we directly test the relationship between current smoothed earnings and future
performance. This study focuses on earnings persistence. Dichev and Tang (2009) found that earnings
volatility relates negatively to earnings persistence. This implies that low earnings volatility in the pasthas the role of a signal regarding future persistent earnings to outsiders. Extending Dichev and Tang
(2009)’s research, Nakano and Takasu (2011) provided evidence that earnings management in theprevious period has a negative impact on future earnings persistence. This implies that past earnings
management has the role of a negative signal to outsiders regarding future earnings persistence.
Although these studies analyzed the relationship between earnings volatility and earnings persistence,
they did not address income smoothing behavior.3 As mentioned above, earnings smoothness (i.e.,
low earnings volatility) may reflect both a firm’s fundamentals and manager discretion (Dechow etal. 2010). However, Dichev and Tang (2009) made little consideration for this point in their research
design. If income smoothing behavior is ad hoc behavior in order to smooth current earnings without
consideration on future performance, discretionary smoothed earnings might not have a role asa signal regarding future earnings persistence. On the other hand, as long as income smoothing
behavior reflects managers’ private information about future earnings stability, discretionary smoothed
earnings could have a role as a signal about future earnings persistence.
From the above discussions, we develop the first hypothesis:
H1: Firms that engaged in more smoothing in the past (period t – 4 to t) have higher
earnings persistence (period t to t + 1) than firms that engaged in less smoothing.
A similar analysis was conducted by Tucker and Zarowin (2006), who analyzed the relationshipbetween income smoothing and earnings persistence. Earnings persistence, however, may not be fully
appropriate to estimate future performance stability because future net income includes management
discretion. To cope with this problem, we also analyze “adjusted” earnings persistence, which is thecoefficient of the regression of pre-discretionary income for year t + 1 on net income for year t. If
income smoothing behavior reflects managers’ private information about future earnings stability andapproximates permanent earnings thorough current smoothed earnings, the coefficient would also
become higher even when pre-discretionary income for year t + 1 is used as the dependent variable.
In the second hypothesis, we analyze the relationship between current smoothed earnings
and future dividend policy. Although this test indirectly analyzes the relationship between current
smoothed earnings and future earnings, we consider future dividend policy as worthwhile ininvestigating whether income smoothing behavior is informative or opportunistic because it wassuggested by Lintner (1956) that the change in dividend amount is dependent on the change inthe level of long-term and persistent earnings. Therefore, from this argument, it is implied that the3

Although Nakano and Takasu (2011) analyzed earnings management in general situations, they did not focus on the incomesmoothing situation specifically.

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The Japanese Accounting Review, 2 (2012), 1-32

change in dividend policy might reflect management belief about future earnings performance.
Denis and Osobov (2008) reported that over 80 percent of Japanese firms paid dividends during theperiod 1990 – 2002. When compared with other countries, this is a unique dividend policy. For instance,
the percentage of dividend payers in 2002 was 19.0 percent in the United States and 19.9 percent in
Canada. In contrast, 83.8 percent of Japanese firms paid dividends in 2002. In addition, our calculation
documents that 40 percent of firms, on average, are categorized as “stable payers” over the period 1995–
2009. “Stable payers” are firms paying the same amount of dividend per share for two consecutive years. It
should be noted that stable dividends are a uniquely Japanese payout strategy.
Through a survey of Japanese firms, Suda and Hanaeda (2008) found that 62.5 percent ofrespondents expected income smoothing to enable stable dividends, and recognized this point as the mostimportant motivation behind their smoothing behavior. Since this income smoothing motivation seems
to reflect managers’ recognition of the importance of stable dividends, it seems managers tend to smoothcurrent earnings in order to pay stable dividends in the current year.4 If income smoothing behavior
reflects earnings garbling behavior to pay stable dividends in the current year without consideration of
future performance, firms that engage in more smoothing will tend to pay volatile dividends in the future
because managers may not be able to maintain ad hoc income smoothing behavior in the future. On theother hand, if income smoothing behavior reflects future firm performance stability, firms that engaged
in more smoothing will tend to pay stable dividends in the future. If current income smoothing behavior
positively relates to a stable dividend policy in the future, current income smoothing has a role as a positive
signal about the firm’s future performance stability because, following Linter (1956)’s implication, a stabledividend policy reflects managers’ belief about future performance stability,
From the above discussions, we develop the second hypothesis:
H2: Firms that engaged in more smoothing in the past (period t – 4 to t) have a higher
tendency to pay stable dividends in the future (periods t to t + 1 and t + 1 to t + 2) thanfirms that engaged in less smoothing.
Hypothesis 2 assumes that income smoothing behavior functions as a signal of future dividend
stability.
Testing these two hypotheses (earnings persistence and stable dividend policy), we investigate therelationship between income smoothing behavior and future firm stability. In this study, we capture thefirm’s stability through future earnings persistence and future stable dividends. On one hand, we regard
future earnings persistence as short-term stability of firm performance because future earnings persistenceis measured by the coefficient estimated from the regression of net income for year t + 1 on the net
income for year t. On the other hand, we regard future stable dividend policy as longer-term stability offirm performance because Lintner (1956) suggested that the change in dividend amount is dependent on
the change in the level of long-term and persistent earnings. Although short-term earnings persistence isviewed as one of the factors that affect dividend policy, it would appear that stable dividend policy reflects
not only short-term earnings persistence but also long-term stability of earnings performance.
4

Note that there is little consensus regarding the reason why managers prefer stable dividends in Japan, despite their strong
preference for stable dividends. This is one of the limitations of our research. Serita et al. (2011), however, provided a clue tointerpreting this phenomenon. They showed that some institutional investors, specifically banks and pension funds, prefer stabledividends. If managers want to cater to the demands of these institutional investors, they might choose stable dividend policies.
In particular, because Japanese firms are highly connected with a specific bank (i.e., main bank), managers might cater to thedemands of that bank.

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3. Research Design
3.1 Income Smoothing Measure
The current study defines “income smoothing” as a manager’s will to decrease reported income
volatility compared to that of pre-discretionary income. The proxy variable of the degree of smoothingis defined as firm-specific historical volatility of net income that is calculated as standard deviation of
it over the most recent five years, divided by volatility of pre-discretionary income that is calculated
as standard deviation of it over the most recent five years (Vol(NI)/Vol(PDI)). Both net income (NI)and pre-discretionary income (PDI) are deflated by total assets at the beginning of year. The smaller
this variable is, the more likely managers are to smooth income. Leuz et al. (2003) and Francis et al.
(2004) use basically the same variable: volatility of reported income, divided by volatility of cash flowfrom operations. Hunt et al. (2000)’s smoothness variable is similar to that of the current study, except
the former includes only accounting discretion; the proxy variable of the current study, on the other
hand, includes both accounting discretion and a part of real discretion. The current study’s measure ofmanager’s smoothing behavior is the most accurate, because the denominator is measuring the purely
pre-discretionary income portion, before either accrual discretion or real discretion has been exercised.
When measuring PDI, the discretionary portion must be specified. As mentioned, discretion
includes both accounting discretion and real discretion. First, this study explains the procedure used toestimate discretionary accruals (DAC); it follows the standard methodology. Total accruals (TAC) aredefined as follows:
Total accrual = (Δcurrent assets – Δcash and cash equivalents)– (Δcurrent liabilities – Δfinancing item5) – Δother allowance6 – depreciation
DAC is estimated as TAC minus nondiscretionary accruals (NDAC). NDAC is estimated via a
regression-based approach, following Kothari et al. (2005).7 In particular, this study estimates NDAC
by industry-year from regression Model (1).
TACt = δ0 + δ 1(1/At–1) + δ 2( ∆St – ∆RECt ) + δ 3 PPEt + δ 4 ROAt + εt

(1)

TACt = total accruals in Fiscal Year t, deflated by total assets
at the beginning of Fiscal Year t
At–1 = total assets at the end of Fiscal Year t –1
∆St = the change in sales from Fiscal Year t-1 to t, deflated by total assets
at the beginning of Fiscal Year t
5∆RECt = the change in accounts receivables from Fiscal Year t-1 to t,deflated
total assets
the inbeginning
FiscalYeartΔfinancing item is the sum of theby
followingitems: atchangeshort-termof
debt,changein commercial
paper, change in current

portion of bonds and convertible bonds.
PPE = gross plant, property and equipment at the end of Fiscal Year t, deflated
Δother allowance is the sum oft the following items: change in allowance for doubtful accounts classified as fixed assets and change
by total assets at the beginning of Fiscal Year t
in long-term provision.
7
This study uses discretionary accruals estimated from Kothari et al. (2005) model. This study focuses on income smoothing wherein= nettheincomebeforeextraordinary
items
Fiscalmodel
Yearusest, deflated
proxies are calculated byROA
considering
variabilityof earnings.
Because Kothariet inal. (2005)
ROA as anby
explanatorytassets at
the beginning
ofatFiscal
Year t removed from our main analyses. The
variable, the effect of earnings ontotal
discretionary
accruals
is, already andleast partially,
results, however, remain unchanged even when we use alternative models, in particular Jones (1991) model and Dechow et al. (1995)
model to calculate discretionary accruals.
6

at the beginning of Fiscal Year t
At–1 = total assets at the end of Fiscal Year t –1
8

The Japanese
Accounting
1-32to t, deflated by total assets∆St = the change
in salesfromReview,
Fiscal2 (2012),
Year t-1
at the beginning of Fiscal Year t∆RECt = the change in accounts receivables from Fiscal Year t-1 to t,deflated
by total assets at the beginning of Fiscal Year t
PPEt = gross plant, property and equipment at the end of Fiscal Year t, deflated
by total assets at the beginning of Fiscal Year t
ROAt = net income before extraordinary items in Fiscal Year t, deflated bytotal assets at the beginning of Fiscal Year t(net income before extraordinary items = net income ± loss and gain from minority interests –gain form extraordinary items + loss from extraordinary items)
DAC is defined as the residual of Model (1).
Second, this study adopts the gain/loss on the sale of marketable securities reported in extraordinary
items, as a real discretion (RD) proxy. This paper does not include other real discretion items such as
research and development (R&D), advertising, or labor expenses because these items are included in
calculation of operating income and we cannot distinguish the effect of these discretionary expenses on
the calculation of DAC from the overall effect of the discretionary expenses on earnings. Also, similarvariable is used in Herrmann et al. (2003). They regard excess income from the sale of assets which ismeasured as income from the sale of fixed assets and marketable securities minus the median for thecorresponding industry and year. They find that firms tend to increase (decrease) earnings through thesale of fixed assets and marketable securities when current reported income is below (above) managers’
forecasts. Due to data restrictions, however, we could not include other items such as gains/losses fromthe sale of fixed assets. Furthermore, in our sample, over fifty percent of firm-years report that the gain/
loss on the sale of marketable securities in extraordinary items is zero. This might imply that there is alow possibility that a firm’s sale of marketable securities is affected by the trend of the same industry-year
firms. If certain firm’s sale of marketable securities was affected by the trend, there are more firm-years
that report the gain/loss on the sale of marketable securities in extraordinary items. Therefore, we regard
the gain/loss on the sale of marketable securities reported in extraordinary items as RD.8 In order to takeaccount of the effect of tax, we estimate the gain/loss on the sale of marketable securities after tax. In
this paper, after tax RD (ATRD) is calculated by multiplying RD by 0.6.9 ATRD is also deflated by total
assets at the beginning of Fiscal Year.10
The sum of DAC and ATRD is defined as total earnings management portion (TEM). PDI is
defined as NI minus TEM.
Total Earnings Management (TEM) = DAC + ATRD
Pre-discretionary income (PDI)= Net income (NI) – Total earnings management (TEM)
Tests are also performed using the gain/loss on the sale of marketable securities minus the median for the corresponding industry
and year as RD. The results remain similar to those reported.
9
To compute the after tax amounts, generally, 40 percent is used as effective tax rate in Japan.
10
In prior literature, normal asset sales are estimated to calculate abnormal asset sales (e.g. Gunny 2010). If a large part of RD isnormal asset sales, our results might be misleading. We regard, however, this concern as a trivial one, because in the robustness
checks where we assume only DAC to be the discretionary portion of NI, the results remain unchanged.
8

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Finally, this study’s proxy variable of smoothness is calculated as the volatility of NI divided
by the volatility of PDI (i.e., Vol(NI)/Vol(PDI)). To control for industry and time effects, following
Tucker and Zarowin (2006), this study uses a firm’s reversed fractional ranking of income smoothing(between 0 and 1) within its industry-year11 and refers to it as Income Smoothing (IS).12 Higher-IS
firms aggressively smooth income in the industry-years to which they belong. Hereafter, this paper
uses IS as a measure of degree of income smoothing. In Section 5, we conduct several robustness
checks with three additional IS measures; IS2, IS3, IS4.
3.2 Framework of Analysis
This paper investigates whether smoothed earnings reflect firm’s future stability of performancethrough the analyses about earnings persistence and dividend policy. This subsection explains theframework and models of this study’s analysis.
3.2.1 Earnings Persistence
In order to investigate the link between smoothing and earnings persistence, this study relies oncommonly used autoregressive regressions of one-year-ahead earnings on current earnings.
NIt+1 = α + β NIt +εt+1(2)

Based on cross-sectional regression, earnings persistence (β) is estimated. When β is close to 1,
earning persistence is high. In contrast, when β is close to 0, earnings include a more transitory factor
and persistence is low.
In the first analysis, ISt quintiles are formed based on the the value of ISt and persistence
is compared. The methodology of Dichev and Tang (2009) is followed for testing differences inpersistence coefficients across quintiles. More specifically, Quintiles 1 (the least smoothing quintile)and 5 (the most smoothing quintile) observations are combined, and Regression (3) on these
combined data is estimated. In Regression (3), Dummyt is a dummy variable that is coded as 1 if a
firm-year belongs to Quintile 1, and 0 if a firm-year belongs to Quintile 5. If the coefficient on theinteraction variable (β3) is statistically significant, the difference in persistence coefficients between
Quintiles 1 and 5 is considered statistically significant.
NIt+1 = α + β1 Dummyt + β 2 NIt + β3 Dummyt *NIt +ε t+1(3)

In the same way, the methodology of Dichev and Tang (2009) is followed for testing
differences in adjusted R2 across quintiles. This study uses a bootstrap test based on a simulationof the empirical distribution of the test statistic, assuming the null is true. In this case, the null
hypothesis is that ISt is unrelated to adjusted R2, and the test statistic is the difference in adjusted
R2 between Quintiles 1 and 5. The empirical distribution under the null is simulated by randomly
splitting the null sample (15,890 observations) into pseudo-ISt quintiles. Regression (2) is thenrun within pseudo-Quintiles 1 and 5 to obtain a difference in adjusted R 2 between the two
1112This paper uses the industry codes of the Securities Identification Code Committee in Japan, which relate to 33 different industries.
For example, assume an industry-year that includes three firms (A, B, and C). If A’s value of the proxy of Income-Smoothing(Vol(NI)/Vol(PDI)) is higher than those of the others and C’s value is lower than those of the others, we rank A, B, and C as 1, 2,
and 3 respectively, and divide each ranking by the number of observations in the industry-year. Therefore, 1/3, 2/3, and 3/3 are theIS values of A, B, and C, respectively.

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The Japanese Accounting Review, 2 (2012), 1-32

Table 1: Definitions of Types of Dividend Policies

Nothing
StableIncrease
Decrease
Omission

From t to t + 1
DPSt = DPSt+1 = 0
DPSt = DPSt+1 ≠ 0
DPSt < DPSt+1
DPSt > DPSt+1
DPSt > DPSt+1=0

Future dividend policy
Our final sample size From t + 1 to t + 2 Our final sample size
1,844
DPSt+1 = DPSt+2 = 0
1,826
7,176
DPSt+1 = DPSt+2 ≠ 0
7,032
4,510
DPSt+1 < DPSt+2
4,428
2,360
DPSt+1> DPSt+2
2,604
521
DPSt+1 > DPSt+2 =0599

Note: DPSt is the dividend per share for Fiscal Year t.		

quintiles. This difference is one observation from the simulated distribution under the null. This
procedure is repeated 1,000 times, yielding a 1,000-observation empirical distribution of adjusted
R2 differences under the null. The formal statistical test is based on a comparison of the actual
observed difference in adjusted R2 against the simulated distribution of differences.
The second analysis is based on Model (4), following Tucker and Zarowin (2006).
NIt+1 = α + β 1 NIt + β 2 ISt + β 3 NI *ISt + εt+1

(4)

Although Model (4) looks similar to Model (3), the former adopts ISt itself rather than a dummy
variable. This model has the advantage of being able to test the relation between income smoothing
behavior and future earnings persistence by using all observations. Of particular interest is the coefficienton NI *ISt, which should be positive if income smoothing reflects future earnings persistence.13
NIt+1 may not be appropriate to estimate future stability because NIt+1 includes management
discretion. To cope with this concern, we estimate model (5) in addition to model (4). In model (5),PDIt+1 is used as the dependent variable. If management use their private information about future
performance and inform their business stability through income smoothing, PDIt+1 may be betterproxy for future stability. In this model, we call β1 “adjusted” earnings persistence.
PDIt+1 = α + β 1 NIt + β 2 ISt + β 3 NI *ISt +ε t+1(5)3.2.2 Dividend Policy
This study explores the link between income smoothing and dividend policy in two ways. First,
it compares the percentages of firms that have “no dividends,” “stable dividends,” “increase dividends,”“decrease dividends”, and “dividends omission” conditioning, based on ISt quintile. Second, logit regressions
are run to investigate the relation between income smoothing in the past and future dividend policy.
This study classifies a firm’s dividend policy as being in one of four categories: no dividends(Nothing), stable dividends (Stable), increase dividends (Increase), and decrease dividends (Decrease).
In addition to these categories, we identify firm-years that omit dividends (Omission). This is because
investors may be interested in future dividend omission. These five categories are defined in Table 1.
Because Omission is the particular type of Decrease, the observations which are included in Omission
also are included in Decrease.
13

Instead of NIt+1, Tucker and Zarowin (2006) use the sum of net income from t+1 to t+3 as the dependent variable. Although we
use the same variable as the dependent variable, the results remain unchanged.

Takasu and Nakano: What Do Smoothed Earnings Tell Us about the Future?

11

In the logit regression analysis, several factors that affect a firm’s dividend policy are controlled.
If the ISt factor is found to be statistically significant even after those factors are controlled, then thelink between smoothing and dividend policy is considered significant. In Japanese corporate law,earnings available for dividends are determined on the basis of unconsolidated earnings. It seems,
however, that consolidated earnings and consolidated payout ratios recently play an important role in
the practice. Therefore we analyze the relation between income smoothing based on the consolidated
earnings and dividends policy. Logit regression is run on Model (6).
		
Yt or t+1 = α + β 1 ISt + β 2 Rank.ROAt + β 3 Rank.Growtht + β4 Tobin sQt + β 5 Rank.Vol(PDI)t+ β 6 Sizet +β 7 Foreignt +β 8 Financialt +β 9 D_inct +β 10 RE / BVEt
+ β 11D_Nothingt–1 + β 12 Stablet–1 + β13 D_Increaset–1 +Yt or t+1 ∈2008

Σ Year dummy + εi=1995it

D_Nothingt , D_Stablet , D_Increaset , D_Decreaset , D_Omissiont
D_Nothingt+1 , D_Stablet+1 , D_Increaset+1 , D_Decreaset+1 , D_Omissiont+1(6)

The dependent variables (Yt or Yt+1) comprise the following ten dummy variables, each of whichtakes one of two possible values. D_Nothingt (D_Nothingt+1) is a dummy variable that is 1 if a firmyear’s dividend policy from t (t + 1) to t + 1 (t + 2) is Nothing, and 0 otherwise. D_Stablet (D_Stablet+1) is a dummy variable that is 1 if a firm-year’s dividend policy from t (t + 1) to t + 1 (t +2) is Stable, and 0 otherwise. D_Increaset (D_Increaset+1) is a dummy variable that is 1 if a firmyear’s dividend policy from t (t + 1) to t + 1 (t + 2) is Increase, and 0 otherwise. D_Decreaset (D_Decreaset+1) is a dummy variable that is 1 if a firm-year’s dividend policy from t (t + 1) to t + 1 (t +2) is Decrease, and 0 otherwise. Finally, D_Omissiont (D_Omissiont+1) is a dummy variable that is 1
if a firm-year’s dividend policy from t (t + 1) to t + 1 (t + 2) is Omission, and 0 otherwise.
The independent variables include the main variable IS t, as well as twelve other control
variables. Denis and Osobov (2008) report that the propensity to pay dividends is higher amongfirms that are larger, are more profitable, and have higher retained earnings. In order to control forthe effect these factors have on dividend policy, the natural logarithm of market value of equity
at the end of Fiscal Year t (Sizet) is added, along with net income before extraordinary income in
Fiscal Year t divided by total assets at the beginning of Fiscal Year t (ROAt), and retained earnings
divided by book value of equity at the end of Fiscal Year t (RE/BVEt). In addition, an earnings
growth dummy (D_inct) is added; it takes a value of 1 if a firm reports positive earnings growthfor Fiscal Year t, and 0 otherwise, because it is possible that the earnings growth affects the firm’s
dividend policy. According to the lifecycle hypothesis vis-à-vis dividends, high-growth firms
tend to retain earnings for reinvesting, thus leading such firms to take a no-dividends strategy. In
contrast, the propensity to pay stable dividends or increase dividends is higher among low-growth,
relatively mature firms. Firms in a declination stage would decrease dividends. The geometricaverage of the five-year sales growth rate (from Fiscal Year t-4 to t) is a proxy for past growth(Growtht). Tobin’s Qt is a proxy variable for investment opportunity in the future. Tobin’s Qt is
defined as the ratio of the sum of the market value of equity and book value of total debt, to thesum of the book value of equity and total debt at the end of Fiscal Year t. PDIt volatility (Vol(PDI)t)is added as a control variable, because managers are sensitive about performance uncertainty when

12

The Japanese Accounting Review, 2 (2012), 1-32

making decisions about payouts. The survey of Brav et al. (2005) shows that institutional investors
affect dividends. Here, the equity ownership percentage of financial institutions at the end of Fiscal
Year t (Financialt) and that of foreign investors at the end of Fiscal Year t (Foreignt) are used; these
two factors may function as discipline for Japanese managers and facilitate aggressive payouts. In
addition, we include D_Nothingt-1, D_Stablet-1, and D_Increaset-1 in Model (6) in order to control
for the effect of past dividend policy.
Considering the effects of industry and year on profitability, growth, and uncertainty, ROAt,
Growtht, and Vol(PDI)t are adjusted. These variables are ranked in ascending order within its
industry-year and divided by the number of observations in each industry-year. This study defines
these as Rank.ROAt, Rank.Growtht, and Rank.Vol(PDI)t.14 Moreover, to control other year effects,
we include year dummies in the model.
In this study, all t-statistics and z-statistics are corrected for heteroskedasticity, and crosssectional and time-series dependence using a two-way cluster at the firm and year level proposedby Petersen (2009) and Cameron et al. (2011).15
3.3 Sample
The empirical analysis is based on Japanese non-financial firms over the 1990–2010 period.
The initial sample includes 59,261 firm-years. Data are basically screened according to thefollowing criteria (figure in parentheses represents sample size after each criterion):(1) The firms have to be Japanese listed firms (59,261 firm-years).
(2) Fiscal Year-end should be March (43,498 firm-years).
(3) The firms should be compliant with Japanese accounting standards (42,928 firm-years).
(4) All data must be available for DAC estimation (40,259 firm-years).
(5) To ensure that the results are not outlier-sensitive, variables in the top and bottom 0.5
percent have been eliminated from the Model (1) estimation (38,599 firm-years).
(6) Firms in the industry-year with more than 10 firms (38,078 firm-years)(7) All financial and market data are available (19,558 firm-years)16(8) Change in number of shares outstanding (from t to t + 1, t +1 to t + 2) is within 20
percent17 (17,947 firm-years)(9) To ensure that the results are not sensitive to outliers, except for dummy variables,
variables in the top and bottom 0.5 percent have been eliminated in Models (2), (4), (5)and (6) estimation18(15,890 firm-years).
Through the use of these criteria, a final sample of 15,890 firm-year observations is generated.19
Even when unranked ROAt, unranked Growtht, and unranked Vol(PDI)t are used instead of Rank.ROAt, Rank.Growtht, and Rank.
Vol(PDI)t, the empirical results remain unchanged.
15
If clustering of the standard errors does not allow for the inclusion of all of our currently included year dummy variables, we
combine at least two year dummy variables into one year dummy variable in order to estimate the regression.
16
This criteria dramatically reduces the sample size. This is mainly because the calculation of our fourth income smoothing measure(see section 5) requires current and past five years’ net income before accrual discretion and DAC (from year t - 5 to t) in orderto calculate the measure for year t, and dividend policy measures (from year t + 1 to t +2) require both DPSt+1 and DPSt+2 in
calculation.
17
Following Ishikawa (2007), we adopt this criteria.
18
Even when we skip criteria (9), the empirical results remain unchanged.
19
The top and bottom 0.5 percent of the regression variables are truncated twice (i.e., criteria (5) and (9)), not only to prevent outliers
from affecting estimations of Regression (1), but also to obtain a large sample to test the hypotheses. To mitigate the effect of achange in the number of shares outstanding on dividends per share, criterion (8) is included. In addition, instead of using Rank.
ROAt, Rank.Growtht, and Rank.Vol(PDI)t, to delete outliers, the ROAt, Growtht, and Vol(PDI)t values are used.
14

Takasu and Nakano: What Do Smoothed Earnings Tell Us about the Future?

100%

13

Figure 1: Distribution of Dividend Policy

90%
80%
70%
60%
50%
40%
30%

Decrease
Increase
StableNothing

20%
10%

19

95
19 19996 6
19 19997 7
19 19998 8
19 19999 920 20000 020 20001 1
20 20002 2
20 20003 320 20004 420 20005 520 20006 620 20007 7
20 200
08 8
-2
00
9

0%

DPSt = the dividend per share for Fiscal Year t.
Nothing means a firm-year without any dividend for both Fiscal Year t and Fiscal Year t + 1.
Stable means a firm-year paying as much DPS for Fiscal Year t + 1 as Fiscal Year t.
Increase means a firm-year paying more DPS for Fiscal Year t + 1 than DPS for Fiscal Year t.
Decrease means a firm-year paying less DPS for Fiscal year t + 1 than Fiscal Year t.

Table 2 provides descriptive statistics. Table 3 presents a correlation matrix of variables
used in OLS and logit regressions. At first glance, high correlations are observed between
Sizet and Tobin’s Qt, Sizet and Foreignt, and Sizet and Financialt. To cope with multicollinearity
issues, regressions are run in advance, with either variable alone, on Models (6). The results
remain the same. 20 Hence, all these variables are, hereafter, included in the logit regression
analysis.
Figure 1 presents distribution of dividend policy over the period 1995-2009. We canobserve interesting dividend policies of Japanese firms. First, there are very few “Nothing”.
Approximately, ninety percent of firms pay dividends. Second, during 2002-2007, Japanese
economy enjoyed booming, which resulted in more “Increase” and less “Decrease”. Third, in
2008-2009, world financial crisis caused more “Decrease” and less “Increase”. Fourth, and mostimportantly, it should be noted that percentage share of “Stable” is stable. The share ranges
from 37.7 and 53.3 percent. Even after world financial crisis in 2008, 39.3 percent of Japanesefirms did not change their DPS.
20

Furthermore, we calculate the VIF in the logit regression of D_Stablet+1. The results show that D_Increaset-1 has the highest VIF
value (2.77). Considering the value of VIF under 10, there exists little concern about multicollinearity problem.

The Japanese Accounting Review, 2 (2012), 1-32

14

Table 2: Descriptive Statistics (Observations during 1995 – 2008)
NIt

Vol(NI)t
PDIt

Vol(PDI)tVol(NI)/Vol(PDI)t
ROAt

Mean
0.016

Std.dev.

0.022

0.026

0.038

0.055

-0.015

0.443

0.353

0.024

0.185

0.044
0.024

0.024

1.46

6.85

0.078

0.364
0.282
22.2

0.008

-0.1640.062

10.071

0.000

0.027

0.311

DPSt

0.012

-0.165

0.015

1.063

Financialt

0.007

0.050

Tobin'sQt
Foreignt

Median

0.015

0.017

-0.004

RE/BVEt25%-0.134Growtht
Sizet

Min

0.029

0.044

0.009

0.015
0.015
0.348
0.021

-0.148-0.032-0.005

0.480

0.866

1.007

0.000

0.007

0.028

0.351

-3.054

0.143

0.013

234.7

0.004

0

9.01

0.067
0.168
4

75%

Max

0.031

0.124

0.045

0.195

0.604

2.559

0.038
0.022

N

15,8900.185

15,8900.158

15,890

0.172

0.170

15,89015,89015,89015,890

9.92

10.99

14.23

15,890

0.419

0.623

0.952

15,890

0.267
7.5

1.187
0.091
0.388
12

2.998
0.417
0.648
8,400

15,89015,89015,89015,890NIt = the net income for Fiscal Year t, deflated by the total assets at the beginning of Fiscal Year t.
Vol(NI)t = the firm-specific volatility of earnings that is calculated as the standard deviation of NI
over the most recent five years.
TACt = total accrual that is defined as (change in current assets – change in cash and cash
equivalents) – (change in liabilities – change in financing item) – change in other allowance– depreciation for Fiscal Year t, deflated by the total assets at the beginning of Fiscal Year t.
NDACt = non discretionary accrual that is estimated by using Kothari et al. (2005) 's model.
DACt = discretionary accrual that is definded by TACt minus NDACt.
ATRDt = real discretion after tax that is definded by the gain/loss on the sale of marketable securities
reported in extraordinary items at Fiscal Year t multiplied by 0.6, deflated by the total
assets at the beginning of Fiscal Year t.
PDIt = the pre-discretionary income that is defined as NIt minus both DACt and ATRDt Fiscal
Year t.
Vol(PDI)t = the firm-specific volatility of PDI that is calculated as the standard deviation of PDI overthe most recent five years.
Vol(NI)/= the ratio of Vol(NI)t to Vol(PDI)t
Vol(PDI)t
ROAt = the ratio of net income before extraordinary items for Fiscal Year t over total assets at the
beginning of Fiscal Year t.
Growtht = the geometric average of the sales growth rate from Fiscal Year t - 4 to Fiscal Year t.
Sizet = the natural logarithm of the market value at the end of Fiscal Year t.
Tobin’s Qt = the ratio of the sum of the market value and total debt to the sum of the book value ofequity and total debt at the end of Fiscal Year t.
RE/BVEt = the ratio of the retained earnings to the book value of equity at the end of Fiscal Year t.
Foreignt = the foreign ownership at the end of Fiscal Year t.
Financialt = the financial institute ownership at the end of Fiscal Year t.
DPSt = the dividend per share for Fiscal Year t.

-0.594-0.102

D_Stablet-1-0.064-0.0870.161-0.023-0.0420.030-0.1350.115-0.021
0.065-0.341
0.283

D_Increaset-1
0.438
0.012
-0.019
0.286
0.090
0.166
0.179
0.140
0.218
0.020
-0.234-0.594

D_inct0.367-0.012
0.016
0.167
0.115
0.097
0.153
0.010
0.067
0.025
0.006
-0.1020.283

NIt = the net income for Fiscal Year t, deflated by the total assets at the beginning of Fiscal Year t.
Vol(NI)t = the firm-specific volatility of earnings that is calculated as the standard deviation of NI over the most recent five years.
TACt = total accrual that is defined as (change in current assets – change in cash and cash equivalents) – (change in liabilities – change in financing item) – change in other allowance –depreciation for Fiscal Year t, deflated by
the total assets at the beginning of Fiscal Year t.
NDACt = non discretionary accrual that is estimated by using Kothari et al. (2005) 's model.
DACt = discretionary accrual that is definded by TACt minus NDACt.
ATRDt = real discretion after tax that is definded by the gain/loss on the sale of marketable securities reported in extraordinary items at Fiscal Year t multiplied by 0.6, deflated by the total
assets at the beginning of Fiscal Year t.
PDIt = the pre-discretionary income that is defined as NIt minus both DACt and ATRDt for Fiscal Year t.
Vol(PDI)t = the firm-specific volatility of PDI that is calculated as the standard deviation of PDI over the most recent five years.
Vol(NI)/Vol(PDI)t = the ratio of Vol(NI)t to Vol(PDI)t
ISt = the within industry-year reversed fractional ranking (between 0 and 1) of Vol(NI)/Vol(PDI) for Fiscal Year t (see text for full details).
Rank.Vol(PDI)t = the within industry-year fractional ranking (between 0 and 1) of Vol(PDI) for Fiscal Year t (see text for full details).
ROAt = the ratio of net income before extraordinary items for Fiscal Year t over total assets at the beginning of Fiscal Year t.
Rank.ROAt = the within industry-year fractional ranking (between 0 and 1) of ROA for Fiscal Year t (see text for full details).
Growtht = the geometric average of the sales growth rate from Fiscal Year t - 4 to Fiscal Year t.
Rank.Growtht = the within industry-year fractional ranking (between 0 and 1) of Growth for Fiscal Year t (see text for full details).
D_inct = 1 if a firm reports earnings growth for Fiscal Year t and 0 otherwise.
DPSt = the dividend per share for Fiscal Year t.
D_Nothingt-1 = 1 if a firm-year without any dividend for both Fiscal Year t-1 and Fiscal Year t.
D_Stablet-1 = 1 if a firm-year paying as much DPS for Fiscal Year t - 1 as Fiscal Year t.
D_Increaset-1 = 1 if a firm-year paying more DPS for Fiscal Year t - 1 than DPS for Fiscal Year t.

Pearson (Spearman) correlations are reported below (above) the diagonal.

NIt
Rank.ol(PDIt )IStRank.ROAt
Rank.Growtht
SIZEt
Tobin's Qt
RE/BVEt
Foreignt
Financialt
D_Nothingt-1
D_Stablet-1
D_Increaset-1
D_inctTable 3: Pearson and Spearman Correlations (15,890 Observations)Rank.Vol(PDIt ) ISt
Rank.ROAt Rank.Growtht SIZEt Tobin's Qt RE/BVEt Foreignt Financialt D_Nothingt-1
0.042
0.094
0.667
0.110
0.268
0.291
0.296
0.358
-0.006-0.265
0.020
0.319
0.035
-0.023-0.1140.054-0.049-0.050-0.119
0.109
0.135
0.319
0.048
-0.0350.041-0.0390.155
0.020-0.003-0.167
0.608
0.035
0.048
0.163
0.238
0.234
0.206
0.271
0.065
-0.221
0.111-0.023-0.035
0.163
0.127
0.132
-0.104
0.062
0.114
0.015
0.260
-0.119
0.037
0.242
0.131
0.484
-0.0020.704
0.564-0.1990.339
0.066-0.043
0.272
0.112
0.451
-0.223
0.232
0.225
0.069
0.304
-0.0590.173
0.209-0.0930.036-0.1350.124-0.122-0.3400.321-0.032
0.012
0.250
0.055
0.624
0.278
0.165
0.392
-0.2100.011-0.121
0.001
0.071
0.116
0.572
0.186
-0.0900.310-0.122-0.261
0.109-0.167-0.221
0.015-0.1990.042-0.402-0.177-0.126-0.029-0.0870.161-0.023-0.0420.027-0.1360.141-0.0420.069-0.341
0.404
0.012-0.019
0.286
0.090
0.171
0.193
0.150
0.222
0.019
-0.2340.358-0.012
0.016
0.167
0.115
0.099
0.155
0.012
0.078
0.027
0.006

NIt

Takasu and Nakano: What Do Smoothed Earnings Tell Us about the Future?
15

The Japanese Accounting Review, 2 (2012), 1-32

16

Table 4: Comparison of Vol(NI) and Vol(PDI) Across Quintiles

Quintiles by ISt

N
Quintle 1
3,178
Quintle 2
3,178
Quintle 3
3,178
Quintle 4
3,178
Quintle 5
3,178
Difference (Quintile 5 - Quintile 1)
p-value on difference

Vol(NI)t
Mean Std.Dev Median
0.032 0.021 0.028
0.021 0.014 0.018
0.016 0.010 0.013
0.011 0.007 0.009
0.006 0.004 0.005-0.026-0.022<0.001<0.001

Vol(PDI)t
Mean Std.Dev Median
0.034 0.020 0.030
0.039 0.021 0.035
0.043 0.022 0.039
0.046 0.023 0.041
0.054 0.026 0.048
0.020
0.018
<0.001<0.001

NIt = the net income for Fiscal Year t, deflated by the total assets at the beginning of Fiscal Year t.
Vol(NI)t = the firm-specific volatility of earnings that is calculated as the standard deviation of NI
over the most recent five years.
TACt = total accrual that is defined as (change in current assets – change in cash and cash
equivalents) – (change in liabilities – change in financing item) – change in other allowance– depreciation for Fiscal Year t, deflated by the total assets at the beginning of Fiscal Year t.
NDACt = non discretionary accrual that is estimated by using Kothari et al. (2005) 's model.
DACt = discretionary accrual that is definded by TACt minus NDACt.
ATRDt = real discretion after tax that is definded by the gain/loss on the sale of marketable securities
reported in extraordinary items at Fiscal Year t multiplied by 0.6, deflated by the total
assets at the beginning of Fiscal Year t.
PDIt = the pre-discretionary income that is defined as NIt minus both DACt and ATRDt for Fiscal
Year t.
Vol(PDI)t = the firm-specific volatility of PDI that is calculated as the standard deviation of PDI overthe most recent five years.

Quintile 1 is the lowest IS (least income smoothing) quintile, and Quintile 5 is the highest IS (most income smoothing)quintile. The p-value for the difference in mean values across quintiles is derived from a t-test. The p-value for thedifference in median values across quintiles is derived from a Mann-Whitney test.

4. Results
4.1 Income Smoothing Behavior and Volatility
Table 4 compares NI volatility and PDI volatility conditioning, in terms of ISt quintiles. Firms
in Quintile 1 have the lowest ISt (i.e., least income smoothing), while firms in Quintile 5 havethe highest ISt (i.e., most income smoothing). The results clearly indicate the effect of smoothing
behavior. Quintile 5 has the highest volatility of pre-discretionary income (0.054) before its earnings
management; the firms in there, however, have the most-smoothed reported net income (0.006),
compared to those in Quintile 1 (0.032). It is clear that firms in Quintile 5 try to control PDI
volatility via smoothing and successfully reduce the volatility of reported NI.
4.2 Income Smoothing Behavior and Earnings Persistence
The regression results of Model (2) are reported in Table 5. Earnings persistence coefficients, β,increase from Quintile 1 to Quintile 5. It is worth noting that the difference of persistence between
Quintile 5 and Quintile 1 (0.871 and 0.425, respectively) is statistically significant at the 0.1percent

Takasu and Nakano: What Do Smoothed Earnings Tell Us about the Future?

17

Table 5: Results for The Earnings Persistence Regression in Model (2)Quintiles by IStaCoefficient t-value
Quintle 1
0.009
3.54 ***
Quintle 20.005
2.12 **
Quintle 3
0.003
1.56
Quintle 4
0.000
-0.21
Quintle 5-0.002-1.07
Difference (Quintile 5 - Quintile 1)
p-value on differenceb
Coefficient
0.425
0.552
0.665
0.799
0.871
0.446
<0.001t-value
14.46***
17.55***
12.64***
12.75***
17.94***

Adj. R2

N

0.232
0.285
0.333
0.354
0.385
0.152
<0.001

3,178
3,178
3,178
3,178
3,178

NIt = the net income for Fiscal Year t, deflated by the total assets at the beginning of Fiscal Year t.
Vol(NI)t = the firm-specific volatility of earnings that is calculated as the standard deviation of NI
over the most recent five years.
TACt = total accrual that is defined as (change in current assets – change in cash and cash equivalents) –(change in liabilities – change in financing item) – change in other allowance – depreciation for
Fiscal Year t, deflated by the total assets at the beginning of Fiscal Year t.
NDACt = non discretionary accrual that is estimated by using Kothari et al. (2005) 's model.
DACt = discretionary accrual that is definded by TACt minus NDACt .
ATRDt = real discretion after tax that is definded by the gain/loss on the sale of marketablesecurities reported in extraordinary items at Fiscal Year t multiplied by 0.6, deflated by
the total assets at the beginning of Fiscal Year t.
PDIt = the pre-discretionary income that is defined as NIt minus both DACt and ATRDt for Fiscal Year t.
Vol(PDI)t = the firm-specific volatility of PDI that is calculated as the standard deviation of PDI
over the most recent five years.
Vol(NI)/Vol(PDI)t = the ratio of Vol(NI)t to Vol(PDI)t
ISt = the within industry-year reversed fractional ranking (between 0 and 1) of Vol(NI)/
Vol(PDI) for Fiscal Year t (see text for full details).

Quintile 1 is the lowest IS (least income smoothing) quintile, and Quintile 5 is the highest IS (most income smoothing)quintile. The p-value for the difference in persistence coefficients across quintiles is derived from a t-test. The p-value forthe difference in the Adj.R2 across quintiles is derived from a bootstrap test (see text for full details). All t-statistics arecorrected for heteroskedasticity, and cross-sectional and time-series correlation using a two-way cluster at the firm andyear level proposed by Petersen (2009).
***, **, and * indicate significance at 1% , 5%, and 10%, respectively.

level. It would be reasonable to conclude that there is a positive relation between income smoothing
behavior in the past and future earnings persistence.
Table 6 indicates the results of regression, for the full sample, on Model (4). Consistent with theresults of Tucker and Zarowin (2006), the coefficient of the intersection term, NI *ISt, is positive andstatistically significant at the 1 percent level. This result again implies that a manager’s smoothing
behavior in the five previous years relates positively to earnings persistence for future periods. Thisevidence reinforces the results found in Table 5.21 Even when we use PDIt+1 as the dependent variable
instead of NIt+1 (Table 7), these results remain unchanged. In the light of these results, it seems that
income smoothing behaviors in the past succeed in exhibiting future earnings persistence.
21

When we analyze the relation between income smoothing measures that are based on DAC (i.e. IS2 and IS4, see also section 5)
and ROA persistence, the tenor of the results remains unchanged.

The Japanese Accounting Review, 2 (2012), 1-32

18

Table 6: Result of Earnings Persistence Regression in Model (4)NIt
ISt
NI*IStCons.
Adj. R2
N

Predicted Sign+?
+/

Coefficient
0.367-0.0130.590
0.009

t-value

11.68***-5.67***
7.80***
3.52***
0.310
15,890NIt = the net income for Fiscal Year t, deflated by the total assets at the beginning of
Fiscal Year t.
Vol(NI)t = the firm-specific volatility of earnings that is calculated as the standard deviation of
NI over the most recent five years.
TACt = total accrual that is defined as (change in current assets – change in cash andcash equivalents) – (change in liabilities – change in financing item) – change inother allowance – depreciation for Fiscal Year t, deflated by the total assets at the
beginning of Fiscal Year t.
NDACt = non discretionary accrual that is estimated by using Kothari et al. (2005) 's model.
DACt = discretionary accrual that is definded by TACt minus NDACt.
ATRDt = real discretion after tax that is definded by the gain/loss on the sale of marketablesecurities reported in extraordinary items at Fiscal Year t multiplied by 0.6, deflatedby the total assets at the beginning of Fiscal Year t.
PDIt = the pre-discretionary income that is defined as NIt minus both DACt and ATRDt
for Fiscal Year t.
Vol(PDI)t = the firm-specific volatility of PDI that is calculated as the standard deviation of PDI
over the most recent five years.
Vol(NI)/Vol(PDI)t = the ratio of Vol(NI)t to Vol(PDI)t
ISt = the within industry-year reversed fractional ranking (between 0 and 1) of Vol(NI)/
Vol(PDI) for Fiscal Year t (see text for full details).
NI*ISt is the interaction term, which is defined as NIt × ISt. All t-statistics are corrected for heteroskedasticity, and crosssectional and time-series correlation using a two-way cluster at the firm and year level proposed by Petersen (2009).
*** indicates significance at 1%."

4.3 Income Smoothing Behavior and Dividend Policy
Table 8 indicates firms’ dividend policies, by ISt quintile. With regard to the period t ~ t + 1(Panel A), the most income-smoothing Quintile 5 includes the least number of no-dividend firms(4.9 percent), dividend omission firms (2.7 percent), and the greatest number of stable-dividend
firms (53.7 percent). The difference between Quintiles 5 and 1 (–16.0 percent, -1.3 percent, and17.7 percent, respectively) is statistically significant at the 1 percent level. For the period t + 1 ~ t + 2(Panel B), reported on the bottom half of Table 8, similar patterns are observed. Higher-smoothing
firms have a tendency to pay stable dividends in the future, and they seldom adopt a no-dividends or
dividend omission policy. With regard to Increase, lower-smoothing firms have a moderate tendency
to adopt dividends increase policy compared to higher-smoothing firms. This trend might imply thatmanagers smooth income to avoid increasing dividends in the future. Meanwhile, income smoothing
in the past period has no effect on a future dividends decrease.

Takasu and Nakano: What Do Smoothed Earnings Tell Us about the Future?

19

Table 7: Result of Earnings Persistence Regression in Model (5)Dependent Variable: PDIt+1
NIt
ISt
NI*IStCons.
Adj. R2
N

Predicted Sign+?
+/

Coefficient
0.396-0.0100.487
0.008

t-value

15.57***-4.61***
6.95***
3.23***
0.113
15,890NIt = the net income for Fiscal Year t, deflated by the total assets at the beginning of
Fiscal Year t.
Vol(NI)t = the firm-specific volatility of earnings that is calculated as the standard deviation of
NI over the most recent five years.
TACt = total accrual that is defined as (change in current assets – change in cash andcash equivalents) – (change in liabilities – change in financing item) – change inother allowance – depreciation for Fiscal Year t, deflated by the total assets at the
beginning of Fiscal Year t.
NDACt = non discretionary accrual that is estimated by using Kothari et al. (2005) 's model.
DACt = discretionary accrual that is definded by TACt minus NDACt.
ATRDt = real discretion after tax that is definded by the gain/loss on the sale of marketablesecurities reported in extraordinary items at Fiscal Year t multiplied by 0.6, deflatedby the total assets at the beginning of Fiscal Year t.
PDIt = the pre-discretionary income that is defined as NIt minus both DACt and ATRDt
for Fiscal Year t.
Vol(PDI)t = the firm-specific volatility of PDI that is calculated as the standard
deviation of PDI over the most recent five years.
Vol(NI)/Vol(PDI)t = the ratio of Vol(NI)t to Vol(PDI)t
ISt = the within industry-year reversed fractional ranking (between 0 and 1) of Vol(NI)/
Vol(PDI) for Fiscal Year t (see text for full details).
NI*ISt is the interaction term, which is defined as NIt × ISt. All t-statistics are corrected for heteroskedasticity, and crosssectional and time-series correlation using a two-way cluster at the firm and year level proposed by Petersen (2009).
*** indicates significance at 1%."

Table 9 presents the results of logit regression, for the full sample, on Model (6).22 This table shows
the results with fully controlled variables. ISt has a negative impact on Nothing and Omission. Meanwhile,it has a positive and statistically significant effect on Stable. The results of the current analysis clearly
indicate that income smoothing has a negative association with both a no-dividends policy and a dividend
omission policy and a positive association with a stable-dividends strategy. Even when several possible
fundamental factors and corporate governance factors are being controlled, ISt remains significant, in boththe t to t + 1 window and the t + 1 to t + 2 window. Financialt and Foreignt negatively relate to Nothing;
this may have been due to the “prudent man” investment restrictions on institutional investors (Brav et al.
22

In some model, observations’ number is not 15,890. This is because, in these models, some independent variables’ values canfit dependent variable values perfectly (e.g. observations whose D_Stablet-1 equal to one can fit D_Nothingt that equals to zero
perfectly). Therefore, we have to drop these observations in the estimation.

The Japanese Accounting Review, 2 (2012), 1-32

20

Table 8: Comparison of Dividend Policy Across IS Quintiles

Panel A: Comparison of Dividend Policy (from t to t + 1) Across IS Quintiles
Quintiles by ISt
Quintile 1

N

3,178

Nothing
Number%663

Quintile 2 3,178
464
Quintile 3 3,178
321
Quintile 4 3,178
240
Quintile 5 3,178
156
Difference(Quintile 5 - Quintile 1)
p-value on difference

20.9%

14.6%
10.1%
7.6%
4.9%

Dividend policy from t to t + 1

StableNumber
%
1142

1321
1482
1525
1706

35.9%

41.6%
46.6%
48.0%
53.7%

Increase
Number
%
929

909
902
916
854

29.2%

28.6%
28.4%
28.8%
26.9%

Decrease
Number
%
444

484
473
497
462

14.0%

15.2%
14.9%
15.6%
14.5%

Omission
Number
%
125

121
99
91
85

3.9%

3.8%
3.1%
2.9%
2.7%

-16.0%

17.7%

-2.4%

0.6%

-1.3%

<0.001<0.001

0.036

0.518

0.005

Panel B: Comparison of Dividend Policy (from t + 1 to t + 2) Across IS Quintiles
Quintiles by ISt
Quintile 1

N

3,178

Nothing
Number%641

Quintile 2 3,178
444
Quintile 3 3,178
315
Quintile 4 3,178
247
Quintile 5 3,178
179
Difference(Quintile 5 - Quintile 1)
p-value on difference

20.2%

14.0%
9.9%
7.8%
5.6%

Dividend policy from t + 1 to t + 2

StableNumber
%
1136

1360
1438
1463
1635

35.7%

42.8%
45.2%
46.0%
51.4%

Increase
Number
%
892

866
911
920
839

28.1%

27.2%
28.7%
28.9%
26.4%

Decrease
Number
%
509

508
514
548
525

16.0%

16.0%
16.2%
17.2%
16.5%

Omission
Number
%
148

132
107
109
103

4.7%

4.2%
3.4%
3.4%
3.2%

-14.5%

15.7%

-1.7%

0.5%

-1.4%

<0.001<0.001

0.135

0.587

0.004

Quintile 1 is the lowest IS (least income smoothing) quintile, and Quintile 5 is the highest IS (most income smoothing)quintile.
DPSt = the dividend per share for Fiscal Year t.
Nothing means a firm-year without any dividend for both Fiscal Year t (t + 1) and Fiscal Year t + 1 (t + 2).
Stable means a firm-year paying as much DPS for Fiscal Year t + 1 (t + 2) as Fiscal Year t (t + 1).
Increase means a firm-year paying more DPS for Fiscal Year t + 1 (t + 2) than DPS for Fiscal Year t (t + 1).
Decrease means a firm-year paying less DPS for Fiscal year t + 1 (t + 2) than Fiscal Year t (t + 1).
Omission means a firm-year omitting dividends for Fiscal year t+1 (t+2).
The p-value for the difference in percentages across quintiles is derived from a chi-square test.

2005). As for Increase and Decrease, ISt has a negative effect on Increase, but this effect is not so powerful.
Moreover, there is no statistically significant effect on Decrease. Our results might suggest managers’
income smoothing relates to avoidance of future dividends increase.
The results of our two tests (earnings persistence and dividend policy) indicate income smoothing
behavior is likely to reflect future stability of earnings performance. Therefore, outsiders could consider amanager’s income smoothing behavior as a signal about the firm’s future stability of performance.

Takasu and Nakano: What Do Smoothed Earnings Tell Us about the Future?

21

Table 9: Tests of Relation Between Income Smoothing and Dividend Policy
Dividend policy from t to t + 1
Coefficient
z-value

D_NothingCons

D_Stable

0.250
1.91*
0.232
0.87

-2.066-2.59 ***
-0.465-2.54 **
-2.025-10.35 ***
0.172
1.21
0.66
3.64 ***
0.334
2.89 ***-0.136-1.61-1.259-0.96-0.235-1.06-0.232-1.98 **
-0.723-4.53 ***
-1.207-5.88 ***
0.389
2.26 **
0.523
2.22 **

Yes

Yes

Yes

Yes

Yes

Yes

Pseudo R2
0.440
0.083
0.139
0.147
0.167
0.509
0.090
0.105
0.112
N
3,919
14,004
15,89014,00414,004
15,89015,89015,89015,890Nothing means a firm-year without any dividend for both Fiscal Year t (t + 1) and Fiscal Year t + 1 (t + 2).
Stable means a firm-year paying as much DPS for Fiscal Year t + 1 (t + 2) as Fiscal Year t (t + 1).
Increase means a firm-year paying more DPS for Fiscal Year t + 1 (t + 2) than DPS for Fiscal Year t (t + 1).
Decrease means a firm-year paying less DPS for Fiscal year t + 1 (t + 2) than Fiscal Year t (t + 1).
Omission means a firm-year omitting dividends for Fiscal year t+1 (t+2).

0.102
15,890Rank.Vol(PDIt )Sizet
Foreignt
Financialt
D_inctRE/BVEt
D_Nothingt-1
D_Stablet-1

Yes

Yes

D_Increaset-1
Year dummy

D_Nothingt
D_Stablet
D_Increaset
D_Decreaset
D_Omissiont
NIt
Vol(NI)tYes-0.459-0.57-0.711-3.08***-2.816-11.82***-0.001-0.01
0.601
3.35***
0.550
4.26***-0.199-2.17**-0.996-0.69-0.310-0.83-0.155-1.31-1.486-5.88***

0.064
0.63
1.370
7.35***
Yes

D_Increase D_Decrease D_Omission-1.045-3.50***-0.083-1.07-0.177-0.97-0.035-0.45-0.096
-0.54
0.033
0.34
-0.076-2.93***
0.746
1.91*
0.229
0.73
-0.133-2.47**-0.113-0.93-1.642-6.76***
0.181
2.31**
0.313
2.78***

Tobin's Qt

0.338
1.20
-0.128-1.05-1.223-7.59***-0.208-2.14**-0.445-2.89***
0.157
1.53-0.120-4.48***
0.586
0.94
0.473
1.69*
-0.504-7.76***-0.277-1.81*

D_Stable-2.382-9.03***-0.121-0.94
0.496
5.16***
0.165
2.17**
0.270
2.07**
0.110
1.39
0.073
2.75***
1.583
3.36***-0.418
-1.61
0.102
1.77*
0.259
2.21**-0.321-1.56-0.419-5.07***-0.001-0.01

Rank.Growtht-2.955-14.68***-0.172-1.65*
1.102
14.20***
0.232
2.58***
0.337
2.58***
0.105
1.54
0.067
3.00***
1.522
3.86***-0.309-1.47
0.332
8.16***
0.361
2.39**-0.389-1.63
1.046-0.66512.76*** -4.94***-0.118-0.039-1.11-0.32

D_Nothing-0.703-2.11**
0.352
3.83***
0.264
2.00**-0.089-1.48-0.383-3.23***-0.250-3.28***
0.061
1.93*
-2.258-5.53***
0.357
1.60
0.036
0.86
0.348
1.97**-1.701-5.02***
0.653
9.79***
0.221
2.69***

Rank.ROAt-0.427-1.4700.362
4.02***
0.000
0.00-0.040-0.44-0.383-3.88***-0.274-3.68***
0.061
2.19**-2.070-6.45***
0.163
0.72-0.001-0.03
0.346
2.24**

D_Increase D_Decrease D_Omission

1.856
4.39***-0.665-3.15***-2.204-7.86***-0.022-0.16
0.772
4.11***
0.429
3.11***-0.253-5.14***-2.220-1.72*-0.453-0.79-0.199-1.77*-1.426-5.87***
1.932
8.24***-1.669-11.78***-1.693-6.74***

ISt

1.338
1.98**-0.675-2.49**-1.914-8.15***-0.192-1.22
1.050
4.64***
0.300
2.17**-0.210-3.70***-2.817-2.72***-0.810-1.30-0.094-1.06-1.583-5.20***
2.768
10.73***

Dividend policy from t + 1 to t + 2
Coefficient
z-value

=
=
=
=
=
=
=

1 if a firm-year's dividend policy from t (t+1) to t+1 (t+2) is Nothing, and 0 otherwise.
1 if a firm-year's dividend policy from t (t+1) to t+1 (t+2) is Stable, and 0 otherwise.
1 if a firm-year's dividend policy from t (t+1) to t+1 (t+2) is Increase, and 0 otherwise.
1 if a firm-year's dividend policy from t (t+1) to t+1 (t+2) is Decrease, and 0 otherwise.
1 if a firm-year's dividend policy from t (t+1) to t+1 (t+2) is Omission, and 0 otherwise.
the net income for Fiscal Year t, deflated by the total assets at the beginning of Fiscal Year t.
the firm-specific volatility of earnings that is calculated as the standard deviation of NI over themost recent five years.
TACt = total accrual that is defined as (change in current assets – change in cash and cash equivalents) –(change in liabilities – change in financingitem) – change in other allowance – depreciation for Fiscal Year t, deflated by the total assets atthe beginning of Fiscal Year t.
NDACt = non discretionary accrual that is estimated by using Kothari et al. (2005) 's model.
DACt = discretionary accrual that is definded by TACt minus NDACt.

(Continued )The Japanese Accounting Review, 2 (2012), 1-32

22(-Continued )ATRDt = real discretion after tax that is definded by the gain/loss on the sale of marketable securities
reported in extraordinary items at Fiscal Year tmultiplied by 0.6, deflated by the total assets at the beginning of Fiscal Year t.
PDIt = the pre-discretionary income that is defined as NIt minus both DACt and ATRDt for Fiscal Year t.
Vol(PDI)t = the firm-specific volatility of PDI that is calculated as the standard deviation of PDI over themost recent five years.
Vol(NI)/Vol(PDI)t = the ratio of Vol(NI)t to Vol(PDI)t
ISt = the within industry-year reversed fractional ranking (between 0 and 1) of Vol(NI)/Vol(PDI) for
Fiscal Year t (see text for full details).
ROAt = the ratio of net income before extraordinary items for Fiscal Year t over total assets at the
beginning of Fiscal Year t.
Rank.ROAt = the within industry-year fractional ranking (between 0 and 1) of ROA for Fiscal Year t (see text
for full details).
Growtht = the geometric average of the sales growth rate from Fiscal Year t - 4 to Fiscal Year t.
Rank.Growtht = the within industry-year fractional ranking (between 0 and 1) of Growth for Fiscal Year t (seetext for full details).
Tobin’s Qt = the ratio of the sum of the market value and total debt to the sum of the book value of equity andtotal debt at the end of Fiscal Year t.
Rank.Vol(PDI)t = the within industry-year fractional ranking (between 0 and 1) of Vol(PDI) for Fiscal Year t (seetext for full details).
Sizet = the natural logarithm of the market value at the end of Fiscal Year t.
Foreignt = the foreign ownership at the end of Fiscal Year t.
Financialt = the financial institute ownership at the end of Fiscal Year t.
D_inct = 1 if a firm reports earnings growth for Fiscal Year t and 0 otherwise.
RE/BVEt = the ratio of the retained earnings to the book value of equity at the end of Fiscal Year t
DPSt = the dividend per share for Fiscal Year t.
All z-statistics are corrected for heteroskedasticity, and cross-sectional and time-series correlation using a two-way
cluster at the firm and year level proposed by Petersen (2009) and Cameron et al. (2011).
***,**, and * indicate significance at 1%, 5%, and 10%, respectively.

5. Robustness Check
In this paper, the degree of smoothing is defined as firm-specific historical volatility of net
income, divided by volatility of pre-discretionary income (Vol(NI)/Vol(PDI)t). In addition, to control
for industry and time effects, following Tucker and Zarowin (2006), this study uses a firm’s reversed
fractional ranking of income smoothing (between 0 and 1) within its industry-year and refers to it as
Income Smoothing (IS). Our IS measure includes both accrual discretion and real discretion.
It may be possible that this measure includes bias. For the purpose of robustness check, we
adopts three additional IS measures. The second measure (IS2) is defined as the ratio of the firm’s
standard deviation of NI over the most recent five years to its standard deviation of net income
before accrual discretion (NI minus DAC, hereafter NIBAD) over the most recent five years: Vol(NI)/
Vol(NIBAD). Although IS2 is used by Hunt et al. (2000), IS2 does not include real discretion portion.
Our Second Income Smoothing Measure = Vol(NI ) / Vol(NIBAD)
IS2= the within industry-year reversed fractional ranking (between 0 and 1) ofVol(NI)/Vol(NIBAD) for Fiscal Year t

Takasu and Nakano: What Do Smoothed Earnings Tell Us about the Future?

23

Table 10: Results for The Earnings Persistence Regression in Model (2)Dependent variable:

Cons
NIt
IS2t
NI*IS2tIS3tNI*IS3t
IS4t

NIt+1

NIt+1

Coefficientt-Statistics
0.009
0.009
3.30***
3.30***
0.384
0.384
12.41***
12.41***-0.012-4.80***
0.538
7.86***-0.012-4.80***
0.538
7.86***NI*IS4t

Adj R2N

0.306
15,8900.306
15,890

NIt+1

0.008
2.85***
0.388
13.88***-0.008-3.51***
0.459
7.25***
0.301
15,890NIBADt+1

CFOt+1

Coefficientt-Statistics
0.01
0.053
3.29 *** 14.63***
0.396
0.269
12.82 ***
8.26***-0.01-4.28 ***
0.468
7.31 ***-0.007-2.48**
0.252
3.05***

0.111
15,8900.040
15,890NIBADt+1

0.008
2.75***
0.392
13.65***-0.006-2.59***
0.413
5.75***
0.109
15,890NIt = the net income for Fiscal Year t, deflated by the total assets at the beginning of
Fiscal Year t.
Vol(NI)t = the firm-specific volatility of earnings that is calculated as the standard deviationof NI over the most recent five years.
TACt = total accrual that is defined as (change in current assets – change in cash and cash
equivalents) – (change in liabilities – change in financing item) – change in otherallowance – depreciation for Fiscal Year t, deflated by the total assets at the
beginning of Fiscal Year t.
NDACt = non discretionary accrual that is estimated by using Kothari et al. (2005) 's model.
DACt = discretionary accrual that is definded by TACt minus NDACt.
NIBADt = the net income before accrual discretion for Fiscal Year t that is calculated as NIt
minus DACt.
Vol(NIBAD)t = the firm-specific volatility of NIBAD that is calculated as the standard deviationof NIBAD over the most recent five years.
Vol(NI)/Vol(NIBAD)t = the ratio of Vol(NI)t to Vol(NIBAD)t.
IS2t = the within industry-year reversed fractional ranking (between 0 and 1) ofVol(NI)/Vol(NIBAD)t.
CFOt = the cash flow from operations for Fiscal Year t that is defined as the net income
before extraordinary items minus TAC t, deflated by the total assets at the
beginning of Fiscal Year t.
Vol(CFO)t = the firm-specific volatility of CFO that is calculated as the standard deviation of
CFO over the most recent five years.
Vol(NI)/Vol(CFO)t = the ratio of Vol(NI)t to Vol(CFO)t.
IS3t = the within industry-year reversed fractional ranking (between 0 and 1) ofVol(NI)/Vol(CFO)t.
(Continued )The Japanese Accounting Review, 2 (2012), 1-32

24(-Continued )r (ΔDAC, ΔNIBAD)t = the correlation coefficient between change in DAC and change in NIBAD overthe most recent five years.
IS4t = the within industry-year reversed fractional ranking (between 0 and 1) ofr (ΔDAC, ΔNIBAD)t.
NI*IS2t= the interaction term, which is defined as NIt × IS2t (NIt × IS3t or NIt × IS4t ).
(or NI*IS3t,NI*IS4t )All t-statistics are corrected for heteroskedasticity, and cross-sectional and time-series correlation using
a two-way cluster at the firm and year level proposed by Petersen (2009).
***, **, and * indicate significance at 1%, 5% and 10%, respectively.

Our third measure (IS3) is defined as the ratio of the firm’s standard deviation of NI over themost recent five years to its standard deviation of CFO over the most recent five years: Vol(NI)/
Vol(CFO). This measure is widely used in prior studies (Leuz et al. 2003; Francis et al. 2004). In thispaper, CFO is defined as the net income before extraordinary items minus TAC.
Our Third Income Smoothing Measure = Vol(NI) / Vol(CFO)
IS3 = the within industry-year reversed fractional ranking (between 0 and 1) ofVol(NI)/Vol(CFO) for Fiscal Year t
The fourth measure (IS4) follows Tucker and Zarowin (2006)’s idea. We redefined “smoothing”
as a correlation coefficient between change in DAC and change in NIBAD over the most recent five
years.
Our Forth Income Smoothing Measure = ρ (ΔDAC, ΔNIBAD)
IS4 = the within industry-year reversed fractional ranking (between 0 and 1) ofρ (ΔDAC, ΔNIBAD)t for Fiscal Year t
To maintain consistency with our primary tests, these three alternative proxies for incomesmoothing are also converted into the within industry-year reversed fractional ranking (between 0
and 1), respectively, to control for industry and time effects.
These three alternative definitions for IS are substituted for all analyses in this paper, including
those presented in Tables 4–9. In total, with regard to IS ’s definitions, we conduct eighteen robustness
check analyses. Still the tenor of the results remains unchanged. In that sense, there are good grounds
to consider this study’s evidence robust, irrespective of the alternative income smoothing measures.
The main robustness check results of Table 5, 6 (persistence) and Table 9 (dividend policy) are shownin Table 10 and Table 11, respectively.
In addition, we use industry-years’ median values to standardize some proxies (i.e. Vol(NI)/
Vol(PDI), ROA, Growth, Vol(PDI)) instead of the firms’ fractional rankings within their industryyear. In particular, these alternative standardized variables are defined as the differences between raw
variables and each industry-year median, deflated by the absolute value of the industry-year median.
Even in this case, the empirical results remain also unchanged (untabulated).

Takasu and Nakano: What Do Smoothed Earnings Tell Us about the Future?

25

Table 11: Tests of Relation Between Income Smoothing and Dividend Policy

Panel A: Using IS2

Dividend policy from t to t + 1
Coefficient
z-value

D_NothingCons

D_Stable

0.232
1.84*
0.225
0.85

-1.055-3.56***-0.025-0.34-0.174-0.95-0.035-0.43-0.092
-0.51
0.015
0.16
-0.077-3.02***
0.758
1.95*
0.230
0.73
-0.135-2.49**-0.121-1.02-1.638-6.74***
0.176
2.22**
0.310
2.75***-2.052-2.60***-0.360-2.24**-2.022-10.36***
0.165
1.16
0.674
3.68***
0.268
2.29**-0.140-1.69*-1.235-0.95-0.237-1.06-0.236-1.99**-0.735-4.69***-1.202-5.77***
0.376
2.15**
0.515
2.18**

Yes

Yes

Yes

Yes

Yes

Yes

Pseudo R2
0.440
0.083
0.139
0.147
0.166
0.509
0.089
0.105
0.112
N
3,919
14,004
15,89014,00414,004
15,89015,89015,89015,890Nothing means a firm-year without any dividend for both Fiscal Year t (t + 1) and Fiscal Year t + 1 (t + 2).
Stable means a firm-year paying as much DPS for Fiscal Year t + 1 (t + 2) as Fiscal Year t (t + 1).
Increase means a firm-year paying more DPS for Fiscal Year t + 1 (t + 2) than DPS for Fiscal Year t (t + 1).
Decrease means a firm-year paying less DPS for Fiscal year t + 1 (t + 2) than Fiscal Year t (t + 1).
Omission means a firm-year omitting dividends for Fiscal year t + 1 (t + 2).

0.101
15,890Tobin's Qt
Rank.Vol(NIBADt)
Sizet
Foreignt
Financialt
D_inctRE/BVEt
D_Nothingt-1
D_Stablet-1

Yes

Yes

D_Increaset-1
Year dummy

D_Nothingt
D_Stablet
D_Increaset
D_Decreaset
D_Omissiont
NIt
Vol(NI)t

Yes

0.349
1.26
-0.064-0.72-1.220-7.52***-0.209-2.13**-0.437-2.80***
0.114
1.33-0.123-4.67***
0.607
0.99
0.472
1.69*
-0.506-7.82***-0.288-1.94*-0.401-0.51-0.540-2.99***-2.816-11.16 ***-0.018-0.12
0.620
3.48***
0.418
4.48***-0.206-2.29**-0.930-0.64-0.312-0.81-0.158-1.33-1.514-5.77***

0.058
0.56
1.367
7.36***
Yes

D_Increase D_Decrease D_Omission-2.375-8.95***-0.086-0.85
0.498
5.19***
0.165
2.18**
0.274
2.13**
0.080
1.13
0.072
2.71***
1.592
3.40***-0.420
-1.62
0.100
1.74*
0.253
2.17**-0.319-1.56-0.422-5.08***-0.003-0.02

Rank.Growtht-2.948-15.06***-0.159-1.76*
1.104
14.11***
0.231
2.57**
0.339
2.61***
0.086
1.41
0.067
2.96***
1.525
3.89***-0.312-1.49
0.331
8.22***
0.359
2.38**-0.390-1.63
1.05-0.66712.72*** -4.90***-0.115-0.040-1.08-0.33

D_Stable-0.718-2.15**
0.271
3.79***
0.257
1.95*-0.087-1.43-0.392-3.30***-0.185-2.91***
0.064
2.01**-2.276-5.59***
0.360
1.60
0.039
0.95
0.362
2.02**-1.705-5.02***
0.660
9.94***
0.225
2.73***

Rank.ROAt-0.452-1.54
0.322
4.08***-0.007-0.04-0.037-0.40-0.389-3.94***-0.218-3.49***
0.063
2.26**-2.081-6.52***
0.166
0.74
0.002
0.04
0.356
2.29**

D_Nothing

1.899
4.53***-0.623-2.86***-2.202-7.76***-0.034-0.24
0.787
4.18***
0.351
2.92***-0.255-5.18***-2.226-1.71*-0.480-0.84-0.203-1.82*-1.436-5.84***
1.929
8.28***-1.676-11.89***-1.698-6.74***

IS2t

1.374
2.07**-0.654-2.56**-1.910-8.04***-0.199-1.24
1.059
5.00***
0.223
1.86*-0.210-3.79***-2.855-2.72***-0.832-1.37-0.106-1.18-1.593-5.08***
2.768
10.67***

D_Increase D_Decrease D_Omission

Dividend policy from t + 1 to t + 2
Coefficient
z-value

=
=
=
=
=
=
=

1 if a firm-year's dividend policy from t (t+1) to t+1 (t+2) is Nothing, and 0 otherwise.
1 if a firm-year's dividend policy from t (t+1) to t+1 (t+2) is Stable, and 0 otherwise.
1 if a firm-year's dividend policy from t (t+1) to t+1 (t+2) is Increase, and 0 otherwise.
1 if a firm-year's dividend policy from t (t+1) to t+1 (t+2) is Decrease, and 0 otherwise.
1 if a firm-year's dividend policy from t (t+1) to t+1 (t+2) is Omission, and 0 otherwise.
the net income for Fiscal Year t, deflated by the total assets at the beginning of Fiscal Year t.
the firm-specific volatility of earnings that is calculated as the standard deviation of NI
over the most recent five years.
TACt = total accrual that is defined as (change in current assets – change in cash and cash equivalents)– (change in liabilities – change in financing item) – change in other allowance– depreciation for Fiscal Year t, deflated by the total assets at the beginning of Fiscal Year t.
NDACt = non discretionary accrual that is estimated by using Kothari et al. (2005) 's model.

(Continued )The Japanese Accounting Review, 2 (2012), 1-32

26(-Continued )DACt = discretionary accrual that is definded by TACt minus NDACt.

NIBADt = the net income before accrual discretion for Fiscal Year t that is calculated as NIt minus DACt.
Vol(NIBAD)t = the firm-specific volatility of NIBAD that is calculated as the standard deviation of NIBAD
over the most recent five years.
Vol(NI)/Vol(NIBAD)t = the ratio of Vol(NI)t to Vol(NIBAD)t.
IS2t = the within industry-year reversed fractional ranking (between 0 and 1) of Vol(NI)/Vol(NIBAD)t.
ROAt = the ratio of net income before extraordinary items for Fiscal Year t over total assets
at the beginning of Fiscal Year t.
Rank.ROAt = the within industry-year fractional ranking (between 0 and 1) of ROA for Fiscal Year t (see text
for full details).
Growtht = the geometric average of the sales growth rate from Fiscal Year t - 4 to Fiscal Year t.
Rank.Growtht = the within industry-year fractional ranking (between 0 and 1) of Growth for Fiscal Year t(see text for full details).
Tobin’s Qt = the ratio of the sum of the market value and total debt to the sum of the book value of equity
and total debt at the end of Fiscal Year t.
Rank.Vol(NIBAD)t = the within industry-year fractional ranking (between 0 and 1) of Vol(NIBAD)t.
Sizet = the natural logarithm of the market value at the end of Fiscal Year t.
Foreignt = the foreign ownership at the end of Fiscal Year t.
Financialt = the financial institute ownership at the end of Fiscal Year t.
D_inct = 1 if a firm reports earnings growth for Fiscal Year t and 0 otherwise.
RE/BVEt = the ratio of the retained earnings to the book value of equity at the end of Fiscal Year t
DPSt = the dividend per share for Fiscal Year t.
All z-statistics are corrected for heteroskedasticity, and cross-sectional and time-series correlation using a two-way
cluster at the firm and year level proposed by Petersen (2009) and Cameron et al. (2011).
***,**, and * indicate significance at 1%, 5%, and 10%, respectively.

Panel B: Using IS3

Cons
IS3t
Rank.ROAt
Rank.Growtht
Tobin's Qt
Rank.Vol(CFOt )Sizet
Foreignt
Financialt
D_inctRE/BVEt
D_Nothingt-1

D_Nothing

1.347
1.92*
-0.749-2.80***-1.910-8.05***-0.195-1.22
1.059
4.67***
0.294
2.22**-0.207-3.55***-2.908-2.82***-0.836-1.39-0.096-1.09-1.581-5.17***
2.765
10.72***

Dividend policy from t to t + 1
Coefficient
z-value
D_Stable-0.433-1.46
0.399
4.71***
0.002
0.01-0.044-0.48-0.382-3.85***-0.299-4.02***
0.061
2.19**-2.071-6.37***
0.162
0.71-0.002-0.06
0.342
2.23**

D_Increase D_Decrease D_Omission-2.964-15.30***-0.201-1.89*
1.100
13.87***
0.234
2.60***
0.334
2.54**
0.138
1.50
0.068
2.97***
1.518
3.81***-0.307-1.46
0.333
8.08***
0.365
2.40**-0.391
-1.64

0.304
1.14
-0.125-1.15-1.228-7.55***-0.203-2.05**-0.448-2.86***
0.205
1.86*
-0.120-4.47***
0.584
0.93
0.479
1.74*
-0.503-7.81***-0.277-1.83*-0.497-0.64-0.699-3.28***-2.830-11.71***
0.012
0.08
0.596
3.33***
0.624
3.76***-0.199-2.21**-1.007-0.71-0.306-0.82-0.154-1.31-1.491-5.97***

D_Nothing

Dividend policy from t + 1 to t + 2
Coefficient
z-value

1.867
4.63***-0.741-3.33***-2.202-7.89***-0.019-0.13
0.777
4.09***
0.440
3.71***-0.251-5.19***-2.284-1.80*-0.466-0.83-0.200-1.79*-1.424-5.87***
1.930
8.30***

D_Stable

D_Increase D_Decrease D_Omission-0.699-2.388-2.22 ** -9.84***
0.339-0.1213.73 *** -0.94
0.264
0.495
2.00 ** 5.08***-0.0930.167-1.54
2.23**-0.3860.270-3.27 *** 2.08**-0.2580.122-2.91 *** 1.25
0.062
0.073
2.01 ** 2.75***-2.266
1.586-5.55 *** 3.34***
0.355-0.417
1.58
-1.62
0.036
0.102
0.88
1.76*
0.352
0.258
1.99 ** 2.23**-1.704-0.319-5.02 *** -1.56-1.062-3.67***-0.034-0.46-0.176-0.96-0.034-0.42-0.094
-0.53
0.030
0.39
-0.077-3.03***
0.755
1.94*
0.232
0.74
-0.134-2.49**-0.120-1.00-1.638-6.73***-2.055-2.43**-0.433-2.61***-2.028-10.47***
0.176
1.22
0.667
3.68***
0.321
2.31**-0.139-1.61-1.240-0.94-0.233-1.06-0.233-1.98**-0.732-4.60***-1.201-5.89***(Continued )Takasu and Nakano: What Do Smoothed Earnings Tell Us about the Future?

27(-Continued )D_Stablet-1

1.044-0.663
12.63*** -4.91***-0.118-0.039
-1.11
-0.32

0.655
-0.4199.80 *** -5.04***
0.222-0.002
2.69 *** -0.01

0.177
2.22**
0.311
2.76***

0.382
2.24**
0.521
2.23**

Yes

Yes

Yes

Pseudo R2
0.441
0.084
0.139
0.148
0.167
0.509
0.090
0.105
0.112
N
3,919
14,004
15,89014,00414,004
15,89015,89015,89015,890Nothing means a firm-year without any dividend for both Fiscal Year t (t + 1) and Fiscal Year t + 1 (t + 2).
Stable means a firm-year paying as much DPS for Fiscal Year t + 1 (t + 2) as Fiscal Year t (t + 1).
Increase means a firm-year paying more DPS for Fiscal Year t + 1 (t + 2) than DPS for Fiscal Year t (t + 1).
Decrease means a firm-year paying less DPS for Fiscal year t + 1 (t + 2) than Fiscal Year t (t + 1).
Omission means a firm-year omitting dividends for Fiscal year t + 1 (t + 2).

0.102
15,890

D_Increaset-1
Year dummy

Yes

Yes

Yes

0.064
0.63
1.371
7.36***

0.246
1.88*
0.233
0.87

-1.667-11.71***-1.694-6.73***

Yes

Yes

Yes

Yes

1 if a firm-year's dividend policy from t (t+1) to t+1 (t+2) is Nothing, and 0 otherwise.
1 if a firm-year's dividend policy from t (t+1) to t+1 (t+2) is Stable, and 0 otherwise.
1 if a firm-year's dividend policy from t (t+1) to t+1 (t+2) is Increase, and 0 otherwise.
1 if a firm-year's dividend policy from t (t+1) to t+1 (t+2) is Decrease, and 0 otherwise.
1 if a firm-year's dividend policy from t (t+1) to t+1 (t+2) is Omission, and 0 otherwise.
the net income for Fiscal Year t, deflated by the total assets at the beginning of Fiscal Year t.
the firm-specific volatility of earnings that is calculated as the standard deviation of NI over themost recent five years.
TACt = total accrual that is defined as (change in current assets – change in cash and cash equivalents)– (change in liabilities – change in financing item) – change in other allowance– depreciation for Fiscal Year t, deflated by the total assets at the beginning of Fiscal Year t.
CFOt = the cash flow from operations for Fiscal Year t that is defined as the net income before
extraordinary items minus TACt, deflated by the total assets atthe beginning of Fiscal Year t.

D_Nothingt
D_Stablet
D_Increaset
D_Decreaset
D_Omissiont
NIt
Vol(NI)t

=
=
=
=
=
=
=

Vol(CFO)t = the firm-specific volatility of CFO that is calculated as the standard deviation of
CFO over the most recent five years.

Vol(NI)/Vol(CFO)t = the ratio of Vol(NI)t to Vol(CFO)t.
IS3t = the within industry-year reversed fractional ranking (between 0 and 1) ofVol(NI)/Vol(CFO)t .

ROAt = the ratio of net income before extraordinary items for Fiscal Year t over total assets at the
beginning of Fiscal Year t.
Rank.ROAt = the within industry-year fractional ranking (between 0 and 1) of ROA for Fiscal Year t (see text
for full details).
Growtht = the geometric average of the sales growth rate from Fiscal Year t - 4 to Fiscal Year t.
Rank.Growtht = the within industry-year fractional ranking (between 0 and 1) of Growth for Fiscal Year t (seetext for full details).
Tobin’s Qt = the ratio of the sum of the market value and total debt to the sum of the book value of equity andtotal debt at the end of Fiscal Year t.
Rank.Vol(CFOt ) = the within industry-year fractional ranking (between 0 and 1) of Vol(CFO)t.
Sizet = the natural logarithm of the market value at the end of Fiscal Year t.
Foreignt = the foreign ownership at the end of Fiscal Year t.
Financialt = the financial institute ownership at the end of Fiscal Year t.
D_inct = 1 if a firm reports earnings growth for Fiscal Year t and 0 otherwise.
RE/BVEt = the ratio of the retained earnings to the book value of equity at the end of Fiscal Year t
DPSt = the dividend per share for Fiscal Year t.

(Continued )The Japanese Accounting Review, 2 (2012), 1-32

28(-Continued )All z-statistics are corrected for heteroskedasticity, and cross-sectional and time-series correlation using a two-way
cluster at the firm and year level proposed by Petersen (2009) and Cameron et al. (2011).
***,**, and * indicate significance at 1%, 5%, and 10%, respectively.

Panel C: Using IS4

D_NothingCons

Dividend policy from t to t + 1
Coefficient
z-value
D_Stable

0.215
1.70*
0.207
0.81

-1.065-3.58***
0.028
0.27-0.174
-0.96
0.001
0.01
-0.033-0.40-0.089-0.50-0.078-3.11***
0.768
1.96**
0.230
0.73-0.136-2.51**-0.129-1.06-1.633-6.72***
0.172
2.16**
0.310
2.75***-2.042-2.63***-0.477-2.62***-2.01-10.34***0.313
3.00***
0.158
1.10
0.664
3.62***-0.135-1.62-1.234-0.95-0.238-1.09-0.237-2.00**-0.713-4.70***-1.219-5.96***
0.367
2.14**
0.507
2.17**

Yes

Yes

Yes

Yes

Yes

Yes

Pseudo R2
0.440
0.083
0.139
0.147
0.168
0.508
0.089
0.105
0.112
N
3,919
14,004
15,89014,00414,004
15,89015,89015,89015,890Nothing means a firm-year without any dividend for both Fiscal Year t (t + 1) and Fiscal Year t + 1 (t + 2).
Stable means a firm-year paying as much DPS for Fiscal Year t + 1 (t + 2) as Fiscal Year t (t + 1).
Increase means a firm-year paying more DPS for Fiscal Year t + 1 (t + 2) than DPS for Fiscal Year t (t + 1).
Decrease means a firm-year paying less DPS for Fiscal year t + 1 (t + 2) than Fiscal Year t (t + 1).
Omission means a firm-year omitting dividends for Fiscal year t+1 (t+2).

0.102
15,890Rank.Growtht
Tobin's Qt
Sizet
Foreignt
Financialt
D_inctRE/BVEt
D_Nothingt-1
D_Stablet-1

Yes

Yes

D_Increaset-1
Year dummy

D_Nothingt
D_Stablet
D_Increaset
D_Decreaset
D_Omissiont
NIt

=
=
=
=
=
=

Yes

0.348
1.23
-0.074-0.74-1.219-7.49***
0.120
1.53-0.209-2.15**-0.437-2.75***-0.123-4.70***
0.608
1.00
0.473
1.70*
-0.506-7.83***-0.284-1.88*-0.390-0.500-0.711-3.19***-2.815-11.82***0.493
4.79***-0.026-0.19
0.600
3.29***-0.198-2.20**-0.981-0.68-0.328-0.890-0.161-1.34-1.468-6.12***

0.056
0.54
1.366
7.37***
Yes

D_Increase D_Decrease D_Omission-2.380-8.86***-0.093-0.87
0.499
5.25***
0.087
1.19
0.164
2.15**
0.274
2.14**
0.072
2.76***
1.594
3.37***-0.416
-1.60
0.100
1.74*
0.256
2.19**-0.320-1.54-0.425-5.15***-0.003-0.03

Rank.Vol(NIBADt )-2.966-15.03***-0.133-1.17
1.108
14.15***
0.087
1.41
0.231
2.56**
0.342
2.61***
0.067
2.88***
1.534
3.87***-0.305-1.45
0.330
8.27***
0.359
2.37**-0.389-1.62
1.064-0.67312.71*** -4.98***-0.110-0.042-1.02-0.34

D_Stable-0.691-2.04**
0.204
2.53**
0.252
1.92*-0.177-2.76***-0.087-1.39-0.397-3.34***
0.064
2.07**-2.298-5.66***
0.351
1.57
0.042
1.02
0.365
2.07**-1.708-5.03***
0.672
9.95***
0.228
2.76***

Rank.ROAt-0.419-1.41
0.254
3.72***-0.013-0.07-0.212-3.36***-0.037-0.40-0.395-3.92***
0.064
2.28**-2.103-6.59***
0.159
0.71
0.005
0.13
0.358
2.32**

D_Nothing

1.887
4.47***-0.538-2.81***-2.219-7.82***
0.361
3.11***-0.048-0.3400.782
4.16***-0.255-5.31***-2.153-1.69*-0.469-0.82-0.209-1.91*-1.429-5.76***
1.922
8.23***-1.703-12.51***-1.708-6.92***

IS4t

1.373
2.03**-0.567-2.07**-1.935-8.06***
0.240
2.09**-0.223-1.39
1.060
4.64***-0.211-3.76***-2.796-2.71***-0.832-1.36-0.107-1.290-1.579-5.15***
2.760
10.59***

D_Increase D_Decrease D_Omission

Dividend policy from t + 1 to t + 2
Coefficient
z-value

1 if a firm-year's dividend policy from t (t+1) to t+1 (t+2) is Nothing, and 0 otherwise.
1 if a firm-year's dividend policy from t (t+1) to t+1 (t+2) is Stable, and 0 otherwise.
1 if a firm-year's dividend policy from t (t+1) to t+1 (t+2) is Increase, and 0 otherwise.
1 if a firm-year's dividend policy from t (t+1) to t+1 (t+2) is Decrease, and 0 otherwise.
1 if a firm-year's dividend policy from t (t+1) to t+1 (t+2) is Omission, and 0 otherwise.
the net income for Fiscal Year t, deflated by the total assets at the beginning of Fiscal Year t.

(Continued )Takasu and Nakano: What Do Smoothed Earnings Tell Us about the Future?

29(-Continued )Vol(NI)t = the firm-specific volatility of earnings that is calculated as the standard deviation of NI
over the most recent five years.
TACt = total accrual that is defined as (change in current assets – change in cash and cash equivalents)– (change in liabilities – change in financing item) – change in other allowance– depreciation for Fiscal Year t, deflated by the total assets at the beginning of Fiscal Year t.
NDACt = non discretionary accrual that is estimated by using Kothari et al. (2005) 's model.
DACt = discretionary accrual that is definded by TACt minus NDACt.

NIBADt = the net income before accrual discretion for Fiscal Year t that is calculated as NIt minus DACt.
Vol(NIBAD)t = the firm-specific volatility of NIBAD that is calculated as the standard deviation of NIBAD
over the most recent five years.
=
thecorrelation coefficient between change in DAC and change in NIBAD.
r (ΔDAC, ΔNIBAD)t

IS4t = the within industry-year reversed fractional ranking (between 0 and 1) of r (ΔDAC, ΔNIBAD)t.
ROAt = the ratio of net income before extraordinary items for Fiscal Year t over total assets
at the beginning of Fiscal Year t.
Rank.ROAt = the within industry-year fractional ranking (between 0 and 1) of ROA for Fiscal Year t(see text for full details).
Growtht = the geometric average of the sales growth rate from Fiscal Year t - 4 to Fiscal Year t.
Rank.Growtht = the within industry-year fractional ranking (between 0 and 1) of Growth for Fiscal Year t(see text for full details).
Tobin’s Qt = the ratio of the sum of the market value and total debt to the sum of the book value of equity
and total debt at the end of Fiscal Year t.
Rank.Vol(NIBAD)t = the within industry-year fractional ranking (between 0 and 1) of Vol(NIBAD)t.
Sizet = the natural logarithm of the market value at the end of Fiscal Year t.
Foreignt = the foreign ownership at the end of Fiscal Year t.
Financialt = the financial institute ownership at the end of Fiscal Year t.
D_inct = 1 if a firm reports earnings growth for Fiscal Year t and 0 otherwise.
RE/BVEt = the ratio of the retained earnings to the book value of equity at the end of Fiscal Year t
DPSt = the dividend per share for Fiscal Year t.

All z-statistics are corrected for heteroskedasticity, and cross-sectional and time-series correlation using a two-way
cluster at the firm and year level proposed by Petersen (2009) and Cameron et al. (2011).
***,**, and * indicate significance at 1%, 5%, and 10%, respectively.

6. Conclusion
This study analyzes the information contents of income smoothing behavior, especially the roleof income smoothing behavior as a signal about future performance. What do smoothed earnings tell
us about the future? To answer this research question, this paper focuses on earnings persistence anddividend policy based on two prior survey papers by Graham et al. (2005) and Suda and Hanaeda(2008). These two issues are the foci of this study, based on Japanese managers’ responses to questions
regarding their motivation for income smoothing. In a survey study in Japan, the top two reasons
given by managers as to why they prefer smoothed income were that (1) it enables stable dividends
and (2) it assures customers/suppliers that the business is stable (Suda and Hanaeda 2008).
This paper provides two new pieces of evidence. First, income smoothing in the previous period
relates positively to future earnings persistence. This implies that income smoothing behavior reflects highearnings persistence in the future. Second, firms that engaged in more smoothing will tend to pay stabledividends in the future, even when we control for past dividend policy, fundamental factors, and corporate
governance factors. Given Lintner (1956)’s argument that the change in dividend amount is dependent

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The Japanese Accounting Review, 2 (2012), 1-32

on the change in the level of long-term and persistent earnings, it would appear that income smoothing
behavior reflects long-term stability of firm performance. Therefore, income smoothing is informativewith respect to a firm’s future stable dividends, in line with the findings within the signaling literature.
In aggregating these pieces of evidence, it becomes clear that Japanese managers, on average,
tend to smooth earnings with future earnings performance in mind. Skinner and Soltes (2011)
found that dividends function as a signal of a firm’s future earnings persistence. The current study’s
findings suggest that income smoothing in the previous five years plays a role of signaling both
future dividends stability and future earnings persistence. It should be noted that income smoothing
behavior itself incorporates valuable information.
This study makes several contributions to the literature and understanding of income smoothing
behavior. First, we build on recent advances in the literature vis-à-vis earnings quality, especially
income smoothing. Although most prior studies focus on economic consequence of incomesmoothing, few studies provide evidence as to whether or not income smoothing reflects future
performance. The current study fills this gap.
Second, the empirical evidence supports the information view rather than a garbling view ofincome smoothing. This study sheds light on the bright side of smoothed earnings rather than its
dark side.
In technical terms, the current study’s definition of income smoothing is comprehensive, as it
encompasses both accrual-based discretion and real discretion. In addition, the results are robust toalternative definitions of “income smoothing”.
This study, of course, has several limitations. Most importantly, it does not cover market
valuation concerning income smoothing. Francis et al. (2004) examined a link between cost of capitaland income smoothing, and they find a negative association between them. In contrast, McInnis(2010) found no evidence those smooth earnings paths lead to a lower cost of equity. A survey study,on the other hand, found that 36.17 percent of Japanese top-level managers answered that having
their firms be “perceived as less risky by investors” was an important factor in choosing to take asmooth earnings path. This answer was the fourth most frequently cited factor. “Reduce the returnthat investors demand,” meanwhile, was in seventh place, with 18.57 percent of the responses (Sudaand Hanaeda 2008). The economic consequences of income smoothing in the capital market would
be the next issue to be explored, in future research.23
This study suggests that, with regard to firms that have succeeded in income smoothing, incomesmoothing behaviors in the past may provide private information about future stability of firm
performance. The current study, however, provides few implications about firms that failed in incomesmoothing. Some prior literature examines about these firms. For instance, Myers et al. (2007)
and Shuto (2010) found that firms with long strings of consecutive increases in earnings enjoyedeconomically significant abnormal returns while the strings were ongoing and suffered significant
stock price declines when the strings were broken. These results might be one of negative economic
consequences of income smoothing. It is not until understanding both effects of succeeding inincome smoothing and that of failing that we can understand a complete picture of economic
consequences of income smoothing. This is another topic that is to be explored in the future research.

23

For example, Takasu (2012) attempts to figure out this puzzle. He uses cost of bank loans as a proxy for cost of capital. From hisanalysis, he finds an information asymmetry between a firm and capital providers plays a key role that determines the relation
between income smoothing behavior and cost of capital.

Takasu and Nakano: What Do Smoothed Earnings Tell Us about the Future?

31

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