Earnings Conservatism Perspective: Political Connections and Earnings Quality

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Earnings Conservatism Perspective: Political Connections and
Earnings Quality
—Evidence from China’s Private Listed Enterprises
ZENG Zhaoming1, LI Xinyi2, YUE Hong3
1. Management School, Jinan University, P.R. China, 510632
2. School of Business, Beijing Technology and Business University, P.R. China, 100048
3. Public Administration Department, Beijing City University, P.R. China, 100083
[email protected]
Abstract: This paper investigates the relationship between political connections and earnings quality of
China’s private listed enterprises based on the perspective of earnings conservatism, which can help to
test the negative impact political connections may have on the private firms’ accounting
information quality. Our study suggests that, other conditions being equal, China’s private listed firms
with political connections have poorer earnings quality than their non-connected peers. Additionally, the
more closely private listed firms are connected with government, the poorer their earnings quality is.
Keywords: Political Connection, Earnings Quality, Private Listed Enterprises
1
Introduction
Earnings quality is an important component of accounting information quality, which can be measured
from various perspectives such as earnings conservatism, predictability, transparency and
value relevance. Dechow and Schrand (2004) suggest that high quality earnings are required to meet
such conditions: First to reflect current operating conditions, provide a more favorable forecast for
future operations, and then be able to truly reflect the company's intrinsic value. Therefore, high
financial reporting quality should be more sustainable and stable, more relevant to future cash flows and
the company's share price or market value. They also point out that only when the company’s earnings
reflect the true value of the company, the sustainability and stability can make sense. The effect of
earnings forecasts cannot be guaranteed if we consider the sustainability and stability in isolation. The
accrual-based measure is one of the vital methods to measure earnings conservatism. Givoly and Hayn
(2002) find that earnings conservatism leads to the reduction of the cumulative reporting earnings in the
accounting period, which is showed as stability negative accrual. So they think that the signal and
amount of cumulative accrual in each accounting period can be a symbolic measure of the earning
conservatism. In the unconservative stability condition (up to 0), the profit keeps consistent with the
cash flows, the accrual will be 0. Ahmed et al. (2002) also believe that the average accrual of the
company in a long period can be an alternative variable to measure the company conservatism. Our
study also adopted the accrual quality as proxy to measure the earning quality from the earning
conservatism perspective.
There are many reasons which may affect the quality of the real earnings absorbed by investors,
especially for China, a country with special institutional background. Of course, political connections
are one of the most important factors among so many factors, which is the truth all around the world not
only in China. In their book named "The Grabbing Hand: Government Pathologies and Their Cures",
well-known economists Andrei Shleifer and Robert W. Vishny (1996) mention three models of
government, which are the invisible hand model, the helping hand model and the grabbing hand model.
They argue the government may perform as the invisible hand when markets work very well and the
helping hand to maximize social welfare when market failures happen; once the government plays as a
grabbing hand, it will be social and economic disaster. The book believes that Russia's transition has
been more difficult in the mid-1990s because of the government's role of the grabbing hand, and the
helping hand is critical to the success of China's reform. Although, the government often plays three
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roles simultaneously to influence the entire society in real life, which makes the role government played
in the economy at different times an ever-changing, never-out-of-date research subject. Under such a
historic background of the increasing trend toward global economic integration today, companies’
political competition is also increasing, more and more enterprises begin to deliberately seek a
reasonable political protection. Because the government's implementation of each policy will definitely
have influence on businesses, major or little, of course companies will not passively wait for the policy
constraints, but actively build and acquire political resources through appropriate channels and methods,
participate in or influence the policymaking process to develop or implement political strategies
conducive to themselves (Wei and Tian, 2004; Wei, 2006). Faccio (2006) points out that political
connections are widespread in the world. Because of the universality of its existence and importance of
its impact on corporate behavior, political connection has become unavoidable practical economic
problems, and also theoretical issues that economics, management and other disciplines focus on. The
existing researches on correlation of political connection at home and abroad focus on its impact on the
company's level of performance, value, taxes and preferential lending, and few on its impact on
accounting information quality, even fewer studies of correlation between political connections and
accounting information quality from the perspective of earnings conservatism using accrual as a variable
to measure the earning quality. Our study proves that earnings quality of China's private listed
companies with political connections is poorer than that of non-connected firms using measurement of
dummy variable, and verifies it with assigning method.
In this study, we build the empirical analysis model between political connections and earnings quality,
which on the one hand provides information about the accounting information quality of China's private
listed companies, on the other hand sets off alarm bells of monitoring for our government and other
regulatory authorities, making our research have a strong theoretical and practical significance. The
upcoming chapters of this paper is organized as follows: Part Two, based on the literature review and a
theoretical analysis, we propose relevant hypotheses; we then focus on research design and sample
selection in Part Three; The empirical results are described and analyzed in the fourth part; in the fifth
and final part, we conclude with a discussion of future research prospects.
2
Literature Review and Hypothesis Development
2.1 Political Connections
Political connections had a very significant impact on enterprises' economic activities (Fisman, 2001;
Ferguson and Voth, 2008; et al.), for political connections is essentially a valuable resource with
reputation value and protection function (Fisman, 2001). As an important reputation mechanism,
political connections is also a social resource of companies for improving the possibility of direct appeal
to the authorities (Sun, Liu and Li, 2005; Ethan Michelson, 2006). In real life, government officials
served as symbols of individual social class status. In this situation, firms connected with government
officials (especially senior government officials) can to a certain extent improve corporate image and
reputation of lawful operation (Wei, 2006). Entrepreneurs’ political identity such as NPC deputies or
CPPCC members not only shows the enterprise’s considerable economic strength, but also shows it is in
good recognition of community and the government, which is a good social signal (Luo and Tang, 2009).
This signal makes banks, corporations’ mutual property and legal system integrated into institutional
environment of public authorities, giving rise to such a phenomenon, that firms with different political
connections have quite distinct abilitiies to get access to economic resources in the market mechanism
which seems fair on the surface. Also, a study by Xin and Pearce (1996) has shown that through the
establishment of certain political ties, private firms can gain support and protection which it is difficult
to get from law and the formal system. Faccio (2004) suggests political connections help firms be more
likely to escape stringent regulation by government, thereby reduce the cost of contract. For enterprises
in states whose markets are at a transition period and system is not that perfect, establishing connections
with the government to some extent is a positive response (Chenetal, 2005; Yu and Pan, 2008; Luo and
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Tang, 2009; et al.). Although, the establishment of political ties will bring some negative effects to firms
or community (Shleifer and Vishny, 1994; Faccio and Larry, 2002; et al.).
Krueger (1974) find that among the reasons why so many firms pursue political connections, the most
important one is that it can bring huge benefits to them. In other words, connections with the
government, on the one hand enable enterprises to significantly reduce the possibility of occupation, on
the other, provide means for companies to enjoy priviledges such as government subsidies, low-cost
financing, tax reduction and so on (Shleifer and Vishny, 1994). These benefits in some cases even far
exceed economic profits created by the business itself.
Political connections bring lots of gains for firms, and firms should also make payments to maintain this
kind of connections (Fan, Wong and Zhang, 2007). To support their rent-seeking activities, politically
connected companies need to inject additional resources, which even to some extent offset the benefits
gained from political connections (Bennedsen, 2000; Fisman, 2001; Johnson and Mitten, 2003). For
example, political connections may weaken the the role of signal and insurance of independent audit and
sometimes may lead to an increase in inefficient employment of firms (Wang, Wong and Xia, 2005;
Bertrand et al., 2004, 2006).
Political connections lead to lower quality of accounting information. Ball, Kothari and Robin (2000)
find that political connections to a certain extent, lower the quality of accounting information, and the
connections also increase the political risk and information risk of firms (Liao and Wang, 2007). In
contrast, local government has a higher information risk (Piotroski, Wong and Zhang, 2008). As for
listed companies, on the one hand the proportion of companies whose income in lower transparency is
positively correlated with the proportion of companies politically-connected, on the other hand the
proportion of politically-connected companies in market value has a significant negative correlation
with the degree of law enforcement, but has no significant relationship with the use of accounting
standards or the number of auditors, which confirms that the political environment is a key factor
affecting the quality of accounting rather than technical factors (Ahmed Riahi-Belkaoui, 2004). Chaney,
Faccio and Parsle (2008) report that managers of politically-connected firms have lesser need to respond
to market pressures to improve the quality of accounting information in contrast with those without
political ties. Hence, appearance is that the politically-connected firms have significantly lower earnings
quality than their non-connected peers, and the degree of political connections has a significant negative
correlation with earnings quality.
2.2 Political Connections and Earning Quality
There are relatively few studies on the association between firms’ political connections and the quality
of their reported earnings and two completely opposite conclusions are reached: political connectedness
has been documented to have both positive effects and negative effects on earnings quality of firms. Of
course, from the existing literature, the majority of scholars believe that: political connections lead to
lower quality of accounting information and increase the political risk and information risk at the same
time, especially firms connected with the local government has much higher information risk (Piotroski,
Wong and Zhang, 2008). Comparing with firms not connected with government, politically-connected
firms tend to neglect to improve the quality of accounting information, thus the quality of their reported
earnings is significantly lower than that of their non-connected peers. Additionally, among the firms
connected with government, quality of earnings reported becomes lower along with the strengthening of
their political connections (Chaney, Faccio and Parsley, 2008). Yan Zi (2010), however, has conducted a
study in depth on the subject, whether political ties will affect firms’ earnings quality, from the
perspective of decision usefulness of accounting information, using Chinese A-share private listed firms
in Shenzhen and Shanghai from 2006 to 2008 as the research sample. In her study, firms are defined as
politically connected if the firms’ chairman or general manager is currently serving or formerly served in
the government or as member of CPPCC, deputy to the NPC. She analyzes earnings quality of the
sample companies from the perspective of ERC (Earnings Response Coefficient) and earnings
management, reaching the following results: private enterprises without political connections have
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conducted more earnings management than those connected peers; additionally, political connections
have enhanced the information content of accounting earnings in the stock price to some degree. Based
on the majority opinion of prior research, we consider that in China, political connections will also lead
to lower earnings quality for private listed firms.
Following the literature, we propose a hypothesis: other conditions being equal, China’s private listed
firms with political connections have a poorer earnings quality than their non-connected peers. In other
words, political connections have a negative effect on earnings quality of private listed companies.
3
Research Design
3.1 Data
This paper selects data from Chinese private listed A-share companies in Shanghai and Shenzhen from
2004 to 2009, excluding financial stocks, and ST, PT stocks, which can meet the conditions below, with
complete data of stock trading prices. Our original sample includes 427 firms and 2,562 firm-year
observations from 2004 to 2009.
In the DD model, we need the data a year ahead and a year behind to measure the discretionary accruals,
which further to calculate the standard deviation of the discretionary accruals in the past 5 years. In
addition to the conditions above, the complete financial data and stock return data between 1999 and
2010 must be selected, so the companies going public in 2006 or after 2006 should be excluded (100).
And companies with missing data should be excluded (113). Then we get an effective sample which
totals 214. Our financial data and stock returns data are obtained from the China Stock Market and
Accounting (CSMAR) database, and the data of political connections are collected manually. We
manually collect politically related information on directors, supervisors, managers and other senior
management members of all private listed A-share companies in China from 2004 to 2009 from their
resumes disclosed in firms’ annual reports. We trace political connections by examining whether
directors, supervisors, managers and other senior management members are currently or were formerly
an officer of the government or military, using two kinds of methods to measure the political
connections. All the data are processed with Excel 2003 and STATA 9.0.
We take only the private listed companies as our sample, the reasons for which are as follows: first of all,
the availability of data, unlisted firms’ data are hard to obtain, and their management change frequently;
second, compared to state-owned firms, the ultimate owners of private firms are individuals, and their
management appointment is not subject to direct government intervention, so hiring executives with
political connections is completely of their own behavior and selecting private firms as our research
sample can avoid the influence of the close ties between state-owned firms and the government; third, in
China, state-owned enterprises have typically enjoyed an advantageous position in the state’s major
resource industries, basic industries and are commonly subject to state intervention. The factors which
may affect their earnings quality are complex and difficult to judge fairly and effectively. Therefore, we
choose the private listed firms as our sample, which have much simpler association with the government
and better to determine objectively, and the results can be more effective to show the impact of firms’
political connections on their earnings quality.
3.2 Measurement of the Key Variables
3.2.1 Measure of political connections
The measures of firms’ political connections can be divided into two categories: one is measured by
senior managers’ or their related characteristics’ political connections; the other method is using firms’
other characteristics to measure the firms’ political connections. Following Fan, Wong, and Zhang (2007)
and other literature, we define a firm as politically connected if it has senior managers with political ties.
However, we extend the range of “senior managers” to include all the non-independent directors and
other management disclosed by the firm, with the exception of the independent directors and external
supervisors. Specifically noted, the independent directors are excluded because they are required to
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maintain their independence from the firms they work for.
We manually collect sample companies’ publicly disclosed annual financial reports from 2004 to 2009,
tracing the appointment information (formerly, currently and concurrently served as some kind of
political positions) from “resumes of non-independent directors and senior managers”, and then use
dummy variable to measure their political connections. Gov is a dummy variable set equal to 1 if the
firm is politically connected and 0 otherwise. A company is classified as politically connected if it has at
least one senior manager who is currently serving or formerly served in the Party Committee, the
Discipline Inspection Commission, the government, NPC (National People's Congress) or CPPCC
(Chinese People's Political Consultative Conference), the people’s court, the people’s procuratorates, the
military, and so on.
3.2.2 Measure of earnings quality
Accrual is an important carrier to measure the impacts earnings have on its measuring ability of
performance or the information content of earnings in the accrual basis of accounting. Healy first
introduced the concept of “accrual” in 1985 and used its narrow sense to measure discretionary accruals
in order to reflect the earnings quality. Accrual quality is an important component of earning quality, and
also one of vital characteristics of earnings quality, so we use accrual as an indicator to measure earnings
quality. That is to say, the larger a firm’s discretionary accrual is, the lower its earnings quality is, and
the converse is also true. There are two commonly used methods to measure the discretionary accruals
in most existing empirical studies: one is the DD model based on the relationship between accruals and
cash flows, the other one is the Jones model with cross-section data. And we adopt the DD model to
measure the accruals in this study.
Following Dechow and Dichev (2002) and Francis etc. (2005), we calculate the company’s accruals
quality (AC) in the year t.
TAj,t =a0 + a1CFOj,t-1 + a2CFOj,t + a3CFOj,t+1 + a4 REVj,t + a5PPEj,t + εj,t
1
Where TA j, t is firm j's total accruals in year t, and TA j, t = Net Income (NIj, t) - Net Cash Flow from
Operating Activities (CFOj, t), REVj, t is the variation of firm j's revenues from year t-1 to t, PPEj, t is
firm j’s net fixed assets in year t. The residual ε j, t is firm j’s discretionary accruals in year t, expressed as
DA; the fitting value of TAj, t is firm j’s inherent accruals in year t, expressed as IA. All variables are
deflated by lagged total assets. TA, IA and DA measure the size of the firm’s accruals that year, and they
can be defined as short-time accruals. They are all opposite indicators, showing the firm’s level of
accrual quality in a given year.
Meanwhile, according to Francis et al. (2005), based on the short-time accrual, we modified the model
to measure the firm-level long-term accrual quality, which can be divided into inherent accrual quality
and discretionary accrual quality.
On a yearly basis, we use formula (1) to estimate each CSRC industry group, of which the
manufacturing industry group C is grouped according to secondary code, arriving at 20 industry groups
in all, each with at least 10 firms. Using formula (1) to estimate by year with cross-section data, we can
get a specific firm’s residual ( εj,t ) in a given year, and construct the basic indicator AQj, t to measure the
accrual quality. AQj, t is the standard deviation of the firm j’s residuals from year t-4 to year t; these two
indicators are both positive indicators, and high AQj, t means low accrual quality. It should be noted that
if a firm’s residuals from year t-4 to year t which are derived with formula (1) are large, the standard
deviation of the residuals will be small. In this case, the companies may have fairly good accrual quality
because the uncertainty of their accruals is low.
△
△
（）
3.3 The Regression Model and Control Variables
Based on our hypothesis before, we calculate the regression models using the following general form:
AQ j ,t = b0 + b1Gov j ,t + b2 LNSize j ,t + b3 STDCFO j ,t + b4 STD Re v j ,t + b5 NegEarn j ,t + v j ,t
Where the control variables are:
LNSize j ,t = the natural logarithm (ln) of firm j’s total assets at the end of year t
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STDCFO j ,t = the standard deviation of firm j’s CFOs during the past 5 years
STD Re v j , t = the standard deviation of firm j’s total sales during the past 5 years
NegEarn j ,t = the ratio of years of loss (firm j’s operating profit is negative) among the past 5 years
4
Empirical Results and Analysis
4.1 Descriptive Statistics
Table 1 presents the descriptive statistics on the political connectedness of the 214 sample firms by year.
From 2004 to 2009, in China’s private listed companies, there are respectively 132, 130, 113, 96, 84, 81
companies are with political ties, covered about half of these companies on average. However, in
general, it shows a decreasing trend, the ratio of the sample with political connections to the full sample
gradually decreases over time from 62% in 2004 to 38% in 2009. The ratio decreases rapidly from 2007,
which may arise in part from that there are a large number of SMEs (most are private enterprises) listed
on the GEM (Growth Enterprises Market) in the Shenzhen stock exchanges. These firms are
characteristically engaged in high-tech industries and typically young, thus they seldom have political
ties. We further distinguish between two kinds of political ties: having senior managers who "formerly
served in government" and "formerly served or currently serving as NPC deputies or CPPCC members",
and the first group occupied the 34% of the full sample, while the second group occupied only 15% of
the full sample. Meanwhile, there are a number of firms have executives formerly served as both
government officials and NPC deputies or CPPCC members. Above all, it shows that political ties are
common among Chinese private enterprises.
Table 1 Descriptive Statistics of Political Connections
Year
2004
2005
2006
2007
2008
2009
Average
2004-2009
# of total sample firms
214
214
214
214
214
214
214
#
%
132
130
113
96
84
81
62
61
53
45
39
38
106
50
#
%
102
97
86
61
48
46
48
45
40
29
22
21
#
%
30
33
27
35
36
35
14
15
13
16
17
16
Connected firms
a.“Government officials” connections
b. “Members of NPC or CPPCC”
connections
73
34
33
15
Using equation (1) we regress the company’s data in the past 5 years to get the standard deviation of the
regression residual, which is used to calculate the company accruals quality AQ in each year.
Table 2 Descriptive Statistics of Accruals Quality
Year
Mean
Median
Standard
Deviation
Min
Max
Observations
2003
2004
0.0435
0.0458
0.0281
0.0299
0.0466
0.0464
0.0063
0.0061
0.3564
0.3398
214
214
2005
0.0440
0.0282
0.0445
0.0053
0.3414
214
2006
0.0395
0.0264
0.0371
0.0051
0.2584
214
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2007
0.0422
0.0293
0.0370
0.0055
0.2487
214
2008
0.0443
0.0318
0.0368
0.0033
0.2469
214
Table 3 describes each variable’s mean, standard deviation, minimum, maximum and median.
4.2 Regression Analysis
In order to test the hypothesis proposed in this paper, we make use of the DD model to measure the
accruals, define the standard deviation of the accruals’ residuals as the dependent variable, the dummy
variable Gov which represents whether a firm has political connections or not as the explanatory
variable, and introduce the firm size (LNSize), firm’s cash flow from operating activities (STDCFO),
firm’s operating revenue (STDRev), the ratio of years of loss (NegEarn) etc. as our control variables, to
conduct the regression analysis.
Year
2004
2005
2006
2007
2008
2009
Table 3 Descriptive Statistics of Control Variables (2004-2009)
Standard
Variables
Mean
Median
Min
Max
Deviation
Observations
LNSize
20.8296
20.8119
0.8633
17.7510
22.8718
214
STDCFO
0.0841
0.0668
0.0687
0.0111
0.5932
214
STDRev
0.1867
0.1405
0.1568
0.0181
0.9452
214
NegEarn
0.1710
0.0000
0.2383
0.0000
1.0000
214
LNSize
20.9457
20.9163
0.9368
17.5367
23.1867
214
STDCFO
0.0823
0.0655
0.0727
0.0072
0.5990
214
STDRev
0.1790
0.1357
0.1428
0.0201
0.8223
214
NegEarn
0.1813
0.0000
0.2444
0.0000
1.0000
214
LNSize
21.0740
21.0304
0.9680
18.1572
24.1710
214
STDCFO
0.0767
0.0589
0.0684
0.0049
0.6067
214
STDRev
0.1755
0.1145
0.2228
0.0105
2.6473
214
NegEarn
0.2056
0.1000
0.2592
0.0000
1.0000
214
LNSize
21.2201
21.1266
1.0257
18.1861
24.3172
214
STDCFO
0.0804
0.0610
0.0738
0.0073
0.6062
214
STDRev
0.1953
0.1270
0.2672
0.0113
2.9759
214
NegEarn
0.1925
0.0000
0.2503
0.0000
1.0000
214
LNSize
21.2277
21.1342
1.0736
18.1839
24.7892
214
STDCFO
0.0867
0.0641
0.0796
0.0067
0.6104
214
STDRev
0.2317
0.1391
0.4300
0.0096
5.1232
214
NegEarn
0.1832
0.0000
0.2461
0.0000
1.0000
214
LNSize
21.3187
21.2788
1.1455
18.1901
25.0141
214
STDCFO
0.0836
0.0617
0.0712
0.0031
0.4315
214
STDRev
0.2379
0.1357
0.4375
0.0066
5.0043
214
NegEarn
0.1944
0.0000
0.2519
0.0000
1.0000
214
We analyze the panel data from 2004~2009 with STATA 9.0, finding that the Hausman test results of
fixed effects model are not so significant as that of random effects model, thus the generalized least
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squares (GLS) method of random effects model is employed in our study. The regression results are
reported in Table 4.
This table reports the regression results on the association between political connections dummy and
accruals quality. The negative correlation was observed between the accruals quality (AQ) and political
connections (Gov), the firm size (LNSize), and the correlation between the accruals quality (AQ) and
firm’s cash flow from operating activities (STDCFO), firm’s operating revenue (STDRev), the ratio of
years of loss (NegEarn) was positive. Moreover, the coefficients of the variables are all significant in
explaining the accruals quality.
The firm size is correlated negatively with AQ, which can be explained as follows: larger companies
have better institutions and organization; hence their operation and management will have narrower
fluctuation. That means smaller uncertainty of accruals and better earnings quality. On the contrary,
smaller companies have much more fluctuated accruals and are easier to manipulate earnings, so their
earnings quality is lower than those companies of large capital scale.
Table 4 GLS Regression Results of the Random-Effects Model
Variables
Intercept
Gov
Coefficient
8.96
**
2.23
0.7892
-0.0179
STDCFO
LNSize
**
2.28
***
-8.83
*
1.72
4.24e-11
-0.0369
STDRev
7.43e-12
NegEarn
**
0.1414
z Value
***
10.97
2
Adj-R
0.2477
Note: *, **, and *** indicate significance at the 10%, 5%, and 1% levels respectively (2-tailed test).
The standard deviation of firm’s net cash flows from operating activities in the past 5 years, the standard
deviation of firm’s operating revenue in the past 5 years are both correlated positively with AQ. This
suggests that the private listed firms who have more fluctuated cash flows from operating activities and
operating revenue are more likely to conduct windowing dressing of financial statements by
manipulating their accounting earnings. The ratio of years of loss among the past 5 years is correlated
positively with AQ, which indicates that the more years of loss a private listed firm has encountered in
the past 5 years, it may have greater likelihood of earnings manipulation, hence greater volatility of its
accrual earnings, and lower earnings quality.
The results show negative correlation between political connections and accruals quality, and also
support our hypotheses: Other conditions being equal, private listed firms with political connections
have a higher earnings quality than their non-connected peers. In other words, in China’s A-share
market, political connections may to some extent lead to a decline in earnings quality of private listed
companies, and give them an opportunity for earnings management. Our findings accord with the
conclusion Chaney, Faccio and Parsley (2008) reached from the study upon foreign markets: comparing
with firms not connected with government, politically-connected firms tend to neglect to improve the
quality of accounting information, thus the quality of their reported earnings is significantly lower than
that of their non-connected peers. In addition, among the firms connected with government, quality of
earnings reported becomes lower along with the strengthening of their political connections.
4.3 Further Test: Regression of Political Connection Level
Political connections are measured in the form of dummy variable in our previous model, and we draw
the conclusion that earnings quality of the politically connected private listed companies is poorer than
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those non-connected firms. On this basis, in order to provide a further test for whether the following
proposition is true or not: the more closely private listed companies are connected with government, the
poorer their earnings quality is. We employ the assigning method to measure the sample companies’
level of political connections. Considering the specific political conditions in China, with reference to
domestic scholars Hu (2006), Wang and Wu (2008), Deng and Zeng (2009) and Du et al. (2010), we
develop the assigning method based on their approach. The detailed process is as follows:
Regarding “Government officials” connections, the assigning procedures are: Step 1, for company’s
each executive (other than independent director), if he or she is currently serving or formerly served in
the Party Committee, the Discipline Inspection Commission, the government, the standing Body of NPC
or CPPCC, the people’s court, the people’s procuratorates, the military, and so on, we will perform an
assignment respectively according to the highest level of official organ and personal position. The
assignments for different levels ranging from the basic-level to the ministerial-level are: ranking below
deputy chief of section 1, deputy-chief-of-section level 2, section-level 3, deputy-division-level 4,
division-level 5, deputy-bureau-level 6, bureau-level 7, vice-ministerial-level 8, ministerial-level 9;
otherwise, those companies who do not have any political ties is set to 0. Step 2, on the basis of the first
step, there are two types of political connection assignment for each government official: (1) organ level;
(2) personal level. The product of these two values is our final result.
Regarding “Members of NPC or CPPCC” connections, for each company executives (other than
independent directors), if he or she is currently serving or formerly served as the Party representative,
member of CPPCC or deputy to the NPC, we will perform an assignment respectively according to the
level: the township level 1, county level 2 , municipal level 3, provincial level 4, state level 5 (but not
including members of the standing Body of NPC or CPPCC).
Finally, take the maximum of the values from the previous two categories as the value of relevant
company’s political connection level.
Year
Table 5 Descriptive Statistics of Political Connection Level GOVMAX
Mean
Median
Standard Deviation
Min
Max
2004
9.29
9
9.21
0
40
214
2005
8.39
6
8.69
0
28
214
2006
7.79
4
9.30
0
35
214
2007
6.94
0
9.13
0
28
214
2008
6.08
0
8.92
0
25
214
2009
6.52
0
9.50
0
40
214
Observations
We define company’s political connection level generated with the assigning method as the explanatory
variable GOVMAX. Table 5 presents the descriptive statistics for the political connection level variable
GOVMAX from 2004 to 2009.
We remodify the model by replacing the explanatory variable with GOVMAX from the assigning method.
The new model is as follows:
AQ j ,t = b0 + b1GOVMAX j ,t + b2 STDCFO j ,t + b3 STD Re v j ,t + b4 LNOperCycle j ,t + v j ,t
Where: GOVMAXj,t, the explanatory variable, is firm j’s political connection level in year t; the new
control variable LNOperCyclej,t is the natural logarithm (ln) of firm j’s operating cycle (= accounts
receivable turnover period + inventory turnover period) in year t.
Table 6 reports the fixed-effects regression results of the modified model on the panel data.
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Table 6 Fixed-Effects Regression Results of the Modified Model
Variables
Intercept
GOVMAX
STDCFO
STDRev
LNOperCycle
Coefficient
***
6.3696
23.90
***
-0.0036
-2.64
***
4.15e-10
0.1252
t Value
6.32
***
4.00
*
1.93
0.0240
F Value
24.32***
2
Adj-R
0.2214
Note: *, **, and *** indicate significance at the 10%, 5%, and 1% levels respectively (2-tailed test).
The results show that company’s level of political connections (GOVMAX) is correlated negatively with
its earnings quality (AQ), which provides further evidence for our hypotheses: Other conditions being
equal, private listed companies’ earnings quality becomes lower along with the strengthening of their
political connections. The private listed firms who are more closely connected with the government have
much greater chance of earnings manipulation, and their earnings quality is proved to be poorer.
4.4 Robustness Tests
To verify the robustness of the models employed in our previous study, we conduct the following test.
We consider alternative measures of earnings quality or different measures of discretionary accruals
(DA), to verify the reliability of the DD model. We re-calculate the sample companies’ discretionary
accruals and AQ with the modified Jones model (cross-sectionally) and check by resubstitution into the
equation of two models, finding that the final conclusions remain unchanged. However, the coefficients
of the control variables are not so significant with AQ eatimated by the modified Jones model
(cross-sectionally). That indicates DD model is more accurate in measuring the degree of earnings
management than the modified Jones model.
This suggests that our empirical results have strong robustness, and the conclusions are credible and
valid.
5
Conclusions and Future Research Prospects
In this paper, we make use of the DD model to measure the accruals, define the standard deviation of the
accruals’ residuals as the dependent variable, the dummy variable Gov which represents whether a firm
has political connections or not as the explanatory variable, and control for the firm size, firm’s cash
flow from operating activities, firm’s operating revenue, firm’s operating cycle and the ratio of years of
loss etc. as our control variables, to conduct the regression analysis. Our results suggest that, other
conditions being equal, China’s private listed firms with political connections have a poorer earnings
quality than their non-connected peers. In other words, in China’s A-share market, political connections
give them an opportunity for earnings management and have a negative effect on earnings quality of
private listed companies. The reasons for this may be that the government and capital market regulatory
authorities in China are easy to neglect in the supervision and regulation of the politically connected
firms and weaken the punishment upon their illegal behaviours of earnings disclosure, making these
firms pay less attention in developing the quality of their earnings and even intentionally manuplate
their earnings for some benefits.
Our study focuses on the correlations betwwen political connections and accounting information quality,
but it is just a beginning in this field. Future reseachers can also conduct more studies in-depth from the
following two aspects: (1) investigate the impact political connections may have on earnings quality
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from diverse perspectives, such as impact on the predictability, stability, value relevance of earnings, to
study and define the impact political connections exert on earnings quality in a more complete view; (2)
to distinguish between the types of political connections, company’s political connections can be
categorised into government officials connected type and NPC deputies or CPPCC members connected
type. From the perspective of size and way, the influence of these two kinds of connections are quite
distinct. As a result, to study the impact these two kinds of political connections may have on earnings
quality and its economic consequences will be of more targeted value and significance.
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