Earnings Management toward Zero:Evidence from Japanese Private Colleges and Universities

M. Kuroki
Assistant Professor
Institute of Humanity and Social Science
Yokohama City University, Japan

ABSTRACT: Leone and Van Horn (2005) describe the existence of earnings management to adjust
discretionary accruals to meet a range just above zero in nonprofit hospitals since nonprofits haveloss-avoidance and income-decreasing incentives. The former incentive arises from the effect oflosses on a CEO’s reputation or to reduce the cost of debt, and the latter incentive arises fromretaining the hospitals' tax-exempt status, attracting donations, or receiving price concessions fromthird-party payers. In this study, I investigate whether managers manage earnings in nonprofit
organizations, specifically Japanese private colleges and universities (PC&Us). Japanese PC&Us
have specific discretionary capital expenditure items that allow PC&U managers to adjust earnings
more easily. I expect that earnings management in Japanese PC&Us exists to decrease income morethan was found by previous studies of nonprofit organizations because PC&Us manage these items
frequently and have different stakeholder incentives (i.e. students and government). I test 2,973
PC&Us from 2009 to 2013 by using an earnings distribution analysis based on Burgstahler andDichev (1997). I find evidence of earnings management toward zero to avoid loss, and strong
evidence of income decreasing decisions by PC&Us. These results suggest that Japanese PC&Us
have incentives to manage earnings toward zero, especially income-decreasing incentives, ascompared to previous studies.

JEL Classification numbers: M41; I22

Keywords: nonprofit organization, private college and university, zero-profit hypothesis,
income-decreasing choices, capital expenditure1. Introduction
Managing earnings holds as much importance for managers of hospitals and otherlarge, nonprofit organizations, as it does for managers of for-profit firms. Large
nonprofit organizations are answerable to many stakeholders and thus have complicatedincentives to manage earnings. In for-profit firms, managers are incentivized to avoid
earnings decreases and losses (Burgstahler and Dichev 1997; Degeorge, Patel, andZeckhauser 1999). This may be accomplished by various means including contracts
with executive compensation and debt or by increasing the stock price. Nonprofit
organizations not only have incentives to increase income and to avoid losing contracts,
but also have incentives to decrease income in order to achieve a tax-exempt status,
receive donations, and negotiate favorably with third-party payers. Additionally, sincenonprofit organizations do not have any incentive to increase stock price, they do not
avoid earnings decreases. Previous research suggests that nonprofit hospital CEOs
manage accruals and real accounting activities to meet a benchmark that is just aroundzero, and do not have any incentive to avoid earnings decreases (Leone and Van Horn
2005; Eldenburg, Gunny, Hee, and Soderstrom 2011).
While Leone and Van Horn (2005) and Eldenburg et al. (2011) support theirzero-profit hypothesis by focusing on nonprofit hospitals only, there are other nonprofit
organizations in large industries. In this study, I investigate whether managers manage
earnings toward zero in Japanese private colleges and universities (PC&Us), which
comprise a large nonprofit industry in Japan. I expect to discover different incentives
and stakeholders (i.e., students and government) as compared to nonprofit hospitals1.
I focus on Japanese PC&Us for two reasons. First, most PC&Us in Japan have
similar financial structures. The revenue source of PC&Us in the U.S. includes tuition
fees, investment management, donations, governmental grants, licenses, and otherprogram fees. In contrast, the revenue source of PC&Us in Japan depends highly ontuition fees and government grants only and hence, their main stakeholders can be
identified as students and the government. This feature of Japanese PC&Us differs fromthe U.S. hospitals’ context (i.e., CEO market, bondholders, regulators, donors, andthird-party payers) identified by Leone and Van Horn (2005) and makes it easier to test
incentives for earnings management.
Second, PC&Us in Japan have two specific profit indicators, earnings before capital
expenditure (Kizoku-Syushi) and earnings after capital expenditure (Syohi-Syushi), that
1

Managers of the PC&Us covered in this study are directors of the board of trustees. In most cases, they have thefinal responsibility to the board to increase profitability in order to sustain their organization.

1

are based on accounting standards. The earnings after capital expenditure (EACE) arecalculated by deducting discretionary capital expenditure (CE) items from the earnings
before capital expenditure (EBCE). These two profit indicators play different roles ineach stakeholder’s evaluation. The Japanese Government, Ministry of Education,
Culture, Sports, Science and Technology (MEXT) considers the EBCE to be anindicator of profitability and emphasizes its importance for the board of trustees orbondholders, similar to for-profit firms. This indicator is mainly dependent on thenumber of students either enrolled at the PC&U or preparing for examinations. Anylosses in the EBCE reported by a PC&U are further highlighted and publicized throughthe country by the press or media. Operating in an intensely competitive, student
acquisition environment, managers of PC&Us would want to avoid negative publicity
among students. Therefore, I expect managers of PC&Us have a strong incentive to
avoid losses in EBCE.
On the other hand, the EACE is an indicator of financial stability to maintain the
fixed assets necessary to educate students. Some stakeholders evaluate the EACE toallocate their resources. For example, the Promotion and Mutual Aid Corporation forPrivate Schools of Japan (PMAC), which was established as a special corporation by
MEXT, uses EACE to evaluate PC&Us when providing governmental grants. If PC&Us
have excess cumulative EACE, PMAC reduces governmental grants. For otherstakeholders, especially donors, can decide to reduce their resources if PC&U managers
report excess EACE. Therefore, I expect managers in PC&Us to make moreincome-decreasing decisions for the EACE than for the EBCE. In this way, it is possible
to test whether PC&U managers manage earnings differently based on different
stakeholder incentives with students and government.
For these reasons, the hypotheses in this study are as follows: 1) PC&U managers
manage EBCE to avoid loss, and 2) PC&U managers manage EACE to a range justaround zero by varying discretionary capital expenditure. By analyzing the earnings
distribution, based on Burgstahler and Dichev (1997), and Degeorge et al. (1999), I test
whether PC&U managers manage both EBCE and EACE toward zero. In addition, if
PC&U managers manage earnings toward zero, then I test whether these results change
depending on incentives from students, the government, and other stakeholders, basedon Beatty, Ke and Petroni (2002).
The results of these tests support my expectations. I find evidence of loss-avoidance
accounting choices for EBCE and income-decreasing accounting choices for EACE.
These results indicate the existence of earnings management toward zero for both the
EBCE and EACE through advances received, extraordinary gain or loss and CE.

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Furthermore, I find evidence that the higher the contractual costs, from students andgovernment, that a manager of a PC&U undertakes, the more earnings management
toward zero he/she conducts.
This study makes two contributions to literature and the understanding of accounting
choices. First, with this being the first study concerning PC&Us, this study contributes
to earnings management literature, especially as it provides additional tests and results
related to zero-profit hypothesis and income-decreasing accounting choices in the
nonprofit sector. These results provide evidence as to whether managers manage
earnings in Japanese PC&Us, which are different from the nonprofit hospitals covered
in previous research. While Leone and Van Horn (2005) and Eldenburg et al. (2011)
suggest that nonprofit managers in hospitals manage earnings through discretionary
accruals and real activities, they do not test other large nonprofit industries. The resultsof this study suggest that their hypothesis is applicable to other large nonprofit
industries as well.
Second, the results of this study suggest that PC&U managers manage earnings
differently if they have differing stakeholder incentives. Leone and Van Horn (2005)
insist that when nonprofit CEOs report earnings, they consider the contracts from theperspective of five stakeholders: the CEO, bondholders, regulators, donors, andthird-party payers. In the Japanese PC&U industry, there is no incentive for contracts
with third-party payers. Instead, there are more incentives for unique contracts withcurrent and prospective students, and with regulators, than in the U.S. nonprofit
hospitals.
The remainder of this paper is organized as follows. Section 2 summarizes the
incentives to manage earnings in Japanese PC&Us, and develops the research
hypotheses. Section 3 presents the research methodology based on previous studies.
Section 4 describes the sample selection procedure and reports the descriptive statistics.
Section 5 presents the empirical results for the zero-profit hypothesis and earnings
changes hypothesis. Section 6 concludes with a summary of the implications of thisstudy.

2. The incentives to manage earnings in Japanese PC&Us
2.1 The institutions and accounting standards of PC&Us in Japan
Japanese PC&Us are considered Incorporated Educational Institutions, which arecorporations formed for the purpose of establishing a private school pursuant to thePrivate Schools Act. According to this Act, private schools must ensure sound3

development and must maintain their educational capacities for medium- to long-term.
In addition, PC&U institutions are obliged to prepare an inventory of assets, balance
sheets, income and expenditure account statements, and business reports within twomonths from the end of every fiscal year. These financial statements are prepared incompliance with the Accounting Standards of Incorporated Educational Institutions,which were set by MEXT in 1971 when it started offering grants to PC&Us, and which
differ from the standards for calculating and reporting earnings of for-profit
institutions2.
The main purpose of these standards was to control and allocate government grants
based on reported financial statements. Even after decades since its establishment, thepurposes and contents of these standards have not been changed. As discussed in detailbelow, these standards set globally unique, discretionary accounting items.
The standards allow PC&Us to transfer capital expenditures from revenues after
calculating earnings, such that PC&Us have two earnings measures, the EBCE andEACE. They reduce EBCE using specific, discretionary accounting items related to thetransfer of capital funds. The first item consists of fixed capital assets (e.g., land,buildings, equipment fixtures, and books) that must be permanently maintained in orderto educate students, and that are managed through real activities to adjust educational
expenditures. The second and third items comprise reserve funds of future expenses byfacility plans and scholarship funds from donors respectively, both of which are
discretionary accounting adjustments. Figure 1 illustrates an example of a PC&U’s
financial statements. It also recommends EACE as the indicator of future financial
stability since capital expenditures contribute to the organizational sustainability to
educate students.
[Insert Figure 1 here]
According to formal documents and past historical research, MEXT established theseunique accounting standards in 1971 due to two reasons. First, PC&Us must maintaintheir educational capacities for medium- to long-term. Hence, it is desirable for thefinancial conditions in PC&Us to be reported by balancing EACE in the medium- tolong-term. Second, radical student movements arose at the time when these standards
were set, with activists vehemently insisting on lower tuition fees in PC&Us. Thesestandards enable easy negotiation of tuition fees with activists through their unique,2

Although earnings management is conducted by Incorporated Educational Institutions, these are referred to as
PC&Us in this study as I focus on the institutions that manage the PC&Us regulated by MEXT.

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income-decreasing accounting items that set them apart from for-profit standards.
2.2 The incentives to manage earnings toward zero in PC&U
Previous studies reveal that for-profit firm managers manage reported earnings to
avoid small losses, earnings decreases, and negative forecast errors (Burgstahler andDichev 1997; Degeorge et al. 1999) in order to realize the incentives to acquire bonuses,
avoid debt covenants, or increase stock price. They describe a histogram of pooled,cross-sectional distributions to find evidence of clear discontinuities at zero in the
distribution of earnings levels, earnings changes, and forecast errors. Burgstahler andDichev (1997) explore how for-profit managers avoid earnings decreases and losses andfind evidence that both operating cash flow and changes in working capital have beenused to increase earnings.
More recent studies focus on earnings management toward zero in the nonprofit
sector through discretionary accruals and real activities (Hoerger 1991; Leone and Van
Horn 2005; Eldenburg et al. 2011). Leone and Van Horn (2005), an important
contribution to literature in this area, finds evidence that hospital managers manage theirearnings to avoid losses (loss-avoidance hypothesis) because of the incentives forcontracts with the market for CEOs and bondholders, similar to for-profit firms. They
explain that reporting losses imposes a higher cost of debt on nonprofit CEOs, which
increases the likelihood that the CEO is terminated. Therefore, nonprofit CEOs manage
earnings to avoid losses.
In addition, they find evidence that hospital managers use income-decreasing
accounting items to manage the profit toward zero (zero-profit hypothesis) because of
the incentives for contracts with regulators, donors, and third-party payers. Reporting
high profits imposes costs on nonprofit CEOs from regulators and donors because it
implies a failure to allocate available resources towards philanthropic objectives. The
zero-profit evidence suggests the different role of earnings between for-profit firms andnonprofit organizations3.
Similar to the nonprofit hospitals studied by Leone and Van Horn (2005), PC&U
managers consider the contracts with stakeholders toward earnings subject to zero profit
constraint (Frank and Salkever 1994) and manage earnings toward zero4. However, I
3

Leone and Van Horn (2005) is based on the study of Hoerger (1991), which finds that managers in nonprofit
hospitals minimize the variance in reported earnings to achieve a target level of earnings within budget constraints.
They examine whether discretionary accruals are positive (negative) when pre-managed earnings are negative(positive) according to the zero-profit hypothesis using a model based on Jones (1991).
4 Managers in PC&Us are presidents of the board of trustees, presidents of the schools, or executive officers. In mostcases, they are one of the members of the board of trustees and are responsible to the board for increasing profitability
to sustain their organization.

5

expect that PC&U managers have different stakeholders and incentives to manage
earnings compared to nonprofit hospitals. In this study, I summarize the stakeholders
and incentives in the order of stakeholders’ importance (i.e., (a) students and theirparents, (b) government, and (c) other stakeholders) to influence reporting of profits orlosses in both EBCE and EACE.
(a) Students and their parents
With the recent decline in the number of children in Japan, Japanese PC&Us compete
intensively for student enrollment. Salamon and Anheier (1996) indicate that 60% of
nonprofit revenue in Japan comes from private fees and charges, the highest of any
country they examined, and for the most part, this comprises tuition receipts for PC&Us.
In the education industry, close to 90% of the income of this important element of theJapanese nonprofit sector takes this form (94). In fact, based on A PMAC Research
Report of PC&U Financial Conditions in 2014, the revenue source in Japanese PC&Us
significantly depends on tuition fees, which comprise approximately 76% of their total
revenue. Based on this revenue ratio, current students or students preparing for
examinations, and their parents, are the most important stakeholders for Japanese
PC&Us.
However, the total number of students entered at Japanese PC&Us has decreased
from about 800,000 in 1993 to 670,000 in 2014, and will continue to decreasesignificantly in the future. In this competitive environment, PC&U managers areunwilling to disclose negative information, especially related to financial distress inproviding educational services, to current and prospective students. Recently, media andpress (such as Daily Diamond, Daily Toyokeizai, and Nikkei-Business) have disclosed
the list of PC&Us that have reported losses in EBCE each year. In addition, empiricalresults of Japanese PC&Us show that once current or prospective students of a PC&U
and their parents know of the negative financial EBCE conditions of that PC&U, they
dis-enroll or discontinue taking the examination (Kuroki 2015). Therefore, the cost ofreporting losses in EBCE is an increased likelihood of reducing current and future
enrollment.
(b) Government
In the U.S., the Internal Revenue Code (IRC) monitors nonprofit hospitals’
profitability to assess whether they should maintain their tax-exempt status. Whenearnings increase, regulatory costs increase from the threat of the divested tax-exempt
status (Leone and Van Horn 2005).

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In the case of Japanese PC&Us, however, MEXT monitors PC&Us’ profitability in
EBCE to assess whether they could continue to provide educational services in the
future. For example, if PC&U managers report losses for two or three years in a row, the
MEXT investigation commissioner steps forward to examine the cause for these losses,
following which PC&U managers receive orders to improve their financial condition.
The cost of reporting losses in EBCE is, therefore, an increased likelihood of being
audited by MEXT5.
In addition, PMAC provides subsidies for PC&U operating costs. These subsidies
formed approximately 13% of the total revenue of PC&Us in 2014 and were determinedbased on an evaluation of the PC&U’s surpluses of cumulative EACE. If a PC&U haslarge surpluses of cumulative EACE, PMAC decreases the subsidies for operating costs.
Japanese PC&U managers manage the EACE to decrease income because the cost ofreporting a high EACE profit is a reduction in subsidies.
(c) Other stakeholders
Leone and Van Horn (2005) and other literature highlight other stakeholders’influence on PC&U managers’ accounting choices. In this study, I consider the effectsof the following three stakeholders: board of trustees, bondholders, and donors.
First, profitability serves as a measure of the manager’s ability to sustain a hospital.
In Japanese PC&Us, the MEXT suggests that EBCE is an indicator of profitability.
Hence, boards of trustees in Japan pay attention to the EBCE. However, based on survey
results conducted in 2012 by the Research Institution in Association of Private
Universities of Japan, directors on the board of trustees of PC&Us retain their job for
13.4 years on average, and appear free from job termination pressures. Hence reporting
losses in EBCE appears to only weakly increase the likelihood that the manager isterminated, as compared to previous studies.
Second, nonprofit hospital managers have the incentive to manage earnings toward
zero to minimize earnings variance, similar to for-profit firms as suggested by Trueman
and Titman (1988). Most Japanese PC&Us also raise debt. The PC&U bondholders pay
attention to profitability as a measure of the PC&U’s capacity to repay this debt. PC&U
managers have an incentive to reduce the cost of debt by managing the EBCE throughloss-avoidance activities, similar to for-profit firms, as reporting losses in the EBCE
increases the cost of debt.
Third, reported earnings influence donors’ decisions. If nonprofit organizations report
However, MEXT does not focus on the large excess EBCE. Thus, I expect that PC&U managers do nothave incentives for income-decreasing choices in EBCE.
57

high earnings, donors are less likely to make donations since the organization does notappear to be a “needy charity.” Therefore, donors view the presence of profits in a
nonprofit organization as evidence that the philanthropic goal has either been met or is
not being pursued appropriately. Previous studies suggest that donations compriseapproximately 2% to 3% of nonprofit revenue (Okten and Weisbrod 2000; Leone and
Van Horn 2005). This ratio also applies to Japanese PC&Us, with A PMAC Research
Report of PC&U Financial Conditions in 2014 indicating that revenues from donors
comprise approximately 2% of total PC&U revenue. Donors make decisions in view of
the two indicators, EBCE and EACE, since they are interested in both the profitability
and financial stability of PC&Us. Japanese PC&U managers manage EBCE and EACE
to decrease income or increase expenditures.
2.3 Hypothesis development
In summary, stakeholders are interested in the financial conditions of PC&Us, andthere are costs to reporting EBCE and EACE. Based on Leone and Van Horn (2005) andEldenberg et al. (2011), I hypothesize that PC&U managers minimize reporting costs bymaking discretionary accruals that move reported profits toward zero6.
Zero-profit hypothesis. When the EBCE and EACE are below (above) zero, PC&U
managers make loss-avoidance (income-decreasing) accruals to achieve profits closer
to just above zero.
The zero-profit hypothesis, therefore, consists of two working hypotheses, which are
the loss-avoidance hypothesis and the income-decreasing hypothesis. These working
hypotheses are related to managers’ incentives to reduce the cost of reporting profits orlosses. Figure 2 summarizes managers’ incentives to manage both the EBCE and EACE
in PC&Us.
[Insert Figure 2 here]
First, reporting a small loss in the EBCE has negative effects including reduced
current and future enrollment, increased government audit, and higher cost of debt.
Based on the Accounting Standards, PC&U managers are restricted in the managementof EBCE as, for instance, they do not use accounts receivable or account reserves. They
Eldenburg et al. (2011) set the benchmark of earnings and tested whether managers will decrease(increase) real spending, when nonprofit organizations’ performance is likely to be below (above)
benchmark. I have also focused on defining the benchmark for earnings in this research.
68can only use advances received and extraordinary gain or loss to manage earnings in
EBCE. Therefore, I expect the existence of loss-avoidance decisions in EBCE using
mainly these two measures.
Hypothesis 1a (H1a). The distribution of the EBCE surrounding zero will be
non-normal just below zero.
Second, it is costly to report a high EACE because a high EACE decreases subsidies
from the PMAC and deters donors. Added to this, MEXT recommends that the financial
conditions in PC&Us are desirable when they report balanced EACE in the medium- tolong-term. When EBCE is higher than expected, managers transfer more discretionary
capital expenditures to capital funds in order to manage EACE toward zero. Therefore, Ialso expect that Japanese PC&Us make more income-decreasing choices toward zerothan found in previous studies of nonprofit organizations, since they can easily manage
these items.
Hypothesis 1b (H1b). The distribution of the EACE surrounding zero will beconcentrated to use discretionary capital expenditures.
Assuming H1a and H1b are supported, I test whether these results change depending
on incentives from the main stakeholders, namely students and government. I expectthat the PC&Us with higher dependence on tuition fees as a revenue source, have more
incentive to avoid a loss in EBCE as any reduction in current and future enrollment
directly affects their financial condition. In addition, I expect that PC&Us that arehighly likely of being audited by MEXT have more incentive to avoid a loss in EBCE
thereby reducing the MEXT audit likelihood.
Hypothesis 2a (H2a). PC&Us with more dependence on tuition fees, tend to reportslightly positive earnings in EBCE.
Hypothesis 2b (H2b). PC&Us with greater incentive to avoid MEXT audit, tend toreport slightly positive earnings in EBCE.
As mentioned earlier, if a PC&U has a large number of calculated surpluses ofcumulative EACE, PMAC decreases the subsidies for operating costs. Therefore, PC&U
managers avoid a reduction in governmental grants through earnings management
toward zero using CE.

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Hypothesis 2c (H2c). PC&Us with greater incentive to avoid a decrease ingovernmental grants, tend to report surrounding zero in EACE.
Finally, I set an earnings changes hypothesis similar to Leone and Van Horn (2005).
In for-profit firms, earnings decreases are avoided due to pressure from stock markets(Burgstahler and Dichev 1997; Degeorge et al. 1999). However, the stock market has noinfluence on nonprofit organizations. Hence, changes in reported earnings are relatively
less important than for for-profit firms. For this reason, I expect that PC&Us do not
avoid earnings decreasing decisions for both the EBCE and EACE.
Hypothesis 3 (H3). The distribution of both the EBCE and EACE changes surrounding
zero will be normal.

3. Research Design
3.1 Research Methods for testing H1a, H1b and H3
To test H1a and H1b related to whether Japanese firm managers engage in earnings
management toward zero to avoid reporting loss and high profits respectively, I adapt
the earnings distribution analysis based on Burgsthaler and Dichev (1997). This study
presents a histogram of the pooled, cross-sectional empirical distributions of scaled
earnings. In constructing the histogram, based on the previous studies (Degeorge et al.
1999; Beatty et al. 2002), I use a bin width of twice the inter-quartile range of thevariable, multiplied by the negative cube root of the sample size. The results of thisestimation indicate that the bin width is 0.003849 in EBCE level, 0.004231 in EACE
level, 0.002217 in EBCE change, and 0.003447 in EACE change7.
In this study, the earnings levels (changes) are reflected in cross-sectional
distributions in the form of unusually low frequencies of small losses (decreases) andunusually high frequencies of earnings level (changes) increases if PC&U managers
conduct loss-avoidance (decrease-avoidance) management on account of the EBCE.
Thus, this study supports H1a (H3). Similarly, the earnings are reflected incross-sectional distributions in the form of unusually low frequencies of higher EACE
than EBCE if PC&U managers conduct income-decreasing accounting choices. Thus,
7

I scale both the EBCE and EACE by the beginning-of-the–year total assets because earnings observations are drawn
from a broad range of PC&Us sizes. This analysis is criticized by Durtschi and Easton (2005: 2009) for its inherent
sample selection bias. Therefore, I alternate the deflating indicator with total revenue as a robustness check and theresults remained the same.

10

this study supports H1b.
To test the statistical significance of H1a, H1b, and H3, I construct a statistical test
based on Burgstahler and Dichev (1997). This test assumes that under no earnings
management, the cross-sectional distributions of EBCE, EACE, and their respective
changes are relatively smooth. The definition of smoothness is that the expected numberof observations in any given interval of the distribution is the average of the number ofobservations in its two immediately surrounding intervals. When I test for a
discontinuity at zero, I focus on one standardized difference and report thecorresponding standardized difference to the right of zero in parentheses8.
3.2 Research Methods for testing H2a, H2b, and H2c
To test how PC&U managers manage earnings in relation to hypotheses H2a, H2b,and H2c, I investigate whether the results for H1a and H1b change depending on
incentives from the two main stakeholders, namely, students and the government. I test
the effects of the student enrollment incentive and the government incentives on the
distribution of both EBCE and EACE levels. Based on Beatty et al. (2002), Burgstahler
et al. (2006), and Shuto and Iwasaki (2014), I establish two Probit regression models,
which denote the signs of small earnings levels (Equations (1) and (2)). Equation (1)tests the effects of student enrollment incentive and government incentive on the
distribution of EBCE, and Equation (2) tests the effect of government incentive on the
distribution of EACE.
𝐸𝐵𝐶𝐸𝑃𝑂𝑆𝑖,𝑡 = 𝛼0 + 𝛽1 𝐼𝑛𝑐𝑒𝑛𝑡𝑖𝑣𝑒_𝑆𝑡𝑢𝑑𝑒𝑛𝑡𝑖,𝑡+ 𝛽2 𝐼𝑛𝑐𝑒𝑛𝑡𝑖𝑣𝑒_𝐺𝑜𝑣𝑒𝑟𝑛𝑚𝑒𝑛𝑡𝑖,𝑡 + 𝛽3 𝐿𝑛𝐴𝑆𝑆𝐸𝑇𝑖,𝑡−1 + 𝛽4 ∆𝐴𝑆𝑆𝐸𝑇𝑖,𝑡+ 𝛽5 ∆𝐶𝐹𝑂𝑖,𝑡 + 𝛽6 𝑊𝐶𝐴𝑖,𝑡 + 𝛽7 𝐸𝑋𝑇𝑖,𝑡 + 𝛽8 𝐵𝑂𝑁𝐷𝑖,𝑡 + 𝛽9 𝐷𝑂𝑁𝑖,𝑡+ 𝛽10−13 𝑌𝐸𝐴𝑅 + 𝜀𝑡

(1)

𝐵𝑒𝑛𝑐ℎ𝑚𝑎𝑟𝑘𝑖,𝑡 = 𝛼0 + 𝛽1 𝐼𝑛𝑐𝑒𝑛𝑡𝑖𝑣𝑒_𝐺𝑜𝑣𝑒𝑟𝑛𝑚𝑒𝑛𝑡𝑖,𝑡 + 𝛽2 𝐿𝑛𝐴𝑆𝑆𝐸𝑇𝑖,𝑡−1 + 𝛽3 ∆𝐴𝑆𝑆𝐸𝑇𝑖,𝑡+ 𝛽4 ∆𝐶𝐹𝑂𝑖,𝑡 + 𝛽5 𝐶𝐸1𝑖,𝑡 + 𝛽6 𝐶𝐸2𝑖,𝑡 + 𝛽7 𝐶𝐸3𝑖,𝑡 + 𝛽8 𝐵𝑂𝑁𝐷𝑖,𝑡 + 𝛽9 𝐷𝑂𝑁𝑖,𝑡+ 𝛽10 𝑇𝑈𝐼𝑇𝐼𝑂𝑁𝑖,𝑡 + 𝛽11−14 𝑌𝐸𝐴𝑅 + 𝜀𝑡(2)where EBCEPOSi,t = an indicator variable that takes the value 1 if EBCE falls within theinterval between 0 (exclusive) and 0.00769 (inclusive), and 0 otherwise. Benchmark =Three Dependent Variables: ( 1) EACEPOSi,t = an indicator variable that takes the value
1 if EACE falls within the interval between 0 (exclusive) and 0.00846 (inclusive), and 0
8

Denoting the probability that an observation will fall into interval i by pi, the variance of the differences between
the observed and expected number of observations for interval i is approximately Npi (1-pi) + (1 / 4) N (pi-1 + pi+1)(1-pi-1-pi+1).

11otherwise; (2) EACENEGi,t = an indicator variable that takes the value 1 if EACE iswithin the interval between -0.00846 (exclusive) and 0 (inclusive), and 0 otherwise; and(3) JustZEROi,t = an indicator variable that takes the value 1 if EACE falls within theinterval between -0.00846 (exclusive) and 0.00846 (inclusive). Incentive_Studenti,t =educational fees, divided by total assets at the end of the previous year.
Incentive_Governmenti,t = an indicator variable that takes the value 1 if the number ofcalculated surpluses of cumulative EACE is more than 0, and 0 otherwise. ASSETi,t-1 =the natural log of total assets for PC&U i at the end of the previous year. ΔASSETi,t = thefirst difference in total assets, divided by total assets, at the end of the previous year.
ΔCFOi,t = the first difference in cash flows, divided by total assets, at the end of theprevious year. WCAi,t = the first difference in advances received, divided by total assets,
at the end of the previous year. EXTi,t = extraordinary items, divided by total assets, atthe end of the previous year. CEi,t = the number of transferring capital expenditures of
PC&U i in period t to report the results using the first fund to third fund. BONDi,t = theinterest cost, divided by total assets at the end of the previous year. DONi,t = donation,
divided by total assets at the end of the previous year; TUITIONi,t = educational fees,
divided by total assets at the end of the previous year, which is identical toIncentive_Studenti,t.
First, to grasp earnings management to avoid loss, I focus on reporting small profits
and losses using EBCEPOS to investigate the level of scaled EBCE within two
intervals: one between -0.00769 (inclusive) and 0 (exclusive), and the other between 0(inclusive) and 0.00769 (exclusive), which is an interval size twice the bin width, basedon Beatty et al. (2002).
Second, to grasp income-decreasing accounting choice toward zero using CE, I focus
on reporting only small profits and losses, noted as Benchmark in the EACE histogram.
Benchmark is composed of three intervals: EACEPOSi,t, EACENEGi,t, and JustZEROi,t.
EACEPOSi,t is an indicator variable that takes the value 1 if EACE falls within theinterval between 0 (exclusive) and 0.00846 (inclusive), and 0 otherwise. In addition, I
test reporting small losses (EACENEGi,t) and reporting small profits and losses(JustZEROi,t) in the EACE because I expect there are weak incentives to avoid losses in
EACE and MEXT recommends that the earnings in PC&Us are desirable to report zerofor medium- to long-term results in EACE.
In the regression model, the coefficient of Incentive measures the relationshipbetween the earnings benchmark and two incentives of earnings management: students
and the government. First, it is expected that PC&Us that have a higher level ofdependency on tuition have more incentive to avoid loss in EBCE because reducing

12current and future enrollment directly affects their financial condition. If the relationshipis consistent with the prediction of H2a, the coefficient of Incentive_Student should bepositive. Second, it is expected that the high likelihood of an audit by MEXT would
give PC&Us more incentive to avoid loss in EBCE. If the relationship is consistent withthe prediction of H2b, the coefficient of Incentive_Government should be positive.
Third, if PC&Us have a large number of calculated surpluses of cumulative EACE,PMAC decreases the operating cost subsidies. Therefore, if the relationship is consistent
with the prediction of H2c, the coefficient of Incentive_Government should be positive.
Similar to previous research models, I control for PC&Us size (ASSETi,t-1), growth(ΔASSETi,t), and profitability (ΔCFOi,t). Consistent with previous research results, if
larger PC&Us have higher growth, and are increasingly more profitable or more likely
to manage earnings, the coefficients of ASSETi,t-1, ΔASSETi,t, and ΔCFOi,t should bepositive. I also control for the three methods of discretionary accounting choices:
working capital accruals (WCAi,t), extraordinary items (EXTi,t), and capital expenditures(CEi,t). As these accruals are likely to be used to manage earnings, the coefficients ofthese three variables are expected to be positive. In addition, I set the extent tostrengthen from bondholders (BONDi,t) and donors (DONi,t). If the bondholders’ anddonors’ incentives promote the management of earnings toward zero, the coefficients ofthese three variables are expected to be positive.

4. Sample Selection and Descriptive Statistics
This study includes all available observations from the annual financial database of
PC&Us, Toyo Keizai, Inc. The earnings level (change) sample for the period 2009
through 2013 is presented in Table 1, which shows the descriptive statistics of theasset-scaled EBCE and EACE for the earnings distribution analysis. Panel A (B) shows
the EBCE (EACE) level and Panel C (D) shows the EBCE (EACE) change.
[Insert Table 1 here]
In Panels A and B, the average EBCE level for the sample period is 0.005 and theaverage EACE level is -0.016. This indicates that the EBCE level is generally more thanthe EACE level because of the transferring discretionary CE, which has an average of
0.021. However, in Panels C and D, the average EBCE change for the sample period is0.003, and the average EACE change is 0.003. This indicates that the EBCE and EACE
changes are very similar.

13

Table 2 summarizes the descriptive statistics of the variables for the regression
analysis to test H2a, H2b and H2c. Panel A suggests the statistics in Equation (1) to test
loss avoidance. The mean of EBCEPOSt is 0.588, which indicates that 58.8% ofobservations in our two interval sample report slight positive earnings in EBCE. Panel B
suggests the statistics in Equation (2) to test decreasing income. The mean of
EACEPOSt, EACENEGt, and JustZEROt are 0.134, 0.163, and 0.297, which indicatesthat 29.3% of observations in our full sample report slight profits or losses in EACE.
[Insert Table 2 here]
Table 3 suggests the correlation matrix among the variables used in Equations (1) and(2). In the correlation analyses, Incentive_Student and Incentive_Government are
positively associated with EBCEPOS, EACEPOS, EBCENEG, and JustZERO, which isconsistent with H2a, H2b, and H2c. There are no multicollinearity relationships among
the variables used in Equations (1) and (2).
[Insert Table 3 here]

5. Empirical Results
5.1 H1a and H1b results for the existence of earnings management
From the histograms used to test H1a and H1b, the earnings distribution in Japanese
PC&Us can be observed. Figure 3 compares the distributions of the scaled EBCE (PanelA) and EACE (Panel B). First, Panel A shows that there are discontinuities at zero in thescaled EBCE distribution in Japanese PC&Us, which suggests that Japanese PC&U
managers have incentive to avoid losses in EBCE, consistent with H1a.
Second, Panel B demonstrates that there are discontinuities at the right half of thehistogram, indicating more than zero in the distribution of the scaled EACE in Japanese
PC&Us, which suggests that Japanese PC&U managers have incentive to decrease
income in EBCE, consistent with H1b9.
[Insert Figure 3 here]
Table 4 summarizes the standardized differences and the earnings management ratio
9

The histograms are described with histogram intervals widths computed by the Degeorge et al. (1999) method.
Using interval sizes 0.5, 1, 2, and 3 times the bin width does not affect our results.

14

in the distributions. The standardized differences are used to test the significance of theirregularities near the zero EBCE, through a statistical test based on Burgstahler andDichev (1997). The standardized differences tests indicate that irregularities near zeroearnings are statistically significant under the 5% levels in only Panel A, which meansthat the PC&U managers manage the EBCE to avoid loss, consistent with H1a.
[Insert Table 4 here]
5.2 Results for H2a and H2b to test for incentives related to loss-avoidance
The results of Panels A and B in Figure 3 suggest that Japanese PC&U managers
avoid losses in the EBCE. The incentives related to loss-avoidance are tested, and Table
5 summarizes the Probit regression results of Equation (1) to examine H2a and H2b.
The regression result in the two interval sample shows that the signs of the coefficientof Incentive_Student and Incentive_Government are positive and significant at the 1%
level, as expected. The results mean that PC&Us with more dependence on tuition orwith greater incentive to avoid MEXT audit tend to report slightly positive earnings,
which are consistent with H2a and H2b10.
[Insert Table 5 here]
5.3 Results for H2c to test for incentives related to decreased income
Table 5 reports the results of the Probit model of Equation (2) as to whether thegovernment incentive is related to a decreased income. As predicted by H2c as thedecreased income hypothesis, Incentive_Government is positive and has less than 1%
significance for three intervals (EACEPOSt, EACENEGt, and JustZEROt). These results
are consistent with the prediction that PC&U managers with greater incentive to avoid
reduction of government grants tend to report surrounding zeros, which supports H2c.
[Insert Table 6 here]
5.4

H3 results for the existence of earnings management changes

To test the earnings changes hypothesis (H3), the distribution of the EBCE and EACE
changes was examined. As presented in Figure 7, the distribution is symmetric, centeredon zero, and has no obvious discontinuity below zero. Therefore, standardized
10

Moreover, the regression result in column (c) shows that the sign of the coefficient of WCAt and EXTt are positiveand significant at the 10% level. These results mean that PC&U managers use advances received and extraordinary
items to avoid losses.

15differences tests in Table 4 indicate that irregularities near zero earnings are notstatistically significant in Panels A and B in Figure 7. These results are consistent with
H2 and those of Leone and Van Horn (2005), and inconsistent with the for-profit firms
case presented by Burgstahler and Dichev (1997). This means that PC&U managers do
not manage earnings, similar to for-profit firms, to report earnings growth.
[Insert Figure 4 here]

6. Conclusion
In this study, I investigate whether Japanese PC&U managers manage earnings to
avoid losses and decrease income. While Leone and Van Horn (2005) and Eldenburg etal. (2011) investigate U.S. hospitals, it is important to determine other organizations’accounting practices in the nonprofit sector. Japanese PC&U managers have different
incentives for earnings management compared to U.S. hospitals, and can use the uniqueaccount items of discretionary capital expenditures. I focus on this accounting practicein Japanese PC&Us, and test the existence and incentives of earnings management
through earnings distribution analysis in line with Burgstahler and Dichev (1997).
First, I find evidence that the distribution of the EBCE surrounding zero is
non-normal just below zero. I also find evidence that PC&Us with more dependence ontuition, or with greater incentive to avoid a MEXT audit, tend to report slightly positive
earnings. This means that PC&U managers have incentives to avoid losses with
contracts with not only current and prospective students, but also the government.
Second, I find that the distribution of the EACE in the right half of the histogram is
non-normal and decreasing. In addition, I also find evidence that PC&U managers withgreater incentive to avoid government grant reduction tend to report a surrounding zero.
This means that PC&U managers have incentives to decrease income from the Japanese
government toward zero in the EACE. Finally, I find that not avoiding earnings
decreasing changes is consistent with the findings of Leone and Van Horn (2005) due tothe lack of stock market influences on nonprofit organizations.
These findings have implications for stakeholders, and especially for the regulators ofaccounting standards in the nonprofit sector. Although regulators considered amending
the Accounting Standards for Incorporated School Institutions and focused on the roleof discretionary capital expenditures for managers and financial statement users, they
did not have evidence of earnings management in PC&Us using this expenditure. The
evidence in this study suggests that if the managers of nonprofit organizations use more

16

discretionary account items and have specific incentives, they could improve their
management of earnings. This signifies that the accounting standards for the nonprofit
sector are important for stakeholders, and future research should examine therelationships between each incentive and the extent of earnings management.

17

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20

Table 1. Descriptive statistics of the variables for Regression Analysis
Panel A EBCE levels
n
2009
583
2010
622
2011
597
2012
585
2013
586
合計
2,973
Panel B EACE levels
n
2009
583
2010
622
2011
597
2012
585
2013
586
合計
2,973
Panel C EBCE changes
n
2009
583
2010
622
2011
597
2012
585
2013
586
合計
2,973
Panel D EACE changes
n
2009
583
2010
622
2011
597
2012
585
2013
586
合計
2,973

mean.
0.003
0.003
0.004
0.007
0.008
0.005

sd.
0.027
0.027
0.028
0.025
0.025
0.027

Q1
-0.010-0.012-0.012-0.006-0.005-0.009

med.
0.004
0.005
0.005
0.007
0.007
0.006

Q3
0.019
0.018
0.018
0.019
0.022
0.019

mean.
-0.019-0.019-0.017-0.014-0.014-0.016

sd.
0.030
0.030
0.029
0.027
0.027
0.029

Q1
-0.031-0.032-0.030-0.027-0.026-0.030med.
-0.014-0.015-0.012-0.010-0.010-0.012Q3-0.001
0.000
0.001
0.002
0.002
0.001

mean.
0.007
0.001
0.002
0.004
0.002
0.003

sd.
0.033
0.027
0.030
0.024
0.022
0.027

Q1
-0.005-0.007-0.009-0.004-0.006-0.006

med.
0.002
0.000
0.000
0.002
0.001
0.001

Q3
0.012
0.009
0.009
0.011
0.009
0.010

mean.
0.006
0.001
0.003
0.003
0.001
0.003

sd.
0.039
0.036
0.035
0.031
0.030
0.034

Q1
-0.009-0.011-0.011-0.008-0.011-0.010

med.
0.002
0.001
0.002
0.002
0.001
0.002

Q3
0.017
0.013
0.015
0.015
0.012
0.015

Note. The EBCE (EACE) is earnings before (after) capital expenditures scaled by the total assets at the end of theprevious year.

21Table 2. Descriptive statistics of the variables for Equation (1) and (2)Panel A: Test variable for Equation (1)VariableN
mean
EBCEPOSt
844
0.588
Incentive_Student
844
0.131
Incentive_Government
844
0.418
ASSETt-1
844
9.983
ΔASSETt
844-0.002
ΔCFt
844
0.000
WCAt
844
-0.006EXTt
844-0.002
BONDt
844
0.001
DONt
844
0.002
Panel A: Test variable for Equation (2)Variable
N
mean
EACEPOSt
2,973
0.134
2,973
0.163
EACENEGt
2,973
0.297
JustZEROt
Incentive_Government
2,973
0.396
ASSETt-1
2,973
9.944
ΔASSETt
2,973
0.004
ΔCFt
2,973
0.002
CE1t
2,973
0.016
CE2t
2,973
0.000
CE3t
2,973
0.001
BONDt
2,973
0.001
DONt
2,973
0.003
TUITIONt
2,973
0.141

sd
0.493
0.050
0.494
1.048
0.019
0.022
0.017
0.005
0.001
0.005

min
0.000
0.022
0.000
7.345
-0.092-0.079-0.088-0.044
0.000
0.000

p25
0.000
0.096
0.000
9.287
-0.010-0.010-0.005-0.002
0.000
0.000

p50
1.000
0.130
0.000
9.945
-0.003
0.001
0.000
0.000
0.000
0.001

p75
1.000
0.160
1.000
10.719
0.004
0.011
0.001
0.000
0.001
0.002

max
1.000
0.364
1.000
12.711
0.155
0.090
0.014
0.020
0.008
0.044

sd
0.340
0.370
0.457
0.489
1.136
0.034
0.026
0.025
0.010
0.006
0.001
0.006
0.060

min
0.000
0.000
0.000
0.000
7.345
-0.092-0.079-0.072-0.052
0.000
0.000
0.000
0.022

p25
0.000
0.000
0.000
0.000
9.165
-0.014-0.010
0.003
0.000
0.000
0.000
0.000
0.101

p50
0.000
0.000
0.000
0.000
9.891
0.003
0.002
0.011
0.000
0.000
0.000
0.001
0.138

p75
0.000
0.000
1.000
1.000
10.715
0.018
0.014
0.024
0.000
0.000
0.001
0.002
0.177

max
1.000
1.000
1.000
1.000
12.711
0.155
0.090
0.121
0.040
0.046
0.008
0.044
0.364

Note. All variables winsorized by year at the extreme 1% and 99%. EBCEPOSi,t = an indicator variable that takes thevalue 1 if EBCE in the interval between 0 (exclusive) and 0.00769 (inclusive), and 0 otherwise; Benchmark = Three
Dependent Variables ( 1) EACEPOSi,t = an indicator variable that takes the value 1 if EACE in the interval between 0(exclusive) and 0.00846 (inclusive), and 0 otherwise; 2) EACENEGi,t = an indicator variable that takes the value 1 if
EACE in the interval between -0.00846 (exclusive) and 0 (inclusive), and 0 otherwise; 3) JustZEROi,t = an indicatorvariable that takes the value 1 if EACE in the interval between -0.00846 (exclusive) and 0.00846 (inclusive));
Incentive_Studenti,t = educational fees, divided by total assets at the end of the previous year; Incentive_Governmenti,t= an indicator variable that takes the value 1 if the number of calculated surpluses of cumulative EACE is more than 0,
and 0 otherwise; ASSETi,t-1 = the natural log of total assets for PC&U i at the end of the previous year; ΔASSETi,t =first difference in total assets, divided by total assets at the end of the previous year; ΔCFOi,t = first difference in cash
flows, divided by total assets at the end of the previous year; WCAi,t = first difference in advances received, divided
by total assets at the end of the previous year; EXTi,t = extraordinary items, divided by total assets at the end of theprevious year; CEi,t = the number of transferring capital expenditures of PC&U i in period t to report the results using
the first fund to third fund; BONDi,t = interest cost, divided by total assets at the end of the previous year; DONi,t =donation, divided by total assets at the end of the previous year; TUITIONi,t = educational fees, divided by total assets
at the end of the previous year, which is identical with Incentive_Studenti,t.

22

Table 3. Correlations matrix among the variables for Equation (1) and (2)Panel A: Test variable for Equation (1) (n=844)
(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(1)

EBCEPOSt

1.000

0.095

0.032

0.178

0.339

0.065

0.041

-0.031

0.025

0.051

(2)

Incentive_Student

0.100

1.000

-0.254-0.171-0.065-0.0170.007-0.096

0.418

0.114

(3)

Incentive_Government

0.032-0.275

1.000

0.061

0.151

-0.011-0.4340.002-0.237-0.449(4)

ASSETt-1

0.171-0.189

0.045

1.000

0.195

-0.058-0.008-0.312-0.0210.082(5)ΔASSETt

0.216

0.065

0.059

0.094

1.000

0.180

-0.205-0.076-0.272-0.023

(6)

ΔCFt

0.062

0.011

-0.013-0.086

0.180

1.000

-0.1200.007-0.037-0.073

(7)

WCAt

0.047

-0.165-0.4920.054-0.063-0.071

1.000

0.060

-0.012

0.452

(8)

EXTt

0.023

-0.060-0.024-0.202-0.021-0.003

0.050

1.000

-0.074-0.043(9)

BONDt-0.0010.307-0.151-0.103-0.101-0.022-0.111-0.010

1.000

0.101

(10)

DONt

-0.028-0.036-0.1700.054-0.017-0.0080.183-0.016

0.023

1.000

Panel B: Test variable for Equation (2) (n=2,973)
(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(1)

EACEPOSt

1.000-0.174

0.604

0.044

0.040

0.191

0.132

-0.080

0.027

0.040

-0.047

0.005

0.030

(2)

EACENEGt-0.174

1.000

0.680

0.081

0.085

0.065

0.078

-0.053-0.030-0.004-0.031

0.047-0.024(3)

JustZEROt

0.604

0.680

1.000

0.099

0.098

0.195

0.162

-0.103-0.0040.026-0.060

0.042

0.003

(4)

Incentive

0.044

0.081

0.099

1.000

0.090

0.093

0.009

-0.0200.052-0.415-0.207-0.465-0.166(5)

ASSETt-1

0.033

0.083

0.092

0.070

1.000

0.219

-0.028

0.138

0.010

0.011

0.020

0.109

-0.196(6)ΔASSETt

0.124

0.046

0.130

0.058

0.132

1.000

0.311

0.328

0.084

-0.124-0.058

0.104

0.237

(7)

ΔCFt

0.093

0.047

0.107

0.001

-0.058

0.301

1.000

-0.085-0.038-0.1230.018-0.040

0.124

(8)

CE1t

-0.081-0.050-0.101

0.011

0.098

0.342

-0.1441.000-0.184-0.075

0.259

0.109

0.267

(9)

CE2t

-0.004-0.028-0.0260.016-0.0220.049-0.043-0.267

1.000

0.027

-0.058

0.030

0.012

(10)

CE3t

0.035

-0.0130.016-0.4990.068-0.095-0.099-0.098

0.044

1.000

-0.0370.422-0.047

(11)

BONDt

-0.060-0.065-0.097-0.134-0.086-0.034

0.034

0.097

-0.020-0.099

1.000

0.103

0.296

(12)

DONt

-0.026

0.046

0.018

-0.174-0.0190.088-0.018

0.094

0.008

0.177

0.071

1.000

0.064

(13)

TUITIONt

0.027-0.034-0.008-0.160-0.241

0.243

0.143

0.182

0.037

-0.1790.196-0.0401.000

Note. All variables winsorized by year at the extreme 1% and 99%. The upper-right-hand portion of the table reports
the Spearman rank-order correlations, and the lower-left-hand portion presents the Pearson correlations. EBCEPOSi,t= an indicator variable that takes the value 1 if EBCE in the interval between 0 (exclusive) and 0.00769 (inclusive),and 0 otherwise; Benchmark = Three Dependent Variables ( 1) EACEPOSi,t = an indicator variable that takes thevalue 1 if EACE in the interval between 0 (exclusive) and 0.00846 (inclusive), and 0 otherwise; 2) EACENEGi,t = anindicator variable that takes the value 1 if EACE in the interval between -0.00846 (exclusive) and 0 (inclusive), and 0
otherwise; 3) JustZEROi,t = an indicator variable that takes the value 1 if EACE in the interval between -0.00846(exclusive) and 0.00846 (inclusive)); Incentive_Studenti,t = educational fees, divided by total assets at the end of theprevious year; Incentive_Governmenti,t = an indicator variable that takes the value 1 if the number of calculated
surpluses of cumulative EACE is more than 0, and 0 otherwise; ASSETi,t-1 = the natural log of total assets for PC&U i
at the end of the previous year; ΔASSETi,t = first difference in total assets, divided by total assets at the end of theprevious year; ΔCFOi,t = first difference in cash flows, divided by total assets at the end of the previous year; WCAi,t= first difference in advances received, divided by total assets at the end of the previous year; EXTi,t = extraordinary
items, divided by total assets at the end of the previous year; CEi,t = the number of transferring capital expenditures of
PC&U i in period t to report the results using the first fund to third fund; BONDi,t = interest cost, divided by total
assets at the end of the previous year; DONi,t = donation, divided by total assets at the end of the previous year;
TUITIONi,t = educational fees, divided by total assets at the end of the previous year, which is identical with
Incentive_Studenti,t.

23

Table 4.

Standardized differences

Values for test intervals
Figure / Panel

Standardized difference to the left of 0
Standardized difference to the right of 0

Values for standardized differences ofremaining intervals
mean.

med.

min.

max.

Figure 3. Panel A-1.652 **0.570-0.1270.000-2.921

2.448

Figure 3. Panel B-0.7181.689 **

-0.184-0.109-2.251

2.031

Figure 4. Panel A

3.142 ***

-1.006-0.162-0.203-1.893

1.568

Figure 4. Panel B

0.000

2.952 ***

-0.1290.000-2.047

2.118*,**,*** Represent statistical significance at the 10%, 5%, and 1% levels, respectively.
Note. The standardized difference is the difference between the observed and expected number of firm-years in aninterval, standardized by the estimated standard deviation of the difference. The standardized difference for theinterval immediately to the left of 0 is expected to provide a more powerful test for earnings management to avoid aloss (decrease) in earnings.

24

Table 5. Probit analysis results for Equation (1)Independent
Variables
Constant

Predicted
Sign

Incentive_Student+

Incentive_Government+

ASSETt-1+

ΔASSETt

+

ΔCFt

+

WCAt

+

EXTt

+

BONDt

+

DONt

?

YEAR
N
pseudo R

Equation (1): Dependent variable = EBCEPOSt
(a)
(b)
(c)
-2.611 ***-2.245 ***-3.187 ***(-4.892)(-4.338)(-5.678)
0.259 **
0.436 ***
(2.165)(3.444)3.866 ***
4.982 ***
(3.819)(4.654)0.249 ***
0.216 ***
0.254 ***
(5.304)(4.703)(5.394)15.077 ***15.078 ***14.576 ***(5.417)(5.492)(5.239)3.083
2.987
3.676 *
(1.466)(1.424)(1.728)7.007
2.449
9.017 *
(1.406)(0.512)(1.791)
16.840 *13.98718.159 *(1.689)(1.418)(1.810)12.51864.116 **28.084(0.386)(2.010)(0.857)-10.882-11.785-9.860(-1.200)(-1.273)(-1.075)
YES
YES
YES
844
844
844
0.08110.07230.0916*,**,*** Represent statistical significance at the 10%, 5%, and 1% levels, respectively.
Note. All variables winsorized by year at the extreme 1% and 99%. EBCEPOSi,t = an indicator variable that takes thevalue 1 if EBCE in the interval between 0 (exclusive) and 0.00769 (inclusive), and 0 otherwise; Incentive_Studenti,t =educational fees, divided by total assets at the end of the previous year; Incentive_Governmenti,t = an indicatorvariable that takes the value 1 if the number of calculated surpluses of cumulative EACE is more than 0, and 0
otherwise; ASSETi,t-1 = the natural log of total assets for PC&U i at the end of the previous year; ΔASSETi,t = firstdifference in total assets, divided by total assets at the end of the previous year; ΔCFOi,t = first difference in cash
flows, divided by total assets at the end of the previous year; WCAi,t = first difference in advances received, divided
by total assets at the end of the previous year; EXTi,t = extraordinary items, divided by total assets at the end of theprevious year; BONDi,t = interest cost, divided by total assets at the end of the previous year; DONi,t = donation,
divided by total assets at the end of the previous year;25Table 6. Probit analysis results for Equation (2)Independent
Variables
Constant

Predicted
Sign

Incentive_Government+

ASSETt-1+

ΔASSETt

+

ΔCFt

+

CE1t

+

CE2t

+

CE3t

+

BONDt

?

DONt

?

TUITIONt?

YEAR
N
pseudo R

Equation (2): Dependent Variables = Benchmark
EACEPOSt
EACENEGt
JustZEROt-2.049 ***-2.281 ***-2.014 ***(-6.042)(-7.284)(-7.169)
0.239 ***
0.289 ***
0.373 ***
(3.051)(3.929)(5.586)
0.067 **
0.117 ***
0.122 ***
(2.347)(4.414)(5.152)
8.158 ***
2.381 **
6.730 ***
(7.450)(2.309)(7.042)1.719
1.688
2.186 **
(1.313)(1.380)(1.984)-12.465 ***-6.747 ***-12.331 ***(-7.708)(-4.673)(-9.121)-10.016 ***-8.701 ***-12.653 ***(-3.230)(-3.097)(-4.902)-18.078 ***-9.427 *-17.616 ***(-2.837)(-1.834)(-3.690)-54.842 **-56.823 **-69.095 ***(-2.078)(-2.401)(-3.304)-9.552
16.239 ***8.430 .
(-1.450)(3.409)(1.811)
0.885
0.344
0.793
(1.513)(0.634)(1.619)
Yes
Yes
Yes
2,973
2,973
2,973
0.089
0.052
0.115

*,**,*** Represent statistical significance at the 10%, 5%, and 1% levels, respectively.
Note. All variables winsorized by year at the extreme 1% and 99%. Benchmark = Three Dependent Variables ( 1)EACEPOSi,t = an indicator variable that takes the value 1 if EACE in the interval between 0 (exclusive) and 0.00846(inclusive), and 0 otherwise; 2) EACENEGi,t = an indicator variable that takes the value 1 if EACE in the interval
between -0.00846 (exclusive) and 0 (inclusive), and 0 otherwise; 3) JustZEROi,t = an indicator variable that takes thevalue 1 if EACE in the interval between -0.00846 (exclusive) and 0.00846 (inclusive)); Incentive_Governmenti,t = anindicator variable that takes the value 1 if the number of calculated surpluses of cumulative EACE is more than 0, and0 otherwise; ASSETi,t-1 = the natural log of total assets for PC&U i at the end of the previous year; ΔASSETi,t = firstdifference in total assets, divided by total assets at the end of the previous year; ΔCFOi,t = first difference in cash
flows, divided by total assets at the end of the previous year; CEi,t = the number of transferring capital expenditures of
PC&U i in period t to report the results using the first fund to third fund; BONDi,t = interest cost, divided by total
assets at the end of the previous year; DONi,t = donation, divided by total assets at the end of the previous year;
TUITIONi,t = educational fees, divided by total assets at the end of the previous year. t.

26

Figure 1. Example Japanese PC&U Balance Sheet and Income and Expense Statement

Figure 2. Incentives for earnings management in PC&Us

(a)

(b)

Stakeholders of nonprofit
organizations

Incentives for earnings
management

Main
indicator

Types ofearnings
management

Current or Prospective students

Avoid loss of students

EBCE

Loss-avoidance

Avoid governmental
audit

EBCE

Loss-avoidance

Avoid decreased
government grants

EACE

Income-Decreasing

Board of trustees

Decreased chance oftermination

EBCE

Loss-avoidance

Bondholders

Decreased bond costs

EBCE

Loss-avoidance

DonorsAvoid loss donations

EACE

Income-Decreasing

Government(MEXT and PMAC)(c)

Note. The EBCE (EACE) is earnings before (after) capital expenditures scaled by the total assets at the end of theprevious year.

27

Figure 3. The distribution of the scaled EBCE and EACE
Panel A: The distribution of EBCE (n=2,973)
300

250

200

150

100

50

0

-0.115-0.1155-0.0770-0.038500.03850.07700.1155

Panel B: The distribution of EACE (n=2,973)
300
250
200
150
100
50
0

-0.1269-0.0846-0.0423

00.04230.08460.1269Note. In Panel A (B), the distribution interval widths are 0.00385 (0.00423) calculated as in Degeorge et al. (1999).
The first interval to the right of 0 contains observations in the [0.00000, 0.00385 (0.00000, 0.00423)], the second
interval contains [0.00385, 0.00770 (0.00423, 0.00846)].

28

Figure 4. The distribution of the scaled EBCE and EACE changes
Panel A: The distribution of the EBCE changes (n=2,973)
300
250
200
150
100
50
0

-0.0666-0.0444-0.022200.02220.04440.0666

Panel B: The distribution of the EACE changes (n=2,973)
300
250
200
150
100
50
0

-0.1035-0.0690-0.034500.03450.06900.1035Note. In Panel A (B), the distribution interval widths are 0.00222 (0.00345) calculated as in Degeorge et al. (1999).
The first interval to the right of 0 contains observations in the [0.00000, 0.00222 (0.00000, 0.00345)], the second
interval contains [0.00222, 0.00444 (0.00345, 0.00690)].

29