How does state ownership affect tax avoidance? Evidence from China

Presented by

Dr Huai Zhang

Associate Professor Nanyang Technological University

#2012/13-18

The views and opinions expressed in this working paper are those of the author(s) and not necessarily those of the School of Accountancy, Singapore Management University.

How does state ownership affect tax avoidance? Evidence from China

Ming Jian

Wanfu Li

Huai Zhang*

ABSTRACT

We examine how the state ownership affects firms’ tax avoidance. Using a proprietary dataset of actual tax filings of firms in China, we find evidence that state-owned enterprises (SOEs) avoid tax to a less extent than non-SOEs. The negative effect of the state ownership on tax avoidance is stronger among bigger firms and is weaker among firms with concentrated non-state ownership. Overall, our results suggest that the executives at SOEs have incentives to please the government through generous tax payments, and that these incentives are curbed by the monitoring of concentrated non-state ownership. Keywords: State ownership; Tax avoidance. JEL Classification: G15, G18, M41.

__________________________ *Corresponding author. Tel: +65-6790-4097. Email: huaizhang@ntu.edu.sg. Li is from Fuzhou University. Jian and Zhang are from Nanyang Technological University. We acknowledge helpful comments from Bin Ke and seminar participants at Chinese University of Hong Kong and Nanyang Technological University.

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1. Introduction

How does state ownership affect firms’ tax avoidance? Given the important role played by

state-owned firms in the world economy, this is an important question. However, it has no obvious

answer. On one hand, prior studies suggest that politically connected firms receive preferential

treatments from the government. For example, Faccio et al. (2006) find that politically connected

firms are more likely to be bailed out by the government. Since state ownership represents a strong

form of political connection, we expect that state-owned firms’ are more capable of wringing out tax

benefits from the government. Managers have incentives to take advantage of these benefits and

evade tax more aggressively than non-state-owned firms. We call this effect as the political favoritism

effect. On the other hand, career prospects of executives of state-owned enterprises (SOEs) are

determined by the government. Since tax revenue helps the government to achieve social objectives,

SOE executives receive positive publicity and enjoy greater chances of promotions if the SOE they

run pays more tax.1

China provides a fruitful setting to examine our research question because it offers a

meaningful number of SOEs. In addition, given the size of the Chinese economy, our finding is likely

to be of economic significance. Using a proprietary dataset of Chinese firms from 2007 to 2009, we

Therefore, these executives have incentives to overpay tax, which lead to our

prediction that SOEs avoid tax to a less extent than non-state-owned firms. We label this effect as the

bureaucratic incentive effect.

1 Since the government owns SOEs, the tax paid by the SOEs is similar to dividends. The government’s encouragement of higher tax payments may seem puzzling at the first glance, because the standard finance textbook suggests that, to maximize the value of the firm, higher dividends shall be avoided for firms with promising investment opportunities. There are two possible explanations. First, the government has incentives to maximize social welfares instead of the value of SOEs. Second, the government officials have limited tenure and they lack the incentive to preserve the long-term value of SOEs. We discuss this in detail in Section 2.2.

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test whether SOEs are more or less tax avoidant than non-SOEs. Our measure of tax avoidance is the

book-tax difference, computed as the pre-tax financial income minus the taxable income divided by

total assets.2

Hanlon, 2003

A higher value of this variable indicates a greater extent of tax avoidance. One notable

advantage over most prior studies is that our dataset provides actual tax filings of firms, eliminating

the need to estimate the taxable income. As prior studies point out ( ; Hanlon and

Heitzman, 2010; McGill and Outslay, 2004), estimating taxable income has many problems.

We find that SOEs avoid tax less than non-SOEs. Specifically, the book-tax difference is

lower by 3.1% on average for SOEs than for non-SOEs.3

We continue to hypothesize that the bureaucratic incentive effect is more pronounced for

bigger firms, for the following two reasons. First, the executives of bigger SOEs are more likely to be

bureaucrats, since bigger firms are economic significant entities to the government and the

government is likely to appoint bureaucrats to these firms to maintain the governmental control.

These bureaucrats have greater political incentives compared to professional managers, implying a

The difference in this tax avoidance measure

widens to 4.7% after we control for various determinants of the book-tax difference, such as

profitability, leverage, the existence of loss carry forward and PPE. This finding suggests that the

bureaucratic incentive effect strongly dominates the political favoritism effect.

2 The effective tax rate has been used by prior literature (e.g., Chen et al., 2010) as a tax avoidance measure. However, in China, the effective tax rate varies with ownership structure. For example, to attract foreign investments, foreign investment enterprises enjoy lower tax rates. Using the effective tax rate will bias for our conclusions that SOEs avoid tax less than non-SOEs. We discuss more about this in Section 4. 3 3.1% may seem too high in magnitude. This is however due to the small size of firms in our sample. As shown in Table 1, the average total assets of firms in our sample are 3.2 million RMB, about 0.45 million USD. Since we use total assets the deflator to compute the book-tax difference, a small deflator may yield a ratio of high magnitude.

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more pronounced bureaucratic incentive effect. Second, big firms are more visible. They are more

likely to be on the radar of the government and expected to contribute to the tax revenue. Failing to

meeting this expectation is costly to the executives of these SOEs, because they may be demoted or

replaced by the government. Therefore, relative to non-SOEs of the same size, we shall observe less

tax avoidance for bigger SOEs.

While paying more tax helps to achieve the social objectives of the government, it hurts other

shareholders’ value, since it represents a wealth transfer from other shareholders to the controlling

shareholder, i.e., the government. We lastly examine whether concentrated non-state ownership

constrains this value-destroying behavior. As argued by Shleifer and Vishny (1986), block

shareholders have strong incentives to monitor management because the benefits that they receive

from their monitoring activities are likely to exceed the costs of monitoring that they have to bear.

Supporting this argument, previous studies (e.g., Chen et al., 2007) show that block shareholders play

an important role in monitoring management. 4 A concentrated non-state ownership means a high

likelihood of the existence of big and powerful block shareholders, whose monitoring counters the

incentives of SOEs’ executives to pay more tax. We therefore hypothesize that the negative effect of

state ownership on tax avoidance is weaker among firms with more concentrated non-state

ownership.5

4 See Holderness (

2003) for a review of empirical literature on the monitoring role of blockholders. 5 We can potentially hypothesize that the effect of the state ownership on tax avoidance is weaker for firms with non-state blockholder than for firms without non-state blockholder. However, there are two issues. First, the ownership of non-state shareholders has a mechanical negative relationship with the state ownership. Our empirical results may be explained by a non-linear relationship between the state ownership and the tax

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This hypothesis not only is interesting in its own right but also guards against an alternative

explanation for our main finding that SOEs are less tax avoidance than non-SOEs. It could be that the

political support is more important for SOEs than for non-SOEs, and the higher tax payment by SOEs

is a necessary value-increasing investment in return for the support. If this alternative explanation is

true, we expect that non-state block blockers encourage this type of investment and consequently the

negative effect of the state ownership on tax avoidance is stronger among firms with more

concentrated non-state ownership. This expectation is the opposite of our hypothesis. Therefore,

results in support of our hypothesis are evidence against this alternative explanation.

Our hypotheses are supported by empirical results. Specifically, we find that among small

firms, there is no significant difference in tax avoidance between SOEs and non-SOEs. Among bigger

firms, the book-tax difference is lower by 4.6%, significant at the 1% level, for SOEs than for non-

SOEs. This result suggests that the negative effect of state ownership on tax avoidance is more

pronounced among bigger firms. Turning to the concentration of non-state ownership, we use the

firm’s Herfindahl index based on the top five non-state owners to measure it. We find that among

firms with less concentrated non-state ownership, the tax avoidance measure is lower by 3.7% for

SOEs than for non-SOEs. However, this difference between SOEs and non-SOEs is reduced to only 1%

among firms with more concentrated non-state ownership. This finding supports the view that

concentrated non-state ownership curbs the bureaucratic incentive effect.

avoidance. Second, it is difficult to decide on the ownership which qualifies as block holding. For firms with very diffuse ownership structure, 1% of ownership may be considered as a block ownership. However, for firms with concentrated ownership structure, 1% of ownership may not represent meaningful holdings.

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In untabulated tests, we check the robustness of our results. First, we are concerned about the

generalizability of our results, because they are based on a sample of small private firms from one city

in China. To address this concern, we rerun our tests using a sample of listed firms for the period

1998-2009. We find that listed firms under the ultimate control of the government avoid tax to a less

extent than listed firms not under state control, suggesting that our main finding is robust to bigger

listed firms from various parts of China.

Second, the Chinese government offers tax benefits to foreign investment enterprises,

including Sino-foreign joint ventures and wholly foreign-owned enterprises. This policy may explain

our main finding, because these foreign investment enterprises are not state-owned and they may

appear to avoid tax to a greater extent than other firms as a result of the tax benefits. We test the

robustness of our results by excluding all foreign investment enterprises from our sample. Our main

finding continues to hold.

Third, we test whether our results are robust to other measures of tax avoidance. Following

Chen et al. (2010), we compute cash effective tax rate and Desai-Dharmapala (2006) residual book-

tax difference. The cash effective rate is the cash tax payment divided by the taxable income while the

Desai-Dharmapala (2006) residual book-tax difference is the residual from the regression of the book-

tax difference on total accruals. We find that our results are robust to these two new measures of tax

avoidance.

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Lastly, we test whether our findings are robust to an alternative measure of the concentration

of the non-state ownership. This measure is based on whether there exists a non-state owner who

owns at least 10% of the firm’s equity. We find that the negative effect of state ownership on tax

avoidance is weaker for firms with such a block non-state owner than for firms without. This finding

suggests that our inference is robust to this alternative measure of the concentration.

Our paper contributes to the prior literature in the following ways. First, our paper extends

prior literature examining how firms’ ownership structure affects their tax reporting practices. Several

papers study the differences in firms’ tax reporting between private and public companies in certain

industries, such as banks and insurers (e.g., Beatty and Harris, 1999; Cloyd et al., 1996; Hanlon et al.,

2007; Mikhail, 1999; Mills and Newberry, 2005). They generally conclude that private companies are

more tax aggressive. Chen et al. (2010) examine large public firms (S&P 1500 firms) and show that

family firms are less tax aggressive than non-family firms, suggesting that the unique agency issues

of family firms are responsible for their lower tax aggressiveness. We show that state-owned firms are

less tax aggressive than non-state owned firms and that the effect of the state ownership is stronger

among bigger firms but weaker among firms with more concentrated non-state ownership. Our

findings suggest that bureaucrats running state-owned firms have incentives to pay more tax and these

incentives are counteracted by monitoring of non-state block owners. To the extent that state-owned

firms from China and other countries play an important role in the world economy, our results mark

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one step forward to a better understanding of the impact of the ownership structure on firms’ tax

behaviors.

Second, we contribute to prior literature on political connections. Fan et al. (2007) find that

firms with a stronger political connection, as proxied by having a former or current government

official as the CEO, experience poorer post-IPO stock returns than other firms. Their results suggest

that political connected executives serve as a vehicle for the government’s rent-seeking activities.

However, they are silent on the specific channel through which the bureaucrats destroy value. To the

extent that lower tax payment leads to higher shareholder value, our results show that the value-

destruction identified by Fan et al. (2007) may be attributed to these executives’ generous tax

payments. We also contribute to prior studies (Faccio et al., 2006; Fisman, 2001) who show

significant economic benefits, such as government subsidies and bailouts, from political connections.

These studies imply that a political connection enhances shareholder value. Our findings however

suggest that a political connection may increase the firm’s tax liability and reduce its value to non-

state shareholders.

The rest of the paper proceeds as follows. Section 2 discusses the institutional setting in China

and develops hypotheses. Section 3 covers sample formation and descriptive statistics. Section 4

covers research design. Section 5 discusses empirical results. Section 6 concludes.

2. Institutional setting and hypotheses development

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2.1 China’s enterprise taxation system

The enterprise income tax in China in many ways is similar to that in the U.S. For example, in

both China and the U.S., accelerated depreciations are allowed in firms’ income tax returns and

charity donations quality for taxable income deductions. A key difference however lies in tax benefits

to foreign investments.

As a developing country, China sought to attract foreign investments. To achieve this

objective, in the early 1990s, China granted foreign investment enterprises (FIEs), including Sino-

foreign joint ventures and wholly foreign-owned enterprises, various tax benefits. For example, FIEs

established in Special Economic Zones, the Pudong Development Zone in Shanghai, and Economic

and Technological Development Zone, enjoyed a flat tax rate of 15 percent, which was much lower

than the normal flat tax rate of 30 percent (Chan and Mo, 2000; National People's Congress (NPC),

1991, Article 7). These tax benefits were unavailable to SOEs.

Over the years, the government has gradually reduced the tax benefits given to FIEs. In 2007,

the Chinese government issued the Enterprise Income Tax Law of the People's Republic of China,

which took effect on January 1, 2008 and largely eliminated the preferential tax treatment to FIEs.

However, the FIEs that were established prior to this new regulation could continue to enjoy the lower

tax rate available at the time of their establishment for the next five years (National People's Congress

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(NPC), 2007, Article 57). Therefore, during our sample period, 2007-2009, the effective tax rates are

largely influenced by the ownership structure of the firm.

2.2. Hypotheses development

Since the 1980s, the Chinese government has decentralized managerial decision rights of

SOEs from the central government down to the local firm level (Qian, 1995). While the operating

decision rights reside in the SOE managers, the government retains ultimate decision rights on the

appointment of CEOs. Often, bureaucrats are appointed as CEOs. For example, Fan et al. (2007)

examine the CEOs of China’s newly partially privatized firms and find that close to 26% of the CEOs

of these firms are either current or former government officials.

Prior studies show that politically connected firms receive preferential treatment in dealing

with the government. For example, they are more likely to obtain loans from state-owned banks or be

bailed out by the local government in the event of financial difficulty (Chiu and Joh, 2004; Cull and

Xu, 2005; Faccio et al., 2006; Johnson and Mitton, 2003; Khwaja and Mian, 2005). Since state

ownership represents a strong form of political connection, SOEs may receive preferential treatment

from the tax bureau than non-SOEs. For example, the executives of SOEs may use their political

connection to convince the government that their firms quality for certain tax benefits. Their political

connections may also help to reduce the likelihood of tax audits, and limit the penalties imposed in the

event that their firms are convicted of tax evasions. Executives of SOEs have incentives to take

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advantage of the preferential treatment from the government and evade taxes to a greater extent, since

the tax saving may be used as cash for personal perks and it may increase managerial compensation

through its impact on firm value. We label this as the political favoritism effect.

However, executives at SOEs may also have incentives to overpay tax. This argument derives

from the fact that they are appointed and evaluated by the government. Although it is not fully

understood how executives at SOEs are evaluated, anecdotal evidence abounds that SOEs’ tax

payment is an important consideration. In China, it is common practice for the government to

recognize and award top tax-paying firms in its jurisdiction. These firms are described as “well-run”

and important contributors to the society by the state-run media. Executives of these firms may also

have the chance to meet high-ranking government officials in the award ceremony. For example,

Hangzhou Daily, on March 3, 2012, reported that the local government organized a meeting to

recognize the contributions of 62 enterprises because these firms paid more than 20 million RMB

taxes in 2011. These firms were described as “making positive contributions to the city’s economic

and social development” by the state-run newspaper. 6

6 The news article can be found at

The positive publicity and favorable

evaluations by the government motivate executives at SOEs to pay more tax. We label this effect as

the bureaucratic incentive effect, which predicts that SOEs avoid tax to a less extent than non-SOEs.

http://hzdaily.hangzhou.com.cn/hzrb/html/2012-03/03/content_1230011.htm. Similar news articles can be found at the following websites: http://wb.sznews.com/html/2009-01/15/content_490642.htm; http://epaper.nfdaily.cn/html/2012-01/11/content_7047401.htm; http://www.chinaneast.gov.cn/2012-04/12/c_131521651.htm

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It is worth considering why the government encourages SOEs to pay high taxes. Since the

government owns SOEs, higher tax payments can be considered as higher dividends to the owner. It is

not clear why a value-maximizing owner would always prefer high dividends. In fact, the standard

corporate finance textbook (e.g., Brealey et al., 2010) suggests that high dividends shall be avoided if

the firm has many positive NPV (net present value) projects. The conflict between the theory and the

practice can be reconciled in the following two ways. First, conceptually, the government’s goal is not

to maximize the value of SOEs, but to maximize social welfare. It is possible that higher tax payments

are necessary for the government to achieve certain social objectives. Second, government officials

have limited tenure. These officials have incentives to optimize their performance in economic

development and social development within their limited tenure. This lack of long-term perspective

may also induce the strong preference for higher tax payments.

Another point worth considering is why the government prefers to receive cash through tax,

given that there are other ways for the government to receive cash from SOEs. For example, as the

owner of SOEs, the government can obtain cash from SOEs through dividend payments. We note that

all tax payment goes to the government while part of the dividends go to non-state owners, for firms

not 100% owned by the government. Therefore, paying dividends is a more costly approach to

transfer cash to the government, for firms not wholly owned by the government. In addition, paying

dividends entails administrative chores and requires shareholder approval. The government may deem

it less cost-effective than paying tax.

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Our prior discussions suggest the bureaucratic incentive effect. Because the political

favoritism effect and the bureaucratic incentive effect have opposite predictions, we present our H1 in

its null form.

H1: SOEs avoid tax to the same extent as non-SOEs.

We continue to hypothesize that the bureaucratic incentive effect is more pronounced for

bigger firms, because of the following. First, since big firms are economically significant entities to

the government, the government is likely to appoint bureaucrats to these firms to maintain the

governmental control. These bureaucrats have greater political incentives than professional managers,

implying a more pronounced bureaucratic incentive effect. Second, bigger firms are more visible and

the executives of bigger SOEs are under greater pressure to contribute to the government’s tax

revenue. The greater pressure makes it more costly for bigger SOEs to avoid tax.

Since the bureaucratic incentive effect implies a negative effect of state ownership on tax

avoidance, our second hypothesis is stated as below.

H2: The negative effect of state ownership on tax avoidance is more pronounced among

bigger firms.

Our last hypothesis is rooted in the notion that while paying more tax advances the

government’s interests, it hurts other shareholders’ value. We examine whether concentrated non-state

ownership constrains this value-destroying behavior. As argued by Shleifer and Vishny (1986), block

shareholders have strong incentives to monitor management because the benefits that they receive

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from their monitoring activities are likely to exceed the costs of monitoring that they have to bear.

Supporting this argument, previous studies (e.g., Chen et al., 2007) show that block shareholders play

an important role in monitoring management.7

H3: The negative effect of state ownership on tax avoidance is reduced among firms with

more concentrated non-state ownership.

A concentrated non-state ownership means a higher

likelihood of the existence of big and powerful block shareholders, whose monitoring counters the

incentives of SOEs’ executives to pay more tax. We therefore hypothesize that the bureaucratic

incentive effect is weaker among firms with more concentrated non-state ownership. Our hypothesis

is stated as follows.

H3 guards against an alternative explanation for our main finding that SOEs are less tax

avoidance than non-SOEs. This main finding is potentially consistent with the notion that the political

support is more important for SOEs than for non-SOEs, and the higher tax payment by SOEs is a

necessary value-increasing investment in return for the support. If this alternative explanation is true,

we expect that non-state block blockers encourage this type of investment and consequently the

negative effect of the state ownership on tax avoidance is stronger among firms with more

concentrated non-state ownership. Evidence in support of H3 contradicts this alternative explanation.

3. Sample formation and descriptive statistics

7 See Holderness (2003) for a review of empirical literature on the monitoring role of blockholders.

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We obtain our data from the tax bureau of one major city in China. The data include private

firms’ tax returns (including their financial statements) filed with the tax bureau between 2007 and

2009. We require the annual sales revenue to be more than 500,000 RMB because firms with sales

figure below this cutoff are economically insignificant and their financial reporting is notoriously

problematic. We further exclude firms from the financial industry according to the China Securities

Regulatory Commission’s industry classifications, because financial firms are heavily regulated and

their tax incentives may differ from firms in other industries. We require the following variables to be

non-missing: BTD, State_Owned, ROA, LEVERAGE, LCF, PPE, INTANG and SIZE. Please refer to

Appendix I for variable definitions. In addition, to prevent outliers from unduly affecting our results,

we winsorize the top and bottom one percentile of all continuous variables.

Panel A of Table 1 provides descriptive statistics for the full sample. The variable, BTD, is

our measure of tax avoidance. It’s computed as pretax financial income minus taxable income divided

by total assets at the end of the year. A higher value indicates a higher level of tax avoidance by the

firm. The mean value of BTD is -0.03, indicating that in our sample, on average, the pretax financial

income is lower than taxable income. While the magnitude of the mean value may seem big, it is

reasonable considering the small size of firms in our sample. State_Owned is a dummy, which is

based on the type of business registered with the Administration for Industry and Commerce in

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China.8

Panel B of Table 1 reports summary statistics separately for state-owned firms and non state-

owned firms. We find that both the mean and median values of BTD are significantly lower for SOEs

than non-SOEs. This evidence is consistent with the notion that SOEs avoid tax to a less extent than

It takes the value of 1, if the firm is a state-owned firm and 0 otherwise. Its mean value is 0.01,

suggesting that about 1% of our sample observations belong to state-owned firms. ROA is defined as

operating income divided by total assets at the end of the year. It has a mean value of -0.01,

suggesting that on average, firms in our sample report losses, perhaps as a result of the 2009 financial

crisis. LEVERAGE is computed as total liability divided by total assets as of the end of the year. Its

mean value is 0.57, suggesting that on average, total liability is about 60% of total assets in our

sample. LCF is a dummy variable, which equals 1 if the loss carry forward is positive and 0 otherwise.

Its mean value suggests that 32% of our sample firms have loss carry forward. PPE is defined as fixed

assets divided by total assets. Its mean value implies that PPE averages about 10% of total assets in

our sample. INTANG is defined as intangible assets divided by total assets. Its mean, median, 1st

quartile and 3rd quartile take on the value of 0, suggesting that the majority of firms in our sample do

not have intangible assets. SIZE is computed as the logged value of total assets measured in RMB. Its

mean value is 14.98, indicating that on average the total assets of firms in our sample are about 3.2

million RMB, or 0.45 million US dollars. The small size of firms in our sample has implications for

interpretations of our results.

8 The following four types are considered state-owned: state wholly-owned firms, state-owned joint ventures, state-owned firms, and state-and-collectively jointly owned enterprises. All the other types are considered non-state owned. We note that measurement errors will bias against any significant findings.

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non-SOEs. The rest of the results in Panel B show that SOEs are more profitable, have higher

leverage, are more likely to have loss carry forward, have more PPE, have more intangible assets and

are bigger than non-SOEs. These differences between SOEs and non-SOEs are controlled in our later

analyses.

Panel C reports the industry distribution of SOEs and non-SOEs in our sample. 26.3% of

SOEs are from Wholesale and Retail Trade industry and 17.41% are from Social Services industry.

The industry profile of non-SOEs is different. 44.21% of non-SOEs are from the Wholesale and Retail

Trade Industry and 12.55% are from the Manufacturing-Electronics industry. The different industry

distribution gives rise to the need to control for industries in our analyses.

4. Research design

This section discusses the research design to test the effect of state ownership on the tax

avoidance, which is at the center of our research.

To examine our research question, we need to find a measure of tax avoidance. Prior literature

(e.g., Chen et al., 2010) uses both the effective tax rate and the book-tax difference to proxy tax

avoidance. Using the effective tax rate however is problematic in our setting because of the tax

benefits offered to attract foreign investments. As discussed in Section 2.1, foreign investment

enterprises are entitled to lower tax rates during our sample period, and by definition, these enterprises

are non-SOEs. Therefore a comparison in tax rates is likely to show that SOEs have higher tax rates

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than non-SOEs, biasing towards our conclusion. This discussion shows that we shall rely only on the

book-tax difference as our measure of tax avoidance.

We use a regression approach to test the effect of state ownership on tax avoidance. Our

regression model is specified as follows:

𝐵𝑇𝐷𝑖 ,𝑡 = 𝛼0 + 𝛼1𝑆𝑡𝑎𝑡𝑒_𝑂𝑤𝑛𝑒𝑑𝑖,𝑡 + 𝛼2𝑅𝑂𝐴𝑖,𝑡 + 𝛼3𝐿𝑒𝑣𝑒𝑟𝑎𝑔𝑒𝑖,𝑡 + 𝛼4𝐿𝐶𝐹𝑖,𝑡 + 𝛼5𝑃𝑃𝐸𝑖 ,𝑡 +

𝛼6𝐼𝑛𝑡𝑎𝑛𝑔𝑖,𝑡 + 𝛼7𝑆𝑖𝑧𝑒𝑖,𝑡 + 𝜀𝑖,𝑡 (1)

Our dependent variable is BTD, our measure of tax avoidance.

State_Owned is a dummy indicating whether the firm is owned by the state.

We control for various firm characteristics that have been shown by prior studies literature

(Dyreng et al., 2008; Frank et al., 2009; Manzon and Plesko, 2002; Mills, 1998) to be correlated with

our tax avoidance measure. This is to ensure that our results are not due to differences in

fundamentals between SOEs and non-SOEs.

We control for ROA because profitability may affect firms’ tax strategy. Profitable firms are

expected to pay more tax and they have greater incentives to evade taxes. Consistent with this notion,

Chen et al. (2010) show a positive and significant correlation between ROA and the book-tax

difference.

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LCF is an indicator for the loss carry forward. Since the loss carry forward reduces the

taxable income, LCF is expected to be positively associated with the book-tax difference. A similar

logic applies to LEVERAGE.

Since the government allows firms to use different depreciation methods for financial and tax

reporting purposes, capital intensive firms may have higher book-tax difference. We therefore control

for PPE. We also control for INTANG, because of the differential book and tax treatments of

intangible assets. Lastly, firm size is controlled because firms’ tax strategies may vary with the size of

the firm.

Following Chen et al. (2010), we measure all control variables in the same year as the tax

avoidance measure, because all the control variables are expected to affect the tax avoidance

contemporaneously.

In addition to these control variables, Chen et al. (2010) controls for the lagged value of tax

avoidance measure, the growth of the firm (measured by the market-to-book ratio) and the change in

the loss carry forward. Since our sample firms are private firms with no market value, we use the sales

growth ratio to proxy for growth. Consequently, all these three measures require the lagged value.

Since our sample has only three years of data, requiring the lagged value takes a heavy toll on our

sample size, reducing it from 86,804 observations to 48,407 observations. To maximize the power of

our test and the generalizability of our results, we choose to report results without controlling for these

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variables. The results after including the additional control variables are however discussed in Section

5.4.

5. Empirical results

5.1 Testing H1

H1 stated in the null form, posits that the state ownership has no effect on firms’ tax

avoidance. Two alternatives are possible. One is related to the political favoritism effect, which

suggests the state ownership encourages a high level of tax avoidance. The other is related to the

bureaucratic incentive effect, which predicts that the state ownership leads to more generous tax

payments. We subject H1 to empirical tests.

The regression model we run is specified in Model (1) in Section 4. Our dependent variable is

BTD, the tax avoidance measure. Our main independent variable is the state-owned dummy. Our

inferences are based upon errors clustered by firm to account for the effect of residual non-

independence (Petersen, 2009).

Regression (1) includes this dummy and dummies representing years and industries. The

coefficient on State_Owned is negative and significant at the 1% level. Its coefficient suggests that on

average, the book-tax difference is lower by 3.1% for SOEs than for non-SOEs.

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Regression (2) adds control variables. The coefficient on State_Owned is -0.047, significant

at the 1% level, suggesting that SOEs avoid tax to a significantly less extent than non-SOEs.

Consistent with Chen et al. (2010), the coefficients on ROA, LEVERAGE and LCF are positive,

implying that the book-tax difference is higher for firms that are more profitable, have more debt and

have loss carry forward.

In sum, our results in Table 2 show that SOEs avoid tax to a less extent than non-SOEs. This

result is consistent with the notion that the bureaucratic incentive effect strongly dominates the

political favoritism effect.

5.2. Testing H2

H2 posits that the bureaucratic incentive effect is more pronounced among bigger firms. We

use the following regression to test this hypothesis:

𝐵𝑇𝐷𝑖 ,𝑡 = 𝛼0 + 𝛼1𝐵𝑖𝑔𝑖,𝑡 + 𝛼2𝑆𝑡𝑎𝑡𝑒_𝑂𝑤𝑛𝑒𝑑𝑖 ,𝑡 + 𝛼3𝐵𝑖𝑔𝑖,𝑡 ∗ 𝑆𝑡𝑎𝑡𝑒_𝑂𝑤𝑛𝑒𝑑𝑖,𝑡 + 𝛼4𝑅𝑂𝐴𝑖,𝑡 + 𝛼5𝐿𝑒𝑣𝑒𝑟𝑎𝑔𝑒𝑖,𝑡

+ 𝛼6𝐿𝐶𝐹𝑖,𝑡 + 𝛼7𝑃𝑃𝐸𝑖 ,𝑡 + 𝛼8𝐼𝑛𝑡𝑎𝑛𝑔𝑖,𝑡 + 𝑌𝑒𝑎𝑟 𝐷𝑢𝑚𝑚𝑖𝑒𝑠 + 𝐼𝑛𝑑𝑢𝑠𝑡𝑟𝑦 𝐷𝑢𝑚𝑚𝑖𝑒𝑠 + 𝜀𝑖,𝑡

(2)

The variable BIG equals 1, if the sales revenue of the firm is higher than the sample median

and 0 otherwise. We use sales revenue instead of total assets to define BIG, because otherwise BIG

will be highly correlated with size (defined as the logged value of total assets) and there will be a

severe multicollineary problem.

21

If H2 is true, we expect the coefficient on BIG*State_Owned to be negative and significant,

suggesting that among bigger firms, the bureaucratic incentive effect is more pronounced.

Our regression results are reported in Table 3. Regression (1) does not include control

variables. We find that the coefficient on BIG is positive and significant, suggesting that firms with

higher sales revenue are more tax avoidant than firms with lower sales revenues. The coefficient on

State_Owned is negative but insignificant. The coefficient on the interaction term, BIG*State_Owned

is -0.036, significant at the 1% level. This result shows that the negative effect of state ownership on

tax avoidance concentrates on bigger firms, lending support to H2.

Regression (2) includes control variables. The coefficient on State_Owned remains

insignificant. The coefficient on BIG*State_Owned is -0.059, significant at the 1% level. This result

is supportive of H2.

In sum, our results in Table 3 show that the negative effect of state ownership on tax

avoidance is more pronounced among bigger firms, lending support to H2.

5.3. Testing H3

H3 posits that the bureaucratic incentive effect is weaker among firms with concentrated non-

state ownership. We use the following regression to test it.

22

𝐵𝑇𝐷𝑖,𝑡 = 𝛼0 + 𝛼1𝑁𝑆𝐶𝑖,𝑡 + 𝛼2𝑆𝑡𝑎𝑡𝑒_𝑂𝑤𝑛𝑒𝑑𝑖,𝑡 + 𝛼3𝑁𝑆𝐶𝑖,𝑡 ∗ 𝑆𝑡𝑎𝑡𝑒_𝑂𝑤𝑛𝑒𝑑𝑖 ,𝑡 + 𝛼4𝑅𝑂𝐴𝑖,𝑡 + 𝛼5𝐿𝑒𝑣𝑒𝑟𝑎𝑔𝑒𝑖,𝑡+ 𝛼6𝐿𝐶𝐹𝑖,𝑡 + 𝛼7𝑃𝑃𝐸𝑖 ,𝑡 + 𝛼8𝐼𝑛𝑡𝑎𝑛𝑔𝑖,𝑡 + 𝛼9𝑆𝑖𝑧𝑒𝑖,𝑡 + 𝑌𝑒𝑎𝑟 𝐷𝑢𝑚𝑚𝑖𝑒𝑠 + 𝐼𝑛𝑑𝑢𝑠𝑡𝑟𝑦 𝐷𝑢𝑚𝑚𝑖𝑒𝑠+ 𝜀𝑖,𝑡

(3)

The variable NSC is a variable indicating the concentration of non-state ownership. For each

firm in our sample, we compute the Herfindahl index based on the top five non-state owned

shareholders. If the index value is higher than the sample median, NSC equals 1; otherwise it equals 0.

Our focus is on the interaction term, NSC*State_Owned. A positive and significant

coefficient on this interaction term implies that the bureaucratic incentive effect is less pronounced

among firms with more concentrated non-state ownership.

Our regression results are reported in Table 4. Regression (1) does not include control

variables. In this regression, the coefficient on State_Owned is -0.037, significant at the 1% level,

indicating that the book-tax difference is lower by 3.7% for SOEs than for non-SOEs, among firms

with less concentrated non-state ownership. The coefficient on NSC*State_Owned is 0.027,

significant at the 1% level, suggesting that the difference in tax avoidance between SOEs and non-

SOEs is reduced to 1% for firms with more concentrated non-state ownership. This result is

supportive of H3.

Regression (2) includes control variables. The coefficient on State_Owned is -0.06 and the

coefficient on NSC*State_Owned is 0.044, both significant at the 1% level. These results support the

notion that the bureaucratic incentive effect is weaker when the non-state ownership is concentrated.

23

In sum, results in Table 4 show that concentrated non-state ownership reduces the negative

effect of state ownership on tax avoidance, lending support to H3.

5.4. Robustness checks

5.4.1. More control variables

In our previous analyses, we do not include lagged value of BTD, growth and changes in loss

carry forward in our regressions because these variables are demanding on data. However, if state

ownership is related to these variables and these variables are valid explanatory variables for BTD,

our coefficient estimates may be biased as a result of the omitted correlated variable problem.

We control for these variables in this section to check the robustness of our results.

Specifically, we rerun the regressions with BTD as the dependent variable after including the three as

additional controls. Our results are reported in Table 5.

Regression (1) shows that the coefficient on state_owned is -0.046, significant at the 1% level.

This finding is consistent with prior results and suggests that the bureaucratic incentive effect

dominates the political favoritism effect. Regression (2) shows that the coefficient on

BIG*State_Owned is -0.061, significant at the 1% level. This finding suggests that the negative effect

of state ownership on tax avoidance is more pronounced among bigger firms. Regression (3) shows

that the coefficient on State_Owned is -0.06 and the coefficient on NSC*State_Owned is 0.047,

suggesting that the effect of state ownership on tax avoidance is reduced from -0.060 to -0.013, when

24

we go from firms with low concentration of non-state ownership to firms with high concentration of

non-state ownership. This finding is consistent with H3.

In sum, our results in Table 5 suggest that our inferences are robust to controlling for more

variables.

5.4.2. Results based on listed firms

Our data contain the actual filings of firms of a major city in China. An important advantage

is that we do not have to deal with the thorny issue of estimating the taxable income. A disadvantage

lies in the potentially limited generalizability of the results. It is not clear whether our results can

apply to firms from other parts in China. In addition, since our sample firms are small non-listed, it’s

questionable whether our conclusions apply to bigger listed firms.

To address this disadvantage, we collect data for all listed firms (these firms are from various

provinces) in China for the period between 1998 and 2009. We assume that the taxable income is

equal to the tax expense divided by statutory tax rate. In China, listed firms provide information

which enables readers to determine whether the government ultimately controls the firm. This

information is used to define state ownership. Our untabulated results show that among listed firms,

firms under the ultimate control of the government avoid tax to a less extent than other firms. This

finding is consistent with the main finding reported in Section 4.2. It demonstrates that our main

finding can be generalized to bigger listed firms.

25

5.4.3. Concerns over foreign investment enterprises

As we discussed in Section 2.1, the Chinese government provides tax benefits to foreign

investment enterprises (FIEs). Since the tax benefits are available to FIEs but unavailable to SOEs,

FIEs may appear to avoid tax to a greater extent than SOEs. Since FIEs are not state-owned, this tax

policy may contribute to our main finding that SOEs avoid tax to a less extent.

To assess whether our results are driven by this tax policy, we delete all FIEs from our sample,

including firms whose investors are from Hong Kong, Macau and Taiwan. We then rerun our tests.

Our untabulated results show that our inferences continue to hold after deleting these firms, evidence

suggesting that our results are not driven by the tax policy of the government.

5.4.4. Other measures of tax avoidance

In addition to the book-tax difference that we use in the paper, there exist alternative measures

of tax avoidance. We test whether our findings are robust to the following two alternative measures.

The first is the cash effective rate. It is computed as the cash tax payment divided by the taxable

income. A higher value indicates a lower level tax avoidance. The second measure is the Desai-

Dharmapala (2006) residual book-tax difference. Desai and Dharmapala (2006) argue that a portion of

the book-tax difference is attributable to earnings management rather than tax avoidance. To mitigate

the impact of earnings management, Desai and Dharmapala (2006) regress the book-tax difference on

26

total accruals and take the residual as a measure of tax aggressiveness. We follow the same

approach.9

Our untabulated results show that our conclusions continue to hold when we use these

alternative measures of tax avoidance, evidence suggesting the robustness of our findings.

Total accruals are defined as the change in non-cash current assets minus the change in

non-debt current liabilities, scaled by lagged total assets. We measure total accruals using the balance

sheet approach rather than the cash flow statement approach, because many firms in my sample do not

report cash flow information.

5.4.5. Alternative measure of concentration of non-state ownership

Finally, we test whether our results are robust to an alternative measure of the concentration of

non-state ownership. This measure is based on the existence of a non-state block owner. Specifically,

we create a dummy, which equals 1 if there exists a non-state owner who has at least 10% of the

firm’s equity, and 0 otherwise. Our untabulated results show that the negative effect of state

ownership on tax avoidance is significantly weaker in firms where this dummy equals 1. These results

show that our findings are robust to this alternative measure of the concentration of the non-state

ownership.

9 Chen et al. (2010) measure the book-tax difference as the sum of the residuals (ui + eit) from the following firm–fixed effects model: BTDit = 𝛽1TACCit +ui + eit, where BTDit indicates the book-tax difference, TACCit indicates total accruals, ui refers to the firm-fixed effect and eit is the error term. Cheng et al (2012) use the same fixed effects model but take the eit as the measure of book-tax difference. Our results are unchanged if we use these two alternative measures of the book-tax difference.

27

5. Conclusions

We are interested in the effect of state ownership on tax avoidance. Ex ante, two opposing

possibilities present themselves. On one hand, prior studies find that politically connected firms

receive preferential treatment in dealings with the government. Since state ownership represents one

form of political connection, SOEs are better able to wring out tax benefits from the government.

SOEs may evade tax to a greater extent by taking advantage of the preferential treatment. We call this

effect as the political favoritism effect.

On the other hand, executives of SOEs are appointed and their career prospects are

determined by the government. Anecdotal evidence abounds that tax payment of the SOEs they run is

one important consideration of their performance. Tax overpayment thus is one way to improve their

performance evaluation. This discussion suggests that SOE executives have lower incentives to avoid

tax than non-SOE executives. We call this effect the bureaucratic incentive effect.

Using a proprietary dataset containing actual tax filing of private firms in a major city in

China, we empirically examine the effect of state ownership on tax avoidance. Our results show

unambiguously that SOEs avoid tax less than non-SOEs. The difference between the two types of

firms is significant both statistically and economically. Our results therefore point to the dominance of

the bureaucratic incentive effect over the political favoritism effect.

28

We continue to hypothesize that the bureaucratic incentive effect is more pronounced among

bigger firms, since executives of bigger firms are more likely to be bureaucrats and these firms are

under greater pressure to contribute to the tax revenue. Our results are supportive. Specifically, we

find that the negative effect of state ownership on tax avoidance concentrates on big firms and it is

absent among small firms.

We lastly hypothesize that the bureaucratic incentive effect is weaker among firms with

concentrated non-state ownership, because these firms are more likely to have non-state block holders

whose monitoring may deter SOE executives’ incentives to overpay tax. Consistent with our

hypothesis, we find that the negative effect of state ownership on tax avoidance is significantly

weaker among firms with concentrated non-state ownership.

Our results survive a battery of robustness tests. We find that our main findings apply to

bigger listed firms from various parts of China. In addition, our main findings are robust to inclusion

of additional control variables, alternative measures of tax avoidance, the elimination of foreign

investment enterprises from our sample, and another measure of the concentration of non-state

ownership.

Overall, our results show that executives of SOEs serve the interest of the controlling

shareholder, i.e., the government, through generous tax payment. This tax practice is however curbed

by the monitoring of concentrated non-state ownership. Our results point to tax payment as a specific

29

channel through which the government seeks rents and extend our understanding of how ownership

structure affects firms’ tax strategies.

30

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33

Table 1 Descriptive statistics Panel A presents the summary statistics. Our sample consists of 86,804 firm-year observations from 2007 to 2009. Please refer to Appendix I for detailed variable definitions. Panel B presents the summary statistics for state-owned and non state-owned firms respectively, with the last two columns reporting the difference between state-owned and non state-owned firms in means and medians, respectively. T-tests (Wilcoxon ranked sum test) are used to test the difference in means (medians). ***, ** and * indicate statistical significance at the 1%, 5% and 10% level, respectively. Panel C presents industry distribution of state-owned and non state-owned firms.

Panel A: Summary Statistics (full sample)

Variable Mean Std. Dev. Q1 Median Q3 BTD -0.03 0.10 -0.04 0.00 0.00 State_Owned 0.01 0.09 0.00 0.00 0.00 ROA -0.01 0.12 -0.03 0.00 0.02 LEVERAGE 0.57 0.29 0.35 0.64 0.82 LCF 0.32 0.47 0.00 0.00 1.00 PPE 0.10 0.15 0.01 0.04 0.13 INTANG 0.00 0.01 0.00 0.00 0.00 SIZE 14.98 1.38 14.00 14.79 15.75

Panel B: Summary Statistics (State-owned vs. Non State Owned)

State Owned (SO) Non State Owned(NSO) Difference (SO-NSO) Variable Mean Median Mean Median Mean Median BTD -0.07 -0.01 -0.03 0.00 -0.033*** -0.007*** ROA 0.02 0.02 -0.01 0.00 0.039*** 0.020*** LEVERAGE 0.48 0.51 0.58 0.64 -0.093*** -0.134*** LCF 0.40 0.00 0.32 0.00 0.082*** 0.000*** PPE 0.16 0.07 0.10 0.04 0.066*** 0.032*** INTANG 0.01 0.00 0.00 0.00 0.008*** 0.000*** SIZE 17.01 16.75 14.96 14.78 2.054*** 1.974***

Panel C: Industry distribution of State Owned and Non State Owned firms

Industry Name State Owned Non State Owned

Frequency Percentage Frequency Percentage Agricultural, Forest, Animal Husbandry, Fishery 5 0.64% 143 0.17% Building 27 3.43% 649 0.75% Comprehensive 9 1.14% 25 0.03% Electricity, Gas and Water Production and Supply 22 2.80% 96 0.11% Information Technology 33 4.19% 1,994 2.32% Manufacturing--Electronics 52 6.61% 10,797 12.55% Manufacturing--Food, Beverage 7 0.89% 271 0.32% Manufacturing--Machinery, Equipment, Instruments 51 6.48% 5,706 6.63% Manufacturing--Metal, Nonmetal 25 3.18% 4,265 4.96% Manufacturing--Others 24 3.05% 4,305 5.00% Manufacturing--Papermaking, Printing 12 1.52% 3,291 3.83% Manufacturing--Petroleum, Chemistry, Revertex, Plastic 16 2.03% 5,197 6.04% Manufacturing--Pharmaceutical, Biological Products 3 0.38% 111 0.13% Manufacturing--Textile, Clothing, Fur 9 1.14% 2,239 2.60% Manufacturing--Wood, Furniture 0 0.00% 183 0.21%

34

Mining and Quarrying 5 0.64% 122 0.14% Real Estate 58 7.37% 443 0.52% Social Services 137 17.41% 5,734 6.67% Transmission, Culture 14 1.78% 187 0.22% Transportation and Warehousing 71 9.02% 2,227 2.59% Wholesale and Retail Trade 207 26.30% 38,032 44.21% Total 787 100.00% 86,017 100.00%

35

Table 2 The effect of state ownership on tax avoidance

This table presents results of OLS regressions. Our sample consists of 86,804 firm-year observations between 2007 and 2009. ***, ** and * indicate statistical significance at the 1%, 5% and 10% level, respectively. p-values based on a two-tailed t test are reported in parentheses. Inferences are based upon errors clustered by firm to account for the effect of residual non-independence (Petersen, 2009). Please refer to Appendix I for detailed variable definitions. The regression model is:

𝐵𝑇𝐷𝑖,𝑡 = 𝛼0 + 𝛼1𝑆𝑡𝑎𝑡𝑒_𝑂𝑤𝑛𝑒𝑑𝑖 ,𝑡 + 𝛼2𝑅𝑂𝐴𝑖,𝑡 + 𝛼3𝐿𝑒𝑣𝑒𝑟𝑎𝑔𝑒𝑖,𝑡 + 𝛼4𝐿𝐶𝐹𝑖,𝑡 + 𝛼5𝑃𝑃𝐸𝑖,𝑡 + 𝛼6𝐼𝑛𝑡𝑎𝑛𝑔𝑖,𝑡+ 𝛼7𝑆𝑖𝑧𝑒𝑖,𝑡 + 𝛼8𝐿𝑎𝑔_𝐵𝑇𝐷𝑖 ,𝑡 + 𝛼9𝐺𝑟𝑜𝑤𝑡ℎ𝑖,𝑡 + 𝛼10𝐶ℎ𝑎𝑛𝑔𝑒_𝑖𝑛_𝐿𝐶𝐹𝑖,𝑡 + 𝑌𝑒𝑎𝑟 𝐷𝑢𝑚𝑚𝑖𝑒𝑠+ 𝐼𝑛𝑑𝑢𝑠𝑡𝑟𝑦 𝐷𝑢𝑚𝑚𝑖𝑒𝑠 + 𝜀𝑖,𝑡

(1) (2)

Intercept -0.028*** 0.001 (<0.001) (0.875) State_Owned -0.031*** -0.047*** (<0.001) (<0.001) ROA 0.717*** (<0.001) LEVERAGE 0.020*** (<0.001) LCF 0.015*** (<0.001) PPE -0.012*** (<0.001) INTANG -0.154*** (<0.001) SIZE -0.003*** (<0.001) Year dummies Yes Yes Industry dummies Yes Yes Adjusted R2 0.005 0.755

36

Table 3 The effect of size on the relationship between state ownership and tax avoidance

This table presents results of OLS regressions. Our sample consists of 86,804 firm-year observations between 2007 and 2009. ***, ** and * indicate statistical significance at the 1%, 5% and 10% level, respectively. p-values based on a two-tailed t test are reported in parentheses. Inferences are based upon errors clustered by firm to account for the effect of residual non-independence (Petersen, 2009). Please refer to Appendix I for detailed variable definitions. The regression model is:

𝐵𝑇𝐷𝑖,𝑡 = 𝛼0 + 𝛼1𝐵𝐼𝐺𝑖,𝑡 + 𝛼2𝑆𝑡𝑎𝑡𝑒_𝑂𝑤𝑛𝑒𝑑𝑖 ,𝑡 + 𝛼3𝐵𝐼𝐺𝑖,𝑡 ∗ 𝑆𝑡𝑎𝑡𝑒_𝑂𝑤𝑛𝑒𝑑𝑖 ,𝑡 + 𝛼4𝑅𝑂𝐴𝑖,𝑡 + 𝛼5𝐿𝑒𝑣𝑒𝑟𝑎𝑔𝑒𝑖,𝑡+ 𝛼6𝐿𝐶𝐹𝑖,𝑡 + 𝛼7𝑃𝑃𝐸𝑖 ,𝑡 + 𝛼8𝐼𝑛𝑡𝑎𝑛𝑔𝑖,𝑡 + 𝑌𝑒𝑎𝑟 𝐷𝑢𝑚𝑚𝑖𝑒𝑠 + 𝐼𝑛𝑑𝑢𝑠𝑡𝑟𝑦 𝐷𝑢𝑚𝑚𝑖𝑒𝑠 + 𝜀𝑖,𝑡

(1) (2) Intercept -0.048*** 0.018*** (<0.001) (<0.001) BIG 0.037*** -0.008*** (<0.001) (<0.001) State_Owned -0.010 -0.000 (0.272) (0.957) BIG*State_Owned -0.036*** -0.059*** (0.001) (<0.001) ROA 0.712*** (<0.001) LEVERAGE 0.026*** (<0.001) LCF -0.011*** (<0.001) PPE -0.010*** (<0.001) INTANG -0.132*** (0.001) SIZE -0.003*** (<0.001) Year dummies Yes Yes Industry dummies Yes Yes Adjusted R2 0.043 0.744

37

Table 4 The effect of concentration for non state ownership on the relationship between state

ownership and tax aggressive

This table presents results of OLS regressions. Our sample consists of 86,804 firm-year observations between 2007 and 2009. ***, ** and * indicate statistical significance at the 1%, 5% and 10% level, respectively. p-values based on a two-tailed t test are reported in parentheses. Inferences are based upon errors clustered by firm to account for the effect of non independence (Petersen, 2009). Please refer to Appendix I for detailed variable definitions. The regression model is:

𝐵𝑇𝐷𝑖 ,𝑡 = 𝛼0 + 𝛼1𝑁𝑆𝐶𝑖,𝑡 + 𝛼2𝑆𝑡𝑎𝑡𝑒_𝑂𝑤𝑛𝑒𝑑𝑖 ,𝑡 + 𝛼3𝑁𝑆𝐶𝑖,𝑡 ∗ 𝑆𝑡𝑎𝑡𝑒_𝑂𝑤𝑛𝑒𝑑𝑖,𝑡 + 𝛼4𝑅𝑂𝐴𝑖,𝑡 + 𝛼5𝐿𝑒𝑣𝑒𝑟𝑎𝑔𝑒𝑖,𝑡+ 𝛼6𝐿𝐶𝐹𝑖,𝑡 + 𝛼7𝑃𝑃𝐸𝑖 ,𝑡 + 𝛼8𝐼𝑛𝑡𝑎𝑛𝑔𝑖,𝑡 + 𝛼9𝑆𝑖𝑧𝑒𝑖,𝑡 + 𝑌𝑒𝑎𝑟 𝐷𝑢𝑚𝑚𝑖𝑒𝑠 + 𝐼𝑛𝑑𝑢𝑠𝑡𝑟𝑦 𝐷𝑢𝑚𝑚𝑖𝑒𝑠+ 𝜀𝑖,𝑡

(1) (2) Intercept -0.028*** -0.000 (<0.001) (0.894) NSC -0.001 -0.002*** (0.218) (<0.001) State_Owned -0.037*** -0.060*** (<0.001) (<0.001) NSC*State_Owned 0.027*** 0.044*** (0.007) (<0.001) ROA 0.717*** (<0.001) LEVERAGE 0.020*** (<0.001) LCF 0.016*** (<0.001) PPE -0.011*** (<0.001) INTANG -0.145*** (<0.001) SIZE -0.002*** (<0.001) Year dummies Yes Yes Industry dummies Yes Yes Adjusted R2 0.043 0.756

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Table 5 Robustness check: results after controlling for additional variables

This table presents results of OLS regressions based on the sample with 48,407 firm-year observations. This sample is formed after we additionally require lag _BTD, change in LCF and Growth to be available. The dependent variable is BTD. ***, ** and * indicate statistical significance at the 1%, 5% and 10% level, respectively. p-values based on a two-tailed t test are reported in parentheses. Inferences are based upon errors clustered by firm to account for the effect of non independence (Petersen, 2009). Please refer to Appendix I for detailed variable definitions.

(1) (2) (3) Intercept -0.004 0.015*** -0.005 (0.244) (<0.001) (0.144) State_Owned -0.046*** 0.005 -0.060*** (<0.001) (0.397) (<0.001) BIG -0.007*** (<0.001) BIG*State_Owned -0.061*** (<0.001) NSC -0.001*** (0.002) NSC*State_Owned 0.047*** (<0.001) ROA 0.707*** 0.674*** 0.707*** (<0.001) (<0.001) (<0.001) LEVERAGE 0.021*** 0.025*** 0.021*** (<0.001) (<0.001) (<0.001) LCF 0.016*** -0.004*** 0.016*** (<0.001) (<0.001) (<0.001) PPE -0.009*** -0.006*** -0.010*** (<0.001) (<0.001) (<0.001) INTANG -0.172*** -0.157*** -0.162*** (<0.001) (<0.001) (<0.001) SIZE -0.002*** -0.003*** -0.002*** (<0.001) (<0.001) (<0.001) Lag_BTD 0.027*** 0.000 0.024*** (<0.001) (0.906) (<0.001) Growth <0.001** 0.000*** 0.000** (0.026) (<0.001) (0.037) Change_in_LCF -0.018** -0.128*** -0.021*** (0.013) (<0.001) (0.005) Year dummies Yes Yes Yes Industry dummies Yes Yes Yes Adjusted R2 0.750 0.754 0.751

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Appendix I Variable definitions

Variable Name Variable Definition

BTD (Pretax Income－Taxable Income) / Total Assets State_Owned A dummy variable that equals 1 if the firm indicates that it is

state-owned in its tax returns and 0 otherwise. ROA Operating Income / Total Assets LEVERAGE Total Liability / Total Assets LCF A dummy variable that equals 1 if loss carry forward is

positive and 0 otherwise PPE Fixed Assets / Total Assets INTANG Intangible Assets / Total Assets SIZE The Log of Total Assets BIG A dummy variable that equals 1 if the firm’s sales revenue is

above the sample median and 0 otherwise. NSC An indicator variable about non state-owned shareholder’s

equity ownership concentration, coded as 1 if the firm’s Herfindahl index calculated based on top five non-state owners is higher than the median, and 0 otherwise.

Change_in_LCF Changes in loss carry forward divided by total assets Growth Sales in year t divided by Sales in year t-1