Public Governance and Tax Avoidance: Evidence from theAnti-Corruption Campaign in China

Abstract
Taking advantage of the China’s anti-corruption campaign initiated in 2012, this study
investigates the effects of public governance on tax avoidance. The campaign
successfully curtails excessive corporate spending and governs the employment offormer government officials in firms. It increases the political risk of officials who
provide firms with favorable tax treatment. Thus it is hypothesized that the campaign
impairs the ability of firms to practice tax avoidance. Consistent with this hypothesis,
we use a sample of listed companies from 2009 to 2015 in China and alternative
measures of tax avoidance, and find that firms practice less tax avoidance after the
initiation of the anti-corruption campaign. Further analysis reveals that both
entertainment and travel costs and their impacts on tax avoidance are reduced after thelaunch of the campaign, thus indicating that the effects of bribery on tax avoidance aresubsequently reduced. We also demonstrate that the contribution of tax avoidance tofirm value decreases after the anti-corruption campaign. This study highlights theimportance of public governance in restricting tax avoidance practice and hence has
meaningful implications on the tax base erosion problem for policy-makers worldwide.
Keywords: Public governance; Tax avoidance; Firm value; Entertainment and travel
costs; Anti-corruption.
JEL Classifications: H26; M40; G38.

Acknowledgments: We thank the following for their helpful comments: Mark DeFond,
In-Mu Haw and workshop participants at University of Macau.
11. Introduction
The extant literature suggests that agency conflicts play an important role incorporate tax avoidance decisions (e.g., Khan, Srinivasan and Tan 2017; Armstrong,
Blouin, Jagolinzer, and Larcker 2015; Desai and Dharmapala 2006; and Crocker andSlemrod 2005). However, these studies mainly focus on the firm-level agency problem1,
and the effects of public sector governance 2 on tax avoidance remains unexplored.
Public governance shapes the environment in which firms operate. Previous studies
have demonstrated the importance of country-level institutions for economic growthand corporate operation (e.g., Doidge, Karolyi and Stulz 2007; La Porta, Lopez-deSilanes, Shleifer and Vishny 1999, 1998). Doidge et al. (2007) distinguish between
investor protection granted by the state and investor protection adopted by the firm andshow that country-level dominates firm-level governance mechanism. In the context ofincome tax, government, as a major stakeholder, may have conflict of interests withcorporations. Thus, public governance is likely to play a different role with firm-levelin corporate tax avoidance decisions.
We take advantage the anti-corruption campaign laughed in 2012 in China to study
the causal effects of public governance on corporate tax avoidance. First, the control ofcorruption is an integrated dimension of public governance. 3 The campaign isperceived to improve the public governance in China 4 , eliciting firms change their

1

Stulz (2005) proposes that there are twin agency problems: the agency problem of corporate insider
discretion and that of state ruler discretion.
2
Governance consists of the traditions and institutions by which authority in a country is exercised.
This includes the process by which governments are selected, monitored and replaced; the capacity of
the government to effectively formulate and implement sound policies; and the respect of citizens andthe state for the institutions that govern economic and social interactions among them.
(http://info.worldbank.org/governance/wgi/index.aspx#home)
3
The World Bank Worldwide Governance Indicator consists of six dimensions and control of corruption
is one of them (www.govindicators.org).
4
According to the Worldwide Governance Indicator, the Control of Corruption sub-index (ranges from
-2.5 (weak) to 2.5 (strong) governance performance) of China is -0.51, -0.56 and -0.51 for 2009, 2010,2

operating strategies. The second challenge to explore the effect of public governance is
the insufficient variation in institutional factors resulting from institutional stability
within a single country. The ongoing anti-corruption campaign serves as an exogenous
shock to public governance, thereby alleviating potential endogeneity problems.
Government corruption, especially in the form of rent-seeking, is pervasive aroundthe world. The World Bank survey indicates that, on average, 18% of firms around theworld have experienced at least one bribe payment request from a public official.5
China has been rather anomalous as the second largest economy in the world and a
growth engine, but has a corruption level that is on par with that of most developing
markets. Due to an ambiguous legal system and poor legal enforcement, many firms
seek benefits by bribing government officials and members of the Communist Party of
China (CPC) and creating connections with them (Wu, John and Rui 2016). The severe
problem of corruption has prompted the CPC to initiate an unprecedented anticorruption campaign in November 2012, shortly after Jinping Xi became the“paramount leader” of China (i.e., General Secretary; President; and Chairman of theCentral Military Commission). He vowed to eradicate the long-standing issue ofpolitical corruption in China. As of 2016, more than 100,000 people have been indicted
for corruption, and 120 high-ranking officials, including five national-level leaders,have been targeted.6
Although the campaign targets political actors, it has spread to the corporate world
and resulted in investigations launched on a large group of executives from a variety ofand 2011, while -0.36, -0.34 and -0.28 for 2013, 2014 and 2015, respectively, indicating an improvementin public governance after the campaign.
5
This is determined by taking the simple average of bribery incidence (% of firms that experience atleast one bribe payment request) from World Bank Development Indicators. For each economy, only
the latest available year of survey data and surveys posted during the years 2010-2017 are used in thiscomputation.
6
See http://usa.chinadaily.com.cn/epaper/2015-03/02/content_19695097.htm
3companies. Recent studies have shown that the consequences of the anti-corruption
campaign in China is not consistent. The campaign may have curbed corruption, butalso has significant impacts on corporate strategy, firm performance, public governance,
shareholder valuations, and accounting quality. For example, Lin, Morck, Yeung andZhao (2017) document positive market reactions, and an increase in firm performanceassociated with the anti-corruption campaign. Ke, Liu and Tang (2017) find that the
campaign reduces the luxury-goods consumption of state-owned enterprise (SOE)firms. Hope, Yue and Zhong (2017) find that the accounting quality of firms with
politically connected directors is improved after the campaign. Zhang (2018) finds thatfirms are less likely to commit fraud in the post-campaign period than in the precampaign period. Thus, one can foresee that, under the anti-corruption campaign, firms
and CPC/government officials may modify their strategies and behavior. Such
strategies and behavior should not be limited to those that have been already examinedin existing studies. However, Griffin, Liu and Shu (2017) suggest that the campaign
targets corrupt managers, appears influenced by political favoritism, and has notbroadly affected Chinese corporate culture. One of the areas that have been left
unexplored is the influence of Xi’s anti-corruption campaign on tax planning. Therefore,
we take the initiation of the anti-corruption campaign in this study as an exogenous
event to examine whether anti-corruption could curb corporate tax avoidance andfurther affect firm value.
In China, CPC/government officials have the ability to assist firms with tax
avoidance. According to the “Enterprise Income Tax Law of China” and “Regulationon the Implementation of the Enterprise Income Tax Law of China”, firms are entitledincome tax deductions or preferential tax discounts as long as they fulfill the statedrequirements. For example, industries and projects that are encouraged by the state, or4investments made by an enterprise for specialized equipment that reduces
environmental pollution, etc., can be granted preferential tax treatment. Moreover, sincemost of the requirements are ambiguous, officials of the tax authorities, the StateCouncil and local governments are infused with immense discretion in their final
judgment on the form of tax privilege that a firm can obtain. This policy ambiguity andauthority of government officials are conducive to rent seeking in the already corrupted
environment of China. Corrupted officials may exploit their discretion to provide tax
privileges in exchange for personal benefits. This argument is confirmed by a recent
survey in China which reveals that 56% of the companies have declared that tax
collectors are the second most-frequent beneficiaries of bribes following government
officials because they can decide on the amount of corporate tax bills.7
We hypothesize that the anti-corruption campaign is likely to mitigate tax
avoidance practices for two reasons. First, the anti-corruption campaign increases thedetection risk of corruption. As corruption has been prevalent in China for decades,
government officials do not consider corruption as a serious crime. Prior to the launchof the campaign, managers would provide officials with pecuniary advantages inexchange for paying less taxes. However, after the anti-corruption campaign has gone
into force, government officials are now under serious scrutiny and violation of relevant
policies is subject to severe punishment if they are caught. Both firms and officials haveless incentive to practice tax avoidance or provide assistance to avoid taxes. Therefore,
officials have become less lenient in approving tax privileges to avoid scrutiny.
Second, the anti-corruption campaign has weakened political connections
between CPC/government officials and firms. As China officials have the power to7

See http://www.charneyresearch.com/wp-content/uploads/2015/01/White-Paper-Corruption-inChina-FINAL-v10.pdf.
5determine the tax payment of firms, managers were motivated to establish politicalconnections with them for their assistance in reducing tax expenses. One of the ways
to facilitate political connections was to employ officials (those who had either resigned
or retired from public life) as managers or independent directors. For instance, among
the listed private manufacturing companies in 2012, 11% of them had at least one senior
executive (chairman of board, CEO, board secretary, or chief financial officer) or actual
controllers with a government background, and 42% of them had top officers withmembership in the National People’s Congress or the Chinese People’s Political
Consultative Conference (Dang and Yang 2016). The greatest benefit of employing
politically connected managers is that the network of the firm will expand, especiallywith the government. Wu et al. (2012) observe that politically connected managers in
Chinese private firms can help firms to enjoy tax benefits. In particular, enterprises
employ chief financial officers (CFOs) or other accounting executives who have work
experience with tax authorities to deal with tax issues. Kim and Zhang (2016) find thatconnected firms are more tax aggressive because they are at less risk of detection,acquire more in-depth information on future changes in tax regulations or enforcement,
are subject to less capital market pressure for transparency, and suffer less political costs
associated with aggressive tax planning, which results in higher risk-taking tendencies.
In a recent study, Lin, Mills, Zhang and Li (2018) suggest that ties to politicians bycorporate boards of directors weaken the effectiveness of tax authorities in constraining
tax avoidance in China.
Nevertheless, this relationship between firms and officials is weakened or severed
after the launch of the campaign. In October 2013, the CPC issued Rule 18 to regulate
the employment of former government officials in firms. The CPC mandated that CPC
and government officials above certain ranks, either in their current position or those6

who have retired within a three year period of time, are prohibited from holding any
part-time or full-time position in any enterprise. This requirement triggered an
unprecedented massive wave of resignation of politically connected directors inpublicly listed firms. Six months after the launch of Rule 18, 118 independent directors
in listed firms who were former officials resigned from their position.8 Hence, thisresulted in the loss of political connections of firms that previously enjoyed politicalconnections through these directors. The following real life example further
exemplifies this phenomenon. Mr. Shanda Xu and Mr. Junhui Cui, former deputy
directors of the State Administration of Taxation, were employed as independent nonexecutive directors at the Industrial and Commercial Bank of China and China National
Petroleum Corporation respectively immediately following their retirement from their
We focus on A-share firms listed on the Shanghai and Shenzhen Stock Exchanges
between 2009 and 2015, and use 2009-2011 as the pre-launch period of the campaign
and 2013-2015 as the post-launch period of the campaign. We find that the level of tax
avoidance decreases significantly after the initiation of the anti-corruption campaign inChina. This finding is robust for alternative measures of tax avoidance, the differencein-differences (DID) method and an array of robustness tests.
We then test how the anti-corruption campaign affected tax avoidance behavior.
We argue that firms achieve tax reduction through good relationships with government
officials. This relationship is often facilitated in two ways: bribing government officials
and/or employing former officials as managers. Prior to the implementation of the anticorruption campaign, firms in China used to entice government officials with feasts,
expensive entertainment, gifts, or even travel to establish and maintain a good8

See http://finance.huanqiu.com/data/2014-06/5022596.html.
7

relationship with them. Part of the luxury consumption for relationship-building is thendeducted as “entertainment and travel costs” when filing taxes. Cai, Fang and Xu (2011)
suggest the use of entertainment and travel costs as a proxy for firm investment inpolitical connections. However, after the anti-corruption campaign, CPC andgovernment officials must practice thrift, maintain a low profile and strictly follow therelevant regulations on accommodations and use of cars, as stipulated in the Eight-point
Policy. The expenses that can be listed for tax deductions are now restricted. Moreover,firms with exorbitant entertainment and travel expenses may be the recipient of further
investigation. Previous studies find that the market has reacted positively to the launchof the campaign with reductions in entertainment and travel costs (Griffin et al., 2017;
Lin et al., 2017). We expect that the anti-corruption campaign deters tax deductions
sought by providing entertainment to government officials.
Consistent with Griffin et al. (2017) and Lin et al. (2017), we find that businessentertainment costs are reduced after the initiation of the anti-corruption campaign, thus
indicating a reduction in corruption. We further analyze whether the campaign haschanged the role of entertainment and travel costs in tax avoidance. The empirical result
demonstrates that entertainment and travel costs have less impact on reducing taxes
after the launch of the anti-corruption campaign. This result suggests that entertainment
and travel costs is a potential means through which the anti-corruption campaign can
reduce tax avoidance.
Liu, Shu and Wei (2017) show that anti-corruption changes the expectations ofinvestors on asset prices. Therefore, we explore next whether markets capitalize on tax
avoidance differently after the launch of the anti-corruption campaign. There are twopotential forces here. On the one hand, it is likely that the campaign increases theenforcement of tax laws and regulations because there is increased scrutiny on the8behavior of officials. Thus, the risk of being detected for tax avoidance may be
increased, and subsequently, may reduce the contribution of tax avoidance to firm value.
On the other hand, Desai and Dharmapala (2009) conclude that the effects of tax
avoidance on firm value is a function of firm governance, and higher-quality firm
governance leads to a greater effects of tax avoidance on firm value. The anti-corruption
campaign has reduced the ability of government officials to do rent seeking andincentives for rent seeking. As a result, the campaign may improve corporate
governance quality.9 Thus tax avoidance may contribute more to firm value after the
campaign. This actually appears to be an empirical question on how the anti-corruption
campaign has impacted the contribution of tax avoidance to firm value. Our empiricalresult supports the first argument and shows that tax avoidance contributes more to firm
value after the anti-corruption campaign.
This study contributes to the literature in several ways. Primarily, we contribute to
the tax avoidance literature (e.g., Khan, Srinivasan and Tan 2017; Armstrong, Blouin,
Jagolinzer, and Larcker 2015; Beck, Lin, and Ma 2014; Desai and Dharmapala 2009,2006; and Crocker and Slemrod 2005). Previous studies have investigated thedeterminants of tax avoidance behavior. More importantly, a stream of studies (e.g.,
Khan et al. 2017; Armstrong et al. 2015; Desai and Dharmapala 2006; Crocker andSlemrod 2005) explore the role of manager-shareholder agency conflicts in determining
tax avoidance. However, in countries outside the U.S., firms are typically controlled bya few major shareholders (Faccio and Lang 2002; Claessens, Djankov and Lang 2000;
La Porta et al. 1999) and the fundamental agency problem produces a conflict of

9

Actually, there is mixed evidence in whether anti-corruption measures improve corporate governance.
Hope et al. (2017) find the accounting quality increases and Xu et al. (2016) show that tunnelingdecreases after the campaign, thus indicating an improvement in corporate governance. However,
Griffin et al. (2017) suggest that the campaign targets corrupt managers, appears to be influenced bypolitical favoritism, and has not broadly affected Chinese corporate culture.
9interests between the controlling owners and the minority shareholders (Shleifer and
Vishny 1997). Moreover, twin agency problems arise because rulers of sovereign states
and corporate insiders pursue their own interests at the expense of outside investors(Stulz 2005). This study adds to this literature by examining the effects of public
governance on tax avoidance. Tax base erosion has become an international problem
and many countries are taking steps to address this issue. The findings in this study
suggest that the anti-corruption reform curbs the tax avoidance behavior of firms.
Therefore, this study provides important implications for policy makers in emerging
economies.
Second, our study adds to the literature on firm value. Corporate tax avoidance
activities represents a transfer of value from the state to shareholders. Desai and
Dharmapala (2009) investigate whether such activities advance shareholder interests.
They find that higher-quality firm governance leads to larger effects of tax avoidanceon firm value. This study extends the literature and finds that, due to the heavy scrutiny
to detect government corruption, the risk of detecting tax avoidance is increased, andhence the contribution of tax avoidance to firm value is significantly reduced after theanti-corruption reform in China was launched.
Third, our paper also contributes to a growing body of studies that examine theeconomic consequences of the anti-corruption campaign in China. Recent studies have
explored the effects of the anti-corruption reform on firm value (Liu et al. 2017; Ke etal. 2017; Lin et al. 2017), investment decisions (Pan and Tian 2018), accounting quality(Hope et al. 2017), tunneling (Xu, Wang, Zhou and Zhou 2016) and corporate fraud(Zhang 2018). However, our study explores the externality of anti-corruption reform
on tax avoidance.

10

The paper proceeds as follows. Section 2 provides the background information on
the anti-corruption campaign in China. The data collection process and research design
are discussed in Section 3. Section 4 presents the empirical results and Section 5
concludes.
2. The Anti-Corruption Campaign in China
Although China has grown into the second-largest economy in the world, there issevere political corruption. The Corruption Perception Index (CPI) developed byTransparency International ranked China 78 out of 175 in the world in 2010 on its
corruptness, which fared worse than many of the emerging economies such as Brazil(69) and Malaysia (56).10
On November 14, 2012, Jinping Xi took leadership of China and stressed that
corruption has threatened the survival of the CPC. Shortly after he took office, heembarked on an anti-corruption campaign. On December 4, 2012, the CPC promulgatedthe Eight-point Policy to regulate the conduct of CPC members (see Appendix A),
which represented the official start of the anti-corruption campaign. The target of thecampaign included all CPC members regardless of their rank. Following theannouncement of the Eight-point Policy, various government agencies made detailed
arrangements to implement the policy. Another important initiative was to curb thecorruptive behavior of government officials by severing ties between government
officials and firms, and imposing more severe punishment for misconducts. On October
19, 2013, the Organization Department of the CPC promulgated Rule 18 to oversee theemployment of government officials in enterprises (see Appendix B). The rule poses
limitations on their employment in enterprises and payment from firms for approved

10

For details, see: http://www.transparency.org/cpi2010/results.
11

cases. The rule also specifies that any breaches of the regulations must be rectified
within a short period of time. This was a warning to all officials that corruption can costthem dearly.
Announced by the Central Commission for Discipline Inspection of CPC on
January 15, 2016, about 336,000 officials received administrative punishment in 2015
and about 14,000 were suspected of committing crimes and referred to judicial
authorities. This unprecedented anti-corruption campaign has been therefore perceived
to improve public governance.
3. Data Collection and Research Design
3.1 Measuring tax avoidance and firm value
3.1.1 Measuring tax avoidance
We follow the previous literature (for e.g., Tang et al. 2017, Hanlon and Heitzman
2010, and Dyreng et al., 2008) and define tax avoidance as any activity that explicitly
reduces the amount of taxes per dollar of pre-tax earnings by managing tax reporting.
We use modified effective tax rates, book-tax differences and residual book-tax
differences to measure tax avoidance in this study.
Modified effective tax rate (METR)
A common measure of corporate tax avoidance in previous studies is the effective
tax rate (ETR), which is the ratio of taxes paid to pre-tax income (Chen et al. 2010;
Hanlon and Slemrod 2009; Wilson 2009; Gupta and Newberry 1997). Thus, the ETR
measures the actual tax burden as a percentage of the pre-tax income within a certain
period of time.

12One limitation of the ETR is that it does not differentiate tax savings from tax
preferences and aggressive tax reporting. This issue has implications for our study
because Chinese listed firms are susceptible to different applicable tax rates (ATRs) due
to the many types of tax preferential policies that cater to specific firms, industries, etc.
(Shevlin and Porter 1992). We address this issue by following Tang et al. (2017) and
Chan et al. (2013), and modify our ETR measures by using the ATR of a company in agiven year to formulate a modified ETR (METR; i.e., the ETR divided by the ATR). The
ATR is a compulsory tax rate that applies to listed firms. That is, the ATR shows whether
a firm receives favorable tax treatment and the reason that a firm has less tax burden
than that stipulated by the standard tax rate from a policy perspective.
We control for the differential effects of the applicable tax rate on the ETR byusing the ATR to modify the ETR, which detects tax avoidance that is carried out bymanaging tax reporting. In line with Tang et al. (2017) and Gupta and Newberry (1997),
we truncate the ETR to [0, 1] before estimating the METR. A smaller (higher) METR
points to more (less) aggressive tax planning.
Book-tax difference (BTD)

The book-tax difference (BTD) is estimated by subtracting the inferred taxable
income from the reported pretax financial income of a firm for the book-tax gap, whichis scaled by pretax financial income11. Specifically, we use the following formula tocalculate BTD.

BTD=

11

When total asset is used as the deflator, we obtain consistent results, however the magnitude of thebook-tax difference becomes much smaller.
13

Residual book-tax difference (RBTD)
Following Desai and Dharmapala (2006), we measure tax avoidance by using theresidual book-tax difference (RBTD) which equals to the residual from the regressionof the firm fixed effects of the total BTD on total accruals (Accrual). Specifically, toaccount for the BTD that is attributable to earnings management, we run the following
ordinary least squares (OLS) regression:
BTDit=

 1 Accrual it   i   it(1)

where BTD is defined above. Total accruals (Accrual) equal pre-tax earnings less net
cash flow from operating activities, scaled by lagged total assets. μi is the average valueof the residual for firm i over the sample period, and νit is the deviation in year t fromfirm i’s average residual ui. Since the total BTD can reflect tax avoidance and accrualmanagement, this measure intends to isolate the components of the estimated BTD thatis not explained by accruals.
3.1.2 Measuring firm value
In emphasizing the value implications of corporate tax avoidance, this paper builds
on the extensive literature in corporate finance on the determinants of firm value.
Within the literature, it has become standard since Demsetz and Lehn (1985) to use
Tobin’s Q to measure firm value. Following Desai and Dharmapala (2009), we modify
the standard definition of Tobin’s Q by excluding deferred tax expenses as follows.12
Tobin’s Q =12Desai and Dharmapala (2009) suggest that current tax avoidance activity may result in changes tofuture tax liabilities and thus create a mechanical correlation between the dependent variable and themeasure of tax avoidance. However, we obtain consistent results by using the standard definition of
Tobin’s Q which includes deferred taxes.
14While Tobin’s Q is the primary dependent variable used in the analysis, we also use anindustry adjusted Tobin’s Q (Ind-adj Tobin’s Q), which equals the firm-level Tobin’s
Q minus the median of Tobin’s Q in a 2-digit SIC code, to measure firm value.
3.2 Sample Selection
In this paper, the sample starts with all A-share companies listed on the Shanghai
and Shenzhen Stock Exchanges from 2009 to 2015. Financial data and board
characteristics are taken from The China Stock Market & Accounting Research(CSMAR) database. The period from 2009 to 2011 is defined as the period before thelaunch of the anti-corruption campaign while 2013 to 2015 is the period after launch of
the anti-corruption campaign.
Following previous studies, financial firms are excluded from our sample. Firms
with missing data and carrying “ST” (special treatment) or “*ST” tags, (firms that suffer
losses for two consecutive years or more, and the other are stocks that enter delistingprocedures) are also removed. To eliminate outliners, observations with ETRs are
restricted within the range of 0 to 1 (Tang et al. 2017; Chen et al. 2010; Gupta andNewberry 1997). The final sample consists of 8,620 firm-year observations. Panel A of
Table 1 shows the process of the sample selection. Panel B reports the distribution of
the sample observations by year, and the number of firm-year observations is almost
evenly distributed in the pre- and post-launch periods of the anti-corruption campaign.
Other continuous variables are winsorized at the 1st and 99th percentiles in order tomitigate the effects of outliners.
3.3 Research design
To examine the effects of the anti-corruption campaign on tax avoidance, we firstcompared the magnitude of tax avoidance over the period of 2009-2015 (2012 is the15event year/year that the campaign was initiated and therefore excluded) by using thefollowing regression with firm-fixed effects.
TaxAvoid = 0  1 Post   k Controls  (2)where TaxAvoid is one of the three tax avoidance measures, METR, BTD or RBTD, asdefined above. The variable of interest is Post, which is a dummy variable used to test
the effects of anti-corruption on tax avoidance. Post equals to 1 if the observations fallin the post-launch period of the campaign (2013 to 2015) and 0 in the pre-launch periodof the campaign (2009 to 2011). If the anti-corruption campaign constrains the ability
and incentive of managers to practice tax avoidance, we expect β1 to be significantly
positive (negative) when METR (BTD or RBTD) is the dependent variable.
To address the potential omitted variables that may drive our results, we also use
a difference-in-differences (DID) method. However, the anti-corruption campaign may
have effects on all government officials and listed firms. It is difficult to find a control
sample in a DID design. We then resort to the second best and propose that firms inregions where political corruption is severe are more likely to be affected by the anticorruption campaign. We thus partition the full sample into high and low corruptionsubsamples based on the median corruption index of the province where a firm islocated. We use the province marketization index to proxy for the corruption level of aprovince. Provinces with less developed market institutions, resources and information
are almost controlled by the government, and political connections are thus essential
for firms to obtain favorable treatment. Thus the impacts of the anti-corruption
campaign on officials would be greater in those provinces. Our regression model is asfollows:
TaxAvoid = 0  1 Post   2 HighCRPT   3 Post * HighCRPT 
 k Controls  16(3)

As discussed above, we use the marketization index to measure region corruption.
The marketization index is produced by the Wang, Fan and Yu (2017) (see Appendix
C), with higher scores indicating that the market plays a more important role in theeconomy. HighCRPT is a dummy variable that equals to 1 if the average marketizationindex of 2009 to 2011 is smaller than the median of the average marketization index
value, and 0 otherwise. By definition, HighCRPT equals to 1 if a firm is located in aprovince with higher levels of corruption. We expect a positive coefficient on
Post*HighCRPT when METR is the dependent variable, and a negative coefficient on
Post*HighCRPT when BTD or RBTD is the dependent variable.
To purge the effects of underlying business processes and other fundamental
drivers of tax avoidance, we include a variety of control variables that have been shown
to be associated with tax avoidance from previous studies (Shevlin et al. 2012; Tangand Firth 2011; Chan, Lin and Mo 2010). We control for return on equity (ROE) because
previous research finds that operating performance impacts the need of a firm to avoid
taxes. We control for accruals because Frank et al. (2009) find a positive association
between financial and tax-reporting aggressiveness. Shevlin et al. (2012) find evidence
that firms concerned with meeting minimum earnings thresholds to issue additional
equities and intangible-intensive firms both engage in more tax-induced income
shifting. To control for these effects, we include Rights and INTAST in our regression.
Rights is an indicator variable that equals 1 if the firm obtains a rights offering in thenext year, and 0 otherwise. INTAST is a measure of the intangible assets scaled by total
assets. Since there are differences in dealing with the depreciation of fixed assets
between accounting and taxes, we include FXTAST (fixed assets, scaled by total assets).
China has preferential tax policies to encourage firms to invest in innovation. We thus
include R&D (research and development expenses, scaled by total assets). Following
17

previous studies, we also include LEV (total liabilities divided by total assets), Size(natural logarithm of a firm’s market capitalization), and Growth (the percentagechange in sales between years) to ensure that our results are robust to these commonlyused control variables. In addition, we include SOE and Duality to further control forthe effect of governance. SOE is a dummy variable and equals to 1 if a firm is controlled
by the government, and 0 otherwise. Duality is a dummy variable and equals to 1 if thechairman and CEO are the same person in a firm, and 0 otherwise. Lagged loss
(LagLoss) is controlled because losses in previous years (up to five years) are allowed
to offset taxable income13. Following Atwood et al. (2012), we include the ATR.
We use firm fixed effects in our main analyses. This design is essential to our study
because it helps to alleviate the concerns on measurement errors in our tax avoidanceproxies caused by firm specific characteristics. Standard errors are computed afterclustering by firm.
To explore the impacts of the anti-corruption campaign on the contribution of tax
avoidance to firm value, we estimate Eq. (4) by using an ordinary least squares
regression and, as before, include firm fixed effects and clustering standard errors byfirm.
Tobin’s Q = 0   1 Post   2 Post * BTD   3 BTD   k Controls  (4)where Tobin’s Q is defined above. Following Desai and Dharmapala (2009), we use
the BTD to measure tax avoidance because both the METR and RBTD do not proxy the
dollar amount of tax avoidance. The major variable of interest is the interaction between
Post and BTD (Post*BTD). The coefficient on the interaction term, γ2, captures theincremental changes in the contribution of tax avoidance to firm value from the pre- to

13

Loss carryforwards are not publically reported in China and thus we use lagged loss as an alternative.
18

the post-launch periods. We do not have a prediction on the sign of γ2.
The set of control variables is taken from prior research, such as profitability(ROE), earnings quality (Accrual), leverage (LEV), firm size (Size), and SOE.
Table 2 lists the summary statistics of the firm characteristics for the sample. We
also partition the full sample into subsamples of the pre- and post-launch periods. The
mean of the METR is 1.099 in the pre-launch period and 1.207 in the post-launch period.
The mean of the METR in the post-launch period is greater than that in the pre-launch
period (significant at the 1% level, not shown), thus indicating that the ETR increases
after the initiation of the anti-corruption campaign. The mean of the BTD is 0.789 in
the pre-launch period and 0.771 in the post-launch period, thus indicating that BTD is
reduced in the post-launch period. The mean of the RBTD is 0.012 in the pre-launch
period and -0.009 in the post-launch period, thus indicating that tax avoidance isreduced in the post-launch period. Table 2 also shows that the ROE and Accrual
decrease, while Growth and R&D increase in the post-launch period. All other variables
are similar in both the pre- and post-launch periods.
Table 3 reports the correlation matrix. The correlation coefficients among the threemeasures of tax avoidance (METR, BTD and RBTD) are -0.883, -0.719 and 0.731,
respectively, thus suggesting that these three measures are effective. The METR ispositively related and the BTD and RBTD are negatively related to Post, which isconsistent with our hypothesis that tax avoidance is reduced after the initiation of theanti-corruption campaign.
4. Empirical Results
4.1 Effects of anti-corruption campaign on tax avoidance
Table 4 presents the empirical results of Model (2). The dependent variables are19the METR in Columns (1) and (2), BTD in Columns (3) and (4), and RBTD in Columns(5) and (6). The coefficient on Post is 0.128 in Column (1) and significantly positive atthe 1% level, thus indicating that the ETR of a firm is increased after the initiation of
the anti-corruption campaign. The coefficient on Post is -0.027 in Column (3) andsignificantly negative at the 1% level, thus indicating that the BTD is reduced after the
initiation of the anti-corruption campaign. The coefficient on Post is -0.025 in Column(5) and significantly negative at the 1% level, thus indicating that firms practice lesstax avoidance after the initiation of the anti-corruption campaign. All the results fromthe three measures of tax avoidance are consistent. We then add control variables inColumns (2), (4) and (6) respectively and the coefficients on Post remain significant at
the 1% level with the predicted signs. These findings are in line with the view that theanti-corruption campaign weakens the political connections of firms and supports our
hypothesis. The results are also economically significant. For example, the result inColumn (2) suggests that firms in the post-launch period have an METR that is 15.0%
greater than that of the pre-launch period. In other words, for a firm with an ETR of
15% in the pre-launch period, the average ETR that this firm pays in the post-launch
period would be 17.25% (15.0%*(1+15%)=17.25%). In all six columns, firm-fixed
effects are included and standard errors are computed after clustering by firm.
The signs of the coefficients on control variables are, in general, consistent withthose of previous studies. For example, larger (Size) and more profitable (ROE) firms
may have greater incentive to avoid taxes (Wilson 2009; Rego 2003; Gupta andNewberry 1997). Growing firms (Growth) practice less tax avoidance (Tang et al. 2017)
Table 5 presents the regression results by using the DID method. Firm fixed effects
are included in Columns (1), (3) and (5) while industry and year fixed effects areincluded in Columns (2), (4) and (6). As predicted, the coefficient on the interaction
20

term, Post*HighCRPT, is 0.101 in Column (1), positive and significant at the 1% level,thus suggesting that the ETR of firms located in provinces with severe politicalcorruption increases after the initiation of the anti-corruption campaign compared tothose located in provinces with less political corruption. This result is robust whenindustry and year fixed effects are used (see Column (2)). The coefficients on
Post*HighCRPT are both negative and significant at the 1% level in Columns (3) and(4), thus suggesting that the BTD for firms located in provinces with severe politicalcorruption is reduced after the initiation of the anti-corruption campaign compared tothose located in provinces with less political corruption. Columns (5) and (6) present
similar results when the RBTD is used to proxy tax avoidance. The results in Table 5
help to alleviate the concern of omitted variables around the initiation of the anticorruption campaign and further confirm the results in Table 4.
We next conduct several robustness tests to validate our findings and present theresults in Table 6.
R&D

China has a preferential tax policy to encourage firms to invest ininnovation. Previous studies also confirm the effects of R&D investments on tax credit(e.g., Thomson 2017). In order to exclude the potential effects of tax preference oninnovation, we exclude the firms that invest in R&D and report the results in Columns(1) to (3) of Table 6. The coefficients on Post for the three measures of tax avoidance
are similar to those reported in Table 4.
Constant sample

Many new initial public offering (IPO) firms are high-techcompanies and may have tax preferences. To exclude the effects from newly listed firms,
we require that every firm must have 6-year observations. Columns (4) to (6) of Table
6 present consistent results based on the sub-sample.

21

Profitable firms only The METR is truncated to [0, 1] in our main tests to remove
the effects from loss firms on the tax avoidance measures. We also remove loss firms
from the sample in order to control for their effects. Our previous assumption holds;
see Columns (7) to (9) of Table 6.
4.2 Effects of entertainment and travel costs on tax avoidance
The main feature of the anti-corruption campaign is the issuance and enforcementof Eight-point Policy and Rule 18. Kim and Zhang (2016) and Lin et al. (2018)
document that political connections increase corporate tax avoidance, indicating that
Rule 18 could be a potential channel through which anti-corruption affects tax
avoidance. In this section, we explore how Eight-point Policy affects tax avoidance.
Cai et al. (2011) propose entertainment and travel costs as a measure of corruption
in Chinese firms. They find that entertainment and travel expenses include claims forreimbursements for bribery of government officials in the form of grease and protection
money, used for managerial excess, as well as entertainment expenditures that build
relational capital.
Panel A of Table 7 compares the entertainment and travel costs at the firm-level
between the pre- and post-launch periods of the campaign. 14 Following Cai et al.
(2011), the entertainment and travel costs (ETC) is scaled by total sales. The t-testsuggests that the mean of the ETC decreases significantly after the anti-corruption
campaign. The Wilcoxon test for the median of ETC demonstrates the same pattern.
These results are consistent with Ke et al. (2017) and Griffin et al. (2017) and indicatethat the incentive of firms to bribe is likely to be constrained, and thus the ability for

14

Not all firms in China disclose their entertainment and travel costs. We obtain 6,227 firm-years thatreport entertainment and travel costs from the CSMAR database.
22

tax planning will be impaired.15
Panel B of Table 7 compares the effects of the ETC on tax avoidance between the
pre- and post-launch periods of the campaign. The dependent variables are METR, BTD
and RBTD, respectively. The coefficient on ETC is negative in Column (1) and positivein Columns (2) and (3), thus indicating that entertainment and travel costs help toreduce the ETR and increase tax avoidance in the pre-launch period. This result is
consistent with Cai et al. (2011) in that firms use entertainment and travel costs as atool to obtain lower tax rates. However, the coefficient on Post_ETC is positive inColumn (1) and negative in Columns (2) and (3), which indicate that the effects of the
ETC on tax avoidance are reduced after the anti-corruption campaign. This finding,
together with the result in Panel A, indicate that after the anti-corruption campaign, on
the one hand, the grease money that firms use to bribe government officials is reduced,
and, on the other hand, the effects of bribery are also reduced. Overall, the results inTable 7 show the potential means through which the anti-corruption campaign can
reduce tax avoidance.
4.3 Effects of anti-corruption campaign on contribution of tax avoidance to firm value
Table 8 presents the results from Model (4). The dependent variable is Tobin’s Q
in Column (1) and industry-adjusted Tobin’s Q (Ind-Adj Tobin’s Q) in Column (2). The
tax avoidance measure is BTD. The coefficient on Post*BTD is -0.615 in Column (1)and -0.433 in Column (2), and both negative and significant, thus indicating that thereis less contribution of tax avoidance to firm value after the initiation of the anti-

15

According to Article 43 of the “Regulation on the Implementation of the Enterprise Income Tax Lawof the People's Republic of China” implemented in 2008, the expenses for business entertainment
incurred by an enterprise related to its production activities and business operations shall be deductedto the extent of 60% of the actual incurred amount but not more than 5% of the sales revenue of thecurrent year.
23corruption campaign. This phenomenon can likely be explained by the increased riskof detection of tax avoidance following the campaign launch.
However, the BTD is a noisy measure of tax avoidance activity. For instance, BTDs
may arise from the tax preferences of R&D investment or the treatment of fixed assets
depreciation. We thus add R&D investment (R&D) and fixed assets (FXTAST) in Model(4). The regression results reported in Columns (3) and (4) are consistent with those in
Columns (1) and (2).
5. Conclusions
China embarked on an anti-corruption campaign in 2012 to reduce political,
military, and business corruption. The ongoing campaign has resulted in a series ofimpressive impacts on the government, society and business environment and an
improvement in public governance. It has changed corporate spending behavior,business strategies and relationships with government officials. Furthermore, thecampaign has brought up an intriguing question, that is, whether the campaign can leadto a reduction in tax avoidance so as to increase the revenue of the government eventhough the policy does not professedly include any tax regulation.
This study extends the tax literature by investigating the impact of the public
governance on corporate tax avoidance. The campaign constrains the motivation of
government officials to do rent seeking. It also unravels political connections. Thus, theanti-corruption campaign is likely to reduce the ability of firms to practice tax
avoidance.
Using a sample between 2009 and 2015 and alternative measures of tax avoidance,
we find that the level of tax avoidance is significantly reduced after the initiation of theanti-corruption campaign in China, which is consistent with our hypothesis. Further
24

analysis demonstrates that both the level of bribery and the effects of bribery on tax
avoidance are reduced after the campaign launch. We also find that the contribution of
tax avoidance to firm value is reduced after the anti-corruption campaign started,
perhaps due to the increased risk of detection.
Political corruption and tax base erosion are two serious problems worldwide16
and these two problems are often mutually reinforcing. The anti-corruption reform in
China provides a useful setting for us to study the causal effects of public governanceon tax avoidance practices. The findings in this study have meaningful implications forpolicy-makers in dealing with the tax base erosion problem which is a global issue
nowadays.

16

Kim and Zhang (2016) and Smith (2016) indicate that both political corruption and tax avoidance areserious even in a country such as the U.S. with a strong legal system.
25

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28

Appendix A: Eight-point Policy17
1. Leaders must keep in close contact with the grassroots. They must understand thereal situation that is facing society through in-depth inspections at the grassroots level.
Greater attention should be placed where social problems are more acute, andinspection tours must be carried out more thoroughly. Inspection tours that are merely
formalities should be strictly prohibited. Leaders should work with and listen to the
public and officials at the grassroots, and people’s practical problems must be addressed.
There should be no welcome banner, no red carpet, no floral arrangement or grand
receptions for official visits.
2. Meetings and major events should be strictly regulated, and efficiency improved.
Political Bureau members are not allowed to attend ribbon-cutting or cornerstonelaying ceremonies, or celebrations and seminars, unless they obtain approval from the
CPC Central Committee. Official meetings should be short and specific and to the point,with no pointless statements and rigmarole.
3. The issuing of official documents should be reduced.
4. Visits of officials abroad should only be arranged when needed with fewer
accompanying members, and on most occasions, there is no need for a reception by
overseas Chinese people, institutions and students at the airport.
5. There should be fewer traffic controls when leaders travel by cars to avoid
unnecessary inconvenience to the public. There should be fewer traffic controls
arranged for the security of the leaders on their trips to avoid unnecessary
inconvenience to the public.
6. The media must not report on stories about official events unless there is true news
value. The regulations also ban worthless news reports on the work and activities ofsenior officials and such reports should depend on need, news value and social effects.
7. Leaders should not publish any works by themselves or issue any congratulatory
letters unless an arrangement with the central leadership has been made. Official
documents without substantial contents and realistic importance should be withheld.
Publications regarding the work and activities of senior officials are also restricted.
8. Leaders must practice thrift and strictly follow relevant regulations on
accommodations and use of cars.

17

http://cpcchina.chinadaily.com.cn/2012-12/05/content_15991171.htm
29

Appendix B: Rule 18
1. The leading party and government cadres who are currently in office and who do nothold office but have not gone through formalities for retirement shall not work parttime (or hold office) in enterprises.
2. The leading party and government cadres who have resigned or retired from public
offices must be subject to strict management and control for their part-time working (orholding office) in enterprises. If they need to work part-time (or hold office) inenterprises due to work needs, they should be strictly examined and approved according
to the cadre management authority.
Within three years after resigning from public office or retirement, the leading party
and government cadres are not allowed to work part-time (or hold office) in enterprises
within the jurisdiction and business scope under their original duties, nor may they
engage in for-profit activities related to their original duties.
Within 3 years after resigning from public office or retirement, the leading party andgovernment cadre who intends to work part-time (or hold office) in an enterprise thatis outside of the jurisdiction and business scope under his/her original duties must report
his/her intention to the Party Committee (or Party Leadership Group) of his/her former
unit. The leading party and government cadre may not work part-time (or hold office)in the enterprise unless the supporting materials for reasons of part-time working (orholding office) are issued by the enterprise and approved by the Party Committee (orParty Leadership Group) of his/her former unit as specified, in addition to the consent
given by the corresponding organization (personnel) department in accordance with thecadre management authority.
After 3 years since resigning from public office or retirement, the leading party andgovernment cadre who intends to work part-time (or hold office) in any enterprise must
report his/her intention to the Party Committee (or Party Leadership Group) of his/her
former unit. The enterprise shall provide the supporting materials for reasons of parttime working (or holding office) to the Party Committee (or Party Leadership Group)of his/her former unit which will approve the materials as specified, and submit themto the corresponding organization and (personnel) department for filing in accordancewith the cadre management authority.
3. The leading party and government cadres who have been approved to work part-timein enterprises according to regulations shall not receive remuneration (such as salary,bonuses, allowances, etc.), equities and other additional benefits from the enterprises;
and shall also not work part-time in more than one enterprise. If the tenure system isadopted, the planned reappointments must be re-approved or put on record again for no
more than two consecutive terms; and the age limit for part-time employment is up to
70 years old.
4. The leading party and government cadres that have been approved to serve on
enterprises pursuant to regulations shall promptly transfer their administrative, wage
and other relations to the enterprises, and shall no longer retain the status of civil
servants and all kinds of treatment of party and government organizations. It is notallowed to transfer their administrative, wage and other relations back to the party andgovernment organizations to handle the formalities of retirement; and if they have
handled the formalities of retirement through those enterprises, it is also forbidden to30

transfer their administrative, wage and other relations back to the party and governmentorganizations.
5. The leading party and government cadres who have been approved to work part-time(or hold office) in enterprises pursuant to regulations shall strictly abide by the laws to
be honest and self-disciplined, and be prohibited from using their powers and influencesin their positions to seek unfair advantages for enterprises or individuals. The
performance of the leading party and government cadres during their part-time
employment in enterprises, and receipt of remuneration or not, position-related
consumption, and reimbursement of relevant work expenses, etc., shall be reported to
the Party Committee (or Party Leadership Group) of their former units at the end ofeach year.
6. The leading party and government cadres who violate the regulations on working
part-time (or holding office) in enterprises shall be disposed within a prescribed time
limit. All departments and units in all regions shall, in accordance with the Opinions,conduct a thorough investigation on the status of the leading party and government
cadres working part-time (or holding office) in enterprises according to the cadre
management authority, and correct the problems found within a limited period of time.
All leading party and government cadres that violate the regulations must be removed
or resign from their part-time (or held) duties within 3 months of the issuance of theOpinions. If it is indeed required by works and complies with relevant regulations, but
the formalities for approval or filing have not been handled, the leading party andgovernment cadres must complete the formalities within 3 months after the issuance of
the Opinions. The leading party and government cadres who have violated the Opinions
to receive remuneration within their term of office shall be subject to relevant
regulations of the CPC Central Commission for Discipline Inspection.
7. After the thorough investigation has been completed, if any leading party andgovernment cadre is found to have violated the Opinions of working part-time (orholding office) in enterprises, or concealing received remuneration, such leading cadre
shall be disposed seriously in accordance with relevant regulations once verified. All
departments and units in all regions shall, if any violation is found in the approval andreview of the status of the leading party and government cadres working part-time (orholding office) in enterprises, hold the principal leader and anyone responsible
accountable.
8. The leading party and government cadres who work part-time (or hold office) inother for-profit organizations shall also be subject to the Opinions.
The leading cadres of people’s organizations and mass organizations under the Civil
Servant Law of the People’s Republic of China, and public institutions shall be subject
to the Opinions; and other leading cadres shall refer to the Opinions.
9. All departments and units in all regions may, in accordance with the Opinions andthe cadre management authority, formulate corresponding management andimplementation measures to strengthen the standardized regulation on all types ofleading cadres at all levels working part-time (or holding office) in enterprises.
10. The Opinions shall come into effect as of the date of promulgation. If there is any
inconsistency with the previous provisions, the Opinions shall prevail.

31

Appendix C: Marketization index
The marketization index of 2001 - 2011 is obtained from Wang et al. (2017).
Province
Anhui
Beijing
Chongqing
FujianGansu
Guangdong
Guangxi
Guizhou
HainanHebei
Heilongjiang
Henan
Hubei
Hunan
Inner Mongolia
Jiangsu
Jiangxi
Jilin
Liaoning
Ningxia
Qinghai
Shaanxi
Shandong
Shanghai
ShanxiSichuan
TianjinTibet
Xinjiang
YunnanZhejiang
Median

2009
6.1
7.34
6.02
6.77
3.81
7.62
5.64
4.39
4.23
5.72
4.95
6.09
5.66
5.34
4.82
8.17
5.53
5.87
6.61
4.36
2.79
4.28
7.04
8.33
4.23
5.86
6.55
1.15
3.55
4.52
8.06
5.66

2010
6.18
7.66
6.14
6.63
3.43
7.73
5.11
3.55
4.59
5.07
4.84
6.19
5.59
5.49
4.56
8.58
5.66
5.49
6.36
3.92
2.53
3.95
6.87
8.74
4.60
5.8
6.98
0.44
2.87
5.01
8.23
5.49

32

2011
6.53
7.83
6.28
6.84
3.48
7.91
5.30
3.63
4.71
5.3
5.02
6.34
5.83
5.74
4.68
9.18
5.87
5.64
6.44
3.99
2.54
4.37
7.02
8.83
4.70
5.86
7.29
0.06
2.95
5.18
8.38
5.74

Average
6.27
7.61
6.15
6.75
3.57
7.75
5.35
3.86
4.51
5.36
4.94
6.21
5.69
5.52
4.69
8.64
5.69
5.67
6.47
4.09
2.62
4.20
6.98
8.63
4.51
5.84
6.94
0.55
3.12
4.90
8.22
5.67

Appendix D: Variable definition
Applicable tax rate is manually taken from financial reports; other data are taken fromthe CSMAR database.
Variable

Definition

ETR

Effective tax rate, calculated as taxes paid divided by pre-tax income.
Cash Taxes Paid = Income Tax expenses + Changes in Delayed Tax
Asset - Change in Delayed Tax Liability

ATR

Applicable income tax rate.

METR

Modified effective tax rate, calculated as the ratio of effective tax
rate (ETR) to applicable tax rate (ATR). A smaller (higher) METR
points to more (less) aggressive tax planning.

BTD

Book-tax differences, calculated by subtracting the inferred taxable
income from the reported pretax financial income of a firm for the
book-tax gap, which is scaled by pre-tax income.
BTD=

Accrual

Total accrual, calculated as the difference of pre-tax income and cash
flows from operating activities, scaled by total assets.

RBTD

Residual book-tax difference, equals to the residual from theregression of the firm fixed effects of the total BTD on total accruals(Accrual).
BTDit=

 1 Accrual it   i   it

μi is the average value of the residual for firm i over the sample
period; and νit is the deviation in year t from firm i’s average residual
ui. The greater (smaller) RBTD points to more (less) aggressive tax
planning.
Tobin’s Q

The ratio of market capitalization plus total liability minus delayed
tax expenses over total assets.
Tobin’s Q =Ind-Adj Tobin’s
Q

Industry-adjusted Tobin’s Q is a firm’s Q minus the median Q in thefirm’s industry in the observation year. Industry is defined based on
two-digit primary SIC code.

Post

Anti-corruption campaign dummy, equals to 1 if the observations fallin post-launch period of the campaign (2013 to 2015) and 0 in prelaunch period of the campaign (2009 to 2011).

HighCRPT

An indicator of corruption at the provincial level, equals to 1 if theheadquarter of a firm is located in a province where the marketizationindex of 2011 is lower than its median value, and 0 otherwise. A
higher level of HighCRPT represents a higher level of corruption.
(Continued on next page.)33

Appendix C (Continued)
Variable

Definition

ROE

Return on equity, calculated as pre-tax profit divided by total equityof shareholders.

Of Leverage

Leverage ratio, calculated as total liability divided by total assets

Size

Firm size, calculated as the natural logarithm of market
capitalization.

GrowthPercentage change in sales between years.

R&D

Research and development costs, scaled by total assets.

INTAST

Intangible assets, scaled by total assets.

FXTAST

Fixed assets, scaled by total assets.

SOE

Dummy variable that equals to 1 if the ultimate controllingshareholder of a firm is a government agency or governmentcontrolled enterprise, and 0 otherwise.

Duality

Chairman CEO duality, equals to 1 if the chairman of board of
directors and the CEO are the same person, and 0 otherwise.

LagLoss

Dummy variable, equals to 1 if a firm suffers a loss in t-1, and 0
otherwise.

RightsDummy variable that equals 1 if the firm issues a rights offering in
the next year, and 0 otherwise.

ETC

Entertainment and travel costs, scaled by net sales.

34

Table1 Sample selection and distribution
Panel A Sample selection
Firm-year observations of all listed A-shares of non-financial firms
between 2009 and 2015 (excluding 2012)

12,030Less observations of firms with ST or *ST tags

441

Less observations with ETR<0 or ETR>1

2,594

Less observations with missing data

375

Final pooled sample

8,620

Panel B: Sample distribution by yearYear

No. of firm-years (%)

2009

1,072

12%

2010

1,204

14%

2011

1,425

17%

2013

1,641

19%

2014

1,628

19%

2015

1,650

19%

Total

8,620

100%

35

Table 2 Descriptive Statistics
This table provides the descriptive statistics of firm characteristics for the full sample and sub-samples partitioned by period. All of the variables
are defined in Appendix D.
Full Sample (N = 8,620)

Post = 0 (N = 3,701)

Post = 1 (N = 4,919)

Variable

mean

p25

p50

p75

Std.

mean

p25

p50

p75

Std.

mean

p25

p50

p75

Std.

METR

1.161

0.773

1.054

1.360 0.766

1.099

0.736

1.031

1.294 0.702

1.207

0.805

1.075

1.419

0.808

BTD

0.779

0.725

0.809

0.861 0.144

0.789

0.733

0.816

0.869 0.138

0.771

0.717

0.802

0.857

0.147

RBTD

0.000

-0.0030.004

0.046 0.101

0.012-0.0260.013

0.062 0.099-0.009-0.039

0.000

0.036

0.101

Tobin’s Q

2.630

1.446

2.052

3.116 1.835

2.609

1.494

2.082

3.068 1.720

2.647

1.412

2.031

3.146

1.917

Ind-Adj
Tobin’s Q

0.390-0.4030.000

0.729 1.552

0.354-0.4010.000

0.718 1.464

0.417-0.406

0.000

0.744

1.615

ROE

0.113

0.051

0.098

0.157 0.094

0.128

0.063

0.111

0.174 0.101

0.102

0.044

0.088

0.142

0.086

Accrual

0.019-0.0370.007

0.058 0.103

0.027-0.0380.014

0.072 0.114

0.014-0.035

0.004

0.049

0.093

Leverage

0.466

0.307

0.470

0.627 0.207

0.484

0.329

0.493

0.645 0.207

0.453

0.292

0.450

0.614

0.206

Size

15.644 14.945 15.527 16.205 0.939 15.435 14.748 15.255 15.930 0.933 15.800 15.149 15.711 16.370

0.913

Growth0.229-0.0130.118

0.278 0.630

0.299

0.043

0.178

0.361 0.670

0.177-0.042

0.078

0.209

0.592

R&D

0.006

0.000

0.000

0.008

0.011

0.004

0.000

0.000

0.001 0.009

0.008

0.000

0.000

0.013

0.012

INTAST

0.049

0.015

0.034

0.059 0.063

0.047

0.013

0.031

0.058 0.063

0.050

0.017

0.035

0.060

0.063

FXTAST

0.241

0.105

0.207

0.343 0.176

0.249

0.109

0.215

0.360 0.179

0.235

0.102

0.202

0.334

0.173

SOE

0.487

0.000

0.000

1.000 0.500

0.552

0.000

1.000

1.000 0.497

0.438

0.000

0.000

1.000

0.496

Duality

0.209

0.000

0.000

0.000 0.407

0.179

0.000

0.000

0.000 0.384

0.232

0.000

0.000

0.000

0.422

(Continued on next page)36

Table 2 (Continued)
Full Sample (N = 8,620)

Post = 0 (N = 3,701)

Post = 1 (N = 4,919)

LagLoss

0.071

0.000

0.000

0.000 0.257

0.072

0.000

0.000

0.000 0.259

0.070

0.000

0.000

0.000

0.256

Rights

0.156

0.000

0.000

0.000 0.363

0.096

0.000

0.000

0.000 0.295

0.200

0.000

0.000

0.000

0.400

ATR

0.197

0.150

0.150

0.250 0.051

0.197

0.150

0.200

0.250 0.050

0.197

0.150

0.150

0.250

0.051

37

Table 3: Correlation Matrix
This table details the Pearson’s correlation matrix for the major variables used in the analyses.
2.BTD
3.RBTD
4.Tobin’s Q
5.Ind-Adj
Tobin’s Q
6.Post7.Size8.Growth
9.Leverage
10.ROE
11.Accrual
12.R&D
13.INTAST
14.FXTAST
15.SOE
16.Duality
17.LagLoss
18.Rights
19.ATR

1.METR-0.883-0.719-0.123

2

3

4

0.731
0.174

0.045

-0.115

0.120

0.032

0.887

0.070
-0.056-0.0110.115-0.133-0.036-0.0130.023-0.0530.014-0.006-0.058-0.005-0.159-0.0630.035-0.013-0.218
0.087
0.019
0.143
-0.0270.060-0.080
0.044
0.044
0.018
-0.239-0.1050.010-0.008-0.0320.088
0.004-0.015-0.0030.015
0.002-0.0070.034-0.007-0.019

0.010
0.089
0.070
-0.364
0.140
0.090
0.186
0.040
-0.120-0.239
0.124
0.080
0.069
-0.137

5

6

7

8

9

10

11

12

13

14

15

0.020
0.012
0.072
-0.285
0.153
0.117
0.120
0.028
-0.075-0.194
0.100
0.077
0.046
-0.0250.193-0.097-0.074-0.136-0.0620.181
0.024-0.039-0.1130.065-0.004
0.142
0.002

0.063
0.075
0.320
0.054
0.055
-0.003-0.0510.135-0.063-0.112
0.063
0.045

0.076
0.209
0.223
-0.004-0.015-0.089-0.037
0.006
0.094
0.043
0.051

0.084
-0.042-0.218-0.0640.012
0.262-0.126
0.126
0.090
0.264

0.269
0.027
-0.023-0.1500.011-0.027-0.122
0.020
0.075

0.018
-0.119-0.334-0.1130.042-0.0450.007
0.023-0.037-0.100-0.1550.102-0.0600.053-0.3330.089
0.036-0.027
0.043
0.017
0.038

0.163
-0.073
0.110
0.002
0.024

-0.2680.030-0.093
0.191

38

16

17

-0.0160.042 0.004-0.100 0.061

18-0.042

Table 4 Effects of Anti-Corruption Campaign on Tax AvoidanceThis table presents the regression results of the effects of the anti-corruption campaign on tax
avoidance. The dependent variables are measures of tax avoidance, i.e., METR, BTD and RBTD.
Firm fixed effects are included. Standard errors are computed after clustering by firm. The twotailed t-statistics are reported in parentheses. All of the variables are defined in Appendix D. *,** and *** denote significance at the 10%, 5%, and 1% levels, respectively.
METR

Variable

Post

(2)

(3)

(4)

(5)

(6)

0.128***(6.66)-0.027***(-7.77)0.794***(403.28)-0.025***(-6.31)0.012***(3.42)-0.011***(-3.75)-0.121***(-5.69)0.221***(7.08)
0.005(0.29)-0.122(-0.52)0.012(0.14)
0.071***(2.93)-0.000(-0.01)-0.004(-0.52)0.034***(3.63)
0.003(0.72)-0.225***(-2.64)0.667***(11.76)-0.025***(-7.55)1.088***(98.91)0.150***(6.84)-0.074***(-3.85)0.059***(4.08)
0.633***(5.72)-1.231***(-7.42)-0.025(-0.26)1.636(1.03)
0.098(0.24)-0.300**(-2.28)0.007(0.08)
0.012(0.31)-0.187***(-3.73)-0.026(-1.19)-4.967***(-9.51)3.106***(9.79)

0.014***(7.68)-0.024***(-6.33)0.012***(3.64)-0.010***(-3.54)-0.114***(-5.59)0.216***(7.29)-0.034*(-1.90)-0.134(-0.60)0.009(0.11)
0.069***(2.98)-0.001(-0.06)-0.005(-0.76)
0.031***(3.53)
0.003(0.69)-0.220***(-2.73)-0.115**(-2.14)

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

0.010
8,620

0.067
8,620

0.014
8,620

0.046
8,620

0.013
8,620

0.045
8,620

GrowthLeverageROE
AccrualR&D
INTASTFXTAST
SOE
Duality
LagLoss
RightsATR

Firm Fixed
EffectClustered by
Firm
R2
N

RBTD

(1)

Size

Constant

BTD

39

Table 5 Effects of Anti-Corruption Campaign on Tax Avoidance (DID Method)
This table presents the regression results of the effects of the anti-corruption campaign on tax
avoidance. The dependent variables are measures of tax avoidance, i.e., METR, BTD and RBTD.
Firm fixed effects are included in Columns (1), (3) and (5), while industry and year fixed effects
are included in Columns (2), (4) and (6). Standard errors are computed after clustering by firm.
The two-tailed t-statistics are reported in parentheses. All of the variables are defined inAppendix D. *, ** and *** denote significance at the 10%, 5%, and 1% levels, respectively.
Variable
Post
Post_HighCRPT
HighCRPT
Size
GrowthLeverageROE
AccrualR&D
INTASTFXTAST
SOE
Duality
LagLoss
RightsATR
Constant

Firm Fixed
Effect

METR
(1)
(2)
0.097*** 0.213***(3.85)(6.37)
0.101*** 0.089***(2.75)(2.61)-0.048*(-1.78)-0.071*** -0.040***(-3.70)(-3.30)0.059*** 0.041***(4.09)(3.17)
0.647*** 0.686***(5.86)(11.32)-1.216*** -1.110***(-7.34)(-9.16)-0.032-0.127(-0.33)(-1.43)1.760-3.010***(1.11)(-3.36)0.069
0.625***(0.17)(2.82)-0.304** -0.261***(-2.31)(-3.44)0.012
0.030(0.14)(1.29)
0.009-0.018(0.23)(-0.74)-0.191*** -0.230***(-3.80)(-5.38)-0.027-0.063***(-1.21)(-2.99)-4.951*** -3.964***(-9.54)(-14.50)
3.051*** 1.736***(9.64)(6.45)
Y

BTD
(3)
(4)
-0.016*** -0.042***(-3.28)(-6.44)-0.019*** -0.017***(-2.79)(-2.67)0.010*(1.89)
0.011***
0.008***(3.27)(3.35)-0.011*** -0.007***(-3.76)(-2.66)-0.123*** -0.126***(-5.83)(-10.51)
0.219***
0.199***(7.01)(8.36)
0.007
0.029(0.35)(1.63)-0.1450.545***(-0.62)(3.85)
0.017-0.096**(0.21)(-2.11)0.072***
0.056***(2.96)(3.67)-0.001-0.003(-0.06)(-0.72)-0.0030.003(-0.43)(0.74)
0.034***
0.046***(3.70)(5.50)
0.003
0.010**(0.74)(2.52)-0.228*** -0.377***(-2.70)(-7.79)0.677***
0.893***(11.96)(17.05)

N

Y

N

RBTD
(5)
(6)
-0.015*** -0.034***(-3.24)(-6.15)-0.018*** -0.015***(-2.77)(-2.64)0.010***(2.83)
0.011***
0.002*(3.49)(1.78)-0.010*** -0.006***(-3.56)(-2.68)-0.117*** -0.033***(-5.74)(-7.34)0.213***
0.104***(7.22)(6.80)-0.033*-0.008(-1.83)(-0.62)-0.156-0.034(-0.69)(-0.47)0.014-0.007(0.18)(-0.39)0.070***
0.011*(3.01)(1.71)-0.002-0.001(-0.12)(-0.64)-0.005-0.000(-0.68)(-0.22)0.032***
0.021***(3.60)(3.41)
0.003
0.003(0.71)(0.79)-0.223***-0.023(-2.79)(-1.19)-0.105**0.001(-1.97)(0.06)Y

N(Continued on next page)40

Table 5 (Continued)
METR
Industry andYear Fixed
Effects
Clustered by
Firm
R2
N

BTD

RBTD

(1)

(2)

(3)

(4)

(5)

(6)

N

Y

N

Y

N

Y

Y

Y

Y

Y

Y

Y

0.068
8,620

0.128
8,620

0.047
8,620

0.158
8,620

0.047
8,620

0.032
8,620

41

Table 6 Robustness Tests
This table presents the regression results of the effects of the anti-corruption campaign on tax avoidance. The dependent variables are measures of tax avoidance,i.e., METR, BTD and RBTD. Firm fixed effects are included. Standard errors are computed after clustering by firm. The two-tailed t-statistics are reported inparentheses. All of the variables are defined in Appendix D. *, ** and *** denote significance at the 10%, 5%, and 1% levels, respectively.
Variable

Post
Size
GrowthLeverageROE
Accrual

METR
(1)

R&D=0
BTD
(2)

RBTD
(3)

METR
(4)

Constant Sample
BTD
(5)

RBTD
(6)

METR
(7)

0.132***(4.88)-0.070***(-2.70)0.052***(2.97)
0.739***(4.87)-1.029***(-5.30)-0.188*(-1.66)-0.023***(-4.40)0.009*(1.84)-0.011***(-2.86)-0.149***(-4.94)0.203***(5.11)
0.033(1.41)-0.023***(-4.53)0.010**(2.02)-0.009**(-2.52)-0.144***(-5.02)
0.195***(5.18)-0.000(-0.02)-0.386(-0.71)-0.333**(-2.16)0.085(0.70)
0.085***(2.84)

0.075(0.64)
0.081***(2.82)

0.138***(5.39)-0.121***(-4.44)0.050**(2.57)
0.681***(5.03)-1.277***(-5.43)0.062(0.47)
1.749(1.11)-0.147(-0.22)-0.417***(-2.70)-0.024***(-5.05)0.019***(4.02)-0.008*(-1.95)-0.130***(-4.83)
0.236***(5.52)-0.009(-0.38)-0.138(-0.61)0.074(0.55)
0.091***(3.08)-0.022***(-4.98)0.018***(3.98)-0.006(-1.63)-0.130***(-4.97)0.226***(5.51)-0.045*(-1.91)-0.129(-0.59)0.066(0.49)
0.086***(2.98)

0.134***(6.16)-0.058***(-3.04)0.066***(4.41)
0.725***(6.46)-2.189***(-11.76)-0.094(-0.97)1.759(1.11)
0.252(0.64)-0.214*(-1.67)R&D
INTASTFXTAST

42

Profitable Firms Only
BTD
RBTD
(8)
(9)
-0.022***-0.022***(-5.63)(-5.68)0.009***
0.009***(2.60)(2.84)-0.013***-0.011***(-4.09)(-3.82)-0.141***-0.134***(-6.51)(-6.44)0.405***
0.386***(11.89)(11.87)0.018-0.023(0.96)(-1.26)-0.130-0.138(-0.56)(-0.61)-0.015-0.016(-0.19)(-0.21)
0.054**
0.053**(2.24)(2.32)(Continued on next page.)Table 6 (Continued)
METR
SOE
Duality
LagLoss
RightsATR
Constant
Firm Fixed
EffectClustered by
Firm
R2
N

0.089
(0.79)-0.019(-0.37)-0.173***(-2.67)
0.003(0.11)-4.507***(-6.82)2.905***(6.59)

BTD
R&D=0-0.017(-0.72)0.006(0.66)
0.035***(2.87)-0.004(-0.71)-0.282**(-2.38)0.731***(8.74)

RBTD

METR

BTD
RBTD
Constant Sample-0.1120.020
0.016(-0.90)(0.84)(0.73)
0.026-0.007-0.007(0.56)(-0.81)(-0.88)-0.1770.028
0.029(-1.45)(1.39)(1.57)
0.001-0.003-0.003(0.04)(-0.57)(-0.55)-4.237***-0.325***-0.326***(-7.57)(-3.27)(-3.35)3.806***
0.550***-0.205***(8.21)(6.91)(-2.71)-0.020(-0.91)0.004(0.39)
0.034***(2.84)-0.004(-0.65)-0.279**(-2.47)-0.042(-0.53)

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

0.062
5,111

0.048
5,111

0.047
5,111

0.083
3,840

0.070
3,840

0.069
3,840

0.101
8,454

0.083
8,454

0.080
8,454

43

METR

BTD
RBTD
Profitable Firms Only
-0.0360.008
0.005(-0.43)(0.48)(0.33)
0.016-0.004-0.005(0.41)(-0.58)(-0.79)-0.208***0.038***
0.035***(-4.05)(3.97)(3.84)-0.0190.001
0.001(-0.88)(0.34)(0.30)-4.823***-0.281***-0.275***(-9.29)(-3.35)(-3.47)2.917***
0.709***-0.074(9.27)(12.71)(-1.40)Table 7: Anti-Corruption Campaign, Entertainment and Travel Costs, and Tax AvoidancePanel A compares the mean and median of entertainment and travel costs (ETC) between the
pre- and post-launch periods of the campaign. Panel B compares the effects of entertainment
and travel costs (ETC) on tax avoidance between the pre- and post-launch periods of thecampaign. Firm fixed effects are included. Standard errors are computed after clustering by
firm. The two-tailed t-statistics are reported in parentheses. All of the variables are defined inAppendix D. *, ** and *** denote significance at the 10%, 5%, and 1% levels, respectively.
Panel A Comparison of entertainment and travel costs (ETC) in the pre-and post-launch periodsof the campaign.
Post = 0(N=2,107

Post = 1(N=4,120)

Differencet (or x2) value

Mean

0.00540.00470.00074.760***Median0.00350.00290.000633.263***

Panel B Effects of entertainment and travel costs (ETC) on tax avoidance between the preand post-launch periods of the campaign.
Variable
ETC
Post_ETC
Post
Size
GrowthLeverageROE
AccrualR&D
INTASTFXTAST
SOE
DualityMETR(1)-16.687***(-3.35)7.470*(1.72)
0.076**(2.28)-0.075***(-3.34)0.045**(2.44)
0.533***(3.91)-1.717***(-8.04)0.069(0.59)
1.588(0.55)
0.368(0.74)-0.088(-0.51)0.030(0.28)-0.045(-0.93)BTD(2)
3.211***(3.26)-1.371*(-1.74)-0.010(-1.59)0.012***(3.11)-0.008**(-2.23)-0.098***(-3.93)0.321***(8.12)-0.007(-0.33)-0.144(-0.34)-0.051(-0.49)0.031(1.01)-0.006(-0.31)
0.005(0.54)
44

RBTD(3)
3.095***(3.23)-1.354*(-1.77)-0.009(-1.46)0.012***(3.27)-0.008**(-2.11)-0.094***(-3.91)0.314***(8.52)-0.042*(-1.95)-0.136(-0.34)-0.066(-0.67)0.033(1.11)-0.008(-0.43)0.002(0.27)(Continued on next page)Table 7 (Continued)

LagLoss
RightsATR
Constant

Firm Fixed Effect
Clustered by Firm
R2
N

METR
(1)
-0.180***(-2.73)-0.017(-0.61)-4.900***(-8.04)3.260***(8.47)

BTD(2)
0.031***(2.62)
0.001(0.26)-0.266**(-2.54)
0.637***(9.49)

RBTD(3)
0.028**(2.49)
0.001(0.24)-0.260**(-2.55)-0.141**(-2.22)

Y
Y
0.069
6,227

Y
Y
0.051
6,227

Y
Y
0.050
6,227

45

Table 8 Tax Avoidance, Firm Value and Anti-Corruption Campaign
The dependent variables are Tobin’s Q and Ind-Adj Tobin’s Q. Firm fixed effects are included.
Standard errors are computed after clustering by firm. The two-tailed t-statistics are reported inparentheses. All of the variables are defined in Appendix D. *, ** and *** denote significanceat the 10%, 5%, and 1% levels, respectively.
Variable
Post
Post_BTD
BTD
Size
Leverage
GrowthROE
Accrual
SOE

Tobin's Q(1)-0.205(-1.14)-0.615***(-2.62)0.603***(2.97)
1.372***(28.14)-0.437(-1.39)-0.142***(-4.07)1.027***(2.59)
0.000***(2.98)-0.192(-0.72)

Ind-Adj Tobin’s Q
(2)
0.112
(0.68)-0.466**(-2.15)0.399**(2.19)
0.589***(12.91)-0.870***(-3.07)-0.077**(-2.31)2.103***(5.47)-0.000**(-2.16)-0.324(-1.37)

Tobin's Q(3)

Ind-Adj Tobin’s Q(4)-8.644***(-11.50)-0.216(-1.21)-0.586**(-2.52)0.564***(2.79)
1.382***(27.91)-0.488(-1.54)-0.136***(-3.97)1.087***(2.70)
0.000***(2.79)-0.183(-0.69)-3.032(-0.93)0.749**(2.30)-18.978***(-22.47)0.122(0.74)-0.489**(-2.27)0.401**(2.21)
0.592***(12.91)-0.899***(-3.17)-0.076**(-2.31)2.125***(5.47)-0.000**(-2.26)-0.322(-1.36)
3.113(0.96)
0.423(1.48)-8.799***(-11.49)-18.707***(-22.95)
Y

Y

Y

Y

Y

Y

Y

Y

0.330
8,620

0.128
8,620

0.332
8,620

0.129
8,620

R&D
FXTAST
Constant

Firm Fixed
EffectClusteredby Firm
R2
N

46