Accrual-Based and Real Activities Based Earnings Management
Behavior of Family Firms in Japan

Abstract
We explore the degree of accrual-based earnings management and real activities based
earnings management, using data of all family and non-family firms listed on the Tokyo
Stock Exchange from 2004 through 2011. A priori family firms are expected to have lower
agency cost because family shareholders and management will be more congruent inpursuing mutual firm goals. A founding family will also pay attention to the reputation of
their firm and family in order to sustain socioemotional wealth. We empirically assess thelevel of earnings management and investigate whether the amount will be lower for family
than non-family firms, and also identify which method is more costly. The level of accruals
and cost may vary among the type of the family firms; that is, whether or not shareholdings
are large and if the CEO is from the founding family. With univariate analysis we find thatthe level of accrual-based earnings management measures is higher for family versus nonfamily firms for some selected measures, while real activities measures are lower for family
firms. With cross section regressions, we find that shares owned by a founding family
increase the level of accrual-based earnings management, while the CEO dummy variable
decreases it. For the level of real activities earnings management, we find that family related
variables decrease it. When we introduce economic measures related to costs of earnings
management: i.e., the choice of an auditor, the number of following analysts, the length ofoperating cycles, market share, estimated distance to default, and effective tax rates, we findthat Japanese family firms utilize accrual-based earnings management more often than real
activities based earnings management.

JEL Classification: M41, G32, M21
Keywords: earnings quality, founding family, CEO, abnormal accruals, overproduction01. Introduction
Among the literature on earnings quality (Sloan, 1996, Xie, 2001, Desai et al., 2004,
Richardson et al., 2005), there are few studies using U.S. family firm data except for Ali etal. (2007) and Wang (2006). Although the financial performance of family firms withJapanese data has been investigated by Claessens et al. (2000), Allouche et al. (2008), Saito(2008), Asaba (2013), and Mehrotra et al. (2013), there are few studies from the viewpointof quality of financial disclosure. Ebihara et al. (2012) find that earnings quality of Japanesefamily firms is lower than non-family firms with univariate analysis using the Jones andmodified Jones models, and that earnings quality is higher for family firms for shareholdingsof founding families up to 33% with multivariate pooled regressions. Kubota and Takehara(2012) find that family firms adopt more conservative earnings reporting than non-family
firms. In this paper we investigate the level of accrual-based earnings management and real
activities based earnings management using data from all family and non-family firms listedon the Tokyo Stock Exchange from 2004 through 2011. However, these previous studies on
Japanese data investigated only accrual-based earnings management. In the current paper we
explore both accrual-based and real activities based earnings management (Roychowdhurry,
2006, and Zang, 2012) of family firms in Japan.
A priori family firms are expected to have lower agency cost because family shareholders
and management will be more congruent in pursuing mutual firm goals by family
shareholdings and/or executive positions. A founding family will also pay attention to thereputation of their product/services, firm name, and family name in order to sustain familysocioemotional wealth even with some sacrifice for best economic performance.1 Thus, we
1

See Barrone et al. (2010) and Gomez-Meja et al. (2007, 2011) for the definition of socioemotional wealth1infer that the amount of earnings management will be lower for family than non-family firms
for reputational purposes, and investigate the level of earnings management identifying
which method is more costly for family firms. In addition, we consider that the level ofaccruals and cost may also vary among the type of family firm; that is, whether or notshareholdings are large and if the CEO is from the founding family. We conduct empiricalanalyses using correlation analysis, portfolio analysis, univariate analysis, and cross section
regressions and find evidence to test these assertions.
Section 2 motivates our study and Section 3 reviews previous studies. Section 4
establishes our hypotheses. Section 5 explains the data and reports basic statistics.

Section

6 reports empirical results in detail, and Section 7 concludes.

2. Motivation of the Study
Family firms are expected to be equipped with management congruent with a family
norm, whether or not the CEO is from the family. Accordingly, we expect that management
possesses stronger real authority inside firms according to the definition of Aghion and Tirole(1997). However, this force can work in two ways.
First, family firms will suffer less from agency cost problems that arise between managers
and share owners (Jensen and Meckling, 1976). This is because a large fraction of shares are
owned by founding families and the family CEO has real authority from the family. These
factors will lead the firm to higher efficiency with less agency cost. Anderson et al. (2009)
makes the point that family firms can provide stronger control and oversight with less agency

used in family firm research literature.

2

cost, enabling their managers to have more direct control over corporate social activity
decisions. They call this strong tendency the “control in-place” hypothesis. Our researchquestion is whether a stronger authority and less agency cost will lead the quality of earnings
to better maintain the reputation of the firm and the family.

We establish our first null

hypothesis in this regard in Section 4.
Second, on the other hand, a stronger authority may make the disclosure level moreopaque because management and the owner care less for other stakeholders. In other words,
family firms may fall into a state of autarky, and non-family managers and employees in fearof losing their jobs may be unable to stand up against the firm.

For example, both Dyer andWhetten (2006) and Anderson et al. (2009) state that families can be self-centered and moreinterested in just protecting their well being, and Anderson et al calls this tendency the“entrenchment hypothesis.” From the viewpoint of keeping a family firm’s socioemotional
wealth, Gomez-Meja et al, (2007, 2011) argue that family firms are willing to yield financial
performance to attain and preserve higher socioemotional wealth. Stockmans et al. (2010)
using Flemish private firm data concludes that socioemotional wealth plays a role as a motive
for upward earnings management. We also test this entrenchment hypothesis as an alternative
hypothesis, against the null hypothesis, which implies lower earnings quality. This will
constitute our first null hypothesis.
For testing the hypothesis between the less agency cost argument versus the entrenchment
effect, we focus on earnings quality rather than financial performance which has been alreadyinvestigated for Japanese family businesses. Earnings quality is one of the major properties
accounting reports ought to possess (Ronen and Yarri, 2008, and Francis et al. 2006) and the3evidence for Japanese family business data is less known except in Ebihara et al. (2012). In
order to investigate the level of accrual-based earnings measurement, we use abnormal
accruals as presented by Dechow, Sloan and Sweeney (1995) as well as other standard
earnings quality measures from the accounting literature. We also investigate the level of real
activities based earnings management as devised by Roychowdhury (2006). We compare thedifference between family and non-family firms by highlighting management styles reflectedin earnings quality and also use measures proposed by Zang (2012), comparing the relative
cost of earnings management. This will lead us to establish the second hypothesis also
defined in Section 4. We will review previous studies related to ours in the next section.

3. Previous Evidence on Family Firm Earnings Management
Among the literature on earnings quality (Sloan, 1996, Xie, 2001, Desai et al., 2004,
Richardson et al., 2005), there are less studies using U.S. family firm data. Ali et al. (2007)
find that U.S. family firms show better quality in financial disclosure, are followed by more
analysts, and trade their stocks with smaller bid-ask spreads. Wang (2006) finds that earnings
quality is higher for U.S. family firms versus non-family firms. Similarly, Jiraporn and
DeDalt (2009) find that stronger control by the founding family leads family firms to lessearnings management for U.S. firms and emphasize the role of family reputation, which we
use to construct our hypotheses in Section 4.
For evidence in other countries, Stockmans et al. (2010) finds family firms have greater
incentive to engage in upward earnings management to preserve their socioemotional wealthusing Finnish data from their own questionnaires. Cascino et al. (2010) uses Italian listed4

firm data and finds that family firms have a higher quality of financial information disclosure
than non-family firms. Using Taiwan family firm data, Yang (2010) finds the larger the levelof insider ownership, the larger the level of earnings management.
These previous studies investigated only accrual-based earnings management. In thecurrent paper we explore both accrual-based and real activities based earnings management(Roychowdhurry, 2006 and Zang, 2012), and compare relative costs for family firms of three
types, which we define in Section 5. For the former earnings management measure, we
decompose total accruals into normal and abnormal components using the modified Jonesmodel proposed by Dechow et al. (1995) and for the latter measure we use the method by
Roychowdhury (2006).
In one of the most widely cited research articles about Asian family business, Claessens
et al. (2000) investigated ownership structure among East Asian countries for evidence onmanagement behavior and financial performance of Japanese family firms. They cover 1,240
Japanese listed firms (op. cit., p.104) and point out that 13.1% of firms are controlled byfamilies with a 10% shareholding cutoff level for founding families, and 9.7% of firms arecontrolled by families with a 20% cutoff level. Saito (2008) finds that family firms slightly
outperformed non-family firms from 1990 through 1998, but their superiority was limited to
the founders’ reign. Allouche et al. (2008) find that family firms outperform the matchedsample of non-family firms with a smaller sample. More recently, Asaba (2013) investigatedinvestment behavior of the electric machinery industry in Japan. His sample of 184 family
firms from 1995-2006 demonstrates more aggressive investment behavior during a boom andmore persistent investment behavior during a recession. Mehrotra et al. (2013) investigated5

Japanese family business succession problems and demonstrated that adopted heirs could
avoid the succession problem. They studied Japanese firms between 1949 and 1970 andfollowed the data up to 2000.
In the accounting literature investigating Japanese firm earnings quality, Kubota andTakehara (2012) find that family firms adopt more conservative earnings reporting than nonfamily firms, and report losses earlier using the Basu (1995) conditional conservatism
regression model. Ebihara et al. (2012) find that earnings quality is lower for family firms
than non-family firms with univariate analysis, but the quality is higher for founding family
shareholdings of up to 33% using multivariate analysis.

4. Hypotheses
We introduced the reasoning in Section 3 and we establish two hypotheses in this section.
The first is related to the preservation motive of socioemotional wealth by family firms. Withstronger authority and less agency cost, family firms are unwilling to boost their accounting
earnings and rather decrease reported earnings. Given real authority (Aghion and Tirole,1997) management and owners do not have to worry about the compensation of managers
geared towards firm performance, and will not engage in income boosting. Given less agency
cost, the founding family and management with more firm shares may be more concerned
than non-family firms with long run value appreciation and may care less about earnings
performance in the short run. We predict that managers of family firms do not choose income
increasing type earnings management practices because it will reduce the founding family
firm reputation and detract from socio-emotional wealth
We expect that the amount of earnings management in family firms is lower than that in non6

family firms. We call this reasoning “founding family’s reputation hypothesis,” and establish
our first hypothesis.
Hypothesis 1: Family firms will not choose an income increasing earnings management
practice which reduces family reputation and socio-emotional wealth.

The alternative hypothesis is that managers and the founding family want to extract morecash by spending more on a family CEO and/or paying out higher dividends with inflated
earnings. Management may incur higher expenditures for perks (Jensen and Meckling, 1976).
In fact, Stockmans et al, (2010) find this behavior in Flemish private family firms. Our
sample is public firms in Japan and our evidence will complement their finding whichever
the direction may be.
The second hypothesis is which kind of earnings management method family firms inJapan pursue: i.e., accrual-based earnings management or real activities based earnings
management. We classify family firms into three types: i.e., Type 1: firms with more than
10% of shares owned by a founding family and the CEO is from the family; Type 2: firms
with more than 10% of shares owned by a founding family, but the CEO is not from thefamily; and Type 3: less than 10% of shares owned by a founding family and the CEO is fromthe family. Based on these classifications and with a sample of non-family firms weinvestigate the following hypothesis based on cost differences of these four types of firms(Zang, 2012).

We call this hypothesis the “earnings management cost hypothesis.”

Hypothesis 2:

Family firms will adopt the earnings management method
which has a lower cost for the founding family.
7

With these two hypotheses we explore the degree of earnings management and costdifferences of Japanese family firms.
5. Data Construction Method and Basic Observation
Our primary observation period is 2004 through 2011 and the sample includes all listed
firms on the Tokyo Stock Exchange. The number of the sample is listed in Table 1 and weconstruct an unbalanced panel data without survivorship and new firm bias.

TABLE 1 ABOUT HEREIn Table 1 we classify firms into non-family firms or three types of family firms defined
above, and report basic statistics.2 In the first subpanel the number of observations for eachyear is reported, then, the listing of the stock exchanges and the sector wise observations.
This sector classification scheme follows one used by Kubota and Takehara (2007), whoinvestigated the cost of capital for Japan. The detail of this scheme is shown in the Appendix.
The first column lists the number of non-family firms, the second, Type 1 firms (more than
10% and CEO from founding family), the third, Type 2 firms (more than 10% and CEO notfrom founding family), the fourth, Type 3 firms (less than 10%, and CEO from founding
family), and the fifth, the total number of firms. For example, in 2011, there are 1010, 426,
104, 152, and 1692 firms, respectively.

2

Note that among the non-family firm group it includes family firms with shareholding percentages less than
10% and the CEO not from the family. When we established our own database this group was classified as
non-family firms.

8

We find the number of family firms of all type increases over the years with a pace higher
than that for non-family firms. For stock exchange listings, we find the largest is fromemerging other stock markets in Japan with 261 firms and 82 firms for Type 1 and Type 2
firms. For Type 3, we find the largest is on the Tokyo Stock Exchange, with Toyota Motor
Co. and Panasonic in this category. For sector-wise observations, for Type 1 and Type 2 firms,
the largest is the service industry, while for Type 3, the largest is the investment goods
industry. Overall, we find that 42% of the firms are classified as listed family firms in Japan.
For these sample firms we use financial statement and stock price data from the Nikkei
NEEDS Database and compute earnings numbers and managed numbers.
In order to compute the amount of total accruals, ACC, and components of accruals,
equation (1) is used as a standard method. All variables in equation (1) are standardized by adivisor with total assets at the beginning of each year.
ACC  COA  COL  NCOL  DEPR
COA(Current Operating Assets)= changes in current assets  changes in cash and cash equivalent s
COL (Current Operating Liabilities)=  (changes in current liabilities  changes in financing items)(1)

NCOL ( Non - Current Operating Liabilities)=  ( changes in allowance for future retirement benefits+ changes in other long term allowance accounts + changes in amortization)
DEPR (depreciation) =  (total depreciation of tangible fixed assets)

Changes in financing items in ΔCOL are composed of changes in 1) short-term borrowing,2) outstanding commercial paper, 3) long-term debt due within one year, and 4) straight bonds
and convertible bonds due within one year. Changes in amortization are composed of changes
9

in amortization of intangible fixed assets, such as goodwill and patent rights. Current assets,
current liabilities, cash equivalents, allowance for future retirement benefits, and tangible
fixed assets are handled the same as the U.S. GAAP. Note also thatΔCOL,ΔNCOL, and
DEPR are defined as negative numbers throughout this paper so that the amount of total
accruals, ACC, gets smaller (larger) as these numbers get larger (smaller).
We decompose total accruals into normal and abnormal components using the modified
Jones model proposed by Dechow, Sloan and Sweeney (1995). We estimate the following
cross-section regression equation separately by each industry for each sample year.3
ACC j ,t / TA j ,t 1   0   01 / TA j ,t 1  1ADJREV j ,t   2 PPE j ,t   j ,t .

(2)

In equation (2), ΔADJREV is the difference in changes in sales and accounts receivables,
PPE is property, plant, and equipment measured at net book value, and νj,t is an residual term.
The fitted values from OLS estimation were used to construct normal accruals (NAC)
components, and their residual terms were used as abnormal accruals (ABNAC). The
abnormal accruals components represent firm-specific accrual components in excess ofindustry averages.
In addition to abnormal accruals, we also use two other measures of accounting based
earnings quality measures. They are measures of variability, and smoothness of earnings.
Variability of earnings (EBEISD) in this study is defined as a past five year standard deviationof earnings before extraordinary items (EBEI). The ‘smoothness’ measure is a ratio of thestandard deviation of EBEI to the standard deviation of CFO.

3

Based on the original 33 industry classifications by the Tokyo Stock Exchange, we classified all nonfinancial firms into 24 industries.

10

For measures to assess the level of real activities based earnings management we follow
the method employed by Roychowdhury (2006) and the data construction method is almost
identical. First, by conducting cross-sectional regressions for every industry and year, we
compute abnormal cash-flows from operations, ABNCFO, which is defined as a residual
term from the following regression model (3).

CFO j ,t / TA j ,t 1   0  1  1 / TA j ,t 1  1  SLS j ,t / TA j ,t 1   2 SLS j ,t / TA j ,t 1   j ,t .

(3)

We also compute two additional measures of real activities based earnings management,
abnormal production (ABNPROD), and abnormal expenditures (ABNEXP), by employing
the following regression models (4) and (5) as proposed by Roychowdhury (2006).4

PROD j ,t 

 0  1  1 / TA j ,t 1

 1SLSt / TA j ,t 1   2 SLS j ,t / TA j ,t 1   3 SLSt 1 / TA j ,t 1   j ,t .

DISEXPj ,t / TA j ,t 1   0  1  1 / TA j ,t 1  1SLSt 1 / TA j ,t 1   j ,t .

(4)

(5)

Table 2 reports the means of the various measures of earnings management as well as
financial characteristics and p-values of the differences for each category of family and nonfamily firms.
TABLE 2 ABOUT HERE

To measure accrual-based earnings quality (Francis et al. 2008), we choose three variables,
abnormal accruals (ABNAC), earnings variability (EBEISD), and smoothness. Reported in

4

Using equations (2) and (3) of Roychowdhury (2006), we computed two additional measures of real-activities
based earnings management: abnormal cost of goods sold, and abnormal inventory growth. However, thePearson correlation between abnormal production (ABNPROD) and abnormal cost of goods sold in our pooled
sample is very high at 0.916. Thus, we decided not to use abnormal cost of goods sold and abnormal inventory
growth in the analysis and focus on abnormal production (ABNPROD).

11

the first row are the percentage of shares owned by the founding family and the differences
are all significant. For abnormal accruals, the smallest is Type 2 firms at -0.481 and thedifference with non-family firms is significant at the 10% level (p-value=0.056). It means thetype of firms where CEOs are not members of the founding family decrease their earnings
the most among all type of firms, which is worth mentioning, and so are the cases forvariability (EBEISD) at 2.236 defined as the past 5 year volatility of earnings. In Type 2
firms, the managers are hired professionals and perhaps are more concerned with their own
reputation as capable managers and/or their own empire building (Berk and DeMarzo, 2011,
Ch. 16). Smoothness is measured by the ratio of variability to the standard deviation of cash
flows from operations, and Type 3 firms have the highest number at 0.523, which shows thelowest earnings quality. However, we find Type 2 firms show a lower number at 0.458 thanother types of firms, which means higher earnings quality. This result is consistent with thefinding for abnormal accruals. Hence, we infer that Type 2 firms without family CEOs may
be more concerned with long term sustainability of earnings, and they may exercise income
decreasing earnings management to pursue long term objectives.
Overall, for the various measures of accrual-based earnings management for different
types of family firms, we find the level of earnings management is somewhat higher in family
firms, although not all significant. Accordingly, the evidence for accrual-based earnings
management is not against Hypothesis 1 with univariate analysis and H1 is weakly supported.
For the measures of real activities based earnings management, the means of abnormal
cash flows from operations (ABNCFO) of Type 1 family firms is higher than that for nonfamily firms and the difference is statistically significant. In the case of abnormal production

12

(ABNPROD), they are the lowest (negative) for both Type 1 and Type 2 firms at -0.018 and-0.008, respectively, and significant. These imply Type 1 and Type 2 family firms utilize lessreal activities based earnings management. On the other hand, abnormal expenditures(ABNEXP) for these two types of firms are larger at 0.017 and 0.003 which means family
firms expend more. It may be due to the stronger real authority of family firms (Aghion andTirole, 1997) with entrenchment effects in force.
Overall, except for abnormal expenditures, we find Type 1 and Type 2 family firms use
less real activities based earnings management than non-family firms and Type 3 firms. From
the univariate analysis result for activities based earnings management, we support
Hypothesis 1, similar to the cases for accrual-based earnings management. Because the sizeof Type 3 firms is large at 11.172 (see the rows of lnTA below) and these are listed firms, it
is reasonable that Type 3 firms show a similar tendency to non-family firms as far as earnings
management of both accrual-based and real activities based is concerned.
In the lowest subpanels we report basic financial characteristics of our sample. Size(lnTA: Natural logarithm of total assets) is used as a dummy variable in cross section
regressions and the other four variables are also used as control variables. That is; ROA: Past
5 year average return on equity, LEV: A firm’s financial leverage defined as non-current
liabilities to total assets, SLSG: Past 5 year growth rate of sales, and LP: Labor productivity
defined as value added per employee. The return on assets (ROA) is highest for Type 1 family
firms at 1.715% and then Type 3 firms at 1.626% . Leverage is lowest for Type 2 firms at
12.589%. Sales growth (SLSG) is higher for non-family firms at 1.045%, but the difference13

is not significant. Labor productivity (LG) is higher for non-family firms at 23.807 million
yen than all types of family firms, and is an interesting result.
6. Empirical Results
6.1 Analysis of Family Shares and CEO Positions
In this sub-section we investigate how ownership affects earnings management behavior,
and whether it matters if the CEO is from the founding family.

TABLE 3 ABOUT HERE

Table 3 reports correlation numbers with Pearson Correlation and Spearman Rank
Correlation between the degree of earnings management and shares owned by a founding
family (shown in the left subpanel). The difference in earnings management depending onwhether the CEO is from the founding family (DCEO=1) or not (DCEO=0) is shown in theright subpanel, both with corresponding p-values. In the lower subpanel are the same figures
for firm characteristics variables.
For correlation numbers, we find that percentage of shares held by a founding family(FFO) are negatively correlated with the abnormal accruals (ABNAC) at 0.016 for Pearson
and it is significant at 10% level. The Pearson and Spearman correlations between FFO andearnings variability (EBEISD) are 0.029 and 0.067, respectively and both of them aresignificant at the 1% level. This means the more shares owned by families, the higher theearnings variability. For smoothness, the Pearson correlations are negative, and not
significant. However, the Spearman correlation is positive and significant at the 5% level.

14

For real activities based earnings management, we find that abnormal production(ABNPROD) are negatively correlated at -0.102 for Pearson and -0.075 for Spearman, As
for abnormal expenditures (ABNEXP), they are positively correlated with family shares at
0.095 for Pearson and 0.065 for Spearman, and this augments our previous findings. That is,a founding family may incur specific and extra expenditure for family managers, whichsometimes may lead to entrenchment effects.5
In the case of the CEO dummy variable shown in the right subpanel, we do not findsignificant differences in accrual-based earnings management. However, for real activities
based earnings management, we find the abnormal production cost (ABNPROD) is lower at-0.010 when CEOs are from the family. It can be said that family CEOs tend to decrease theproduction cost to increase profit. Abnormal expenditures (ABNEXP) are higher in the casewhere the CEO is from the family (0.010 vs. -0.008) and this augments the previous finding.
So far, the evidence weakly supports Hypothesis 1.
For firms’ financial characteristics variables, shares owned by founding families (FFO)
are positively correlated with ROA at 0.012 for Pearson, and negatively correlated with size
(lnTA) and leverage (LEV) at -0.303 and -0.111, respectively. The CEO dummy contributes
to higher ROA (1.689% vs. 1.429%), but lower leverage (14.874% vs. 17.875%), lower log
size (10.451 vs. 11.012), lower sales growth (SLSG) (1.015% vs. 1.050%) and laborproductivity (LP) (17.162 million yen vs. 23.542 million yen).
Table 4 classifies firms into five portfolios based on the percentage of shares owned by
the founding family (FFO) and compares the same variables as in Table 3.
5

See the case for Daio Seishi Co. in which the CEO from the founding family used company money for his
personal gambling and was prosecuted in 2012.

15

TABLE 4 ABOUT HERE

The second to the upper most right column reports the difference between the highest shareowned group (P1) with more than 50% minus the lowest group (P5) with less than 10%
owned and the upper most right column shows the corresponding p-values.
For this difference variable (P1-P5), they are at -0.414, 0.360, and 0.049 for the abnormal
accruals (ABNAC), the earnings variability (EBEISD), and smoothness, respectively. Thus,earnings are decreased more largely and earnings variability becomes higher as more shares
are owned by founding families. This finding supports previous findings in Tables 2 and 3.
In case of real activities based earnings management, abnormal production costs(ABNPROD) is smallest at -0.017 in P1 in which FFO is greater than 50%, while abnormal
expenditures (ABNEXP) are positively correlated.
In sum, this ranked portfolio test confirms the previous result shown in Tables 2 and 3
both for accrual-based earnings management and real activities based earnings management.
Also, note that the shares owned by the founding family are negatively related with all
financial characteristics variables, but the result for leverage is not significant.

6.2 Cross Section Regressions
In this sub-section we report the results from cross section regressions of the following
specification in equation (6). EQ is an earnings management variable of our interest. FFO
and DCEO are the percentage of shares owned by the founding family and CEO dummy. CVs
are control variables, composed of ROA, leverage, sales growth, and labor productivity.
DSize are firm size dummies (large-cap, mid-cap, and small-cap) defined based on the16ranking in each year by book value of total assets, DSector is as defined in the Appendix, and
DYear is the year dummies.
EQ jt     1  FFO jt   2 DCEO jt
4

3

6

2010

i 1

i 2

i 2

t  2004   i CVijt    i DSizeijt   i DSectorijt   t DYearijt   jt

(6)

Table 5 reports the result from OLS regressions, where p-values are computed withWhite’s heteroskedasticity corrections.

TABLE 5 ABOUT HERE

For the level of accrual-based earnings management, when we look at the family sharevalue FFO, we find the slope for the abnormal accruals (ABNAC) is negative at -0.004. The
slope for DCEO is also negative at -0.058. Insignificant slopes for FFO and DCEO suggestthat family firms have tendencies to avoid income boosting, which supports Hypothesis 1.
As for earnings variability (EBEISD), slope of FFO is positive at 0.002 and significant at
the 10% level, which means that more shares are owned by the family, the higher the earnings
variability.
In the case of real activities based earnings management, the magnitude of coefficientsfor both FFO and DCEO become much smaller. We find the coefficients of family shares(FFO) to explain the abnormal production cost (ABNPROD) is negative and significant at 0.001. In addition, coefficients on abnormal expenditures (ABNEXP) are positive at 0.001
and significant. Again, family firms expend more, and the coefficient for abnormal
expenditures of DCEO variable is 0.006 and significant at the 1% level. The effects of DCEO

17

on other earnings management variables are similar to the case for FFO variable.
Overall, we find a tendency that CEOs from the founding family play a positive role toimprove the earnings quality both on accrual-based earnings management and real activities
based earnings management. It means the family CEO is concerned with the reputation of
the firm as reliable in terms of disclosure effort leading at the same time to increased
socioemotional wealth.

The latter may mean that more shares that are held by founding

families, the less attention paid to stockholders outside the family.
6.3 Further Analysis of Costs of Earnings Management
We have confirmed in Tables 2 through 5 that family firms have a general tendency todecrease their reported earnings by utilizing both accruals based and real activities based
earning management strategies. These findings support our Hypothesis 1 and suggest thatfamily firms are more concerned with the reputation of investors. Also, we have to recall thefact that the magnitude of income decreasing by using accruals based strategies is much larger
than that by real activities based strategies. The reason why family firms utilize accruals
based strategies to a large extent to manage their earnings is worth exploring. One of thepossible reasons to explain such family firm earnings management behavior is the ease to
manage earnings, in other words, for family firms, potential cost to manage earnings by
accruals based strategies is lower than that of real activities based strategies. This prediction
leads to our Hypothesis 2.
In this subsection, we compare the relative cost of earnings management: accrual-based
versus activities based. Following Zang (2012) we use the following variables as surrogatesfor cost of earnings management for both cases.
18

We use the same variables as Zang sinceU.S. and Japanese GAAP and their disclosure regulations based on Sarbanes and Oxley typelaws are more similar to each other than to European countries with IFRS standards. That is,
we use a dummy variable for choosing a large auditing firm (big 4 in the Japanese case) ornot, the number of following analysts (Athanasakou et al., 2011), and the length of operating
cycle as cost for accrual-based earnings management. We use market shares (Harris, 1998),
the distance to default (Merton, 1974, and Gray et al., 2006) using the Black-Sholes-Merton
model for European options and measuring the distance to reach the default boundary(standard deviations divided by means of the geometric Brownian motions) at the end of one
year, and effective marginal tax rates (Graham, 1996 and Scholes et al., 2002) as cost for real
activities based earnings management. Volatility parameters of the option valuation model
was computed from annual financial data and the method to compute the effective tax rates
for Japanese accounting systems follows Kubota and Takehara (2007).
Table 6 reports the cost of earnings management classified by three types of family andnon-family firms.
TABLE 6 ABOUT HERE

The results for accrual-based earnings management reveal that the choice of auditors is
significantly less for all types of family firms at 10% level, the number of analysts issignificantly less for Type 1 and Type 2 firms at 1% level, and the trading cycle issignificantly less for Type 2 firms at 10% level, but longer for Type 1 and Type 3 firms though
not significant. Accordingly, we conclude earnings management will be easier for family
firms from these three cost comparisons, except for a shorter trading cycle for Type 2 firms.
Note for the number of analyst variables, Type 3 firms attract more analysts on average19

(2.645) versus non-family firms (2.537) although the difference is not significant. Moreover,Type 3 and Type 1 firms show a longer operating cycle than non-family firms, but again it is
not significant.
For real activities based earnings management, market shares (MShare) are significantly
lower for all types of family firms, and for Type 2 it is the lowest with 1.485 percent while
the market share for Type 3 firms is 5.018 percent, comparable to 6.821 percent of non-family
firms, though the difference is not significant. It means the cost of earnings management ishigher for family firms. For the distance to default (DD) threshold point, all family firms
have a significantly smaller likelihood to default.6 The largest is Type 1 firms with 3.768.
Type 2 and Type 3 firms show distances of 3.499 and 3.510, respectively, which issignificantly larger than 3.318 for non-family firms. We find family firms are safer and forthat reason, if they want, the cost for upward earnings management will be less. Type 2 andType 3 firms have higher effective tax rates and it shows that the cost of earnings management
is higher. Type 3 firms have lower effective marginal tax rates (Graham, 1996) with 29.8%
versus 30.4% for non-family firms. Accordingly, except for distance to default (DD), the costof real activities based earnings management for family firms seems to be larger than for
non-family firms.
Hence, for Hypothesis 2 we conclude that family firms choose accrual-based earnings
management over real activities based earnings management. We will re-confirm this point
as a robustness check in the following two tables.
6

In Table 2 we have shown that family firms are less leveraged. However, this is only one factor, and we also
have to look at variability of operating profit. One of the co-authors of this paper has already confirmed that thevariability of profit for family firms is lower than non-family firms. The result is available upon request fromthe authors.

20

Table 7 reports Pearson and Spearman rank correlation numbers between the degree of
earnings management and shares owned by the founding family in the left subpanel. The
difference in earnings management depending on whether the CEO is from the founding
family (DCEO=1) or not (DCEO=0) is in the right subpanel with corresponding p-values.

TABLE 7 ABOUT HERE
From the left subpanel we find that the percentage of shares owned by the family are
negatively correlated with costs related to the choice of auditor (-0.024) and the number ofanalyst (-0.154) variables in the direction of reducing the cost of accrual-based earnings
management. The results for trading cycles are mixed; with the Pearson rank it is positive
with 0.009, but negative and significant for Spearman with -0.041. For the CEO dummy,
again for the auditor choice and number of analyst variables, CEOs from the founding family
tend to reduce earnings management cost (0.752 firms vs. 0.773 firms, and 1.591 analysts vs.
2.443 analysts, respectively).
In the lower subpanel, the percentage of shares owned by the family are negatively
correlated with market shares at -0.223, and positively correlated with distance to default andeffective marginal tax rates at 0.067 and 0.082, respectively. The results for market share andmarginal tax rates imply the costs are higher as more shares are owned by families. However,
the observation for distance to default reveals that family firms in which a large proportionof stock is held by founding family are more risk averse to avoid bankruptcy, which isconsistent with the view that a family seeks long-term sustainability and preservation ofsocioemotional wealth.

21

Table 8 reports the results from regression analysis as in equation (8) and logistic
regression model for the big 4 auditors (Audit4), in which dependant variables are in thiscase the costs of each earnings management method.

TABLE 8 ABOUT HERE

The results for accrual-based earnings management reveal that the choice of auditors withlogistic regression model is not significant, but DCEO tends to hamper the choice of big
auditors. When we consider the cost of earnings management as in Zang (2012), other results
for both FFO and DCEO variables demonstrate that these variables make the cost of accrualbased earnings costs less because coefficients for the number of analysts are negative at 0.040 and -0.216, respectively, and those for trading cycles are positive at 0.120 and 1.487,
although the coefficients for DCEO variable are not significant.
For real activities based earnings management, again except for distance to default, thecosts will be higher because the coefficients for both FFO and DCEO variables for market
shares are negative at -0.061 and -1.106 and those for effective marginal tax rates are positiveat 0.001 and 0.000, respectively.
In sum, from the analyses in this section we conclude that family firms in Japan choose
accrual-based earnings management (supporting Hypothesis 2) over real activities based
earnings management, when more shares are owned by the founding family with a family
CEO. Furthermore, family firms, in particular, in the case CEOs are not from the founding
family (Type 2), and tend to conduct larger earnings management (rejecting Hypothesis 1)
than non-family firms.
22

7. Conclusion
We investigated the degree of accrual-based earnings management and real activities
based earnings management using data of all family and non-family firms listed on the Tokyo
Stock Exchange from 2004 through 2011. A priori family firms are expected to have lower
agency cost because family shareholders and management will be more congruent inpursuing mutual firm goals. We also inferred that the founding family will pay attention to
the reputation of their firm and family in order to sustain socioemotional wealth. Thus, we
expect that the magnitude of income decrease will be larger for family than non-family firms.
With univariate analysis we find that the magnitude of income decrease by accruals based
strategies is larger for family than non-family firms, and real activities measures are also
lower for family than non-family firms. With cross section regressions, we find both of theshares owned by the founding family (FFO) and CEO dummy (DCEO) decrease abnormal
accruals. For the level of real activities based earnings management, we find family firm
related variables decrease the level of earnings management. Furthermore, when we
introduce various economic measures that are related to costs of earnings management, wefind family firms in Japan utilize more accrual-based earnings management than real
activities based earnings management by comparing cost differences. This is the first study
using Japanese data to investigate the level of accrual-based earnings management and real
activities based earnings management of three types of family firms and non-family firms.

23

Appendix

Sector Classification for Japan

Based on 33 industry classifications by the Tokyo Stock Exchange, we redefine seven sectors
following Kubota and Takehara (2007) for Japanese firms.

SectorIndustry
Fishery and Agriculture
Foods
Consumption Textiles and Apparels
Goods
Pharmaceutical
Electric Appliances
Other Products
MiningConstruction
Pulp and Paper
Chemicals
Oil and Coal Products
Rubber Products
Investment
Glass and Ceramics Products
Goods
Iron and Steel
Nonferrous Metals
Metal Products
MachineryTransportation Equipment
Precision Instruments

SectorServices

Financial

Industry
Communication
Wholesale Trade
Retail Trade
Services
Banks
Securities
Insurance
Other Financial BusinessLand Transportation

Transportation Marine Transportation
Air Transportation

Utility
Real Estate

24

Electric Power and Gas
Warehousing
Real EstateReferences:
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27

Table 1. Number of the Sample
Type 1, more than 10% shareholdings and CEO from family, Type 2, more than 10% shareholdings, but CEO
not from founding family, Type 3, less than 10% shareholdings, CEO from the founding family.
observation period is from 2004 through 2011.

Non Family

Type 1

Type 2Type 3

Total

2004

934

307

61

131

1433

2005

931

317

59

139

1446

2006

966

340

67

147

1520

2007

1044

382

85

165

1676

2008

1018

393

88

165

1664

2009

997

409

99

165

1670

2010

989

420

105

160

1674

2011

1010

426

104

152

1692

TSE First Section

821

209

73

154

1257

TSE Second Section

208

104

29

25

366

Other Exchanges

301

261

82

38

682

Consumption Goods

303

131

46

51

531

Investment Goods

603

145

51

105

904

Services

250

236

73

42

601

Transportion

62

13

4

10

89

Utility

20

1

0

1

22

Real Estate

55

22

5

6

88

57.85224.519

8.009

9.620

100.000%Family Firms

28

The

Table 2. Differences between Family Firms and Non-Family Firms
FFO: Percentage of shares held by the founding family, |ABNAC|: the absolute value of abnormal accruals,
Persistence: Persistency measure of earnings which is defined as first order autocorrelation of earnings,
EBEISD: Past 5 year S.D. of earnings before extraordinary items, Smoothness: Smoothness measure definedas S.D. of earnings to S.D. of cash-flows from operations, ABNCFO: Abnormal cash-flows from operations,
ABNCOGS: Abnormal cost of goods sold, ABNINV: Abnormal inventory, ABNPROD: Abnormal product,
ABNEXP: Abnormal R&D expenditures, lnTA: Natural logarithm of total asset, ROA: Past 5 year average
return on equity, LEV: Firm’s financial leverage defined as non-current liabilities to total asset, SLSG: Past 5
year growth rate of sales, LP: Labor productivity defined as value added per employee. ‘p-value’ immediateright of each type of family firms are the probability values from the Welch’s two-sample t-test which test thedifference of variables between family and non-family firms.

Non-FB

Type 1

p -value

Type 2

p -value

Type 3

p -value

FFO

0.569

31.4910.000

24.084

0.000

4.039

0.000

ABNAC

0.092

-0.1070.132-0.481

0.056

0.133

0.825

EBEISD

1.996

2.011

0.704

2.236

0.005

2.027

0.608

Smoothness

0.489

0.483

0.489

0.458

0.052

0.523

0.021

ABNCFO-0.001

0.003

0.003

0.002

0.259

-0.0030.348

ABNPROD

0.010-0.0180.000-0.008

0.001

0.009

0.841

ABNEXP-0.009

0.017

0.000

0.003

0.015

-0.007

0.553

lnTA

11.08010.1560.000

10.2110.000

11.172

0.019

ROA

1.430

1.715

0.031

1.414

0.953

1.626

0.278

LEV

18.32314.4140.000

12.5890.000

16.001

0.000

SLSG

1.045

1.017

0.207

1.104

0.496

1.010

0.115

LP

23.80816.2580.000

20.3970.057

19.3710.000

29

Table 3. Earnings Management versus Founding Family’s Ownership and CEO Positions
DCEO is a dummy variable which is equal to 1 if the CEO is from the founding family or at least one executive
who has a representative right of the firm from the founding family. Definitions of other firms’ earnings
management measures and control variables are the same as Table 2.

Correlation between FFO and Firm's
Characteristics
Pearsonp -value Spearman

p -value

Presence or Absence of CEO
from Founding Family
DCEO=1 DCEO=0p -value

ABNAC-0.0160.078-0.0080.383-0.038

0.048

0.472

EBEISD

0.029

0.001

0.067

0.000

2.016

2.015

0.977

Smoothness-0.005

0.608

0.017

0.049

0.494

0.486

0.346

ABNCFO

0.036

0.000

0.026

0.004

0.001

-0.0010.080

ABNPROD-0.1020.000-0.0750.000-0.010

0.008

0.000

ABNEXP

0.095

0.000

0.065

0.000

0.010

-0.008

0.000

lnTA

-0.3030.000-0.3220.000

10.45111.012

0.000

ROA

0.012

0.169

0.048

0.000

1.689

1.429

0.024

LEV

-0.1110.000-0.1850.000

14.87417.875

0.000

SLSG

-0.0050.548-0.006

0.532

1.015

1.050

0.103

LP

-0.0600.000-0.1550.000

17.16223.5420.000

30

Table 4. Five Portfolios Ranked by Percentage of Shares Held by Founding Families
FFO denotes percentage of shares held by the founding family. P1 is a portfolio of firms whose FFO is equal
or greater than 50%. P2 is a portfolio of firms whose FFO is less than 50% but equal to or greater than 1/3. P3
is a portfolio of firms whose FFO is less than 1/3 but equal to or greater than 20%. P4 is a portfolio of firms
whose FFO is less than 20% but equal to or greater than 10%. P5 is a portfolio of firms whose FFO is less than
10%. We test the difference of mean of variables between P1 and P5 by Welch’s two-sample t-test. Probability
values from t-tests are shown in the ‘p-value’ column.

P1#Firms

P2

P3

P4

P5

(P1-P5)p -value

395

986

1122

1159

9113

FFO

57.81241.45326.63314.4791.035

56.777

0.000

ABNAC

-0.317-0.013-0.314-0.131

0.098-0.4140.171

EBEISD

2.360

2.085

2.011

1.960

2.000

0.360

0.001

Smoothness

0.543

0.471

0.453

0.486

0.493

0.049

0.036

ABNCFO

0.001

0.005

0.006

-0.002-0.001

0.002

0.509

ABNPROD-0.017-0.034-0.018

0.000

0.009

-0.0260.002

ABNEXP

0.022

0.025

0.012

0.004

-0.008

0.030

0.001

lnTA

9.857

9.922

10.23310.41311.092-1.235

0.000

ROA

0.668

1.642

2.261

1.431

1.456

-0.7880.008

LEV

17.652

13.46013.78413.68018.011-0.359

0.660

SLSG

1.000

1.011

1.030

1.066

1.040

-0.0410.056

LP16.721

14.19419.89016.72623.212-6.4910.000

31

Table 5. Results from Regression Analysis
Definition of variables are the same as Tables 2 and 3 and p-values are computed with White heteroskedasticity
corrections.

Intercept

FFO

DCEO

ROA

LEV

SLSG

ABNAC

-0.274-0.004-0.058

0.121

0.007

0.004

Adjusted R-0.0030.021

p -value

0.100

0.357

0.618

0.000

0.075

0.687

0.002

EBEISD

2.215

0.002

-0.021-0.007

0.001

0.003

0.002

p -value

0.000

0.060

0.579

0.065

0.243

0.599

0.000

Smoothness

0.530

0.000

0.017

0.000

0.002

0.000

0.000

p -value

0.000

0.869

0.043

0.890

0.000

0.900

0.000

ABNCFO-0.0010.000-0.001

0.002

0.000

0.000

0.000

p -value

0.387

0.002

0.636

0.000

0.000

0.578

0.000

ABNPROD

0.003-0.001-0.003-0.002

0.000

0.000

0.000

p -value

0.481

0.000

0.193

0.000

0.000

0.839

0.000

ABNEXP

0.000

0.001

0.006

-0.001

0.000

0.000

0.000

p -value

0.934

0.000

0.006

0.001

0.704

0.823

0.364

32

LP

0.073
0.057
0.078
0.045
0.027

2

Table 6. Difference of the Cost of Earnings Management
Audit4: Big 4 Audit firm dummy variable, NEst: Number of Analysts who follow the firm, Cycle: Operation
cycle, MShare: Market share of the firm, DD: Distance to default, MTR: Marginal tax rate.

Non-FB

Type 1

p -value

Type 2

p -value

Type 3

p -value

Audit4

0.776

0.761

0.100

0.740

0.042

0.733

0.002

NEst

2.537

1.160

0.000

1.332

0.000

2.645

0.426

Cycle

55.53155.6080.960

51.1750.059

58.3070.350

MShare

6.821

1.613

0.000

1.485

0.000

5.018

0.000

DD

3.318

3.768

0.000

3.499

0.036

3.510

0.002

MTR

0.304

0.334

0.000

0.320

0.009

0.298

0.191

Table 7. Costs of Earnings Management, Founding Family’s Ownership, and CEO Position
Audit4: Big 4 Audit firm dummy variable, NEst: Number of Analysts who follow the firm, Cycle: Operation
cycle, MShare: Market share of the firm, DD: Distance to default, MTR: Marginal tax rate.

Correlation between FFO and Firm's
Characteristics
Pearsonp -value Spearman

p -value

Presence or Absence of CEO
from Founding Family
DCEO=1 DCEO=0p -value

Audit4-0.0240.007-0.051

0.000

0.752

0.773

0.012

NEst

-0.1540.000-0.152

0.000

1.591

2.443

0.000

Cycle

0.009

0.332

-0.0410.000

56.39155.191

0.404

MShare-0.2230.000-0.387

0.000

2.601

6.405

0.000

DD

0.067

0.000

0.058

0.000

3.693

3.332

0.000

MTR

0.082

0.000

0.075

0.000

0.324

0.305

0.000

33

Table 8. Further Results from Regression Analysis
Audit4: Big 4 Audit firm dummy variable, NEst: Number of Analysts who follow the firm, Cycle: Operation
cycle, MShare: Market share of the firm, DD: Distance to default, MTR: Marginal tax rate. The six independent
variables are the same with Table 5 and p-values are computed with White heteroskedasticity corrections. When
Audit4 is used as a dependent variable, we run a logistic regression and Nagelkerke’s pseudo R2 is reported in
the table.

Intercept

FFO

DCEO

ROA

LEV

SLSG

LP

Audit4

1.426

0.003

-0.075

0.026

0.000

0.001

Adjusted R
0.001
0.061

p -value

0.000

0.081

0.202

0.000

0.852

0.932

0.155

NEst

5.374

-0.040-0.216

0.102

0.034

-0.0360.011

p -value

0.000

0.000

0.178

0.000

0.000

0.010

0.000

Cycle

49.456

0.120

1.487

-0.567

0.127

0.030

-0.023

p -value

0.000

0.001

0.157

0.000

0.001

0.792

0.017

MShare3.544-0.061-1.106

0.096

0.090

0.056

0.023

p -value

0.000

0.000

0.000

0.000

0.000

0.400

0.000

DD

3.604

0.005

0.130

0.063

-0.032-0.0110.000

p -value

0.000

0.000

0.001

0.000

0.000

0.032

0.569

MTR

0.287

0.001

0.000

0.007

-0.002

0.000

0.000

p -value

0.000

0.000

0.968

0.000

0.000

0.603

0.645

34

0.110
0.133
0.142
0.333
0.145

2