Rev Account Stud (2010) 15:70–105
DOI 10.1007/s11142-008-9081-4
Propping through related party transactions
Ming Jian Æ T. J. Wong
Published online: 20 September 2008
Ó Springer Science+Business Media, LLC 2008
Abstract Based on a sample of Chinese listed firms from 1998 through 2002, this
paper documents that listed firms prop up earnings by using abnormal related sales
to their controlling owners. Such related sales propping is more prevalent among
state-owned firms and in regions with weaker economic institutions. We also find
that these abnormal related sales are not entirely accrual-based but can be cashbased as well, and they serve as a substitute rather than complement to accruals
management for meeting earnings targets. Since these abnormal related sales can be
cash-based, there is significant cash transfer via related lending from listed firms
back to controlling owners after the propping. However, no cash transfer via related
lending is found to be associated with accruals earnings management.
Keywords Propping Related party transactions Corporate governance Controlling shareholders
JEL Classifications
G3 M4
1 Introduction
Using a sample of listed firms in China, we study how institutions and firm
organizational structures in a transitional economy shape the ways firms use related
M. Jian (&)
Division of Accounting, Nanyang Business School, Nanyang Technological University, S3-B1b-75,
Nanyang Avenue, Singapore 639798, Singapore
e-mail: amjian@ntu.edu.sg
T. J. Wong
School of Accountancy, Faculty of Business Administration, The Chinese University of Hong Kong,
Shatin, Hong Kong
e-mail: tjwong@cuhk.edu.hk
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Propping through related party transactions
71
party transactions to manage earnings. This paper is motivated by recent research on
economic institutions and accounting properties (Ball et al. 2000; Bushman et al.
2004; Fan and Wong 2002; Leuz and Oberholzer-Gee 2006). In contrast to prior
studies that attempt to draw broad inferences from data across many countries, this
paper utilizes the intricate institutional structures of a particular country and the
variation of the institutions across provinces within the country. In addition, by
analyzing related party transactions as a form of earnings management, this paper
complements prior research such as Leuz et al. (2003) and DeFond et al. (2007),
who focus primarily on the relationship between accruals and earnings management.
Specifically, we address the following five questions in this paper. Do Chinese
firms use related sales to the controlling owner to prop up earnings?1 Are such sales
transactions entirely accrual-based or can they also be cash-based? Are they a
complement or substitute to discretionary accruals in earnings management? If cash
sales are involved, is this type of propping associated with subsequent cash transfers
back to the controlling owner? Do political and economic institutions shape firms’
related sales propping behavior?
China offers a natural setting for a study of the questions above for three reasons.
First, as in many other emerging markets, the capital, product, and labor markets in
China are underdeveloped. As a result, firms in these markets organize into groups
to form internal markets to lower transaction costs (Khanna and Palepu 2000).
Further, the restructuring process before the initial public offering of listed stateowned enterprises (hereafter SOEs) creates corporate groups with frequent related
party transactions between the listed subsidiaries and the parent companies, which
serve as the controlling owners.
Second, the bright-line rules for share issuance and delisting in China allow us to
identify clear evidence of earnings management incentives. Chinese securities
regulators have set two earnings targets that regulate firm listings. In particular, a
firm must report at least 0% return on equity (ROE) to maintain its listing status and
10% (6% after 2001) ROE to issue new shares. These targets create incentives for
controlling owners to assist listed firms in managing ROEs. We expect that more
income-inflating transactions are associated with reported ROEs that are only
slightly above the earnings targets.
Third, the weak legal and market institutions in China implies a higher frequency
of propping (Cheung et al. 2006) and increases the power of our tests. The
significant variation in the degree of market development and government
intervention in business activities across China’s thirty provinces, autonomous
regions and municipalities (excluding Hong Kong and Macau SAR) allows us to
examine the cross-sectional effects of legal and market institutions on propping.
Our evidence shows that Chinese listed firms use related sales to their controlling
owners to prop up earnings. We find that the levels of related sales and operating
profits from related sales are abnormally high when firms have incentives to manage
earnings. Moreover, using a method similar to that described in Bertrand et al.
1
We use ‘‘propping’’ to describe the scenario whereby a controlling owner uses its own resources to
manage the listed affiliate’s earnings. This is different from accruals management in which the controlling
owner or another affiliated firm is not involved in the listed firm’s earnings management.
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(2002), we document that when there are incentives to meet earnings targets, related
sales are used to dampen the effects of negative industry shocks on listed firms’
earnings.
Further analysis shows that discretionary related party accounts receivable is not
significantly positive when firms have incentives to meet earnings targets. This
suggests that the high abnormal related sales documented in our study are not purely
a result of abnormal accrued sales, which would generate significantly positive
discretionary related accounts receivable; rather, the abnormal related sales can also
be cash sales from the listed firms to their controlling owners. This explains why we
find that related sales propping is associated with subsequent cash transfers from the
listed firms back to the controlling owners, while accruals management is not
associated with any such cash transfers. We also find that propping through related
sales serves more as a substitute than as a complement to earnings management
through accruals. More specifically, the evidence shows that when the related sales
propping option is available or when it is actually used for earnings management,
firms engage in significantly less accruals earnings management in meeting earnings
targets. Finally, we find evidence that the level of propping through related party
transactions is significantly affected by the quality of institutions in the regions in
which the firms operate.
This paper contributes to the earnings management literature in a number of
ways. First, it identifies a unique form of profit manipulation (Healy and Wahlen
1999). Although quite a lot of anecdotal evidence suggests that firms do use related
party transactions to manage earnings, to date there has been very little large sample
research that investigates related party transactions as an earnings management
tool.2 Second, we show that cash-based related sales are likely to be a popular
method to manage earnings for firms that typically engage in related sales
transactions. Thus, future earnings management research that investigates earnings
management or accounting quality in emerging economies, where group firms and
related party transactions are prevalent, should not focus only on accruals but also
on cash-based transactions. Third, by using clearly defined transactions such as
related sales and clear earnings benchmarks, our evidence extends the work of
Roychowdhury (2006), who examines real earnings management. Fourth, this paper
makes use of a setting where corporate insiders manage earnings to meet clear
earnings targets. However, the opportunistic incentives arise not from compensation
as in Healy (1985) but from capital market pressures that have an impact on
insiders’ wealth. Finally, we extend the income-shifting literature by providing
evidence of earnings management through related transactions for purposes other
than taxation (Gramlich et al. 2004; Klassen et al. 1993).
2
For example, it was reported (Security Market Week, April 6, 2002) that Tianjin Nankai Guard, a
company listed on the Shenzhen Stock Exchange, was facing operating difficulties. This firm reported
enormous profits in the years before 2001 with 99.9% of its sales from related party transactions. When
the new accounting rule about related party transactions was implemented on December 21, 2001, any
such sales with a mark-up of more than 20% above book value could no longer be counted towards profits
in the income statement. This new standard has significantly undermined Tianjin Nankai Guard’s
accounting performance since 2001.
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Propping through related party transactions
73
This study also extends a few lines of research in economics and finance. First, it
complements Bertrand et al. (2002), who document that group structures in India
facilitate wealth expropriation by controlling shareholders with low cash-flow rights
in a group subsidiary. It shows that in contrast to India, groups in China facilitate
cash-based earnings management via related party transactions. Second, the current
work extends Friedman et al. (2003) by providing direct evidence of a form of
propping and a subsequent cash transfer that is not necessarily designed for wealth
extraction from outside shareholders. Third, by examining a large sample of related
party transactions between controlling owners and listed firms, this study
complements a number of recent studies on internal markets and intra-group
transactions (Khanna and Palepu 2000; Khanna and Yafeh 2005, 2007).
The remainder of this paper is organized as follows. Sect. 2 provides a discussion
of the hypotheses. Sect. 3 presents the sample and empirical results. A number of
robustness checks are reported in Sect. 4. Finally, conclusions are presented in
Sect. 5.
2 Hypothesis development
2.1 Earnings management incentives
We consider two situations in which the controlling owner has incentives to prop up
its listed firm through related party transactions. First, the controlling owner may
want to inflate earnings to avoid reporting losses. Compared with the loss avoidance
studies of Leuz et al. (2003) and Bhattacharya et al. (2003) that analyze countries
other than China, earnings management incentives are much stronger among
Chinese listed firms because reports of losses will lead to heavy government
scrutiny or delisting.3
The second situation in which the controlling owner has strong incentives to
engage in propping is during rights issue offerings. After the initial public offering
(hereafter IPO), rights issue offerings are an important source of funds for listed
firms in China. Thus, maintaining a firm’s listing status and qualification for rights
issues is an important objective for controlling owners. Even for the SOEs, central
and local governments as the ultimate controlling owners have strong incentives to
help listed firms maintain their listing status (Bai et al. 2005) and qualify for raising
more funds, as such firms are better able to help relieve unemployment problems
and enhance the infrastructure development of the ministries where the firms belong
or of the regions where the firms operate (Li and Zhou 2005).
Due to the high information costs in controlling the allocation of key resources,
government regulators have instituted bright-line rules for rights issues, but they still
face difficulties in reducing earnings management (Watts and Zimmerman 1986).
3
According to Article 157 of China’s Company Law, if a listed company sustains losses for three
consecutive years, it will be temporarily delisted by the China Securities Regulatory Commission (CSRC)
and subjected to ‘particular transfer’ (the stock can only be traded in the stock exchange on Fridays) and
other transfer constraints. If it sustains losses for two consecutive years, it will have ‘ST’ (special
treatment) prefixed to its name as a warning.
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M. Jian, T. J. Wong
From 1996 to 1998, companies were required to have a minimum of 10% ROE (9%
in protected industries including agriculture, energy, raw materials and infrastructure) for the three consecutive years before the offering (CSRC Notice No. 17,
1996). In 1999, the requirement was modified to an average ROE of at least 10% as
well as a minimum of 6% in each of the three years before the offering (CSRC
Notice No. 12, 1999). The rule was further modified and made effective in March
2001 to an average net ROE of at least 6% in the three years before the offering. To
adjust for potential reporting abuse, securities regulators calculate ROE as the lower
of ROE or ROE before nonrecurring items. Many prior studies provide evidence of
Chinese listed companies managing their earnings to reach the 10% benchmark
(Chen and Yuan 2004; Chen 1998; Chen et al. 2000b; Haw et al. 2005; Jiang and
Wei 1998).
2.2 Do Chinese firms prop through related sales?
We hypothesize that controlling owners inflate Chinese listed firms’ revenues and
earnings through related sales to qualify for rights issues or to avoid delisting.4
Chinese firms have ample opportunities to use related sales for earnings
management because related party transactions are very common. One reason for
their prevalence is that SOEs rely heavily on internal markets for materials,
products, labor, and capital. Before China’s economic reforms, these markets were
non-existent as the central government directed all aspects of SOEs’ operations.
Another reason is that close to 80% of the listed firms in China were previously
production units that had been carved out from their parent SOEs, which serve as
the controlling owners after the listing (Aharony et al. 2000). After the carve-out
and IPO, the listed subsidiaries continue to engage in frequent related party
transactions with their parent SOEs.
Following Khanna and Yafeh (2005), we use related sales to proxy for propping
because they are one of the most frequent types of related party transactions in our
sample. The high frequency of these transactions allows sellers to inflate earnings
simply by shifting next period’s related sales to the current period. Compared with
real activities manipulation such as aggressive price discounts to increase sales or
deferral of R&D projects discussed in Roychowdhury (2006), accelerating related
sales are likely to be less costly to the manipulating firm. Also, the high volume of
these transactions can increase the power of our tests. We hypothesize that the level
of related sales is abnormally high when firms try to meet earnings targets.
We note that firms could use other types of related party transactions such as
asset injections as an alternative way to achieve propping, but such transactions are
much more infrequent and thus more easily detected. According to the CSRCs 1999
4
There is plenty of anecdotal evidence of related sales propping. For example, Tianjin Nankai Guard
Co., Ltd. reported a significant drop in earnings in 2003 (decrease by 100.41%, from a RMB 70 million
net profit in 2002 to a RMB 289,000 loss in 2003). In 2002 (2001), the listed firm sold almost RMB 88
(RMB 272) million worth of products to its parent company’s subsidiary, which amounted to 92% (84%)
of total sales. The drop in profit in 2003 was due to two factors. First, the listed firm had to recognize bad
debt of RMB 57 million as its parent’s subsidiary experienced financial difficulty and failed to pay back
the accounts receivable. Second, the sales to the same related party decreased to less than RMB 127,000.
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Propping through related party transactions
75
regulations for rights offerings, infrequent items such as gains and losses from
investments and sales of fixed assets are no longer allowed to be included in the
calculation of ROE, which suggests that government regulators regard nonrecurring
items as potential earnings management tools. In the diagnostic checks reported in
Sect. 4, we examine other operating items, such as related purchases, and nonoperating items, such as asset or cash injections. The results do not support the
notion that firms use these items for propping around the time of share issuances and
delistings.
2.3 Is earnings management via related sales entirely accrual-based?
A typical way for a focused (nongroup) firm to inflate earnings is to accelerate credit
sales to customers (Teoh et al. 1998). It is difficult to increase cash sales because
customers are not willing to cooperate when cash is involved. However, we argue
that when group firms attempt to accelerate related party sales, they are not
necessarily bound to use accrued sales; they can also use cash sales or a combination
of the two to manage earnings. Thus, Chinese listed firms are likely to consider
cash-based related sales for propping for two reasons.
First, similar to the arguments for real earnings management by Graham et al.
(2005), Chinese listed firms will consider using cash-based related sales to manage
earnings because they can reduce the excessive accruals that draw auditors’
attention. Despite the presumably weak monitoring role of Chinese auditors due to
the country’s weak legal environment, they are likely to pay attention to excessive
accrued sales that increase accounts receivable and bad debt. Consistent with this
conjecture, recent research on Chinese listed firms shows that total receivable over
total assets is positively associated with audit fees and auditors’ propensity to issue
modified opinions (Chen et al. 2007; Wang et al. 2008).
Second, it is less costly for Chinese listed firms, which are typically group firms,
to engage in cash-based related transactions. Compared with a sales transaction of a
focused firm with an unaffiliated firm, a Chinese firm can more easily accelerate
cash sales to an affiliated firm within the same group because it can transfer cash
back from the seller through related lending. Although this subsequent cash transfer
will increase the seller’s other receivable accounts, as credit sales do, it can be
carried out over a few years, thereby reducing any sharp increases in receivables.
Further, the group structure allows the subsequent cash transfer to be effected not
only via the seller but also through a number of other affiliated firms within the
group. Related lending between parent SOEs and their listed subsidiaries was
permitted during our sample period from 1998 through 2002 as long as the listed
firms properly disclosed such transactions to the public.5
Based on these two reasons, we conjecture that the Chinese listed firms are likely
to increase earnings via cash-based or a combination of cash- and accrual-based
related party sales. However, this remains an empirical issue because it is hard to
5
In 2003 the CSRC promulgated Notice No. 56 urging listed companies to reduce related lending to their
affiliated firms. In 2005, CSRC issued an opinion requiring listed firms and their parent companies to
eliminate related lending by the end of 2006.
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directly ascertain whether the use of cash-based related sales is more cost effective
than that of pure accrual-based related sales in managing earnings.
2.4 Do related sales and accruals used for earnings management serve
as complements or substitutes?
In the previous section, we argued that related sales can be cash-based, that is, they
need not be entirely accrual-based. If Chinese firms can use cash-based related sales
to achieve their earnings management targets, does this reduce their propensity to
use not only accrued sales but also total accruals to manage earnings?
This is an empirical question that has two opposing predictions. On the one hand,
we expect an affirmative answer because, as we argued in the previous section,
accrual-based related sales management, when compared with cash-based related
sales management, sends a stronger alarm to auditors because of the potential risks of
bad debt exposure. This substitution effect between cash-based related sales and
accrual-based related sales may actually extend to other accruals management items.
This is consistent with the finding in Graham et al. (2005) that to avoid scrutiny,
managers choose real earnings management that burns up real cash flows over
accrual earnings management that draws the attention of the auditors. The managers’
preferences for the mix between taking accounting versus real actions to manage
earnings are a function of the costs of the real actions and the level of regulators’ and
auditors’ enforcement against accrual management. Thus, to the extent that the
subsequent cash transfer is not excessive and does not attract auditors’ scrutiny as
much as accruals management, cash-based related sales can substitute not only
accrued related sales management but also total accruals management.
On the other hand, although cash-based related sales reduce firms’ incentives to
manage earnings through accrual-based related sales, firms will still use other
accruals to supplement the earnings management. One reason is that the subsequent
cash transfer or related lending transactions associated with cash-based related sales,
if excessive, will increase firms’ total receivables and trigger auditors’ scrutiny, thus
putting a limit on the amount the firm can use toward earnings management.6 In
addition, Leuz et al. (2003) find that firms in countries with weaker investor
protection have a higher propensity to manage earnings through accruals than those
with stronger investor protection. This suggests that companies in China, where
investor protection is relatively weak, will have a strong tendency to engage in
accrual-based earnings management.
2.5 Propping and subsequent cash transfers
We argued in Sect. 2.3 that in contrast to cash sales in an arms-length transaction,
cash paid to the seller in cash-based related sales can be transferred back to the
buyer through other related party dealings. To test this conjecture, we use related
6
Although no firm was penalized by securities regulators for excessive related lending during our sample
period, three firms (company ID 600698, 000766, and 000925) were scrutinized for not providing
adequate disclosure about their related lending.
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Propping through related party transactions
77
lending as our measure of cash transfers from the listed firm to its largest
shareholder. Related lending is defined as the net amount between the loans lent to
related parties minus the loans borrowed from related parties. To eliminate the
effects of related sales and purchases on the net amount of related lending, we
exclude accounts receivable and accounts payable from the calculations. Results
that are obtained using alternative measures of related lending are discussed in the
robustness checks section.
We use related lending to proxy for cash transfers because compared with other
related party transactions that allow the largest shareholder to transfer cash back
from the listed firm, these transactions are more direct and frequent. Also, the
largest shareholder receives favorable terms in this type of cash transfer: related
lending interest rates reported in the footnotes of our sample firms’ financial
statements show that only 16.26% of the related loans earned interest revenue, of
which the average interest rate was 0.55%. This rate was significantly lower than the
typical bank rates of 5–10% per year over the sample period.7
2.6 The effects of political and economic institutions
The economic institutions of a country or region can determine its firms’ accounting
properties (Ball et al. 2000; DeFond et al. 2007; Leuz et al. 2003). In our context,
the level of market development and the degree of government involvement in a
region can shape its firms’ decisions to trade in external markets or form their own
internal markets. Thus, weak market development and heavy government
intervention is expected to lead to more frequent related party transactions, giving
rise to more opportunities for propping.
China offers a good setting to test the relation between market institutions and
accounting properties because the levels of market development and government
intervention vary significantly across the 30 provinces, autonomous regions and
municipalities. To test whether economic institutions play a role in influencing the
propping activities of listed firms in China, we include four institutional variables in
our analyses: Market Development Index and Deregulation Index, which measure the
level of the regions’ market development, and Unemployment and Fiscal Surplus,
which measure the incentives of government intervention in the markets (see Sect. 3.1
for a more detailed description of the indexes). We expect that there is more propping
in regions with weaker market development and more government intervention.
3 Empirical results
3.1 Sample and data
Chinese listed companies have been required to disclose related party transactions
since 1997. This disclosure was incomplete and irregular in the first year (Yuan
7
Information on the bank lending rates provided by the National Bureau of Statistics of China can be
found in http://www.stats.gov.cn/tjsj/ndsj/yb2004-c/indexch.htm.
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M. Jian, T. J. Wong
1998), but more systematic thereafter. Most companies report in a special footnote
to their financial statements the identity of their related parties, the relation with
these related parties (for example, percentage of shares held), and the types and
amounts of related party transactions. Due to the complexity of some Chinese
corporate groups, footnote disclosures of these connected dealings can be very
complicated. For instance, Shanghai Dragon Corporation reported more than 140
transactions with more than 100 related parties in 2002 alone.
Based on the financial statement footnotes on related party transactions, we
manually collect and classify each transaction by the nature of the transaction and
the related party involved. Generally, the major related parties are the shareholders
(or companies in the shareholder’s group), the subsidiaries and the associated
companies of the listed companies. Some other related parties include the
subsidiary’s minority shareholders and the listed companies’ ex-shareholders. We
classify related party transactions into 17 different types of transactions. The firmyear frequency and the average value for each transaction are as follows: sales
(47.29%, RMB 303 million), purchases of goods and products (44.50%, RMB 5.5
billion), accounts receivable and payable (37.07%, RMB 1 billion), loans to and
from related parties and other receivables and payables (51.32%, RMB 1.8 billion),
service revenues (12.53%, RMB 78 million) and expenses (22.08%, RMB 66
million), interest income (14.57%, RMB 11 million) and expenses (3.6%, RMB 18
million), asset purchases (10.44%, RMB 136 million) and sales (5.69%, RMB 75
million), stock purchases (7.95%, RMB 6.8 billion) and sales (5.56%, RMB 51
million), rent revenues (11.90%, RMB 10 million) and expenses (28.63%, RMB 35
million), joint investments (2.73%, RMB 83 million), and loan guarantees to related
parties (24.87%, RMB 1.4 billion) and from related parties (23.49%, RMB 3.6
billion). The average total assets of these firms are RMB 1.96 billion.
Our sample period covers 1998 through 2002. All financial and stock return
variables are obtained from the China Securities Market and Accounting Research
(CSMAR) Database. We use two market indexes and two regional variables to
capture the cross-region variation in institutional development. The first market
index is the Market Development Index, which was developed by Fan and Wang
(2003). This index has been widely used in economics research on China, including
that by Li et al. (2006) and Gwartney et al. (2005). The second market index is the
Deregulation Index, which was developed by Demurger et al. (2002) using the
number of special economic zones developed in a region as a proxy for market
development. The two regional variables are Unemployment and Fiscal Surplus,
obtained from the China Infobank.
We use the Big 10 auditors and the corporate pyramidal structure as proxies for
good governance. Past research has used Big 10 auditors based on the total assets of
audit clients to capture the auditor quality. DeFond et al. (1999) find that Big 10
auditors in China are more stringent based on their propensity to issue modified
opinions. Big 10 auditors’ tougher requirements on disclosure and more stringent
modified opinion threshold can serve as a deterrent against propping. This is a
credible threat because Chinese companies with modified reports must explain the
nature and underlying reasons for the receipt of a modified report directly to the
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Propping through related party transactions
79
CSRC (Chen et al. 2000a), and such disclosure can result in sanctions, delisting or
loss of qualifications for rights issues.
Our second corporate governance proxy is the number of pyramidal layers (firms)
between the ultimate controlling owner and the listed firm, obtained from Fan et al.
(2007). Since the Chinese government, as the largest owner in many former SOEs,
cannot sell its controlling stakes to the public, it sets up pyramidal layers as a
constraint on direct intervention by the government. The government has incentives
to commit to such arrangements because decentralization (less intervention)
increases efficiency through collocation of decision rights and knowledge. The
commitment not to intervene through the setting up of pyramidal layers is credible
because the added corporate layers increase bureaucratic costs for controlling the
firm at the bottom of the pyramid (Williamson 1964). Unlike the typical pyramid
that increases the divergence between voting and cash-flow rights and thereby
induces the controlling shareholder to expropriate from minority shareholders, this
leveraging effect does not exist in Chinese state-owned firms because all the upper
layers (above the listed firm) of the pyramid are 100% controlled by the
government. To the extent that a higher degree of government intervention induces
more earnings management through related party transactions, we conjecture that
firms with more pyramidal layers will engage in less related sales propping.
After excluding firm-years with missing market prices and controlling ownership
types, our final sample consists of 5,015 firm-year observations. Panel A of Table 1
shows that our sample is quite representative, covering 94–99% (average 97%) of
the population of CSMAR A-share firms from 1998 through 2002. The sample is
evenly distributed over the 22 CSRC industry classifications.
Panel B of Table 1 reports that the Chinese listed firms are controlled by three
general types of ultimate shareholders. The largest category is local government
firms (64%), followed by nonstate firms (21%) and central government firms (15%).
Among the three groups, the local government firms have the lowest growth (lowest
MARKET-TO-BOOK) and the weakest governance (lowest percentage of Big 10
auditor appointments and fewest pyramidal layers), and they are generally from the
most regulated regions, with the least developed markets.
We also divide our sample into firms that have related sales in any of the years
during the sample period (RPS [ 0) and those that have none in the sample period
(RPS = 0). Panel C of Table 1 shows that a majority of the firms have related sales
during the sample period, making up 65% of the firm-year observations
(N = 3,237). Firms that have related sales during the sample period tend to be
larger in size and have lower leverage and market-to-book ratios, and they are in
regions with slightly higher unemployment and inferior market institutions and
fiscal conditions.8 They also have a higher percentage of central government firms
and a lower percentage of nonstate firms.
Panel A of Table 2 reports summary statistics on related sales with various types
of related parties in the three general categories of firm ownership. Specifically, 57
8
Similarly, when the sample is partitioned into firms in good and bad regions based on the Market
Development Index median, the good regions have fewer firms that have related sales (62%) while the bad
regions have more (67%).
123
123
25
26, 27
28, 29, 30
36
32, 33, 34
35, 36, 37
38
39
49
15, 16, 17
40, 41, 42, 44, 45, 46, 47
48
50, 51, 52, 53, 54, 55, 56, 57, 58, 59
60, 61, 62, 63, 64, 67
65
43, 70, 80, 82, 83
Furniture Manufacturing
Paper and Allied Products; Printing
Petroleum, Chemical, Plastics, and Rubber Products
Manufacturing
Electronics
Metal, Non-metal
Machinery, Equipment, and Instrument Manufacturing
Medicine and Biological Products
Other Manufacturing
Utilities
Construction
Transportation and Warehousing
Information Technology
Wholesale and Retail Trades
Banking & Financial Institutions
Real Estate
Public Facilities and Other Services
20
22, 23
Textile, Apparel, Fur and Leather
Mining
Food & Beverage
01, 02, 07, 08, 09
10, 12, 13, 14
Farming, Forestry, Animal Husbandry, and Fishing
SIC equivalent
CSRC industry classifications
Panel A: Firms in the sample
Table 1 Sample descriptiona
28
28
1
84
43
25
13
31
7
37
129
74
27
92
17
1
32
38
6
18
1998
Year
33
29
1
84
46
31
17
35
11
44
143
88
29
104
19
1
40
46
9
18
1999
39
30
1
92
55
39
18
41
14
55
164
99
31
121
23
2
53
52
13
27
2000
39
34
1
94
57
45
18
43
15
62
170
104
35
128
24
2
61
57
15
28
2001
40
32
1
95
56
44
18
43
15
61
167
103
34
127
23
2
60
53
16
28
2002
179
153
5
449
257
184
84
193
62
259
773
468
156
572
106
8
246
246
59
119
Subtotal
180
159
32
466
260
190
84
194
64
266
793
481
157
581
107
8
249
249
60
125
All
99
96
16
96
99
97
100
99
97
97
97
97
99
98
99
100
99
99
98
95
Coverage (%)
80
M. Jian, T. J. Wong
13.10
0.71
5.56
0.22
2.10
6.29
1.23
3.33
-0.05
SIZE
LEVERAGE
MARKET-TO-BOOK
BIG 10
LAYERS
Market Development Index
Deregulation Index
Unemployment
Fiscal Surplus
-0.03
3.30
1.24
6.36
2.00
0.00
4.69
0.51
13.11
0.05
0.85
0.80
1.30
0.63
0.42
3.19
0.68
1.07
-0.04
3.08
1.27
6.35
2.75
0.30
5.61
0.50
13.41
-0.03
3.30
1.24
6.24
3.00
0.00
4.76
0.31
13.33
Median
Mean
Mean
Median
CENTRAL (N = 729)
98
937
916
79
9
1999
LOCAL (N = 3,219)
Panel B: Firm characteristics by ownership type
99
826
A-share firms available in CSMAR
% Covered
814
75
8
1998
Year
Subtotal
STD
78, 79, 84
Communication and Cultural Industries
Conglomerates
SIC equivalent
CSRC industry classifications
Panel A: Firms in the sample
Table 1 continued
0.03
1.13
0.80
1.21
0.70
0.46
3.16
0.56
1.15
STD
98
1,087
1,060
81
10
2000
96
1,152
1,103
75
10
2002
-0.04
3.36
1.37
6.48
2.21
0.28
7.13
0.94
12.60
Mean
-0.03
3.40
1.43
6.65
2.00
0.00
6.10
0.64
12.58
Median
48
389
0.05
0.90
0.83
1.42
0.83
0.45
3.83
0.90
1.08
STD
5,015
Nonstate firms (N = 1,067)
96
1,164
1,122
79
11
2001
Subtotal
97
95
94
-0.04
3.30
1.27
6.34
2.22
0.25
5.90
0.73
13.04
Mean
-0.03
3.30
1.24
6.36
2.00
0.00
4.92
0.50
13.03
Median
0.05
0.91
0.81
1.31
0.72
0.43
3.40
0.73
1.11
STD
Coverage (%)
All (N = 5,015)
5,166
410
51
All
Propping through related party transactions
81
123
123
0.65
5.83
0.25
2.26
6.27
1.19
3.32
0.64
64%
17%
19%
LEVERAGE
MARKET-TO-BOOK
BIG 10
LAYERS
Market Development Index
Deregulation Index
Unemployment
Fiscal Surplus
LOCAL
CENTRAL
Nonstate firms
0.64
3.30
1.24
6.36
2.00
0.00
4.78
0.46
13.13
39%
37%
48%
0.15
0.91
0.76
1.30
0.67
0.43
3.41
0.67
1.10
26%
10%
64%
0.65
3.26
1.40
6.47
2.14
0.25
6.03
0.86
12.83
0.71
3.30
1.24
6.40
2.00
0.00
5.14
0.60
12.83
44%
30%
48%
0.16
0.92
0.88
1.32
0.79
0.43
3.37
0.82
1.11
STD
This table presents the sample distribution by industry membership and calendar year in Panel A. Summary statistics of firm characteristics across three ownership types
are presented in Panel B. Panel C reports summary statistics of firm characteristics for firms that have related sales during the sample period (RPS [ 0) and those that do
not (RPS = 0). SIZE is the natural logarithm of total assets at year-end. LEVERAGE is the total debt over total assets at year-end. MARKET-TO-BOOK is the market value
divided by book value of total equity at year-end. BIG 10 is an indicator variable that equals one if the firm’s auditor is one of the 10 largest accounting firms based on
client assets in China and zero otherwise. LAYERS represents the number of layers between the listed company and its ultimate shareholder. Market Development Index is
the integrated market index developed by Fan and Wang (2003), which measures the progress of institutional transformation in China’s 30 provinces (excluding Tibet due
to lack of data) and identifies the differences in institutions and economic policies among various regions. Deregulation Index is the index from Demurger et al. (2002),
which measures the amount of preferential treatment granted to the region by the central government from 1978 to 1998, and proxies for the degree of deregulation in
China. The higher the index, the less regulated is the region. Unemployment is the unemployment rate in different provinces in China obtained from China InfoBank.
Fiscal Surplus is the difference between provincial financial revenue and expenses, divided by provincial GDP. LOCAL refers to the subsample of firms whose ultimate
shareholder is the local government. CENTRAL refers to the subsample of firms whose ultimate shareholder is the central government. Nonstate firms refers to the
subsample of firms whose ultimate shareholder is NOT the government
a
13.16
SIZE
Median
Mean
STD
Mean
Median
Raw RPS = 0 (N = 1,778)
Raw RPS [ 0 (N = 3,237)
Panel C: Firm characteristics by related sales group
Table 1 continued
82
M. Jian, T. J. Wong
0.06
6.37
Others
ALL
0.14
5.74
Others
ALL
0.00
0.15
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
13.76
0.59
1.77
0.73
0.00
13.34
13.30
0.28
0.47
0.11
0.00
13.28
53
11
17
13
3
42
48
7
10
7
2
40
8.79
3.05
0.13
0.42
0.18
0.00
2.31
8.99
0.06
0.12
0.03
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.45
0.00
0.00
0.00
0.00
0.00
Median
10.54
0.58
1.52
0.67
0.00
10.17
16.26
0.28
0.47
0.11
0.00
16.28
STD
50
11
17
13
5
38
57
7
12
9
5
48
Freq
(%)
5.39
0.22
0.56
0.26
0.00
4.36
3.32
0.07
0.11
0.02
0.00
3.13
Mean
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
Median
13.94
0.78
1.77
0.84
0.00
13.50
9.60
0.31
0.46
0.10
0.00
9.59
STD
Nonstate firms (N = 1,067)
49
15
19
14
5
36
37
8
9
5
3
27
Freq
(%)
5.27
0.16
0.51
0.21
0.00
4.39
6.11
0.06
0.11
0.02
0.00
5.91
Mean
0.05
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
Median
All (N = 5,015)
13.41
0.63
1.74
0.75
0.00
12.99
13.21
0.28
0.46
0.11
0.00
13.19
STD
52
12
17
13
4
40
47
7
10
7
2
38
Freq
(%)
This table reports the magnitude and frequency of related sales and related lending of the firms in our sample. We divide the firms by the types of their ultimate
shareholders (LOCAL: the subsample of firms whose ultimate shareholder is the local government, CENTRAL: the subsample of firms whose ultimate shareholder is the
central government. and Nonstate firms: the subsample of firms whose ultimate shareholder is not the government), and the types of related parties (Largest shareholder,
2nd largest shareholder, Subsidiaries, Associated companies, and Others) involved in the related party transactions. Related sales include the sales of products and
provision of services. Related lending is total receivables net of total payables. Total receivables include other receivables, loans, and other advanced payment to related
parties and total payables include other payables, loans, and other prepayment from related parties. Accounts receivable and payable are excluded to eliminate the effects
of related sales and purchases. Both related sales and related lending are deflated by total sales of the listed firm in the same year times 100%
a
0.21
0.52
Associated
companies
2nd largest
shareholder
Subsidiaries
4.87
0.00
Largest shareholder
Panel B: Related lending
0.02
0.11
Associated
companies
2nd largest
shareholder
Subsidiaries
6.18
0.00
Largest shareholder
Panel A: Related sales
Freq
(%)
Mean
STD
Mean
Median
CENTRAL (N = 729)
LOCAL (N = 3,219)
Table 2 Descriptive statistics of related sales and related lendinga
Propping through related party transactions
83
123
84
M. Jian, T. J. Wong
and 48% of the central and local government firms, respectively, have related sales,
while only 37% of the nonstate firms report such dealings. The majority of these
intra-group trades involve the largest shareholder, with 48% of central government
firms and 40% of local government firms. Related sales with the second-largest
shareholder are much less frequent, ranging from 2% for local government firms to
5% for central government firms. Subsidiaries and associated firms do have
reasonable amounts of related sales with the sample firms, but their impact on the
listed firms’ earnings will be cancelled out during consolidation. Thus, we only
focus on related sales with the largest shareholder in our final analysis.9
Panel B of Table 2 presents summary statistics on the related lending variable.
Similar to related sales, intra-group lending is very frequent among the three types
of firms, with local firms having the highest frequency (53%) and nonstate firms the
lowest (49%). Also, most of the lending is done with the largest shareholders.
Finally, the relations among all the variables used in the study are presented in the
Pearson correlation matrix in Appendix 1.
3.2 Propping through related sales
In this section, we use two tests to analyze whether Chinese listed firms use related
sales in earnings management. In the first test, we examine if the level of related
sales and their associated operating profits are abnormally high when there is an
incentive to manage earnings. In the second test, we use an approach similar to the
one in Bertrand et al. (2002) to investigate whether related sales are used to reduce
negative industry shocks when firms have incentives to meet earnings targets.
Before providing more detailed results of the two tests, we first discuss how we
measure abnormal related sales and abnormal related lending.
3.2.1 Measuring abnormal related party transactions
Similar to accounting accruals, the level of related party transactions can either be
normal or abnormal for the firm. We use an OLS regression model to remove any
normal components of related party transactions that are associated with industry
classifications and firm characteristics such as size, measured by the natural
logarithm of total assets; leverage, measured by total debt over total assets; and
growth, measured by market-to-book equity. The residual term is our measure of
abnormal related party transactions. We run two sets of year-by-year (1998–2002)
regressions, one each for sales and lending as dependent variables. The range and
9
The summary statistics of abnormal related party transactions with the largest shareholders (not
reported) show that central government firms tend to have higher abnormal related sales (mean = 0.01)
than local (mean = 0) and nonstate firms (mean = -0.01), while they have a similar level of abnormal
related lending as local government firms. For the subsample of firms with an incentive to manage
earnings, both central and local government firms have positive abnormal related sales (mean = 0.04 and
0.01, respectively) while nonstate firms have an average of -0.02 abnormal related sales. Moreover, local
government firms tend to have higher abnormal related lending than central government and nonstate
firms in this subsample.
123
Propping through related party transactions
85
number of significant coefficients for the five years of regressions are reported in
Appendix 2.
The related sales models have an adjusted R-square ranging from 0.08 to 0.11.
Both the coefficients on SIZE and LEVERAGE are statistically significantly positive
and negative, respectively, in all the five years. The petrochemicals, metal,
machinery, utilities, mining, and furniture manufacturing industries are found to
have more related sales. Compared with related sales, the firm characteristic and
industry classification variables have much less explanatory power for related
lending, with adjusted R-squares ranging from 0.001 to 0.03. As a robustness check,
we find similar results after including state ownership as a determining factor for
normal related party transactions. We have also used gross and industry-adjusted
related party transactions as alternative measures for all our main analyses and the
results remain the same.
3.2.2 Test on abnormal related party sales and associated operating profits
In this section, we examine whether related sales and the associated operating
profits are abnormally high when Chinese firms have a strong incentive to manage
earnings. First, we test the abnormal related sales level by regressing it on
INCENTIVE, firm ownership and the governance variables. INCENTIVE equals one
when the firm’s ROE is at the margin of qualifying for a rights issue (9–11% for
protected industries and 10–12% for others before 2001; 6–8% afterwards), when
the firm’s ROE is just above zero (0–2%), or when the firm seeks to have a rights
issue in the following year and zero otherwise. All regressions are run using a
pooled sample of five years with standard errors clustered by firm to control for
serial correlation.
In Table 3, column 1 reports the benchmark model with only INCENTIVE as the
test variable. The coefficient on INCENTIVE is positive and statistically significant,
which suggests that there is a higher level of abnormal related sales around these
narrow ROE ranges.10 This evidence supports our conjecture that firms use related
sales to inflate earnings to meet securities regulators’ share issuance and delisting
ROE thresholds.
Next we add LOCAL, CENTRAL and their interactions with INCENTIVE as
explanatory variables to the regression model in column 2. The coefficients on both
interaction terms are significantly positive, showing that local and central
government firms are more likely to have abnormal related sales when earnings
are close to the securities regulators’ earnings targets. For example, on average, the
central government firms inflate their related sales more than nonstate firms do by
2.8% of total sales when they have to meet the earnings targets, which amounts to
RMB 31 million of abnormal related sales. State firms engage in propping more
10
We conduct the following robustness check: (1) randomly select two 2% ROE intervals from a feasible
ROE range in our sample, i.e., [-25%, 25%], set INCENTIVE equal to one for firm-years whose ROEs
fall in these intervals and zero otherwise; (2) regress abnormal related sales on the pseudo-INCENTIVE.
We repeat the above steps 1,000 times and find that the coefficient on pseudo-INCENTIVE is significant at
the 10% level in only approximately 10% of the regressions. This suggests that the model in Table 3 is
well specified and its results are unlikely to be spurious.
123
86
Table 3
M. Jian, T. J. Wong
Earnings management through related salesa
Panel A: Abnormal related sales, propping incentives and firm-level factors
INCENTIVE
1
2
3
4
0.009
-0.003
0.010
0.011
(2.66)***
(0.73)
(1.05)
(1.16)
0.000
0.001
0.002
(0.03)
(0.24)
(0.25)
-0.006
-0.013
-0.013
(0.48)
(1.07)
(1.09)
-0.007
-0.006
(1.04)
(0.93)
0.011
0.011
LOCAL
CENTRAL
BIG 10
LAYERS
(3.00)***
(3.00)***
0.012
0.011
INCENTIVE 9 LOCAL
0.013
(1.99)**
(1.85)*
(1.66)*
INCENTIVE 9 CENTRAL
0.028
0.033
0.033
(2.35)**
INCENTIVE 9 BIG 10
INCENTIVE 9 LAYERS
(2.72)***
(2.65)***
0.002
0.001
(0.30)
(0.11)
-0.006
-0.007
(1.73)*
(1.71)*
Previous year’s ROS
0.00
(2.42)**
Intercept
-0.008
-0.008
-0.029
-0.030
(2.14)**
(1.49)
(3.13)***
(3.11)***
N
5,015
5,015
5,015
4,597
Adjusted R2
0.004
0.010
0.010
0.010
a
This table presents results on whether firms inflate related sales when there are earnings management
incentives. The dependent variable of the regression is abnormal RPS, which is the residual term from the
annual regression of overall related sales on SIZE, LEVERAGE, MARKET-TO-BOOK, and industry
dummies (see Appendix 2 for details). The independent variables include INCENTIVE, which equals one
when the firm’s ROE is at the margin of qualifying for a rights issue (9–11% for protected industries and
10–12% for others before 2001; 6–8% afterwards), when the firm’s ROE is just above zero (0–2%), or
when the firm is going to seek a rights issue in the following year and zero otherwise; LOCAL, which
equals one when the firm’s ultimate shareholder is the local government and zero otherwise; CENTRAL,
which equals one when the firm’s ultimate shareholder is the central government and zero otherwise; BIG
10, which equals one when the firm’s auditor is one of the 10 largest accounting firms based on client
assets in China and zero otherwise; LAYERS, which represents the number of layers between the listed
firm and its ultimate shareholder; and Previous year’s ROS, which is the return on sales of the firm one
year before the related party transaction occurs. The results presented in columns 1–4 use OLS regression
and the absolute robust t-statistics are based on standard errors clustered by firm as shown in parentheses
* Significant at 10%; ** Significant at 5%; *** Significant at 1%, two-tailed tests
123
Propping through related party transactions
87
Table 3 continued
Panel B: Operating profit margin generated by abnormal related sales, propping incentives, and firm-level
factorsb
1
2
3
4
0.008
-0.003
-0.007
-0.008
(1.94)*
(1.57)
(0.33)
(0.35)
LOCAL
-0.007
-0.006
-0.005
(1.32)
(1.36)
(1.27)
CENTRAL
-0.002
-0.006
-0.005
(0.85)
(1.34)
(1.20)
0.003
0.003
(1.01)
(1.03)
0.007
0.007
INCENTIVE
BIG 10
LAYERS
(1.11)
(1.12)
0.016
0.016
INCENTIVE 9 LOCAL
0.017
(1.99)**
(1.95)*
(1.89)*
INCENTIVE 9 CENTRAL
0.006
0.005
0.005
(1.97)*
(1.83)*
INCENTIVE 9 BIG 10
(2.65)***
-0.006
-0.006
(0.99)
(0.96)
INCENTIVE 9 LAYERS
0.003
0.003
(0.28)
(0.33)
Previous year’s ROS
-0.002
(0.99)
Year Dummies
Yes
Yes
Yes
Yes
Intercept
-0.009
-0.004
-0.019
-0.020
(2.20)**
(1.53)
(1.41)
(1.46)
N
5,015
5,015
5,015
4,597
Adjusted R2
0.005
0.010
0.007
0.006
b
This panel reports the regression results on whether operating profits generated by abnormal related
sales are significantly higher when there are incentives for earnings management. The dependent variable
in the regression is the operating profit generated by abnormal related sales (abnormal related sales
multiplied by the firm’s operating profit margin) divided by the firm’s total equity at the year-end. The
independent variables include INCENTIVE, which equals one when the firm’s ROE is at the margin of
qualifying for a rights issue (9–11% for protected industries and 10–12% for others before 2001; 6–8%
afterwards), when the firm’s ROE is just above zero (0–2%), or when the firm is going to seek a rights
issue in the following year and zero otherwise; LOCAL, which equals one when the firm’s ultimate
shareholder is the local government and zero otherwise; CENTRAL, which equals one when the firm’s
ultimate shareholder is the central government and zero otherwise; BIG 10, which equals one when the
firm’s auditor is one of the 10 largest accounting firms based on client assets in China and zero otherwise;
LAYERS, which represents the number of layers between the listed firm and its ultimate shareholder; and
Previous year’s ROS, which is the return on sales of the firm one year before the connected transaction
occurs. The results presented in columns 1 to 4 use OLS and the absolute robust t-statistics are based on
standard errors clustered by firm as shown in parentheses
* Significant at 10%; ** Significant at 5%; *** Significant at 1%, two-tailed tests
123
88
M. Jian, T. J. Wong
because compared with nonstate firms, there are more intra-group trades between
the listed firms and their parent SOEs (see Table 2), which gives them greater
capacity to hide their propping in normal related sales.
The coefficients on the interaction terms with LOCAL and CENTRAL remain
positive and statistically significant when the governance variables, BIG 10 and
LAYERS (column 3), and the firm performance variable, the previous year’s return
on sales (ROS) (column 4), are added. The ROS variable controls for the
possibility that government-controlled firms are weaker and need more propping
to avoid delisting or to qualify for rights offerings or both. The coefficient on
LAYERS is significantly positive, while the coefficient of INCENTIVE 9 LAYERS
is negative and statistically significant in columns 3 and 4. This suggests that firms
with more complex layering structures generally have more related sales, but these
layers serve as a deterrent for controlling shareholders to use related sales to
manage earnings.
Turning to the analysis of operating profits generated by abnormal related sales,
we rerun the regressions in Panel A of Table 3 using operating profits from
abnormal related sales divided by total equity as the dependent variable. Since we
do not know the exact profit margins for related sales, we use the companies’
average profit margins from related and nonrelated sales in computing the profits
from related sales. In this test, we cannot distinguish between whether listed firms
increase related sales profits by raising (1) the volume of related sales or (2) the
operating margin. To the extent that the firms inflate the profit margins of nonrelated
sales to meet earnings targets, we would have to interpret our results with caution.
However, it should be easier for the firms to inflate profit margins of related sales
transactions than arms-length sales transactions.
The results reported in Panel B of Table 3, column 1, show that the operating
profits associated with related sales increase when there is an incentive to manage
earnings. When the interaction terms INCENTIVE 9 LOCAL and INCENTIVE 9 CENTRAL are included in columns 2–4, their coefficients are positive
and statistically significant. For example, the results in column 2 indicate that
central government firms inflate operating profits more than nonstate firms do by
0.6% of total equity, which amounts to RMB 5.9 million of operating profits.
Perhaps state firms’ higher frequency of related sales compared to nonstate firms
(Table 2, Panel A) provides the former more opportunities to use related sales for
earnings management.
3.2.3 Test on related sales and earnings shocks
In the second test, we use a method similar to that described by Bertrand et al.
(2002), who use group firms’ sensitivity to industry earnings shocks to measure the
extent of wealth extraction by the controlling owner. In our test, we use the Chinese
firms’ sensitivity to industry earnings shocks to analyze the extent of earnings
management. We predict that if Chinese firms engage in earnings management, they
will be less sensitive to negative industry shocks.
First, as a baseline regression, we regress the listed firms’ change in ROS (DROS)
on the change in industry average ROS based on the industry classifications in
123
Propping through related party transactions
89
Table 4 Related sales and earnings shocksa
Pooled sample
Subsamples
1
2
INCENTIVE = 1
3
INCENTIVE = 0
4
0.367
0.675
0.668
0.570
(2.48)**
(3.47)***
(3.00)***
(2.05)**
DRPS
0.053
0.023
0.079
(1.25)
(0.49)
(1.28)
NEGATIVE SHOCK
-0.017
-0.034
-0.009
(1.38)
(2.48)**
(0.51)
NEGATIVE SHOCK
9 DIND_ROS
-0.203
2.131
-0.733
(0.18)
(1.72)*
(0.50)
DIND_ROS 9 DRPS
2.822
1.148
4.300
(1.17)
(0.54)
(1.24)
0.067
0.295
-0.083
(0.64)
(2.25)**
(0.70)
-12.772
-31.040
0.286
DIND_ROS
NEGATIVE SHOCK 9 DRPS
NEGATIVE SHOCK
9 DIND_ROS 9 DRPS
(1.06)
(2.96)***
(0.02)
0.019
-0.005
0.031
(6.27)***
(5.21)***
(1.06)
(5.89)***
-0.111
-0.099
0.036
-0.147
(7.69)***
(6.36)***
(1.70)*
(7.10)***
MARKET-TO-BOOK
0.003
0.003
0.001
0.004
(4.20)***
(3.10)***
(1.36)
(3.63)***
Intercept
-0.285
-0.274
0.036
-0.433
SIZE
0.020
LEVERAGE
(6.20)***
(5.10)***
(0.58)
(5.75)***
N
4,601
3,883
1,328
2,555
Adjusted R2
0.020
0.010
0.020
0.020
a
This table presents the results on whether related sales are used to damp negative industry ROS shocks
on firms’ change in ROS. The dependent variable in the regressions is the firm’s change in ROS (DROS),
which is the ROS of the current year minus the ROS of the prior year. The independent variables include
the following: DIND_ROS, which is the change in industry average ROS (excluding the test firm’s DROS)
based on the industry classifications in Table 1; DRPS, which is the change in abnormal related sales;
NEGATIVE SHOCK, which equals one when DIND_ROS is negative and zero otherwise; SIZE, which is
the natural logarithm of total assets at year-end; LEVERAGE, which is total debt over total assets at yearend; and MARKET-TO-BOOK, which is the market value divided by book value of total equity at yearend. We run the regressions using the pooled sample in columns 1 and 2. We also partition the pooled
sample into two subsamples based on INCENTIVE = 1 in column 3 and INCENTIVE = 0 in column 4.
INCENTIVE equals one when the firm’s ROE is at the margin of qualifying for a rights issue (9–11% for
protected industries and 10–12% for others before 2001; 6–8% afterwards), when the firm’s ROE is just
above zero (0–2%), or when the firm is going to have rights issue in the following year and zero
otherwise. The results presented in columns 1–4 use OLS and the absolute robust t-statistics are based on
standard errors clustered by firm as shown in parentheses
* Significant at 10%; ** Significant at 5%; *** Significant at 1%, two-tailed tests
123
90
M. Jian, T. J. Wong
Table 1 (DIND_ROS), and other firm-specific variables including SIZE, LEVRAGE,
and MARKET-TO-BOOK.11 The results of column 1 in Table 4 show the coefficient
on DIND_ROS is significantly positive suggesting that industry shocks do have a
significantly positive effect on firms’ earnings.
Next, we perform the main test by adding to the regression NEGATIVE SHOCK,
which is equal to one when DIND_ROS \ 0 and zero otherwise, and DRPS, which is
the firm’s change in abnormal related sales for the year. If related sales can damp
the effect of negative industry shocks on firms’ earnings, the coefficient on
NEGATIVE SHOCK 9 DIND_ROS 9 DRPS will be significantly negative. That is,
the firms use abnormal related sales (DRPS [ 0) to mitigate the effect of negative
industry shocks on their earnings. Since we expect that firms have more incentives
to use related sales to mitigate negative industry shocks when they have to meet
earnings targets, we run the regression using the full sample in column 2 as well as
subsamples separated into firm-years that have incentives for meeting share
issuance and delisting earnings targets (INCENTIVE = 1) in column 3 and those
that do not (INCENTIVE = 0) in column 4.
The results in column 3 show that the coefficient on NEGATIVE SHOCK 9 DIND_ROS 9 DRPS is significantly negative. For example, a one-standard
deviation change in abnormal related sales (8.19%) can more than undo the
negative industry shock on firm-specific ROS when there is an incentive to manage
earnings. None of the interaction terms is significant in the full sample (column 2)
and in the subsample with INCENTIVE = 0 (column 4).
In summary, the results suggest that related sales management can mitigate the
effect of negative industry shocks on firms’ earnings. This evidence is statistically
significant when firms have incentives to manage earnings but is statistically
insignificant otherwise.
3.3 Related sales and accruals management
3.3.1 Is related sales propping entirely accrual-based?
Next, we test whether earnings management through related sales is purely accrualbased or whether it can also be cash-based. We use the cross-sectional Jones (1991)
model to measure discretionary related party accounts receivable by regressing the
change in related party accounts receivable on the change in related sales. If the
listed firm inflates accrued related sales, we would expect to find high discretionary
related party accounts receivable. In the pooled regressions reported in Table 5,
column 1, we do not find that the change in accounts receivable generated by related
sales is abnormally high when there is an incentive to manage earnings. This
evidence indicates that the abnormal related sales documented in Table 3 are likely
to be cash-based, or a combination of cash- and accrual-based.
11
We exclude the tested firms’ DROS in calculating DIND_ROS. However, the results remain unchanged
if we include the tested firms’ DROS in the calculation.
123
Propping through related party transactions
91
Table 5 Related sales and accruals earnings managementa
Discretionary
related
receivable
Pooled
Discretionary total accruals
Raw
RPS = 0
3
Pooled
RPS [ 0
RPS B 0 Pooled
1
Raw
RPS [ 0
2
4
5
6
7
0.001
0.239
0.297
0.309
0.218
0.265
0.233
(1.59)
(3.61)***
(2.84)***
(4.30)*** (4.26)*** (5.83)*** (7.08)***
0.000
0.005
-0.026
-0.002
0.043
0.016
0.018
(0.04)
(0.19)
(0.77)
(0.07)
(1.64)
(0.66)
(0.95)
0.001
0.034
0.012
0.019
-0.010
0.061
0.043
(0.73)
(0.90)
(0.24)
(0.62)
(0.23)
(1.80)*
(1.54)
0.000
0.000
0.018
0.020
0.055
0.014
0.021
(0.12)
(0.02)
(0.60)
(1.12)
(1.42)
(0.82)
(1.38)
0.000
0.053
0.026
0.045
0.052
0.020
0.027
(0.93)
(3.37)***
(0.74)
(2.11)**
(2.15)**
(1.15)
(1.95)*
INCENTIVE 9
LOCAL
0.000
0.004
-0.049
-0.013
-0.029
-0.038
-0.030
(0.05)
(0.12)
(1.30)
(0.44)
(0.85)
(1.43)
(1.45)
INCENTIVE 9
CENTRAL
0.000
-0.005
-0.097
-0.021
0.018
-0.075
-0.049
(0.54)
(0.10)
(1.80)*
(0.56)
(0.36)
(2.14)**
(1.69)*
INCENTIVE 9
BIG 10
0.000
-0.009
-0.024
-0.025
-0.042
-0.024
-0.025
(0.14)
(0.31)
(0.73)
(1.06)
(1.00)
(1.31)
(1.49)
INCENTIVE 9
LAYERS
0.000
-0.045
-0.041
-0.045
-0.060
-0.021
-0.029
(1.26)
(1.85)*
(1.08)
(1.97)**
(2.28)**
(1.18)
(2.04)**
Previous year’s 0.000
ROS
(1.05)
0.039
0.001
0.005
0.019
0.000
0.001
(1.58)
(0.52)
(1.26)
(2.67)*** (0.01)
(0.49)
LEVERAGE
0.000
0.019
-0.003
0.008
0.005
0.007
0.006
(0.46)
(1.20)
(0.20)
(0.75)
(0.45)
(1.18)
(1.10)
0.000
-0.016
-0.022
-0.018
-0.028
-0.011
-0.016
(1.40)
(0.77)
(2.25)**
(1.33)
(3.38)*** (2.73)*** (4.17)***
0.000
0.010
-0.003
0.005
0.000
-0.001
-0.001
(1.06)
(1.91)*
(1.03)
(1.46)
(0.16)
(0.57)
(0.55)
INCENTIVE
LOCAL
CENTRAL
BIG 10
LAYERS
SIZE
MARKET-TOBOOK
D_RPS
0.046
INCENTIVE 9
D_RPS
Intercept
0.033
(1.42)
(2.27)**
-0.062
-0.035
(1.85)*
(2.02)**
0.000
-0.129
0.093
-0.094
0.102
-0.045
-0.002
(0.11)
(0.49)
(0.63)
(0.51)
(0.72)
(0.75)
(0.03)
N
4,593
2,944
1,649
4,593
1,238
3,355
4,593
Adjusted R2
-0.010
0.010
0.040
0.010
0.070
0.034
0.026
123
92
M. Jian, T. J. Wong
Table 5 continued
a
This table provides results for two separate tests: (1) whether firms use purely accrual-based related
sales for earnings management and (2) whether related sales and accruals earnings management are
complements or substitutes. The first test uses discretionary receivables from related parties (the residual
of the annual regression model in which related party accounts receivable is regressed on related sales) as
the dependent variable in column 1; the second test uses discretionary total accruals as the dependent
variable in columns 2–7. In the regressions of the second test, we examine the pooled sample in columns
4 and 7, and the two subsamples based on whether the firm has opportunities to use related sales for
earnings management, with raw RPS [ 0 (firms with related sales in at least one year during the sample
period) in column 2, and raw RPS = 0 (firms without any related sales during the sample period) in
column 3. In the second partition we examine the subsamples based on whether the firm has used related
sales in earnings management during the year, with RPS [ 0 (firms-year with positive abnormal related
sales) in column 5, and RPS B 0 (firms without positive abnormal related sales) in column 6. The
independent variables in the regressions of both tests include the following: INCENTIVE, which equals
one when the firm’s ROE is at the margin of qualifying for a rights issue (9–11% for protected industries
and 10–12% for others before 2001; 6–8% afterwards), when the firm’s ROE is just above zero (0–2%),
or when the firm is going to seek a rights issue in the following year and zero otherwise; LOCAL, which
equals one when the firm’s ultimate shareholder is the local government and zero otherwise; CENTRAL,
which equals one when the firm’s ultimate shareholder is the central government and zero otherwise; BIG
10, which equals one when the firm’s auditor is one of the 10 largest accounting firms based on client
assets in China and zero otherwise; LAYERS, which represents the number of layers between the listed
firm and its ultimate shareholder; Previous year’s ROS, which is the return on sales in the prior year;
SIZE, which is the natural log of total assets at the year end; LEVERAGE, which is the total debt over total
assets at year-end; and MARKET-TO-BOOK, which is the market value divided by book value of total
equity at year-end. An additional independent variable is used for the second test: D_RPS equals one if
the firm reports related sales in any year over the sample period and zero otherwise in column 4; D_RPS
equals one if the firm reports positive abnormal related sales during the year and zero otherwise in column
7. The results presented in columns 1–7 use OLS and the absolute robust t-statistics are based on standard
errors clustered by firm as shown in parentheses
* Significant at 10%; ** Significant at 5%; *** Significant at 1%, two-tailed tests
3.3.2 Earnings management via related sales versus total accruals
Given that Chinese firms can use cash-based related sales to manage earnings, does
this lower their propensity to inflate earnings via total accruals? To answer this
question, we use two approaches, partitioning the sample based on (1) whether firms
have opportunities to use related sales for earnings management and (2) whether
they have actually used related sales in earnings management.
In the first approach, the first subsample (raw RPS [ 0) includes firms that have
related sales in at least one year during the sample period, indicating they are likely
to have the option to inflate earnings through related sales. The second subsample
(raw RPS = 0) includes firms that do not have any related sales during the sample
period, suggesting that managing related sales is unlikely an option.
To test formally whether having the option to manage earnings through related
sales affects accruals management, we regress discretionary total accruals on
INCENTIVE and the control variables used in Table 3 for the first (raw RPS [ 0)
and second (raw RPS = 0) subsamples of firms separately and then pooled together
using a dummy (D_RPS) to test for the difference in the coefficients on
INCENTIVE. D_RPS equals one when firms belong to the first subsample and
123
Propping through related party transactions
93
zero otherwise. Discretionary total accruals are computed using the cross-sectional
modified Jones Model in Dechow et al. (1995). As reported in Table 5, the
coefficient on INCENTIVE is 0.297 for RPS = 0 in column 3, which is higher than
the coefficient on 0.239 for RPS [ 0 in column 2. In the pooled regressions in
column 4, the coefficient on INCENTIVE 9 D_RPS is negative and statistically
significant, further suggesting that discretionary total accruals are less significantly
used when related sales are an available earnings management option.
In the second test, we partition the sample into two groups based on firms’
actual related sales management level. More specifically, we divide the sample
into firm-years that have positive abnormal related sales (RPS [ 0) and those that
do not (RPS B 0). We rerun the regression in columns 2–4 using this new
partition. The results reported in columns 5–7 suggest that when related sales
management is used, firms have are less likely to use total accruals to manage
earnings.
In summary, the two approaches provide evidence that related sales activities do
affect firms’ propensity to manage accruals to meet earnings targets. This provides
support to the argument that related sales serve as a substitute rather than a
complement to total accruals earnings management.
3.4 Related sales, cash transfers and economic institutions
3.4.1 The association between propping and subsequent cash transfers
We now turn to our analysis of the relation between related sales and subsequent
cash transfers. We argue that cash-based related sales can be achieved in the group
context because cash can be transferred back to the buyer via related transactions.
Thus, we predict that related sales earnings management is positively associated
with cash transfers via related lending.
Table 6, column 1, reports the regression results of whether abnormal related
lending is associated with PROP, which is a dummy variable that equals one when
INCENTIVE equals one and abnormal related sales are greater than zero in the
current or prior year and zero otherwise. The results show that related sales earnings
management is associated with related lending. The significantly positive coefficient
on PROP 9 LOCAL indicates that the relation between propping and cash transfers
is more pronounced in local government firms than in nonstate firms. This is
consistent with the results in Table 3 that, compared with private owners, local
governments as controlling owners engage in more cash-based related sales
management and thus transfer more cash back from the listed firms. However, the
coefficient on PROP 9 CENTRAL is significantly negative, despite the prior results
in Table 3 that abnormal related sales are higher among central government firms
than nonstate firms. The weaker link between propping and cash transfers suggests
that central government firms have more resources for cash-based earnings
management and do not need to transfer the cash back.
In contrast to related sales management, further analysis shows that subsequent
cash transfers are not associated with accruals earnings management. More
123
94
M. Jian, T. J. Wong
Table 6 Relation between propping and subsequent cash transfersa
Related sales
Discretionary total accruals
Pooled sample
Subsamples
1
Raw RPS [ 0
2
Raw RPS = 0
3
RPS [ 0
4
RPS B 0
5
-0.036
0.053
-0.009
-0.011
0.019
(1.29)
(1.62)
(0.41)
(0.28)
(0.80)
0.008
0.010
0.017
0.017
0.008
(0.99)
(0.94)
(1.49)
(0.94)
(1.02)
0.006
-0.007
0.026
-0.020
0.008
(0.58)
(0.57)
(1.55)
(0.99)
(0.76)
BIG 10
-0.003
-0.013
0.014
-0.010
-0.007
(0.52)
(1.75)*
(1.24)
(0.66)
(1.15)
LAYERS
-0.001
0.005
-0.002
0.017
-0.002
(0.18)
(0.76)
(0.34)
(1.49)
(0.45)
PROP 9 LOCAL
0.049
-0.022
-0.002
0.027
-0.009
(2.02)**
(1.02)
(0.11)
(1.56)
(0.61)
-0.035
-0.032
-0.019
0.020
-0.010
(1.70)*
(1.42)
(0.83)
(0.67)
(0.59)
PROP 9 BIG 10
-0.017
-0.013
0.004
0.023
0.005
(1.30)
(1.02)
(0.22)
(1.06)
(0.45)
PROP 9 LAYERS
0.018
-0.010
0.008
-0.015
-0.002
(1.55)
(0.92)
(0.90)
(1.02)
(0.29)
Previous year’s ROS
-0.003
-0.014
-0.002
0.003
-0.003
(1.10)
(2.14)**
(0.94)
(0.17)
(1.09)
Rights issue dummy
-0.006
-0.013
0.004
-0.020
0.001
(0.91)
(1.60)
(0.38)
(1.50)
(0.11)
Change in debt
-0.031
-0.026
-0.032
-0.032
-0.033
(3.26)***
(1.83)*
(2.46)**
(1.87)*
(2.97)***
Year Dummies
Yes
Yes
Yes
Yes
Yes
-0.001
PROP
LOCAL
CENTRAL
PROP 9 CENTRAL
Intercept
Subsamples
0.001
-0.002
-0.016
-0.030
(0.08)
(0.12)
(0.84)
(0.89)
(0.05)
N
4,593
2,944
1,649
1,238
3,355
Adjusted R2
0.020
0.010
0.020
0.010
0.005
a
This table presents regression results of whether abnormal related lending is associated with earnings
management through related sales and through discretionary total accruals. We regress abnormal related
lending on PROP, ownership and corporate governance variables and their interaction terms. The
dependent variable, abnormal RPL, is the residual term from the regression of net related lending
(excluding related accounts receivables and related accounts payables) on SIZE, LEVERAGE, MARKETTO-BOOK, and industry dummies (see Appendix 2 for details). In testing the relation between related
lending and related sales (column 1), we set PROP equal to one if the listed firm has propping incentives
(INCENTIVE = 1) and the abnormal related sales are greater than zero in the current or previous year and
zero otherwise. In testing the relation between related lending and discretionary total accruals (columns
2–5), we partition the sample into two subsamples based on (1) whether the firm has opportunities to use
related sales for earnings management, with raw RPS [ 0 (firms with related sales in at least one year
123
Propping through related party transactions
95
Table 6 continued
during the sample period) in column 2, and raw RPS = 0 (firms without any related sales during the
sample period) in column 3; (2) whether the firm uses related sales in earnings management in the year,
with RPS [ 0 (firms-year with positive abnormal related sales in the year) in column 4, and RPS B 0
(firms without positive abnormal related sales in the year) in column 5. Moreover, in this set of
regressions we set PROP equal to one if the listed firm has propping incentives (INCENTIVE = 1) and
the discretionary total accruals are greater than zero in the current or previous year and zero otherwise.
Other independent variables for the regressions include: LOCAL, which equals one if the firm’s ultimate
shareholder is the local government and zero otherwise; CENTRAL, which equals one if the firm’s
ultimate shareholder is the central government and zero otherwise; BIG 10, which equals one if the firm’s
auditor is one of the 10 largest accounting firms based on client assets in China and zero otherwise;
LAYERS, which represents the number of layers between the listed firm and its ultimate shareholder;
Rights issue dummy, which equals one if the listed firm has a rights issue in the year and zero otherwise;
Change in Debt, which is the change in total debt of the listed firm in the current year, divided by total
sales of the firm in the year; Previous year’s ROS, which is the return on sales of the firm in the prior year;
and Year Dummies for calendar years 1998–2002. The results presented in columns 1–5 use OLS and the
absolute robust t-statistics are based on standard errors clustered by firm as shown in parentheses
* Significant at 10%; ** Significant at 5%; *** Significant at 1%, two-tailed tests
specifically, when the sample is partitioned based on raw related sales (Table 6,
columns 2 and 3) or abnormal related sales (Table 6, columns 4 and 5), we fail to
document that abnormal related lending is significantly associated with PROP,
which equals one when INCENTIVE equals one and discretionary total accruals are
greater than zero in the current or prior year and zero otherwise.
3.4.2 Propping and economic institutions
The results reported in Table 7 suggest that the level of market development plays
a role in influencing whether related sales are used for propping. The interactions
between INCENTIVE and the two market institution variables in columns 1 and 2
are statistically significant in the regressions. The coefficient on INCENTIVE 9 Market Development Index is negative and statistically significant with
a t-value of 1.75. A one-standard deviation increase in the Market Development
Index can cause the abnormal related sales to decrease by 0.53% of total sales
(RMB 5.9 million), while it can further reduce the abnormal related sales by
0.79% (RMB 8.9 million) when there is an incentive to meet earnings targets.
Similarly, the coefficient on INCENTIVE 9 Deregulation Index is negative with a
t-value of 1.81 in the regression. Results in columns 3 and 4 show that the effects
of government interventions on propping are not as pronounced as those of the
market institutions. The coefficients on INCENTIVE 9 Unemployment and
INCENTIVE 9 Fiscal Surplus have the expected signs, but they are not
statistically significant.
In summary, the economic institutions of a region in China do influence propping
and the way in which firms manage their earnings. This further supports prior
research that demonstrates the effects of institutions on accounting and the necessity
of paying attention to institutional development when comparing accounting
properties or qualities across countries or regions.
123
96
M. Jian, T. J. Wong
Table 7 Propping and institutional factorsa
INCENTIVE
Market Development Index
1
2
3
4
0.029
0.016
0.021
0.039
(2.12)**
(2.19)**
(1.69)*
(1.88)*
-0.004
(1.52)
Deregulation Index
-0.012
(3.32)***
Unemployment
0.005
(0.53)
Fiscal Surplus
-0.036
(1.69)*
INCENTIVE 9 Market Development Index
-0.006
(1.75)*
INCENTIVE 9 Deregulation Index
-0.008
(1.81)*
INCENTIVE 9 Unemployment
0.015
(1.21)
INCENTIVE 9 Fiscal Surplus
-0.052
(1.59)
Previous year’s ROS
0.010
0.005
0.015
0.010
Year dummy
(0.61)
(0.31)
(0.94)
(0.63)
Yes
Yes
Yes
Intercept
0.011
Yes
0.015
0.001
0.021
(0.96)
(1.77)*
(0.07)
(1.34)
N
4,567
4,567
4,567
4,567
Adjusted R2
0.010
0.010
0.001
0.010
a
This table presents the regression analysis of institutional effects on propping. We regress abnormal
related sales (Abnormal RPS) on INCENTIVE, institutional factors, and their interaction terms.
INCENTIVE equals one when the firm’s ROE is at the margin of qualifying for a rights issue (9–11% for
protected industries and 10–12% for others before 2001; 6–8% afterwards), when the firm’s ROE is just
above zero (0–2%), or when the firm is going to seek a rights issue in the following year and zero
otherwise. Other independent variables include: Market Development Index, which measures the progress
of institutional transformation in China’s 30 provinces (excluding Tibet due to lack of data) and identifies
the differences in institutions and economic policies among various regions (Fan and Wang 2003);
Deregulation index, which measures the degree of deregulation in these different provinces (Demurger
et al. 2002); Unemployment, which is the unemployment rate in the different provinces in China; Fiscal
Surplus, which is the fiscal surplus divided by GDP for the province in which the firm is located; and
Previous year’s ROS, which is the firm’s return on sales in the prior year. The results presented in
columns 1–4 use OLS and the absolute robust t-statistics are based on standard errors clustered by firm as
shown in parentheses
* Significant at 10%; ** Significant at 5%; *** Significant at 1%, two-tailed tests
123
Propping through related party transactions
97
4 Robustness checks
We perform four sets of robustness checks. First, we use gross and industry-adjusted
related sales and related lending for all the regressions.12 In addition, we include
two additional ownership variables, LOCAL and CENTRAL, as independent
variables in the regressions to determine normal related sales and lending (similar
to Appendix 2). All of our main results remained qualitatively the same.
Second, we vary the range of ROE around the earnings targets as a robustness
check. Our main results remain qualitatively the same if we use the following two
sets of ranges: (1) 0–1.5 and 9–10.5% for protected industries and 10–11.5% for
other industries before 2001, and 6–7.5% afterwards, and (2) 0–2.5 and 9–11.5% for
protected industries and 10–12.5% for other industries before 2001, and 6–8.5%
afterwards. As mentioned in footnote 10, we also try to replicate the regression with
pseudo-incentives randomly generated in the feasible ROE range, and the results
suggest that our tests are well specified.
Third, we use other related party items to proxy for propping. In addition to
related sales, we use related purchases as another propping mechanism. Controlling
owners can reduce their listed firms’ cost of goods sold through granting significant
purchase discounts. However, when related purchases, instead of related sales, are
used in the Table 3 regressions, the coefficient on INCENTIVE becomes statistically
insignificant. This suggests that Chinese listed firms tend to not use related
purchases for propping. One potential explanation is that, since the last-in-first-out
cost flow assumption is not allowed in China, the parent companies might choose
other more ‘timely and efficient’ ways to prop up listed firms. Another possible
reason is that propping through reducing the listed firm’s cost of goods sold may
result in a decrease in the total amount of related purchases. The parent company
could simply reduce the per-unit charge while maintaining the total quantity sold to
the listed firm, thereby lowering the total amount of related purchases. This would
work against finding a positive correlation between related purchases and the
earnings management incentive.
Firms can also use asset or cash injections for propping. These include sales of
assets and shares, exemptions for rent or other charges, and debt-asset swaps.
However, there is no strong evidence that firms use asset or cash injections to inflate
earnings to meet listing or rights issue earnings targets. One possible reason for not
finding results with asset injections is that these one-time items can be easily
detected by securities regulators and thus are not commonly used to meet the
government’s earnings targets. Also, the frequency of these transactions is low
(around 10% occurrence in our sample), which lowers the power of our tests.
To ensure that the relation between related sales and related lending is not
spurious (that is, firms with more related party transactions have more related sales
and related lending), we regress abnormal related lending on abnormal related sales,
INCENTIVE and the interaction between the two variables. The coefficients on
abnormal related sales and the interaction term are both positive and statistically
12
An industry-adjusted related party transaction is the gross figure minus the industry mean figure of the
same year based on the CSRC industry classification.
123
98
M. Jian, T. J. Wong
significant, which show that the positive relation between abnormal related sales
and abnormal related lending is particularly high when there is an incentive for
earnings management. This provides evidence that the relation is not driven by
spurious correlations. We also rerun regressions in column 1 of Table 6 using PROP
based on lagged related sales. That is, the dependent variable is the abnormal related
lending in year t, while the independent variable, PROP, equals one when
INCENTIVE equals one and abnormal related sales are larger than zero in year t - 1
(lag one period). The result remains qualitatively the same.
Note that in our definition of related lending, we exclude the possibility of cash
transfers through trade credits (accounts receivable and payable) because these items
are likely to be associated with related sales or purchases. As a diagnostic check, we
repeat the analyses by including these two items in the related lending calculations. All
the main results in Tables 6 remain qualitatively the same.
Fourth, both of our test variables, related sales and related lending, are highly
skewed. To address this potential problem, we winsorize the two variables at the top
and bottom 5% to avoid extreme values in all of our regressions. In addition, we
rerun all regressions using rank regressions. All major results remain unchanged.
5 Conclusion
This study uses a sample of firms listed in China from 1998 through 2002 to provide
evidence of propping through related party transactions. China offers a natural
setting for studying the shifting of resources between controlling owners and listed
firms due to its underdeveloped capital, product, and labor markets; bright-line rules
for share issuance and delisting; and weak legal and market institutions.
Our evidence shows that controlling owners of Chinese listed firms engage in
propping through related sales. The increase in related sales is associated with higher
operating profits, and related sales are used to damp negative industry earnings
shocks when listed firms have incentives to manage earnings. By using such intercompany trades to meet securities regulators’ earnings targets, the controlling owners
help the listed firms maintain their listing status or qualify for rights issues.
Propping through related sales can be effected through cash-based, rather than
entirely accrual-based, transactions. Related sales and discretionary accruals are
found to be substitutes for earnings management. When firms generally have sales
transactions with their related parties or they have positive abnormal related sales,
they have a weaker tendency to use discretionary accruals to meet earnings targets.
However, we find that firms have a stronger tendency to use discretionary accruals to
inflate earnings when they do not have related sales or when they have not engaged in
related sales management. Also, cash-based propping through related sales is
associated with the transfer of cash back to the controlling owner through related
lending. Since discretionary accruals management does not involve cash transfers,
such earnings management activity is not linked with subsequent cash transfers.
Finally, we document that the degree of propping is significantly lower in regions
with stronger economic institutions than in those with weaker economic institutions.
123
Propping through related party transactions
99
Acknowledgements This paper, previously titled ‘‘Earnings Management and Tunneling through
Related Party Transactions: Evidence from Chinese Corporate Groups’’, has benefited from discussions
with seminar participants at the Chinese University of Hong Kong, the Hong Kong University of Science
and Technology, Nanyang Technological University of Singapore, Shanghai University of Finance and
Economics, the University of Hong Kong, the 2003 European Finance Association Conference, the 2004
Asian Finance Association Meeting, the 2004 American Accounting Association Annual Meeting, and
the 2005–2006 Global Issues in Accounting Conference at University of North Carolina—Chapel Hill.
We especially appreciate comments from Kee-Hong Bae, Robert Bushman, Kalok Chan, Kevin Chen,
Joseph Fan, Chul Park, Joseph Piostroski, Gordon Richardson, Woody Wu, and Tianyu Zhang. Any errors
are our own. We thank Tianyu Zhang for providing the pyramid data. We also acknowledge the financial
support of the Direct Allocation Grant at the Chinese University of Hong Kong and Singapore Ministry of
Education Academic Research Fund Tier 1, Grant number of project SUG 1/04.
Appendix 1
Correlation matrix
This table presents the correlation matrix for all variables used in Tables 3 through
7. The variables include: Abnormal RPS, which is the residual term from the
regression of related sales on SIZE, LEVERAGE, MARKET-TO-BOOK, and industry
dummies (see Appendix 2 for details); Abnormal RPL, which is the residual term
from the regression of net related lending (excluding related party accounts
receivables and related party accounts payable) on SIZE, LEVERAGE, MARKETTO-BOOK, and industry dummies (see Appendix 2 for details); Operating profit
from abnormal RPS, which equals abnormal RPS multiplied by the firm’s average
operating profit margin, divided by the firm’s total equity at year-end; discretionary
related receivable, which is the residual term of the annual regression model in
which related party accounts receivable is regressed on related sales; discretionary
total accruals from the cross-sectional modified Jones Model in Dechow et al.
(1995); the firm’s change in ROS (DROS), which is the ROS of the current year
minus the ROS of the prior year; DIND_ROS, which is the change in industry
average ROS (excluding the tested firm’s change in ROS) based on the industry
classifications in Table 1; NEGATIVE SHOCK, which equals one when DIND_ROS
is negative and zero otherwise; DRPS, which is the change in abnormal related
sales; INCENTIVE, which equals one when the firm’s ROE is at the margin of
qualifying for rights issue (9–11% for protected industries; 10–12% for other
industries before 2001; 6–8% afterwards), when the firm’s ROE is just above zero
(0–2%), or when the firm is going to seek a rights issue in the following year and
zero otherwise; PROPRPS, which equals one if the listed firm has propping
incentives (INCENTIVE equals one) and abnormal related sales are greater than zero
in the current or previous year and zero otherwise; PROPacc, which equals one if the
listed firm has propping incentives (INCENTIVE equals one) and discretionary
accruals are greater than zero in the current or previous year and zero otherwise;
LOCAL, which equals one when the firm’s ultimate shareholder is the local
government and zero otherwise; CENTRAL, which equals one when the firm’s
ultimate shareholder is the central government and zero otherwise; BIG 10, which
equals one when the firm’s auditor is one of the 10 largest accounting firms based on
123
123
0.00
0.40
0.04
0.67
0.04
0.02
0.06
-0.03
0.06
-0.05
-0.08
NEGATIVE SHOCK
DRPS
INCENTIVE
PROPRPS
PROPacc
LOCAL
CENTRAL
BIG 10
LAYERS
Market
Development
Index
Deregulation Index
0.00
0.00
0.00
0.02
LEVERAGE
SIZE
MARKET-TO-BOOK
Previous year’s ROS
0.01
0.01
DIND_ROS
Fiscal Surplus
0.00
0.01
DROS
0.02
0.01
0.01
0.02
Discretionary total
accruals
Unemployment
0.03
0.06
Discretionary related
receivable
-0.02
-0.10
0.21
-0.19
0.02
0.00
0.00
0.06
0.00
0.08
-0.01
0.02
-0.03
0.01
0.02
-0.01
0.03
0.02
0.07
1
0.12
Abnormal
RPL
Operating profit from
abnormal RPS
Abnormal
RPS
Abnormal RPL
Appendix 1
-0.01
0.04
-0.03
0.02
0.01
-0.01
0.03
0.02
0.01
-0.01
-0.01
0.01
0.01
0.04
-0.01
0.07
-0.01
0.00
0.03
0.00
0.02
1
-0.01
0.01
-0.01
0.00
0.00
0.00
0.00
0.00
0.00
-0.01
0.01
-0.01
0.02
0.01
0.01
0.10
0.00
0.00
0.01
-0.01
1
Operating profit from Discretionary
abnormal RPS
related receivable
0.01
0.02
-0.04
0.02
-0.02
0.00
0.00
-0.01
0.01
0.00
0.01
-0.01
0.10
0.02
0.05
0.00
0.00
0.01
0.02
1
Discretionary
total accruals
1
0.03
0.01
0.02
0.64
0.05
0.01
0.01
0.07
0.01
-0.16 -0.03
0.01
0.16
-0.25 -0.07
0.03
-0.02 -0.12
0.00 -0.01
0.01 -0.01
0.03 -0.03
0.01
0.04 -0.01
0.03
0.08 -0.02
0.06
0.57
0.02
0.02
0.09
1
DROS DIND_
ROS
-0.02
0.06
-0.08
0.02
0.04
-0.17
0.05
0.04
-0.01
0.02
0.00
0.00
-0.04
0.00
0.00
0.03
1
NEGATIVE
SHOCK
0.03
0.01
0.04
0.02
0.28
0.12
1
0.01
0.20
0.02
0.06
0.01 -0.14
-0.01
-0.01 -0.32
0.01
-0.01 -0.04
-0.01 -0.05
-0.01 -0.03
0.01
0.00
0.00
0.01
-0.01
0.03
0.02
1
DRPS INCEN
TIVE
0.04
-0.02
0.02
0.01
-0.01
0.03
-0.10
-0.07
0.05
-0.04
0.05
0.03
0.07
1
0.07
-0.07
0.01
-0.08
-0.06
-0.02
-0.10
-0.09
0.02
-0.06
0.02
-0.03
1
0.01
-0.13
0.07
-0.04
-0.06
0.04
-0.06
-0.05
-0.22
-0.07
-0.55
1
PROPRPS PROPacc LOCAL
100
M. Jian, T. J. Wong
0.01
Rights Issue Dummy
-0.05
0.01
Previous year’s ROS
Change in debt
-0.04
MARKET-TO-BOOK
0.13
-0.13
LEVERAGE
SIZE
0.05
0.00
Deregulation Index
Fiscal Surplus
0.00
Market Development Index
-0.10
0.31
Unemployment
0.05
-0.03
-0.04
0.03
0.04
0.15
0.01
0.11
0.05
0.20
0.20
0.06
1
BIG 10
-0.04
-0.01
-0.01
-0.03
0.02
0.08
0.06
0.02
0.03
-0.03
0.08
0.07
1
LAYERS
Operating profit from
abnormal RPS
CENTRAL
-0.13
LAYERS
-0.03
Change in
debt
0.00
Abnormal
RPL
BIG 10
0.01
Rights Issue
Dummy
Abnormal
RPS
Appendix 1 continued
-0.07
-0.06
-0.02
0.03
0.12
0.01
0.74
-0.08
0.84
1
Market
Development
Index
0.03
0.01
Discretionary
related receivable
-0.05
-0.08
-0.02
0.05
0.11
0.09
0.42
-0.12
1
Deregulation
Index
0.04
0.03
1
0.01
-0.11
-0.02
-0.11
0.04
0.04
-0.05
0.05
-0.10
-0.01
-0.01
0.01
0.16
-0.06
1
Fiscal
Surplus
-0.15 -0.05
0.03
DROS DIND_
ROS
Unemployment
Discretionary
total accruals
1
0.35
-0.13
-0.03
0.17
-0.44
-0.04
0.01
0.03
-0.44
1
SIZE
-0.01 0.03
0.03 0.14
0.02
0.00
1
-0.09
-0.06
-0.08
0.09
0.03
1
Previous
year’s
ROS
0.13
0.14
0.01
1
Rights
Issue
Dummy
-0.04
0.01
PROPRPS PROPacc LOCAL
MARKET
TO-BOOK
DRPS INCEN
TIVE
LEVERAGE
0.00
0.06
NEGATIVE
SHOCK
Propping through related party transactions
101
123
102
M. Jian, T. J. Wong
client assets in China and zero otherwise; LAYERS, which represents the number of
layers between the listed firm and its ultimate shareholder; Market Development
Index, which measures the progress of institutional transformation in China’s 30
provinces (excluding Tibet due to lack of data) and identifies the differences in
institutions and economic policies among various regions (Fan and Wang 2003);
Deregulation index, which measures the degree of deregulation in these different
provinces (Demurger et al. 2002); Unemployment, which is the unemployment rate
in different provinces in China; Fiscal Surplus, which is the fiscal surplus divided by
provincial GDP for the province in which the firm is located; LEVERAGE, which is
total debt over total assets at the year-end; SIZE, which is the natural logarithm of
total assets at the year-end; MARKET-TO-BOOK, which is market value divided by
book value of total equity at the year-end; Previous year’s ROS, which is the return
on sales of the firm one year before the related party transaction occurs; Rights issue
dummy, which equals one if the listed firm has a rights issue in the year and zero
otherwise; and Change in Debt, which is the change in total debt of the listed firm in
the current year, divided by the total sales of the firm over the year.
The numbers shown in the table are the Pearson correlation coefficients. If the
absolute value of the coefficient is higher than 0.04, it is significant at the 1%
level.
123
Propping through related party transactions
103
Appendix 2
Abnormal related party transaction regressions
Independent variables
Dependent variables
Related sales
coefficients
Min
LEVERAGE
Max
Related lending
coefficients
# of
Sig
-0.186 -0.155 5
SIZE
Min
-0.070
Max
# of
Sig
0.116 2
0.019
0.028 5
-0.049 -0.013 3
MARKET-TO-BOOK
-0.001
0.013 3
-0.008
0.011 2
Industry
dummy
-0.006
0.059 0
-0.136
0.073 1
Mining
0.066
0.225 4
-0.123
0.043 0
Food & Beverage
0.019
0.076 1
-0.075
0.028 0
Textile, Apparel, Fur and Leather
0.028
0.087 3
-0.063
0.153 1
Furniture Manufacturing
0.082
0.769 2
-0.136
0.517 1
Paper and Allied Products; Printing
0.043
0.121 2
-0.071
0.156 1
Petroleum, Chemical, Plastics, and
Rubber Products Manufacturing
0.056
0.108 5
-0.090
0.076 3
Electronics
0.021
0.055 0
-0.066 -0.029 0
Metal, Non-metal
0.109
0.158 5
-0.080
0.098 2
Machinery, Equipment, and Instrument
Manufacturing
0.067
0.100 5
-0.053
0.026 0
Farming, Forestry, Animal Husbandry,
and Fishing
Medicine and Biological Products
Other Manufacturing
Utilities
N
Adjusted R2
0.017
0.118 3
-0.031
0.075 0
-0.035
0.107 1
-0.048
0.178 1
0.148
0.267 5
-0.099 -0.025 1
Construction
-0.007
0.038 0
-0.106
0.033 0
Transportation and Warehousing
-0.046 -0.001 0
-0.113
0.066 1
Information Technology
-0.008
0.040 0
-0.120 -0.022 2
0.007 0
Wholesale and Retail Trade
-0.015
Banking & Financial Institutions
-0.098 -0.017 0
-0.106
0.000 0
Real Estate
-0.011
-0.109
0.101 1
0.042 0
-0.135 -0.017 4
Public Facilities and Other Services
-0.030
0.018 0
-0.073 -0.043 0
Communication and Cultural Industries
-0.037
0.049 0
-0.136
0.106 0
Conglomerates
-0.332 -0.221 5
0.183
0.783 4
816
0.080
1124
0.110
816
0.001
1122
0.030
123
104
M. Jian, T. J. Wong
This table presents the results on abnormal related party transactions. Annual
regressions are run using related sales (RPS) and related lending (RPL) as dependent
variables and LEVERAGE, SIZE, MARKET-TO-BOOK, and the Industry dummies
(see Table 1 for SIC equivalence). SIZE is the natural logarithm of total assets at
year-end; LEVERAGE is total debt over total assets at year-end, and MARKET-TOBOOK is the market value divided by book value of total equity at year-end. The
numbers reported in the table are the maximum and minimum coefficients in the
five annual regressions (1998–2002) and the number of significant coefficients (10%
level, two-tailed). The residuals obtained from these annual regressions are used to
proxy for abnormal related sales and related lending in later analyses.
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