Political Connected CEOs and Earnings Management:

Evidence from China

Jing Chia1, Jing Liaoa and Xiaojun Chena

This Version: May 2015

Abstract

This paper examines the impact of politically connected CEOs on earnings management in

China and the results show that firms with politically connected CEOs have significantly

lower earnings management, measured by total accruals and discretionary accruals. We argue

that the concern of political reputation and easy access to capital and recourse possibly lead

to less incentive for these firms to conduct earnings management. Evidence is found that

firms with political connected CEOs issue more H-shares, have higher leverage and conduct

less seasoned equity offerings (SEOs) after listing. In addition, our difference-in-difference

tests show that earnings management in firms with politically connected CEOs are higher in

non-state controlled firms or in post non-tradable share (NTS) reform period, compared to

state controlled firms and pre-NTS reform period.  These results suggest that the government

support or the privilege of politically connected CEOs can be key factors that influence

earnings management behavior of political connected CEOs. Finally, our findings are robust

after controlling for the endogeneity.

Keywords: Political connected CEOs, earnings management, China

JEL Codes: G34, G38

1a All authors are from the School of Economics and Finance, Massey University. Corresponding Author: Jing Chi. School of Economics and Finance, Massey University (Manawatu Campus), Private Bag 11-222, Palmerston North 4442, New Zealand, Tel: +64-6-3569099 ext. 84048; Email: J.Chi@massey.ac.nz.

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1. Introduction

Are political connections beneficial to firms? To date, there is no definite answer. Faccio

(2006), Liu, Tang and Tian (2013), Zhou (2013) among others argue that such connections

are recognized as an important political capital which creates value for individual firms.

Some literature shows that politically connected firms have better access to recourses, which

can be in various forms such as preferential treatment by government-owned banks or raw

material producers, lighter taxation and relaxed regulatory oversight, and thus political

connections are found to improve firm value and performance (i.e., Chen, Li, Su and Sun,

2011; Fisman, 2001; Faccio 2006). On the contrary, other studies find negative impact of

political connections, particularly on firm performance and the quality of financial reporting.

Fan, Wong and Zhang (2007) report that firms with politically connected CEOs in China

underperform those without politically connected CEOs based on three-year post-IPO stock

returns and accounting performance. Chaney, Faccio and Parsley (2011) document that the

quality of earnings reported by politically connected firms is significantly poorer than that of

similar non-political connected ones, using accounting data in 19 countries. In this paper, we

use all listed firms in China, a hand collected database of Chinese politically connected CEOs

and different earnings management measures to study whether firms with political connected

CEOs engage more or less earnings management to cast new light on the importance of these

two competing viewpoints.

China provides an ideal situation to study the impact of politically connected CEOs on

earnings management for the following reasons. First, given that a high proportion of Chinese

listed companies were transferred from the state-owned enterprises (SOEs), the political

connections in Chinese listed companies are popular. Fan, Wong and Zhang (2007) report

that 27% of the Chinese IPO firms appoint politically connected CEOs, who were current or

former government or military officials. Second, the Chinese Securities Regulatory

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Commission (CSRC) is the regulatory body in China which takes in charge of proving Initial

Public Offerings (IPOs), Seasoned Equity Offerings (SEOs) or firm delisting, and these

decisions are primarily based on accounting performance. In the Chinese markets, where

accounting information is essential for regulatory controls and where the investor protection

is weak, literature shows that earnings management is rife (i.e. Liu and Lu, 2007; Kao, Wu

and Yang, 2009). Our paper is closely related to Fan, Guan, Li and Yang (2014), which

employs a sample of networked firms with 45 high-level Chinese bureaucrats involved in

corruption scandals from 1996 to 2007, and studies the patterns in the earnings

informativeness of these firms, measured by abnormal accruals derived from different

models, related party transactions and non-operating items in the earnings. They find that a

significant increase in the earnings informativeness of the networked firms following the

public exposure of a scandal, indicating a negative impact of political connections on

earnings informativeness. However, their study only focuses on 45 corruption scandal cases

in China, while in our paper we study all Chinese listed firms for the time period from 2000

to 2010.

The plan of this paper involves two steps. First, it aims to show how politically connected

CEOs affect firms’ earnings management. We utilize empirical evidence to argue that

politically connected CEOs may not only help firms to access key resources and

opportunities, but also provide governance and monitoring for companies to keep their

political reputation in less developed and transition economies. Therefore, the incentives for

earnings management in these firms would be reduced. Second, this study applies this

relationship to two subsamples, i.e. non-state controlled firms versus state controlled firms as

well as firms in the post non-tradable share (NTS) reform2 period versus firms in the pre-NTS

22. The China Securities Regulatory Commission (CSRC) launched the Non-Tradable Share (NTS) reform to transfer non-tradable shares mainly held by state-owned enterprises and state agencies into tradable shares in April 2005. It is expected that state control in listed firm will be gradually reduced due to the implementation of the NTS reform (Liao, Liu, and Wang, 2014).

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reform period, in order to empirically test whether the impact of politically connected CEOs

on earnings management would change if the government support on resources reduces or the

level of market development increases. The implementation of the NTS reform provides an

excellent natural experiment opportunity to examine the impact of political connection on

earnings management given that the reform is exogenous and therefore we use the difference-

in-difference approach to address the possible endogeneity.

We find that firms with politically connected CEOs have significantly lower earnings

management, measured by total accruals and discretionary accruals. We argue that the

concern of political reputation and relatively easy access to the capital and recourse possibly

lead to less incentive for these firms to conduct earnings management. Evidence is also found

that firms with political connected CEOs issue more H-shares, have higher leverage and

conduct less SEOs after listing. In addition, our difference-in-difference tests show that

earnings management in firms with politically connected CEOs are, however, higher in non-

state controlled firms or in post-NTS reform period, compared to state controlled firms and

pre-NTS reform period. These results suggest that the government support or the privilege of

politically connected CEOs can be key determinants to earnings management behaviour of

political connected CEOs. In addition to difference-in-difference tests, our results are robust

to further tests for endogeneity, e.g. using generalized method of moments (GMM) tests.

This paper makes the following contributions to the existing literature. First, it contributes to

the political connections literature by investigating a particular mechanism through which

politically connected CEOs influence earnings management. To our knowledge, this is the

first paper that empirically tests this relationship using a comprehensive dataset of the

Chinese sample firms. This paper shows that this relationship is influenced by the equilibrium

of benefit and cost of earnings management to the politically connected CEOs. Second, it also

contributes to the more specific literature on Chinese earnings management by showing that

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politically connected CEOs may provide a monitoring role on earnings management given

the level of the financial support they can access.

Following this introduction is the section on theoretical background and hypothesis

development. The data and methodology are described in Section 3. We present the empirical

results and robustness tests in Section 4 and conclude our study in Section 5.

2. Theoretical background and hypothesis development

2.1 Earnings management in China

Healy and Wahlen (1999) define earnings management as a behaviour that “… occurs when

managers use judgment in financial reporting and in structuring transactions to alter financial

reports to either mislead some stakeholders … or to influence contractual outcomes …

(p.368)” . There are a number of emphases in previous research on earnings management,

including how to measure earnings management (Dechow, Sloan, & Sweeney, 1995; Jones,

1991; Kothari, Leone and Wasley, 2005), the incentives of earnings management

(Bergstresser and Philippon, 2006; Guidry, Leone and Rock, 1999), and the timing of

earnings management (Yu, Du and Sun, 2006; Liu and Lu, 2007).

In the US, earnings management activities are primarily motivated by managers’ job tenure

and executive compensation (Cheng and Warfield, 2005). While in China, given the facts that

high ownership concentration is the main source of agency conflicts in listed firms and that

the CSRC make decisions on IPOs, SEOs and delisting based on accounting measures, the

earnings management activities often take place before IPOs, SEOs and delisting process and

are initiated by the controlling shareholders to fulfil certain goals (Yang, Chi and Young,

2012; Liu and Lu, 2007).

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Liu and Lu (2007) study the relation between corporate governance and earnings

management from a tunnelling perspective, using data of the Chinese stock markets from

1999 to 2005. They find that firms with higher corporate governance levels have lower levels

of earnings management. Their results strongly suggest that agency conflicts between

controlling and minority shareholders account for a significant portion of earnings

management in Chinese firms. Their empirical findings also show that listed firms that escape

the risk of de-listing engage in more serious earnings management than firms that are de-

listed, indicating these companies could have managed their reported profits upwards to

avoid de-listing.

As reported profit is an official criterion for firms getting permission from the CSRC to issue

IPOs and SEOs, it is not surprising that Chinese firms engage in serious earnings

management before their IPOs and/or SEOs to increase the chance and amount of raising

capital. Aharony, Lee and Wong (2000) and Kao, Wu and Yang (2009) both find that firm’s

profitability peaks in the IPO years and decline after going public, and attribute the post-IPO

underperformance to firm earnings management activities before their IPOs and argue that

this is caused by IPO pricing regulations based on reported earnings. In addition, Chen and

Yuan (2004) and Yu, Du and Sun (2006) find that firms conducting rights issues have heavy

concentrations of return on equity (ROE) that just exceed the CSRC required ROE threshold

(10% before 2001 and 6% after 2001). They argue that rights issuing firms manipulate

reported profits upwards to meet ROE benchmarks.

2.2 Political connection and its impact on listed firms

Recent literature shows that political connection and corporate performance are related,

although there is no definite answer on the sign of this relation. In China, the current market

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economy comes from the government planned economy and the government has always

played a crucial role in regulating, monitoring and participating in the economy.

2.2.1 Political connection and firm performance

Some researchers find that political connection is related to inefficiency, low firm value and

poor corporate governance. Fan, Wong and Zhang (2007) study the impact of politically

connected CEOs on the post-IPO performance of Chinese firms and find that firm with

politically connected CEOs underperform those without politically connected CEOs by

nearly 18% measured by three-year post IPO stock and accounting performance. They also

find that firms with politically connected CEOs are more likely to have boards consisting of

current or former government bureaucrats and people with low degrees of professionalism.

Berkman, Cole and Fu (2010) examine the wealth effects of three regulatory changes aiming

to improve minority shareholder protection in the China’s stock markets and find that firms

with strong political ties do not benefit from the regulation changes, indicating that minority

shareholders do not expect regulators to enforce the new rules on the firms with strong ties to

the government.

However, others consider political connections to be valuable to firms. Faccio (2006) studies

over 20,000 listed firms in 47 countries and find a significant increase in corporate value

when there is announcement of businessperson entering politics. Francis, Hasan and Sun

(2009) find firms with political connections receive significant benefits when going public in

China. Feng, Johansson and Zhang (2014) find that firms controlled by entrepreneurs who

participate in politics show significant post-IPO outperformance in China, and Liu, Tang and

Tian (2013) document a positive relationship between a politically connected executive and

the probability of IPO approval of entrepreneurial firms.

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2.2.2 Political connection and earnings management (or earnings quality)

There is also limited research studying the relationship between political connections and

earnings quality (or earnings management). Using accounting data from 19 countries,

Chaney, Faccio and Parsley (2011) reveal that the presence of political connections is

negatively associated with accounting earnings quality. On the other hand, Cahan (1992)

finds that US firms reduce their discretionary accruals while they are under investigation for

antitrust violations to avoid political costs. In addition, Yen (2013) studies China-based

companies listed in the Hong Kong Stock Exchange and documents that there is no evidence

that a firm’s political connections play a significant role in increasing the potential for firms’

fraudulent financial reporting.

Networks and political connections are particularly important in emerging markets where

formal institutions provide weak protection for investors or business transactions. Political

connections can function in different ways. First, this relationship is likely to result in rent

seeking, particularly in economies that lack formal institutions to discipline those in power

(Feng, Johansson and Zhang, 2014). Literature shows that obtaining political connections

could help to access political capital, including favourable government subsidies, government

contracts or taxation policies. A typical rent seeking channel that has been found is

preferential access to finance (Dinc, 2005), while in China one of the well-documented

motivations for earnings management is to get the CSRC’s permission to issue SEOs (Yu, Du

and Sun, 2006). In this case, we suggest that firms with politically connected CEOs could

have better access to the capital and the necessity to manage earnings for further financing

would be low. Second, political connection may also serve as a form of political certification

or a mechanism for monitoring due to the concern of political reputation. Hung, Wong and

Zhang (2012) study the motivation of politically connected Chinese firms listing in overseas

markets and find that connected firms’ post-overseas listing performance is worse than that of

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non-connected firms, but connected firms’ managers are more likely to receive political

media coverage or a promotion after overseas listing than domestic listing. Their results

illustrate that connected firms’ managers conduct overseas listing for political reputation and

benefit. Political reputation would also be an important concern when politically connected

CEOs conduct earnings management, given the high possibility of these CEOs returning to

the government as bureaucrats. Therefore, we propose the following hypothesis:

H1: Firms with politically connected CEOs have lower earnings management than firms

without politically connected CEOs.

3. Data and methodology

3.1 Earnings management measures

Following Jones (1991) and Liu and Lu (2007), we use two proxies to measure earnings

management in Chinese listed firms, namely, total accruals (ACC) and discretionary accruals

(DACC). The definitions of these two proxies are listed as follows.

ACC i ,t=¿ i ,t−CFOi ,tTAi , t

(1)

Accrualsi , tTA i ,t−1

=a1

TAi ,t−1+a2∆ Rev i ,t /TA i ,t−1+

a3 PPEi , tTAi ,t−1

+εi , t (2)

Total accruals (ACC) equal the difference between net income (NI) and cash flows from

operation (CFO) divided by total assets (TA). Using Equation 2, we run the ordinary least-

square method regression and keep residuals to use as the discretionary accruals (DACC).

∆ Rev i ,t is the change of revenue and PPEi ,t is the net fix assets (data of gross fix assets are

not available in CSMAR) in year t for company i.

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3.2 Independent variables in the research

Our research aims to examine how politically connected CEOs affect firms’ earnings

management. Our main independent variable in the regression is a dummy variable, which

equals 1 if a firm’s CEO is politically connected. We hand collect the profiles of CEOs of all

listed firms in the main boards and small and medium enterprise (SME) board of Chinese

markets through the Sina Finance, Yahoo Finance and Sohu Finance websites. Following

Fan, Wong and Zhang (2007), we define politically connected CEOs by the fact whether he

or she was currently or formerly an officer of the central government, a local government or

the military. As in Cheng and Leung (2012), we actually study executive chairperson instead

of normally defined chief executive officer (CEO) or general manager, as in China the

chairperson is a full-time position, who normally ranks higher than the CEO, approves all

major decisions and enjoys the highest pay in a firm.

In addition, we include the following independent variables documented in existing literature

which could impact firms’ earnings management.

Research finds that CEO characteristics impact corporate policies and decisions, which

include gender, age and duality (Barker and Mueller, 2002; Farrell and Hersch, 2005). In our

paper, we use CEO gender dummy, CEO age and CEO duality dummy to measure these

characteristics. CEO gender dummy equals 1 if the chairman of the board (who is called CEO

in this paper) is male. CEO age is measured by natural logarithm of the age of the chairman

of the board. CEO duality dummy equals 1 if the chairman of the board and the general

manager is the same person. It has been suggested that men have higher expectations on

masculine tasks than women (Beyer and Bowden, 1997); that psychological changes that

occur with age affect CEO behaviour and older CEOs are more likely to have a preference for

the less competitive activities (Bertrand and Schoar, 2003); and that CEO duality is positively

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related to risk-taking (Li and Tang, 2010). Therefore, we could expect firms with male

CEOs, young CEOs and CEO and board of director being the same person are more likely to

manage earnings.

As discussed earlier, listed firms in China have high ownership concentration, which has

been found to be a major source for agency problems and poor performance in these firms

(Fan and Wong, 2002; Liu and Lu, 2007). With high ownership concentration, the largest

shareholder would have more incentive and capability to obtain the private interest from the

company, which is called ‘tunnelling’. We include the percentage of shares held by the

largest shareholder in the regression analysis, and expect this variable has positive effect on

earnings management. On the other hand, we also include the sum of percentage of shares

held by the 2nd to 10th shareholders in the analysis, as we expect a firm with higher percentage

of shares held by the 2nd to 10th shareholders could lead to better monitoring to the largest

shareholder and lower earnings management.

The former literature proposes that the characteristics and the independence of the board

affect the financial reporting behaviour (Chen, Firth, Gao and Rui, 2006). We define two

variables to represent the monitoring power from the boards. One is board size, which is

measured by the natural logarithm of total number of directors on board, and the other is

board independence, which is the percentage of the independent directors. Fama and Jenson

(1983) suggest that outside directors are efficient monitors and it is in their best interest to

develop reputations as experts in decision making. We expect board independence would

have monitoring effect on a firm, and therefore reduce earnings management, while the effect

of board size on earnings management could be an empirical question.

As for the external monitoring mechanism, we employ the HBshare dummy variable, which

equals 1 when a company is also listed in the Hong Kong Stock Exchange or issues B shares

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to foreign investors. We expect multiple legal environments and accounting requirements

could mitigate earnings management activities.

In addition, we use variable SEO to proxy the motivation of earnings management, as

research finds that the most pronounced motivation for Chinese listed firms to carry out

earnings management is to get access to SEOs (Yu, Du and Sun, 2006). We use SEO dummy

which equals 1 if the observation year is any three years prior to a SEO, as the CSRC needs

to assess the accounting figures of three years prior to any SEO to give permission. We

would expect earnings management to be higher in these years.

Finally, we use firm size (the nature logarithm of the total assets) and leverage (total liability

to total assets) to control for firm characteristics in the regression analysis. The definitions of

all independent variables and dependent variables are provided in the Appendix.

3.3 Data

We collect the data from the CSMAR Financial Databases developed by the Shenzhen GTA

Information Technology Co. This research focuses on all A-share companies in the Chinese

stock markets from 2000 to 2010, including the main board and the SME board3. We drop

observations with missing value and winsorize extreme value (1% of total observations) in

any variables. Finally, our sample consists of 11117 firm year observations. Table 1 provides

distribution of the sample by firm-year observations. 22.33% of observations have politically

connected CEOs.

<Insert Table 1 here>

Table 2 shows the descriptive statistics of all variables involved in the research. The mean of

total accruals is -2.59%, and the mean of discretionary accruals is -8.49%. There is a large

3 The firm characteristics and listing requirements of these two boards are very similar. In general, the only difference is that firms listed in the main board are bigger in sizes.

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standard deviation of DACC, which is 0.6779. As for the independent variables, the data

shows that 95.9% of CEOs are male, but only 12.22% of CEOs also hold the chairman of the

board of the directors. On average, the percentage of independent directors is 31.59%; the

largest shareholder holds 39.38% of a firm’s total shares; the sum of the 2nd to 10th

shareholders’ holding is 17.71%; and the leverage ratio is 50.09%. In addition, there are

9.41% firms issuing B shares or H shares and 21.26% firm-year observations taking place in

any three years prior to a SEO. The results show that the sum of holdings of the 2nd to 10th

shareholders is much less than that of the largest shareholders, which illustrates the high

ownership concentration and possible poor monitoring role from the 2nd to 10th shareholders

in Chinese firms.

<Insert Table 2 here>

4. Empirical results

4.1 Univariate analysis of the identified variables

Before going further with the tests, we run correlation matrix for all variables in the

regression study. The results are provided in Table 3. The correlations are not high enough to

cause multicollinearity in the regression analysis.

<Insert Table 3 here>

Table 4 reports the results of univariate analysis of the main variables in the regression

analysis. First, we compare the earnings management measures (ACC and DACC) between

firms with politically connected CEOs and firms without politically connected CEOs. The

results show that firms with politically connected CEOs have lower ACC and DACC values

and the differences on means and medians are statistically significant. This result is primarily

consistent with our hypothesis. Second, on other independent variables, the results indicate

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that firms with politically connected CEOs have significantly larger firm size, higher

proportion of independent directors, and higher ownership concentration. In addition, as

discussed earlier, firms with political connections are more likely to conduct rent seeking

through access to financing, particularly in an emerging market like China where the formal

institutional is not developed (Feng, Johansson and Zhang, 2014). At the same time,

politically connected top managers could make corporate decisions not only for firm

profitability, but also for their political reputation and further promotion opportunities (Hung,

Wong and Zhang, 2012). Interestingly, we find evidence in Table 4 that companies with

politically connected CEOs have significantly higher leverage ratios, less SEOs, and higher

proportion of B shares or H shares. These results indicate that firms with politically

connected CEOs are more capable of accessing loans and therefore have less need of issuing

SEOs. They also issue more foreign shares in order to get more media attention and

promotion opportunities.

<Insert Table 4 here>

4.2 Baseline regression

In this part, we run panel data regression with year and industry fixed effects to test the

relationship between the two earnings management measures (ACC, and DACC) and

politically connected CEOs and other independent variables. The baseline model is shown as

follows:

ACC/DACC = α + β1PCEO + β2CEO Gender + β3CEO Age + β4CEO Duality + β5Firm Size +

β6Leverage + β7 Board Size + β8Board Independence + β9HBshare + β10Concentration +

β11Largest 2-10 + β12 SEO + ε (3)

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Table 5 reports the panel data regression results. Columns (1) and (2) show the regression

results on ACC and DACC respectively. We find that the coefficients of PCEO are

significantly negative at the 5% or 1% level, indicating that firms with politically connected

CEOs do have lower earnings management. Therefore, our hypothesis is supported. As for

the impact of other variables on earnings management, we find that firms with female CEOs

and firms with young CEOs tend to carry out more earnings management. The latter result is

expected. However, the results on female CEOs are out of our expectation. Given that the

proportion of female CEOs in Chinese firms is very low, only about 4%, we need to analyse

this result with caution. We also find that CEO duality has no impact on firms’ earnings

management. Consistent with Liu and Lu (2007), we find that firms with high ownership

concentration have significantly high earnings management. As the proportion of the 2nd to

10th shareholders’ holding is much less than the largest shareholding (shown in Table 2), we

are not surprised to see that the coefficient of largest 2-10 shareholding is significantly and

positively related to earnings management, indicating the 2nd to 10th largest shareholders

working closely with the largest shareholder rather than monitoring them. As in Chen and

Yuan (2004), we find that firms’ earnings management is significantly higher in any three

years prior to a SEO, and conducting a SEO is one of the main motivations for earnings

management in China. In addition, we find that the coefficient of HBshare on ACC is

negative and significant at the 1% level, which illustrates that the multiple legal environments

and accounting requirements are helpful for limiting earnings management. Finally, we find

that board independence has no significant impact on firms’ earnings management and board

size has a significantly negative impact on earnings management. The results show that the

board monitoring role is weak in Chinese listed firms, and bigger board might help firms to

access more resources in the capital market, which would reduce the motivation of earnings

management.

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<Insert Table 5 here>

4.3 Endogeneity issues

Research in corporate finance is complicated by endogeneity, such as unobservable

heterogeneity and simultaneity (Wintoki, Linck and Netter, 2012). In this section, we report

the tests that control for the possible endogeniety.

4.3.1 Granger causality test and GMM test

The results from the baseline regression support our hypothesis that firms with politically

connected CEOs have lower earnings management. Following Massa, Zhang and Zhang

(2011), we apply the Granger causality test on sample firms with all lagged value for

independent variables to control for the possible causality issue.

Table 6 reports the results when the lagged values of independent variables are use in the

regression. The coefficients of lagged PCEO are shown to be significant and negative at the

5% and 1% level on ACC and DACC regressions, respectively, while the results on other

independent variables remain qualitative the same.

<Insert Table 6 here>

The dynamic panel generalized method of moments (GMM) approach, developed in a series

of studies such as Holtz-Eakin, Newey and Rosen (1988) among others, is suggested to have

advantages compared to traditional fixed-effects estimates (Wintoki, Linck and Netter, 2012).

In this case, if current political connection is related to past earnings manage, then the GMM

approach can be used to address this causality issue, as it relies on a set of “internal”

instruments contained within the panel itself and it eliminates the need for creating external

instruments (Wintoki, Linck and Netter, 2012).

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Using GMM approach in Table 7, we find that the coefficient for PCEO on DACC is still

significantly negative at the 5% level. These robustness tests confirm that firms with

politically connected CEOs do have lower earnings management.

<Insert Table 7 here>

4.3.2 Difference-in-different regression analyses

There are two types of shares, tradable shares (TS) and non-tradable shares (NTS) in Chinese

listed firms. Tradable shares and non-tradable shares enjoy the same voting and cash flow

rights, but non-tradable shares which are held mainly by the state or legal persons cannot be

traded freely in the stock exchanges and their initial offering prices are also much lower than

those of tradable shares. Research finds that this two-tier share structure is perceived to cause

many problems in Chinese stock markets, including tunnelling of controlling shareholders

and weak protection of minority investors (Allen, Qian and Qian, 2005). In 2005, the NTS

reform, which is also called split share structure reform, was carried out to make NTS

tradable gradually. This reform is expected to reduce concentrated ownership and boost the

stable development of capital markets (China Securities Regulatory Commission, 2008).

Other key objectives of the NTS reform are to increase liquidity (Beltratti, Bortolotti and

Caccavaio, 2012), and at the same time, to offer further opportunity for privatization in the

Chinese stock markets (Liao, Liu and Wang, 2014).

The NTS reform can be used as a natural shock to test the impact of political connections on

earnings management. The benefit and resource that political connection can bring to a firm

are expected to decrease due to the possibility of improved corporate governance and market

monitoring mechanism associated with the implementation of the NTS reform. If the reason

that firms with politically connected CEOs have lower earnings management is due to the

fact that political connections can bring firms more resources and rent seeking opportunities,

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we would expect that the earnings management of firms with politically connected CEOs will

increase in the post-NTS reform period.

To further control for the potential endogeneity, we use difference-in-difference regression

analyses by forming a variable PCEO × Reform. Reform is a dummy equals 1 if the

observation year is 2005 and onwards. It is expected that the coefficient on PCEO × Reform

will be positive indicating the increasing incentive of politically connected CEOs to conduct

earning management after the NTS reform.

The difference-in-difference regression results are provided in Table 8. As we expected, we

find that in columns 1 and 2, the coefficients of reform dummy are statistically significant

and negative at the 1% level, indicating that after the NTS reform, with the development of

the capital market, corporate governance and market monitoring mechanism, the overall

earnings management level will decrease. However, with the possible reduction of the benefit

of political connections, the motivation and incentive of earnings management of firms with

politically connected CEOs could increase. We find the evidence that the coefficients of the

interaction terms between PCEO and reform dummy become positive, although only the

coefficient in the DACC regression is statistically significant at the 10% level.

<Insert Table 8 here>

For the robustness check, we also define a variable PCEO × Non-state. Non-state is a dummy

equals 1 if the largest shareholder of a firm is not the state, otherwise equals 0. Although the

change of largest shareholder is not always exogenous, the interaction between PCEO and the

nature of largest shareholder can provide further evidence on the impact of PCEO on earnings

management.

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Literature finds that political connections can come through in a form of ownership or

management. If a firm’s largest shareholder is the state, this firm will get more benefit from

the government than a firm which is not owned by the state. Sun and Tong (2002) suggest

that state ownership benefit SOEs, including providing better access to capital and business

opportunities. Therefore, we propose that the coefficients on PCEO × Non-state will be

positive given that politically connected CEOs in non-state-owned firms would have more

incentive to manage earnings as they have less government support through ownership.

We find that in columns 3 and 4 of Table 8, the coefficients of non-state dummy are

statistically significant and positive, showing that in non-state firms, with less government

support and benefit, the earnings management is higher. The results on the interaction terms

between PCEO and non-state dummy are also positive and significant at the 5% level in the

DACC regression, as we expected.

The difference-in-difference regressions confirm that the main reason for firms with

politically connected CEOs to have lower earnings management is that these firms can access

more resources and support from the government and therefore their incentive of earnings

management would be low.

5. Conclusions

This research studies the impact of politically connected CEOs on earnings management in

all Chinese listed firms from 2000-2010 and we find that firms with politically connected

CEOs have significantly lower earnings management, measured by total accruals and

discretionary accruals. The empirical evidences show that the concern of political reputation

and easy access to capital and recourse possibly lead to less incentive for these firms to carry

out earnings management. We also find that firms with political connected CEOs issue more

H-shares or B-shares, have higher leverage and conduct less SEOs after listing, indicating

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that these firms care about political reputation and have more access to capital without

needing to go through tough SEO application process.

In addition, our difference-in-difference tests show that earnings management in firms with

politically connected CEOs are higher in non-state controlled firms or in post NTS reform

period, compared to state controlled firms and pre-NTS reform period.  These results suggest

that the government support or the privilege of politically connected CEOs can be the key

determinants that influence earnings management behavior of political connected CEOs.

Without government support and easy access to capital, the earnings management in firms

with politically connected CEOs would increase.

20

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Appendix: Definition of variables

This appendix reports the definition and acronym of variables and expected relations with earnings management measures.

Variable AcronymExpected relation

Definition

Total accruals ACCThe difference between net income and cash flow from operations divided by total asset

Discretionary accruals

DACC The residual of Jones (1991) model

Politically connected CEO

PCEO -A dummy variable that equals 1 if the chairman of the board is politically connected

CEO Gender CEO Gender +A dummy variable that equals 1 if the chairman of the board is male

CEO Age CEO Age - Natural log of the age of the chairman of the board

CEO Duality CEO Duality +A dummy variable that takes the value 1 if the chairman of the board and the general manager is the same person

Firm Size Firm Size + Natural log of total assetsLeverage Leverage + Total liabilities to total assets

Board Size Board Size +/-Natural log of the total number of directors on board

Board Independence

Board Independence

-The number of independent director to the total number of directors on board

Multiple legal environment

HBshare - A dummy variable that equals 1 if firm also issue H share or B share

Largest shareholder ownership

Concentration +Percentage of shares held by the largest shareholder

Other controlling shareholders ownership

SHARE2_10 -Sum of percentage of shares held by the 2nd to 10th shareholders

Seasoned Equity Offering

SEO +A dummy variable that equals 1 if the observation year is any three years prior to a SEO

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Table 1: Distribution of the sample by firm-year observations

This table reports the distribution of sample firm-year observations by year, industry, and political connection over the 2000 to 2010 sample period.

Panel A: By year Panel B: By IndustryYear Number Percentage Industry Number Percentage

2000 742 6.67% Public Utility 1131 10.17%2001 870 7.83% Real Estate 616 5.54%2002 914 8.22% Conglomerates 917 8.25%2003 983 8.84% Industry 7562 68.02%2004 1085 9.76% Commercial 891 8.01%2005 1170 10.52%2006 1154 10.38% Total 11117 100%2007 1107 9.96%2008 1113 10.01%

2009 1152 10.36% Panel C: By Political Connection

2010 827 7.44% CEO Number PercentagePCEO 2482 22.33%Non-PCEO 8635 77.67%

Total 11117 100% Total 11117 100%

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Table 2: Summary statistics of the identified variables

This table reports the summary statistics of the variables included in the analysis. The description of the variables is summarized in the Appendix.

Variable Obs Mean Std. Dev. Min MaxACC 11117 -0.0259 0.0880 -0.8854 0.4131DACC 11117 -0.0849 0.6779 -2.8926 2.5749PCEO 11117 0.2233 0.4165 0 1CEO Gender 11117 0.9590 0.1983 0 1CEO Age 11117 3.8990 0.1518 3.3322 4.3820CEO Duality 11117 0.1222 0.3276 0 1Firm Size 11117 21.3590 1.0750 15.4680 27.6163Leverage 11117 0.5009 0.1902 0.0822 1.3986Board Size 11117 2.2207 0.2228 1.0986 2.9444Board Independence 11117 0.3159 0.2255 0 1HBShare 11117 0.0941 0.2920 0 1Concentration 11117 0.3938 0.1632 0.0350 0.8858Largest 2-10 11117 0.1771 0.1293 0.0021 0.6603SEO 11117 0.2126 0.4092 0 1

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Table 3: Correlation matrix of the identified variables

This tables reports the correlation matrix of the variables for the sample of 1,292 firms with 11,117 firm-year observations over the 2000 to 2010 sample period. The description of the variables is summarized in the Appendix.

ACC DACC PCEO CEO Gender

CEO Age

CEO Duality

Firm Size Leverage Board

SizeBoard Independence

HB share Concentration Largest 2-

10 SEO

ACC 1DACC 0.193 1PCEO -0.025 -0.063 1CEO Gender -0.001 -0.044 0.005 1CEO Age 0.005 -0.042 0.097 0.007 1CEO Duality -0.001 0.020 -0.032 -0.023 -0.082 1Firm Size 0.056 -0.058 0.071 0.018 0.217 -0.077 1Leverage -0.130 0.050 0.028 0.009 -0.052 -0.004 0.168 1Board Size -0.006 -0.071 0.017 0.017 0.086 -0.073 0.215 0.015 1Board Independence 0.003 -0.004 0.039 0.010 -0.004 -0.104 -0.06 -0.041 0.113 1HBshare -0.027 -0.033 0.057 0.001 0.088 -0.014 0.226 0.021 0.074 0.031 1Concentration 0.027 -0.037 0.033 0.001 0.076 -0.087 0.173 -0.111 0.004 0.109 -0.001 1Largest 2-10 0.010 0.004 -0.007 0.012 -0.067 0.0423 -0.115 0.017 0.097 0.044 0.080 -0.556 1SEO 0.079 -0.003 -0.034 0.011 0.021 -0.007 0.115 0.009 0.035 0.016 -0.047 0.032 0.023 1

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Table 4: Univariate analysis of the identified variables

This tables reports the univariate analysis of the identified variables for the sample of 1,292 firms with 11,117 firm-year observations over the 2000 to 2010 sample period. SEOT is a dummy variable that equals 1 if the firm issues seasoned equity offering in a specific year. The other description of the variables is summarized in the Appendix. *, ** or *** indicates significance at the 90%, 95% or 99% confidence levels, respectively.

Meanst-statistic

Mediansz-statistic

PCEO Firms Non-PCEO Firms Difference PCEO Firms Non-PCEO

Firms Difference

ACC -0.0299 -0.0247 -0.0052 -2.2510** -0.0276 -0.0212 -0.0064 -3.034***DACC -0.1649 -0.0619 -0.103 -6.4005*** -0.1151 -0.0263 -0.0888 -5.562***Firm Size 21.5047 21.3180 0.1867 7.1492*** 21.3526 21.2037 0.1489 6.886***Leverage 0.5106 0.4980 0.0126 2.8410*** 0.5097 0.5 0.0097 2.374***Board Size 2.2277 2.2187 0.0090 1.7494* 2.1972 2.1972 1.843*Board Independence 0.3325 0.3112 0.0213 4.1685*** 0.3333 0.3333 4.657***HBshare 0.1251 0.0850 0.0401 5.5045*** 0 0 6.037***Concentration 0.4040 0.3910 0.0130 3.4862*** 0.3863 0.3719 0.0144 3.438***Largest 2-10 0.1754 0.1776 -0.0022 -0.7289 0.1444 0.1560 -0.0116 -1.051SEOT 0.0657 0.0762 -0.0105 -1.8360* 0 0 -1.768***

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Table 5: Political connection and earnings management

This table reports the estimates of the following regression model for two measures of earnings management.

ACC/DACC = α + β1PCEO + β2CEO Gender + β3CEO Age + β4CEO Duality + β5Firm Size + β6Leverage + β7 Board Size + β8Board Independence + β9HBshare + β10Concentration + β11Largest 2-10 + β12 SEO + ε

The description of the variables is summarized in the Appendix. *, ** or *** indicates significance at the 90%, 95% or 99% confidence levels, respectively.

Expected Relation (1)ACC (2)DACCPCEO - -0.0051** -0.1101***CEO Gender + -0.0005 -0.1416***CEO Age - -0.0097* -0.0906**CEO Duality + -0.0004 0.0147Firm Size + 0.0062*** -0.0516**Leverage + -0.0730*** 0.0708**Board Size +/- -0.0058 -0.1209***Board Independence - -0.0028 0.0406HBshare - -0.0106*** -0.0057Concentration + 0.0208*** 0.1564***Largest 2-10 - 0.0377*** 0.1815***SEO + 0.0147*** 0.0215

Concept Yes YesYear fixed effects Yes YesIndustry fixed effects Yes Yes# of observations 11117 11117Overall R2 0.0475 0.0278

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Table 6: Political connection and earnings management, lagged value approach

This table reports the estimates of the following regression model for two measures of earnings management.

ACC /DACC = α + β1PCEOt-1 + β2CEO Gender t-1 + β3CEO Age t-1 + β4CEO Duality t-1 + β5Firm Size t-1 + β6Leverage t-1 + β7 Board Size t-1 + β8Board Independence t-1 + β9HBshare t-1 + β10Concentration t-1 + β11Largest 2-10 t-1 + β12 SEO t-1 + ε

The description of the variables is summarized in the Appendix. *, ** or *** indicates significance at the 90%, 95% or 99% confidence levels, respectively

Expected Relation (1)ACC (2)DACCPCEOt-1 - -0.0045** -0.0986***CEO Gender t-1 + 0.0010 -0.1138***CEO Age t-1 - -0.0104* -0.1041**CEO Duality t-1 + 0.0000 0.0017Firm Size t-1 + 0.0014 -0.0644***Leverage t-1 + -0.0520*** 0.1051***Board Size t-1 +/- -0.0045 -0.1263***Board Independence t-1 - 0.0008 0.0579*HBshare t-1 - -0.0036 0.0104Concentration t-1 + 0.0299*** 0.0758Largest 2-10 t-1 - 0.0362*** 0.0884SEO + 0.0184*** 0.0123

Concept Yes YesYear fixed effects Yes YesIndustry fixed effects Yes Yes# of observations 9348 9348Overall R2 0.0343 0.0337

30

Table 7: Political connection and earnings management, GMM approach

This table reports the estimates of the following regression model for two measures of earnings management.

ACC/DACC = α + β1PCEO + β2CEO Gender + β3CEO Age + β4CEO Duality + β5Firm Size + β6Leverage + β7 Board Size + β8Board Independence + β9HBshare + β10Concentration + β11Largest 2-10 + β12 SEO + ε

The description of the variables is summarized in the Appendix. *, ** or *** indicates significance at the 90%, 95% or 99% confidence levels, respectively

Expected Relation (1)ACC (2)DACC

ACCt-1 0.0438*ACCt-2 0.0069DACCt-1 0.2418***DACCt-2 0.0513*

PCEO - -0.0051 -0.0677**CEO Gender + 0.0079 -0.0078CEO Age - 0.0169 0.0876CEO Duality + -0.0034 -0.0022Firm Size + 0.0664*** -0.0055Leverage + -0.2238*** -0.2808**Board Size +/- 0.0044 0.0077Board Independence - -0.0016 0.0225HBshare - 0.0102 -0.1295Concentration + -0.0104 0.5131**Largest 2-10 - -0.0357 0.0119SEO + 0.0023 0.0114

Concept Yes YesYear effects Yes YesIndustry effects Yes Yes# of observations 7366 7366

31

Table 8: Political connection and earnings management, difference-in-difference approach

This table reports the estimates of the following regression model for two measures of earnings management.

ACC/DACC = α + β1PCEO + β2Reform+ β3PCEO×Reform + β4CEO Gender + β5CEO Age + β6CEO Duality + β7Firm Size + β8Leverage + β9 Board Size + β10Board Independence + β11HBshare + β12Concentration + β13Largest 2-10 + β14 SEO + ε

Reform is a dummy variable that equals 1 if the year of the observation equals or is greater than 2005, otherwise equals 0. Non-state is a dummy variable that equals 1 if the largest shareholder is not the state, otherwise equals 0. The other description of the variables is summarized in the Appendix. *, ** or *** indicates significance at the 90%, 95% or 99% confidence levels, respectively.

Expected Relationship

(1)ACC (2)DACC (3)ACC (4)DACC

PCEO - -0.0031 -0.0520** -0.0048** -0.1208***Reform - -0.0099*** -0.1055***PCEO × Reform + 0.0025 0.0415*

Non-state + 0.0039* 0.0537***PCEO × Non-state + 0.0003 0.0808**

CEO Gender + -0.0038 -0.0903** -0.1212 -0.1212***CEO Age - 0.0023 0.0117 -0.0801 -0.08018CEO Duality + 0.0054 0.0435** 0.0139 0.0139Firm Size + 0.0357*** 0.0366*** -0.0503*** -0.0503***Leverage + -0.1386*** -0.0622 0.0588*** 0.0588*Board Size +/- -0.0012 0.0026 -0.1098 -0.1098***Board Independence - -0.0003 -0.0073 0.0511 0.0511*

HBshare - -0.0128 -0.3551 -0.0009 -0.0009Concentration + 0.0464*** 0.4741*** 0.1469*** 0.1469***Largest 2-10 - 0.0439*** 0.469*** 0.1021*** 0.1021*SEO + 0.0132*** 0.0233* 0.0140*** 0.0140

Concept Yes Yes Yes YesYear fixed effects Yes Yes Yes YesIndustry fixed effects Yes Yes Yes Yes# of observations 11117 11117 11116 11116Overall R2 0.0222 0.0001 0.0315 0.0170

32