trade liberalization and corporate income tax...
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Trade Liberalization and Corporate Income Tax Avoidance
Yao Lu Xinzheng Shi*
Tsinghua University
December 2016
Abstract
We identify the effect of trade liberalization on corporate income tax
avoidance in a sample of Chinese manufacturing firms, using China’s entry
into the World Trade Organization (WTO). We find that firms engage in
more tax avoidance in industries with larger tariff reductions. We also find
that firms with better corporate governance engage in less tax avoidance than
their counterparts. Further analysis shows that firms with a lack of cash or a
high demand for cash before WTO entry tend to engage in more tax
avoidance after WTO entry. Our study also provides evidence that
manipulating costs is one way that firms avoid corporate income tax.
Keywords: Trade liberalization; tax avoidance; WTO entry
JEL code: D22; F61; F63; H26
* Yao Lu is an Associate Professor in the Department of Finance in the School of Economics and Management, Tsinghua University; Xinzheng Shi is an Associate Professor in the Department of Economics in the School of Economics and Management, Tsinghua University. We wish to thank Rui Wang for providing excellent research assistance, and Hongbin Li and the participants in the CCER Summer Institute 2016 for helpful comments. Corresponding author: Xinzheng Shi ([email protected]).
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1. Introduction
After the Second World War, many developing countries chose import
substitution as a strategy for industrialization. However, in the past three
decades, many countries have begun to favor global economic integration,
particularly trade liberalization, as a development strategy. Previous research
has documented that, faced with a more competitive environment after trade
liberalization, 1 firms invest more in technological development, 2 which
improves their productivity3 and therefore the likelihood of their survival.4
Collectively, this leads to rapid growth in the whole economy.5
However, one possible behavioral response of firms to trade
liberalization, i.e., corporate income tax avoidance, has seldom been studied.6
Corporate income tax avoidance is a commonly observed behavior among firms.
Schneider and Ernste (2000) point out that tax avoidance is widespread in
developing countries and estimate that the tax avoidance rate is above 50% in
many low-income countries. In China, the National Auditing Office uncovered
RMB11.89 billion (roughly 1.6 billion dollars) in tax avoidance in 2003, based
on a nationwide investigation of 788 randomly selected companies in 17
provinces and cities (Asian Wall Street Journal, A2, September 20, 2004). In
this paper, we investigate the effect of trade liberalization on corporate income
tax avoidance by manufacturing firms in China, taking advantage of China’s
1 Levinsohn, 1993; Krishna and Mitra, 1998; Brandt et al., 2012; Lu and Yu, 2015. 2 Rodrik, 1988; Brandt and Thun, 2010. 3 Topalova and Khandelwal, 2011; Pavcnik, 2002; Amiti and Konings, 2007; Tybout and Westbrook, 1995; Krishna and Mitra, 1998; Brandt, et al., 2012; Ederington and McCalman, 2007; Trefler, 2004; Schor, 2004; Lileeva and Trefler, 2010; Harrison, 1994. 4 Baggs, 2005. 5 See Nunn and Trefler (2010) and Brandt and Thun (2010). However, some researchers find that the benefits of trade liberalization are not distributed equally among different groups. For example, Topalova (2007) finds that trade liberalization leads to an increase in the poverty rate and poverty gap in rural districts where industries more exposed to liberalization are concentrated. 6 “Corporate income tax avoidance”, “corporate tax avoidance” and “tax avoidance” are used interchangeably in this paper. Following the literature, we do not distinguish between tax avoidance (legal) and tax evasion (illegal) but call both of them tax avoidance.
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entry into the WTO.
The effect of trade liberalization on tax avoidance is not straightforward
from a theoretical perspective. Previous studies (Levinsohn, 1993; Krishna and
Mitra, 1998; Brandt et al., 2012; and Lu and Yu, 2015) have shown that a
reduction in import tariffs due to trade liberalization increases the level of
competition in the domestic market. As Shleifer (2004) notes, the cost of ethical
behavior is high under heightened competitive pressure. In addition, Slemrod
(2004) finds that firms whose profit performance decreases due to greater
competition may resort to noncompliance so that they have more cash to invest
and thus improve their prospects. Trade liberalization may therefore lead to
higher incentives for corporate income tax avoidance. However, the increased
competitiveness in product markets fostered by trade liberalization may increase
the real value of the same amount of money. That is, one dollar gained or lost
means more for firms in a more competitive environment. As Slemrod (2004)
also notes, people normally value a given amount of punishment higher than the
equivalent amount of tax savings. Thus, trade liberalization may increase the
real cost of being caught, making firms more conservative and leading to a
lower incentive for corporate tax avoidance. Therefore, the theoretical
prediction of the effects of trade liberalization on corporate tax avoidance is not
clear, and empirical studies are needed.7
A common difficulty in studying tax avoidance is how to measure it. In
the literature, book income is usually used as a proxy for firms’ true accounting
profits, and therefore the gap between book and taxable income (scaled by total
assets) is used as a measure of tax avoidance (Desai, 2003, 2005; Desai and
Dharmapala, 2006). However, this approach works only for publicly listed firms,
as book income is usually not available for non-listed firms. In this paper, we
7 Trade liberalization could affect firms’ tax avoidance through other channels such as reducing input tariffs, increasing excess to foreign markets, and changing domestic legal environments. However, robustness checks in our paper show that these possible channels do not drive the main results.
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follow Cai and Liu (2009) in calculating an imputed profit based on the national
income account. That is, we calculate the imputed profit by subtracting
intermediate inputs from gross output. The gap between imputed profit and
reported profit is our measurement of tax avoidance. However, the imputed
profit can be legitimately different from the true accounting profit, due to
differences in revenue and expense recognition rules between the national
income account and the General Accepted Accounting Principles (GAAP) with
which accounting profit is calculated.8 Fortunately, the panel feature of Chinese
manufacturing firms allows us to control for any time-invariant systematic
difference between these two accounting systems, which may mitigate this
problem. In addition, we conduct several robustness checks, described later, to
justify this measurement.
After China entered the WTO, import tariffs were reduced to a uniquely
low level, which means that reductions were correspondingly larger for
industries with higher tariff levels before WTO entry. Combining before–after
variation and the different levels of tariffs before WTO entry across industries,
we use a difference in difference (DID) strategy to identify the effect of trade
liberalization on tax avoidance, using data from Chinese manufacturing firms.
We find that WTO entry induced firms in industries with a tariff one percentage
point higher in 2001 to engage in RMB76,000 (roughly $12,000) more tax
avoidance, accounting for 5% of the corporate income tax paid in 2001.
Considering that the average tariff decreased by roughly five percentage points
from pre- to post-WTO entry, the induced aggregate corporate income tax
avoidance would account for 25% of corporate income tax paid in 2001.
We conduct several tests to investigate the validity of our identification
strategy. We first check whether the pre-existing time trends of firms’ tax
avoidance are the same for different industries. We then check whether firms
8 For example, asset depreciation rules can be different; gross output in the current year is not equal to revenue in the same year.
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adjusted their tax avoidance behavior in anticipation of WTO entry. We also
investigate whether the reform of state-owned enterprises (SOEs) and regulation
changes for foreign direct investment (FDI) that occurred in the same period
have a contaminating effect on our main results. WTO entry may change law
implementation, and we check whether this change affects our results. WTO
entry decreases not only output tariffs but also input tariffs, and enlarges firms’
exposure to international markets. We further investigate whether our main
results are affected by these two factors. As processing traders are not affected
by the tariff change, we estimate the same effects for processing traders as a
placebo test. Finally, we check whether sample attrition affects our results. All
of the results of these tests justify our identification strategy.
We then conduct several tests to justify the validity of our tax avoidance
measurement. We first identify a subsample of industrial firms that are publicly
listed and for which information on the book-tax income gap is therefore
available. For this subsample, we find a significantly positive correlation
between the imputed-reported profits gap and book-tax income gap. We then
estimate the effect of WTO entry on the book-tax income gap using this
subsample, and find that WTO entry significantly enlarges the book-tax income
gap, confirming our paper’s main finding. Second, we follow Cai and Liu (2009)
to investigate how WTO entry affects the response of reported profits to
imputed profits. We find that WTO entry weakens the response, which confirms
our finding that WTO entry induces more corporate income tax avoidance.
Third, we investigate whether firms over-report output because of declining
sales income after WTO entry, which may over-estimate imputed profit and
therefore our measurement of corporate tax avoidance. We find no evidence that
firms over-report output. These results provide support for our tax avoidance
measurement.
In addition, we conduct other robustness checks to examine whether our
main finding is robust to different outcomes and explanatory variables. The
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results show that our main finding is robust to different tests.
After establishing a causal relation between trade liberalization and tax
avoidance, we investigate the heterogeneous effects in terms of firms’ corporate
governance. We find that firms with weak corporate governance (i.e., SOEs)
engage in more tax avoidance than other types of firms in response to the
reduction in tariffs after WTO entry.
We then examine the possible mechanisms through which trade
liberalization affects firms’ corporate tax avoidance behavior. We find that firms
that have higher leverage, lower profitability, or faster growth before WTO
entry engage in more tax avoidance after WTO entry. This finding suggests that
being short of cash or a higher demand for cash could be the reason firms
engage in more tax avoidance in a more competitive environment. Finally, we
investigate how firms engage in tax avoidance by estimating the effects of WTO
entry on costs per unit of sales income (including administrative costs, sales
costs, financial costs, wages, and benefits). The costs for firms in industries with
larger tariff reductions increase more, suggesting that manipulating costs could
be a way to avoid corporate income tax.
Our paper makes several contributions to the literature. First, previous
research has documented that integration with the global economy is an
important factor driving economic growth in developing countries. However,
very few studies investigate firms’ tax avoidance behaviors in response to the
trade liberalization. Our paper is the first to study this issue in a developing
country. 9 Besides the extension of the literature on the effects of trade
liberalization, focusing on developing countries is of particular importance. Tax
administration in these countries is far less effective than in developed countries
such as the U.S., induced tax avoidance is more likely to take illegal forms,
suggesting that the social benefits of economic growth may not be as large as
9 The only other paper studying the same issue is Chen and Lin (2013), using data on publicly listed firms from the U.S. They find that more tariff reductions are related to more tax avoidance, and the effect is greater for financially constrained firms and smaller for firms with better corporate governance.
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expected. Policymakers need to exert more effort to increase the efficiency of
tax administration to international standards during the process of integration
with the global economy. Second, we also investigate the mechanism through
which trade liberalization affects tax avoidance and one possible approach used
by firms to engage in tax avoidance. Although the results can only be
considered suggestive, they provide useful insight into firms’ tax avoidance
behavior. Third, we find that better corporate governance can mitigate firms’ tax
avoidance behavior, providing additional evidence supporting predictions by
Desai and Dharmapala (2006). Lastly, using China’s entry into the WTO as a
natural experiment, we can credibly identify a causal relation between trade
liberalization and firms’ corporate tax avoidance.
Our paper is also linked to the public finance literature that examines
various determinants affecting tax avoidance activities; see, e.g., Johnson et al.
(1997, 1998), Slemrod (2004), Desai and Dharmapala (2006, 2009), Crocker
and Slemrod (2005), Hanlon and Slemrod (2009), Kim et al. (2011), and Beck
et al. (2014). In particular, Fisman and Wei (2004) identify evidence of
pervasive tariff evasion in China, and Cai and Liu (2009) investigate the
relationship between competition and corporate tax avoidance among Chinese
manufacturing firms. A most recent study by Chen et al. (2016) find that a
substantial fraction of Chinese firms’ response to fiscal incentive for R&D
investment is due to tax evasion.
The rest of this paper is organized as follows: Section 2 introduces the
institutional background; Section 3 describes the data and empirical strategies;
Section 4 presents the main results; Section 5 shows robustness checks and
heterogeneous effects; Section 6 investigates the mechanisms; Section 7 studies
how firms engage in tax avoidance; and Section 8 offers our conclusions.
2. Background
2.1. The Corporate Income Tax System in China
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The evolution of China’s corporate tax system can be divided into four
periods: (1) 1949-1978; (2) 1979-1994; (3) 1995-2007; and (4) 2008-present.
The central planning system dominated the first period (1949-1978),
when the majority of Chinese industrial firms were state-owned and all
surpluses were sent to the government. Therefore, as described in Wu (2003),
there was no corporate income tax in this period.
The Chinese government introduced an income tax system in 1979. In
the 1980s, large SOEs were subject to an income tax rate of 55%. These firms
also divided after-tax profits between themselves and the government according
to a given formula. The tax rates were 10-55% for small SOEs and 35% for
private firms.
In the 1980s the Chinese government introduced SOE reforms that
focused on “delegating decision power and giving incentives.” These reforms
continued through the 1990s, when a modern corporation system focusing on
corporatization and governance was emphasized. During this process, many
small and medium-sized SOEs were privatized and others were transformed into
corporations. As a part of these reforms, the Chinese government enacted the
Corporate Income Tax Code in 1994, which overhauled corporate taxation.
One feature of the corporate income tax schedule in the 1994-2007
period was that domestic and foreign firms were subject to different tax rates.
With the exception of small firms with taxable incomes of less than RMB30,000,
which paid 18% corporate income tax, all domestic firms paid 33% income tax.
However, most foreign firms paid only 15% corporate income tax. In addition,
various exemptions, tax credits, and reductions were applied to most foreign
firms, meaning that they generally enjoyed much more favorable tax treatment.
The different treatment of foreign firms and domestic firms lasted until
2007. A new Corporate Income Tax Code was announced at the end of 2007.
Since 2008, the corporate tax rate for both domestic and foreign firms has been
set at 25%. The government phased in the increase for tax rates on foreign firms
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over the following five years.
Tax collection agencies in China were reformed in 1994. Before 1994,
all taxes were collected by provincial tax collectors, and the central government
and provincial governments divided the tax revenue according to a given
formula. In the 1994 reform, taxes were classified into central taxes and local
taxes. Under the supervision of the State Administration of Taxation, a National
Taxation Bureau and provincial taxation bureaus were established to separately
collect central taxes and provincial taxes. Today, corporate income tax is
classified as a central tax and is therefore collected by the National Taxation
Bureau. The growth in corporate income tax, like the growth in the economy,
has been impressive since 1994; total corporate income tax revenue was
RMB93 billion in 1998 and increased to RMB878 billion in 2007 (China
Statistical Yearbook, 2008).
2.2. China’s Entry into the WTO
Before the economic reform in 1978, Chinese trade took place within a
central-planning framework. The State Planning Commission made plans for
almost all of China’s export and import activities, and a few foreign trade
companies controlled by the Ministry of Foreign Trade were responsible for
carrying out export and import plans. In 1977, Chinese trade accounted for only
0.6% of world trade by volume (Lardy, 1994).
Although China began its economic reform at the beginning of the
1980s, trade liberalization did not start at the same time. On the contrary, the
government raised import tariffs on most commodities in the early years of
reform. The average tariff rate was 43% in 1985. This high tariff level was
maintained until 1992 (Lardy, 2002).
Starting in 1986, as part of China’s efforts to join the WTO, the Chinese
government implemented several tariff cuts. The average import tariff rate was
reduced from 43% in 1992 to 17% in 1997. There was little change in tariff after
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1997 until China joined the WTO at the end of 2001(Lu and Yu, 2015).
According to the agreement, the Chinese government promised to reduce the
average tariff level to under 10% by 2005. Figure 1 shows the changes in the
average tariff rates over time.
The average value of import tariffs hides the variation in tariffs across
industries. In 2001, the variation in tariffs over two-digit industries was large,
equal to 0.10 (compared with the mean, 0.15). Additionally, the different levels
of import tariffs in different industries before WTO entry meant there were
different reductions in tariffs in different industries after WTO entry. Figure 2
shows the correlations between industry import tariffs in 2001 and the tariff
reductions from 2001 to 2002, 2003, and 2004. Figure 2 also shows the
correlation between industry import tariffs in 2001 and the 2002-2004 average
industry import tariffs. We can see from these graphs that industries with higher
tariffs in 2001 had larger reductions in tariffs after China entered the WTO.
3. Data and Empirical Strategies
3.1. Data
In this study, we mainly use two types of data: manufacturing firm data
and import tariffs.
The manufacturing firm data come from the National Bureau of
Statistics of China (NBS). All SOEs and non-SOEs with sales above RMB5
million (roughly $769,000) are required to file a report on their production
activities and accounting and financial information with the NBS every year.
This is the most comprehensive firm-level dataset in China, and it is used to
calculate matrices in the national income account and major statistics published
in the China Statistical Yearbooks. The data collected by this survey have been
widely used by researchers, e.g., Lu, Lu, and Tao (2010); Brandt, Van
Biesebroeck, and Zhang (2012); Brandt et al. (2012); Yu (2014); Lu and Yu
(2015).
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The NBS issues an identification code for each firm such that we can
construct a firm panel. A four-digit Chinese Industrial Classification (CIC) code
is also assigned to each firm. However, the classification system for the industry
code was changed in 2003, from GB/T 4754-1994 in 1995-2002 to GB/T
4754-2002 after 2002. To achieve consistency in industry codes for the whole
period, we convert the industry codes to GB/T 4754-1994.
Although this dataset includes rich information, some samples are still
noisy, largely because of misreporting by firms. Following the literature (Cai
and Liu, 2009; Yu, 2014; Lu and Yu, 2015), we delete any observations for
which one of the following is true: (i) the value of fixed assets is below RMB10
million; (ii) the value of total sales is below RMB5 million; (iii) the number of
employees is less than 30; (iv) total assets are smaller than liquid assets; (v)
total assets are smaller than fixed assets; (vi) total assets are smaller than the net
value of fixed assets; or (vii) accumulated depreciation is smaller than current
depreciation. After this procedure, we have 308,179 observations, including
103,505 unique firms. All of the monetary values are deflated to 1998 values.
We use data from 1999 to 2004: three years before WTO entry (1999-2001) and
three years after WTO entry (2002-2004).
An important variable in our study is tax avoidance. One widely used
measure of tax avoidance is the book-tax gap (Desai, 2003, 2005; Desai and
Dharmapala, 2006). However, the manufacturing firm dataset we use in this
study does not include information about book income. Therefore, following
Cai and Liu (2009), we use the gap between imputed profits and reported profits
as a proxy for tax avoidance. The reported profits, ��, are the profits reported
by firms when they file their annual reports with the NBS. The imputed profits
are calculated according to the national income accounting system as follows:
�� = � − �� − � − � �� − ���� − ��� (1)
Here, � is the gross output, �� is the intermediate inputs excluding
financial charges, � is the financial charges, � �� is the total wages paid,
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���� is the current depreciation, and ��� is the value-added tax. All of
these variables are reported by firms. Therefore, the tax avoidance engaged in
by firms, ��, is measured as �� minus ��. We normalize the gap in this
paper using total assets.
One caveat to bear in mind is that the difference between imputed profits
and reported profits reflects not only the tax avoidance engaged in by firms but
also the systematic differences between the accounting system and the national
income account system, including different expense recognition rules, asset
depreciation rules, and tax credit and tax loss carry-over rules. In our analysis,
we include firm fixed effects to control for time-invariant systematic differences,
and we also conduct robustness checks to investigate the validity of our
measurement.
The import tariff data are from the World Integrated Trade Solution
(WITS) provided by the World Bank. Import tariffs are set at the six-digit level
of the Harmonized System (HS) product classification. To merge the data with
the manufacturing firm categories, which have only CIC four-digit industry
codes, we map the HS six-digit codes onto the CIC four-digit codes. As each
CIC four-digit industry includes several six-digit industries, each of which has
an import tariff, we construct an average tariff for each four-digit industry as
follows:
� ������ =�
�∑ � ������
���� . (2)
Here, � ������ is the average tariff level for a four-digit industry k in year t;
� ������ is the tariff level in a six-digit industry j in year t. Using the same
method, tariffs in three-digit and two-digit industries can be calculated. Using a
simple average, rather than a weighted average (using imports as weight), can
avoid bias due to the endogenous response of imports to tariffs. However, our
results are robust when imports are used as weights when calculating four-digit
tariffs, as shown in the robustness section.
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Table 1 shows the summary statistics for the main variables. Panel A of
Table 1 shows the summary statistics for firm characteristics. On average, the
reported profits by firms are RMB10 million, while the imputed profits are
RMB17 million. The firms on average underreport profits by 7 million. In our
data, 33% of firms are exporters and 8% of firms are processing traders. Among
all firms, 24% are SOEs and 14% are foreign invested firms. We can also see
that on average their sales income is RMB177 million and they have 764
employees. Panel B in Table 1 shows the average tariffs in two-, three-, and
four-digit industries, which are about 16%.
3.2. Empirical Strategy
Two variations are combined to identify the effect of trade liberalization
on tax avoidance. One is the tariff reduction from before WTO entry to after
WTO entry. Another results from the larger tariff reductions of industries with
higher tariff levels before WTO entry. Essentially, we exploit the DID strategy.
The baseline regression is estimated as follows:
����� = � + ��� �����" � ∗ �$%&� + ��'� + �� �� + (���. (3)
Here, ����� is the tax avoidance of firm i in the four-digit industry k in
year t.10 � �����" � is the tariff level in industry k in 2001. �$%&� is a
dummy variable indicating the post-WTO year, i.e., 2002-2004 in our study. ��
is the coefficient of interest. ��'� is a set of firm fixed effects. We also
include year fixed effects, �� ��, in the regression to control for different levels
of average tax avoidance in different years. (��� is an error term with a mean
equal to zero. Standard errors are calculated by clustering over industry.
One issue to consider is that industry tariffs in 2001 were not randomly
assigned; it is possible that industries with higher or lower tariffs in 2001 could
be systematically different. These pre-existing differences could affect firms’ tax
10 We normalize tax avoidance using firms’ total assets.
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avoidance behavior differently after WTO entry, thus contaminating our
estimates. Fortunately, Lu and Yu (2015) show that the industry-level output
share of SOEs, average wage per worker, and export intensity have robustly
significant effects on industry-level tariffs in 2001. Therefore, to alleviate this
concern, we follow Gentzkow (2006) and Lu and Yu (2015) to control for the
interaction of the output share of SOEs, average wage per worker, and export
intensity in 2001 with �$%&� in the regression.
Several other assumptions need to hold to obtain consistent estimates
of Equation (3). First, we assume that tax avoidance in industries with higher
tariffs in 2001 would have followed the same trend as in industries with lower
tariffs in 2001 if there had been no WTO entry. We test this assumption using
data before WTO entry, i.e., data from 1999 to 2001. The details are shown in
Section 4.2.
Second, one possible issue is that China’s entry into the WTO at the
end of 2001 was expected, so firms might have adjusted their tax avoidance
behavior even before the actual tariff reductions. As a robustness check, we
include an additional control in the regression, � �����" � ∗
*+� �� � ,��$�� ��* �+&�-� , to investigate whether firms changed their
behavior in anticipation of WTO entry.
Third, if other policy changes in this period affected industries with
high versus low tariffs differently, then our estimates would be biased. In the
early 2000s, there were two important reforms: SOE reform and the relaxation
of FDI regulations. To address this concern, we add the SOE shares, i.e., the
number of SOEs divided by the number of firms in each industry, and FDI, i.e.,
the logarithm form of the number of foreign invested firms in each industry, to
the regression to check whether the main results hold.
Fourth, besides output tariffs, WTO entry reduced input tariffs as well,
making it possible for Chinese firms to use more imported intermediate inputs.
Furthermore, China’s trading partners might have also decreased their tariffs on
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Chinese products, giving Chinese firms greater access to larger foreign markets.
Both could affect firms’ tax avoidance as well. To address this concern, we add
industry-level input tariffs and export intensity to the regression to check the
robustness of results.
Fifth, WTO entry may improve law implementation to different
degrees in different provinces. If more industries with lower tariffs were based
in provinces in which law implementation was more significantly improved by
WTO entry, then our estimates could be biased. To address this concern, we add
an index for law implementation at the provincial level to check whether our
results change.11
To further investigate the assumptions behind the identification method
used in our strategy, we also conduct a placebo test using processing traders. To
address potential selection bias due to sample attrition, we also estimate
Equation (3) using a balanced panel.
4. Empirical Results
4.1. Main Results
Table 2 shows the main results. In column 1, we control for industry
and province fixed effects. The coefficient of � �����" � ∗ �$%&� is 0.057 and
statistically significant at the 1% level. It shows that the higher the tariff level in
2001, the greater the increase in tax avoidance. In column 2, we add the
interactions of �$%&� with three industry-level variables in 2001, i.e., average
wage per worker, export intensity, and SOE shares, to the regression. The
coefficient of � �����" � ∗ �$%&� remains very similar at 0.059 and is still
significant at the 1% level. In columns 3 and 4, we replace the industry and
province fixed effects with firm fixed effects, and in column 4 we add the
interactions of �$%&� with the three variables in 2001. The coefficient of
� �����" � ∗ �$%&� decreases to 0.033 in column 3 and 0.031 in column 4.
11 This index is constructed by Fang and Wang (2006).
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Both are significant at the 1% level. The similarity of these two coefficients also
suggests that industry tariffs in 2001 are not likely to be endogenous. Using the
specification in column 4, which we prefer, we can see that for firms in
industries with tariffs 10 percentage points higher in 2001 (roughly one standard
deviation), the increase in corporate tax avoidance induced by WTO entry is
RMB757,000 more, accounting for roughly 47% of corporate income tax paid
by an average firm in 2001.
4.2. Testing the Identification Assumptions
In this section, we conduct several tests to see whether the assumptions
behind our identification are valid.
Pre-existing Time Trend. We test whether the tax avoidance behavior of
firms in different industries follows the same pre-existing time trend. We use the
sample from before WTO entry, i.e., from 1999 to 2001. We first define a
dummy denoting 2000 and 2001, and then replace Post in Equation (3) with this
dummy and estimate the equation. We also define another dummy denoting
2001 and replace Post in Equation (3) with this dummy. We then estimate this
equation again. The results of these two exercises are shown in columns 1 and 2
in Table 3. We can see that no coefficient of the interactions of the newly
defined dummies and � �����" � is significant, suggesting that the
pre-existing time trends are the same for firms in different industries.
Behavior Change Before WTO Entry. One concern is that firms in
industries with higher tariffs in 2001 were more likely to change their tax
avoidance behavior if they expected tariff reductions after WTO entry, thus
biasing our estimates. To address this concern, we add � �����" � ∗
*+� �� � ,��$�� ��* �+&�-� to the regression.
*+� �� � ,��$�� ��* �+&�-� is a dummy variable indicating 2000, one
year before WTO entry. The results are shown in column 3 in Table 3. We can
see that the coefficient of � �����" � ∗ *+� �� � ,��$�� ��* �+&�-� is
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not significant, suggesting that firms did not change their behavior before WTO
entry.
Other Policy Changes. In the early 2000s, there were two other reforms:
SOE reform and the relaxation of FDI regulation. If these two reforms affected
firms in different industries differently, then our estimates would be biased. To
address this concern, we add the share of SOEs among all firms in the industry
and the number of foreign invested firms in the industry to the regression. The
results are shown in column 4 in Table 3. We can see that no coefficients of
these two variables are significant, and that the coefficient of interest remains
positive and significant.
Input Tariffs and Larger Foreign Markets. Entry into the WTO
decreased not only output tariffs but also input tariffs, making it possible for
Chinese firms to use more imported intermediate inputs, which are usually
considered of better quality. Furthermore, China’s trading partners might have
also decreased their tariffs on Chinese products, giving Chinese firms greater
access to larger foreign markets. Having better inputs and gaining access to
larger foreign markets could have increased firms’ profitability and therefore
affected their tax avoidance behavior. To address this concern, we further add
industry-level input tariffs and export intensity to the regression. The results are
shown in column 5 in Table 3. We can see that the coefficient of interest is more
or less the same.
Change of Law Implementation. WTO entry might have had different
effects on law implementation in different provinces. If more industries with
smaller tariff reductions were located in provinces with larger improvements in
law implementation after WTO entry, then our estimates would be biased. To
address this concern, we add an index for law implementation at the provincial
level. The index was constructed by Fan and Wang (2006). The results are
shown in column 6 in Table 3. Adding this variable does not change the
coefficient of the interaction of tariffs in 2001 and the post dummy.
18
Processing Traders. A feature of the Chinese trading regime is that a
proportion of Chinese exporters are processing traders, i.e., firms that are
allowed to import intermediate materials free of tariffs but are required to export
all of their outputs. These firms should not be affected by China’s entry into the
WTO. We therefore use the sample of processing traders to estimate Equation
(3), and the results are shown in column 7 in Table 3. We can see that the
coefficient of � �����" � ∗ �$%&� is not significant.
Sample Attrition. We use an unbalanced panel of firms in the main
analysis. However, if firms were more likely to exit the market in industries
with higher tariff levels in 2001 and if these firms tended to engage in more (or
less) tax avoidance, our estimates would be biased. We test whether this concern
is valid by estimating Equation (3) using a balanced panel of firms. The results
are shown in column 8 in Table 3. We can see that the coefficient of
� �����" � ∗ �$%&� is still positive and significant, suggesting that sample
attrition is not a concern.
5. Robustness Checks
5.1. Justification of the Tax Avoidance Measurement
We use the gap between imputed profits and reported profits to measure
corporate tax avoidance. There are concerns about whether this method can
accurately measure tax avoidance. In this section, we provide several
justifications for using this measurement.
Correlation with Book-Tax Income Gap. A commonly used
measurement of corporate income tax avoidance is book-tax income gap (Desai,
2003, 2005; Desai and Dharmapala, 2006). Although we do not have
information on book income for industrial firms, we match industrial firms with
publicly listed firms and obtain a subsample of 325 firms between 1999 and
2004. For this small sample of firms, we have information on the book-tax
19
income gap.12 The summary statistics of these firms are presented in Appendix
Table A. We first regress the gap between imputed profits and reported profits
on the book-tax income gap. Table 4 shows the results: we can see that all the
coefficients are significantly positive and the magnitudes are large, between
0.357 and 0.591, which shows that these two measures are highly correlated. We
then replicate the regressions in Table 2, replacing the gap between imputed and
reported profits with book-tax income gap using this subsample. Table 5 shows
the results. We can see that the coefficients of Tariff2001*Post in all columns
are significantly positive, consistent with the results in Table 2. These results
suggest that the gap between imputed and reported profits is consistent with the
book-tax income gap in terms of measuring corporate tax avoidance. One caveat
we need to bear in mind is that the matched firms only account for a small part
of the whole sample, therefore the supporting evidence presented here can only
be considered as suggestive.
Response of Reported Profits to Imputed Profits. Following the approach
of Cai and Liu (2009), we estimate the effect of WTO entry on the response of
reported profits to imputed profits. If WTO entry reduced the response of
reported profits to imputed profits, we would have more evidence that trade
liberalization induces more tax avoidance. The results are shown in Table 6. We
can see that the coefficient of the triple interaction of the tariff in 2001,
post-WTO dummy, and imputed profits is negative and significant in all
columns. The results confirm our finding that WTO entry induces more tax
avoidance.
Over-reporting Output. One concern is that firms in industries facing
larger tariff cuts may be more likely to over-report outputs because of declining
sales income due to more intense competition after WTO entry. In other words,
imputed profits could be overestimated in industries with larger tariff cuts,
12 The list of publicly listed firms and information on the book-tax income gap come from RESSET (www.resset.cn).
20
making it hard to differentiate this phenomenon from higher corporate tax
avoidance. To see whether this issue may arise, we replicate regressions in Table
2 but replace the outcome variable with total output divided by sales income. If
firms were more likely to over-report output due to the decline of sales income
in industries with larger tariff cuts, we would expect to see a significantly
positive coefficient of Tariff2001*Post. However, none of the coefficients
shown in Table 7 are significant. This result shows that firms did not over-report
outputs due to the decline of sales income.
5.2. Other Measurements of Explanatory or Outcome Variables
In our main analysis, the four-digit industry-level tariffs are the
unweighted average of the six-digit industry-level tariffs. In this section, we
construct the four-digit industry-level tariffs using the weighted average of the
six-digit industry-level tariffs (1998 import values are used as the weight). For
further robustness checks, we also exploit the variation of two-digit industry
tariffs and three-digit industry tariffs, respectively. The results are shown in
columns 1-3 in Table 8. We can see that all of the coefficients of interest are
positive and significant, consistent with the main results.
In addition, we also use effective tax rate, which is the ratio of corporate
income tax paid by firms to pre-tax profits, to measure tax avoidance, and
investigate how WTO entry affects effective tax rate. The results are shown in
column 4 in Table 8. Although the coefficient of � �����" � ∗ �$%&� is not
precisely estimated, it is negative, providing some evidence that trade
liberalization induces more tax avoidance.
5.3. Heterogeneous Effects in Terms of Corporate Governance
Desai and Dharmapala (2006) emphasize the importance of corporate
governance in determining tax avoidance. They argue that firms with better
corporate governance tend to engage in less tax avoidance. As we do not have a
21
direct measurement of firms’ corporate governance, in this section we
investigate whether the effect of trade liberalization on tax avoidance differs for
firms with different types of ownership, i.e., SOEs, non-SOE domestic firms,
Hong Kong-Macau-Taiwan invested firms, and foreign invested firms. SOEs are
usually considered to have weak corporate governance, while foreign invested
firms have better corporate governance, especially in terms of financial
transparency (Bushman, Piotroski and Smith, 2004).
Table 9 shows the heterogeneous effects. In this table, columns 1-4 are
for SOEs, non-SOE domestic firms, Hong Kong-Macau-Taiwan invested firms,
and foreign invested firms, respectively. We can see that the coefficient of
� �����" � ∗ �$%&� is positive and significant in column 1 (SOEs), while the
coefficient is not significant in the other columns.
Our results show that firms with weak corporate governance respond to
WTO entry by engaging in more tax avoidance, reinforcing the prediction of
Desai and Dharmapala (2006).
6. Channels through which Trade Liberalization Affects Tax Avoidance
Firms experiencing reduced profit performance due to the increased
competition induced by WTO entry tend to rely on noncompliance so that they
have more cash to invest and thus improve their prospects (Slemrod, 2004).
Therefore, firms short of cash or with a higher demand for cash tend to engage
in more tax avoidance. In this section, following Almeida, Campello, and
Weisbach (2004), we use firms’ profitability and leverage before WTO entry to
measure whether they are short of cash. Lower profitability or higher leverage
means a higher degree of cash shortage. We use firms’ growth rate before WTO
entry to measure their demand for cash. The higher the growth rate, the higher
the demand for cash.
Table 10 shows the results. Columns 1 and 2 are for firms with high and
low profitability, respectively. We can see that the coefficient of � �����" � ∗
22
�$%&� is significantly positive for firms with low profitability (column 2).
Columns 3 and 4 are for firms with high and low leverage, respectively. We can
see that the coefficient of � �����" � ∗ �$%&� is significant and positive for
firms with high leverage (column 3). The combination of these two results
suggests that firms short of cash tend to engage in more tax avoidance after
WTO entry.
Columns 5 and 6 are for firms with high and low growth rates before
WTO entry. We use the growth rate of firms to measure their demand for cash.
The higher the growth rate, the higher the demand for cash. We see that the
coefficients in columns 5 and 6 are significantly positive and that the coefficient
for firms with a higher growth rate is larger. This finding suggests that firms
with a higher demand for cash did engage in more tax avoidance after WTO
entry.
7. How Did Firms Engage in Tax Avoidance?
There are several ways firms can avoid corporate income tax, among
which under-recording sales revenues, over-recording costs, and transfer pricing
with affiliated firms are the most common. As we do not have information on
transfer pricing, our focus in this section is whether firms under-report sales
revenues or over-report costs after WTO entry. In particular, we investigate the
effect of WTO entry on administrative costs, sales costs, financial costs, wages,
and benefits, all of which are scaled by sales income.
Indeed, WTO entry significantly increases costs per unit of sales income.
The results are shown in Table 11. We can see that the coefficients in all five
columns are positive and significant at the 10% level or more. This result shows
that firms in industries with higher tariffs in 2001 spent more for each unit of
sales income, which is evidence that over-reporting costs could be a way that
firms avoid corporate income tax.
23
8. Conclusions
In this study, we investigate the effect of trade liberalization on
manufacturing firms’ tax avoidance, using China’s entry into the WTO as a
natural experiment. Comparing firms in industries with different tariffs in 2001
and therefore different reductions between the pre- and post-WTO entry periods,
we find that WTO entry induced firms in industries with tariffs 10 percentage
points higher to engage in tax avoidance totaling RMB757,000, accounting for
47% of the corporate income tax paid by an average firm that year.
Furthermore, we find that firms with better corporate governance (i.e.,
non-SOEs or foreign invested firms) tended to engage in less corporate tax
avoidance in response to WTO entry. We then investigate the possible channels
by which WTO entry affects firms’ corporate tax avoidance. We find that firms
short of cash or with a higher demand for cash engage in more tax avoidance
when facing a more competitive environment after WTO entry. We also find
evidence that firms avoid corporate income tax by over-reporting costs.
Trade liberalization has been considered an important factor in China’s
rapid economic growth in the past three decades. Our findings suggest that the
social benefits may be undermined by illegal activities induced by this trend.
Government policymakers should therefore work to improve tax administrative
efficiency during integration with the global economy.
24
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28
Figure 1. Tariffs in Four-digit Industries (1999-2004)
Note: The average tariff in each year is the mean value of import tariffs for 476 China
Industry Classification (CIC) system four-digit industries. China entered the WTO at the end
of 2001, which is denoted by the vertical line in the figure.
.1.1
2.1
4.1
6.1
8T
ari
ff
1999 2000 2001 2002 2003 2004Year
29
Figure 2. Correlation between Tariffs in 2001 and Tariffs after WTO Entry
Note: The dots in the graphs are for CIC four-digit industries. The X-axis in each graph shows the average
tariff in 2001. The Y-axis in the top two graphs and the bottom-left graph is for tariff reductions from 2001
to 2002, 2003, and 2004, respectively. The Y-axis in the bottom-right graph is for tariff reductions from
2001 to the average tariff level over 2002 to 2004.
0.2
.4.6
Tari
ff R
eduction (
2001-2
002)
0 .2 .4 .6 .8Tariff in 2001
2001-2002
0.2
.4.6
Tari
ff R
eduction (
2001-2
003)
0 .2 .4 .6 .8Tariff in 2001
2001-20030
.2.4
.6T
ari
ff R
eduction (
2001-2
004)
0 .2 .4 .6 .8Tariff in 2001
2001-2004
0.2
.4.6
Tari
ff R
eduction (
2001-A
vera
ge(0
2-0
4))
0 .2 .4 .6 .8Tariff in 2001
2001-Average(2002-2004)
30
Table 1. Summary Statistics
Mean S.D.
Panel A. Firm characteristics
Reported profit (1,000 yuan) 10,079.356 231,839.186
Imputed profit (1,000 yuan) 16,893.610 233,166.300
Total assets (1,000 yuan) 244,199.425 1,208,199.082
Exporter 0.333 0.471
Processing trader 0.080 0.272
Export (1,000 yuan) 29,285.834 260,377.499
Effective income tax rate 0.179 15.137
Sales (1,000 yuan) 176,624.208 937,413.619
SOE 0.235 0.424
FDI 0.136 0.342
Administrative expenditures (1,000 yuan) 10,701.175 59,786.793
Sales expenditures (1,000 yuan) 6,506.970 44,024.018
Financial costs (1,000 yuan) 3,549.309 20,237.050
Total wages (1,000 yuan) 9,359.691 43,457.963
Total employment 763.770 2,573.373
OBS 281,522 281,522
Panel B. Tariff
42 two-digit industries 0.154 0.101
188 three-digit industries 0.159 0.105
476 four-digit industries 0.159 0.109
Note: Reported profits are the profits firms reported when they filed annual reports to the NBS. Imputed profits are equal to output minus intermediate inputs, financial charges, total wages paid, current depreciation, and value added tax. Effective income tax rate is the ratio of corporate income tax paid by firms to pre-tax profits. SOEs are defined as firms with more than 50% state-owned shares. FDI firms are defined as firms with more than 25% foreign-owned shares.
31
Table 2. Effects of Trade Liberalization on Firms’ Tax Avoidance
(1) (2) (3) (4)
Dependent variable: (Imputed Profits minus Reported Profits)/Total Assets
Tariff2001*Post 0.057 0.059 0.033 0.031
(0.012)*** (0.012)*** (0.011)*** (0.011)***
Average wage in 2001*Post
-0.001
-0.000
(0.000)***
(0.000)
Export intensity in 2001*Post
-0.026
-0.006
(0.009)***
(0.009)
SOE share in 2001*Post
-0.001
-0.008
(0.008)
(0.007)
Industry and province fixed effects Yes Yes No No
Firm fixed effects No No Yes Yes
Year fixed effects Yes Yes Yes Yes
Observations 281,522 281,522 281,522 281,522
R-squared 0.06 0.06 0.64 0.64
Robust standard errors in parentheses are calculated by clustering over four-digit industry; * significant at 10%; ** significant at 5%; *** significant at 1%. Average wage in 2001 is the average wage per worker for each industry in 2001; export intensity in 2001 is the ratio of exports to sales in each industry in 2001; SOE output share in 2001 is the share of outputs produced by SOEs for each industry in 2001.
32
Table 3. Pre-assumption Tests (Dependent Variable: (Imputed Profits Minus Reported Profits)/Total Assets)
(1) (2) (3) (4) (5) (6) (7) (8)
Pre-trend
(1999-2001) Next year Additional Controls
Processing Traders
Balanced Panel
Tariff2001*Post
0.026 0.030 0.024 0.024 0.049 0.039
(0.011)** (0.011)*** (0.012)** (0.012)** (0.140) (0.012)***
Tariff2001*One year before
-0.016
(0.010)
Tariff2001*Dummy for 2000 and 2001 0.002
(0.014)
Tariff2001*Dummy for 2001
-0.010
(0.014)
SOE
-0.016 -0.019 -0.018
(0.011) (0.011)* (0.011)
Ln(FDI)
0.001 -0.001 -0.001
(0.001) (0.002) (0.002)
Input tariff
-0.035 -0.035
(0.042) (0.042)
Exports/Sales
0.093 0.093
(0.057) (0.058)
Index for law implementation
-0.001
(0.001)
Variable in 2001*Post Yes Yes Yes Yes Yes Yes Yes Yes
Firm fixed effects Yes Yes Yes Yes Yes Yes Yes Yes
Year fixed effects Yes Yes Yes Yes Yes Yes Yes Yes
Observations 123,795 123,795 281,522 281,522 218,592 218561 17520 108447
R-squared 0.71 0.71 0.64 0.64 0.65 0.65 0.64 0.48
Robust standard errors in parentheses are calculated by clustering over four-digit industry; * significant at 10%; ** significant at 5%; *** significant at 1%; variables in 2001 include the average wage per worker for each industry in 2001, the ratio of exports to sales in each industry in 2001 and the share of outputs produced by SOEs for each industry in 2001. Index for law implementation is a provincial level variable indicating how well laws are implemented; a larger value indicates better law implementation.
33
Table 4. Correlation between Measures of Corporate Income Tax
(1) (2) (3)
(Imputed Profits minus Reported Profits)/Total
Assets
Book-tax income gap/Total assets 0.357 0.411 0.591
(0.113)*** (0.118)*** (0.117)***
Industry and province fixed effects No Yes No
Firm fixed effects No No Yes
Year fixed effects No Yes Yes
Observations 699 699 699
R-squared 0.01 0.41 0.64
Robust standard errors are in parentheses; * significant at 10%; ** significant at 5%; *** significant at 1%.
34
Table 5. Using Publicly Listed Firms
(1) (2) (3) (4)
Dependent Variable: Book-tax income gap/Total assets
Tariff2001*Post 0.078 0.091 0.067 0.070
(0.027)*** (0.026)*** (0.027)** (0.027)**
Average wage in 2001*Post
0.001
0.000
(0.001)
(0.001)
Export intensity in 2001*Post
-0.004
0.003
(0.021)
(0.024)
SOE share in 2001*Post
0.019
0.008
(0.020)
(0.019)
Industry and province fixed effects
Yes Yes No No
Firm fixed effects No No Yes Yes
Year fixed effects Yes Yes Yes Yes
Observations 699 699 699 699
R-squared 0.30 0.30 0.47 0.47
Robust standard errors in parentheses are calculated by clustering over four-digit industry; * significant at 10%; ** significant at 5%; *** significant at 1%. The sample used in this table is drawn from publicly listed firms. Average wage in 2001 is the average wage per worker for each industry in 2001; export intensity in 2001 is the ratio of exports to sales in each industry in 2001; SOE output share in 2001 is the share of outputs produced by SOEs for each industry in 2001.
35
Table 6. Effects on the Responses of Reported Profits to Imputed Profits
(1) (2) (3) (4)
Dependent Variable: Reported Profits Scaled by Total Assets
Tariff2001*Post*Imputed profits scaled by total assets -0.096 -0.104 -0.073 -0.083
(0.049)* (0.050)** (0.036)** (0.036)**
Tariff2001*Post -0.003 0.003 -0.020 -0.014
(0.006) (0.006) (0.007)*** (0.006)**
Imputed profits scaled by total assets 0.143 0.142 0.064 0.063
(0.014)*** (0.013)*** (0.010)*** (0.010)***
Imputed profits scaled by total assets*Post 0.033 0.035 0.038 0.041
(0.014)** (0.014)** (0.010)*** (0.010)***
Tariff2001*Imputed profits scaled by total assets -0.044 -0.039 -0.023 -0.017
(0.048) (0.048) (0.043) (0.042)
Variable in 2001*Post Yes Yes Yes Yes
Firm fixed effects Yes Yes Yes Yes
Year fixed effects Yes Yes Yes Yes
Observations 281,522 281,522 281,522 281,522
R-squared 0.23 0.23 0.76 0.76
Robust standard errors in parentheses are calculated by clustering over four-digit industry; * significant at 10%; ** significant at 5%; *** significant at 1%; variables in 2001 include the average wage per worker for each industry in 2001, the ratio of export to sales in each industry in 2001, and the share of outputs produced by SOEs for each industry in 2001.
36
Table 7. Effects of Trade Liberalization on Firms’ Output Relative to Sales
(1) (2) (3) (4)
Dependent variable: (Imputed Profits minus Reported Profits)/Total Assets
Tariff2001*Post -0.036 -0.024 0.010 0.018
(0.026) (0.026) (0.026) (0.026)
Average wage in 2001*Post
0.002
0.001
(0.001)***
(0.001)**
Export intensity in 2001*Post
-0.017
-0.042
(0.019)
(0.024)*
SOE share in 2001*Post
0.007
-0.004
(0.016)
(0.018)
Industry and province fixed effects Yes Yes
Firm fixed effects
Yes Yes
Year fixed effects Yes Yes Yes Yes
Observations 281,515 281,515 281,515 281,515
R-squared 0.02 0.02 0.56 0.56
Robust standard errors in parentheses are calculated by clustering over four-digit industry; * significant at 10%; ** significant at 5%; *** significant at 1%. Average wage in 2001 is the average wage per worker for each industry in 2001; export intensity in 2001 is the ratio of exports to sales in each industry in 2001; SOE output share in 2001 is the share of outputs produced by SOEs for each industry in 2001.
37
Table 8. Other Robustness Tests
(1) (2) (3) (5)
Imputed Profits minus Reported
Profits/Total assets Effective Tax Rate
Tariff2001_New*Post 0.024
(0.010)**
Tariff2001_2digit*Post
0.046
(0.015)***
Tariff2001_3digit*Post
0.026
(0.010)**
Tariff2001*Post
-0.097
(0.127)
Variable in 2001*Post Yes Yes Yes Yes
Firm fixed effects Yes Yes Yes Yes
Year fixed effects Yes Yes Yes Yes
Observations 281,522 281,522 281,522 275,104
R-squared 0.64 0.64 0.64 0.33
Robust standard errors in parentheses are calculated by clustering over four-digit industry; * significant at 10%; ** significant at 5%; *** significant at 1%; Tariff2001_New is at the four-digit industry level and is calculated as the weighted average of tariffs in the HS six-digit industry level using imports as weights. Variables in 2001 include the average wage per worker for each industry in 2001, the ratio of export to sales in each industry in 2001, and the share of outputs produced by SOEs for each industry in 2001.
38
Table 9. Heterogeneous Effects in Terms of Corporate Governance
(1) (2) (3) (4)
Dependent variable: (Imputed Profits minus Reported Profits)/Total Assets
SOE Domestic Non-SOE HK-Macau-Taiwan FDI
Tariff2001*Post 0.052 0.015 0.031 0.022
(0.014)*** (0.014) (0.033) (0.031)
Variable in 2001*Post Yes Yes Yes Yes
Firm fixed effects Yes Yes Yes Yes
Year fixed effects Yes Yes Yes Yes
Observations 66,661 156,937 35,347 188,251
R-squared 0.54 0.55 0.50 0.56
Robust standard errors in parentheses are calculated by clustering over four-digit industry; * significant at 10%; ** significant at 5%; *** significant at 1%. Variables in 2001 include the average wage per worker for each industry in 2001, the ratio of export to sales in each industry in 2001, and the share of outputs produced by SOEs for each industry in 2001.
39
Table 10. Heterogeneous Effects
(1) (2)
(3) (4)
(5) (6)
Dependent variable: (Imputed Profits minus Reported Profits)/Total Assets
Profitability prior to WTO entry
Leverage prior to WTO entry
Sales growth prior to WTO entry
Top 50
percentile Bottom 50 percentile
Top 50 percentile
Bottom 50 percentile
Top 50 percentile
Bottom 50 percentile
Tariff2001*Post 0.012 0.050
0.042 0.013
0.047 0.029
(0.016) (0.012)***
(0.015)*** (0.014)
(0.017)*** (0.012)**
Variable in 2001*Post
Yes Yes
Yes Yes
Yes Yes
Firm fixed effects Yes Yes
Yes Yes
Yes Yes
Year fixed effects Yes Yes
Yes Yes
Yes Yes
Observations 120,910 103,500
109,742 114,653
76300 73541
R-squared 0.56 0.51 0.57 0.54 0.53 0.48
Robust standard errors in parentheses are calculated by clustering over four-digit industry; * significant at 10%; ** significant at 5%; *** significant at 1%. Variables in 2001 include the average wage per worker for each industry in 2001, the ratio of exports to sales in each industry in 2001, and the share of outputs produced by SOEs for each industry in 2001.
40
Table 11. Suggestive Evidence for Tax Avoidance Channels
(1) (2) (3) (4) (5)
Ratio of
Administrative Expenditures
Sales Expenditures
Financial Costs
Wages Benefits
Tariff2001*Post 0.013 0.007 0.016 0.024 0.004
(0.007)* (0.003)** (0.005)*** (0.005)*** (0.002)**
Variable in 2001*Post
Yes Yes Yes Yes Yes
Firm fixed effects Yes Yes Yes Yes Yes
Year fixed effects Yes Yes Yes Yes Yes
Observations 281,472 281,436 281,515 281,515 281341
R-squared 0.72 0.81 0.68 0.74 0.45
Robust standard errors in parentheses are calculated by clustering over four-digit industry; * significant at 10%; ** significant at 5%; *** significant at 1%. Variables in 2001 include the average wage per worker for each industry in 2001, the ratio of exports to sales in each industry in 2001, and the share of outputs produced by SOEs for each industry in 2001.
41
Table A. Summary Statistics of Publicly Listed Industrial Firms
Mean S.D.
Panel A. Firm characteristics
Book-tax income gap/Total assets 0.003 0.033
Reported profit (1,000 yuan) 97,481.815 249,141.064
Imputed profit (1,000 yuan) 158,694.200 627,524.400
Total assets (1,000 yuan) 1,908,515.927 2,701,504.283
Exporter 0.571 0.495
Processing trader 0.008 0.088
Export (1,000 yuan) 108,796.604 352,569.848
Effective income tax rate 0.165 0.342
Sales (1,000 yuan) 1,228,955.401 2,327,948.040
SOE 0.321 0.467
FDI 0.035 0.183
Administrative expenditures (1,000 yuan) 72,780.540 170,093.573
Sales expenditures (1,000 yuan) 53,764.699 153,295.582
Financial costs (1,000 yuan) 19,427.010 41,365.234
Total wages (1,000 yuan) 51,402.294 105,109.469
Total employment 2,688.077 3,478.291
OBS 699
Number of firms 325
Number of 4-digit industries 162