abstract we examine how the us and eu antidumping (ad...

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Do Antidumping Measures Affect Chinese Exporting Firms?

ABSTRACT

We examine how the US and EU antidumping (AD) cases against Chinese firms affected their

stock prices and long-term financial performance during 1995–2012, and whether the affected

Chinese firms received more or less government subsidies in the subsequent years. Our findings

indicate that AD news, especially the final decision on imposing antidumping measures, has

significant negative effects on the stock price of relevant Chinese export firms. Besides, little

empirical evidence reveals an increase in government subsidies given to AD affected firms after

the imposition of AD duties, but we find a decrease in subsidies for non-SOEs.

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1. INTRODUCTION

Trade disputes between China and its trading partners often appear in the headlines. In fact,

China is the largest recipient of anti-dumping (AD) investigations and measures (duties/tariffs) in the

world. Using a sample of listed firms, we examined whether AD cases against China that are initiated

in the US and EU affected the relevant Chinese exporting firms, specifically their stock prices, long

term financial performances, and the subsidies they received from the government.

The antidumping petition is now the most popular means used by import-competing firms,

trade associations, and labor unions in WTO member countries to seek trade protection from their

governments. Our study is interesting for several reasons. First, China is the largest exporter in the

world as well as the top recipient of AD investigations, while the US and the EU are China’s top two

trading partners and also frequent initiators of AD investigations, as both countries have run chronicle

trade deficits with China. Hence, AD cases against China that initiated in the US and EU offer a

particularly good setting to investigate the possible effects of AD on export-oriented firms.i Second,

China is facing increasing difficulties to maintain its export growth, which has been an important

engine for its economic miracle.ii AD cases against China have not only caused concerns for Chinese

export-oriented firms and the Chinese government but also for investors and the general public. How

does the Chinese stock market react to AD investigations and measures in the short-term as well as in

the long-term? Do AD measures affect Chinese firms’ performances in terms of profitability? Does the

government provide aid to firms affected by AD in the form of more subsidies? Our investigation can

shed light on these questions.

Our study contributes incrementally to the existing literature. Prior authors have examined the

effect of AD investigations and measures on the output, productivity, profitability, and the trading

volume of Chinese export-oriented firms, as well as the number of firms in relevant Chinese export-

oriented industries.iii We used the capital market approach to further examine how these AD

investigations and measures would affect the stock prices of the relevant firms. This approach can

capture the expected AD effect and provide an alternative to estimate the effect of AD investigations

and measures against Chinese firms. Many listed firms in China are export-oriented, yet there is no

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systematic study on how trade conflict news may affect the stock price of these firms. If AD

investigations and measures are expected to have negative effects on a firm’s future cash flow or

increase the uncertainty they face, the stock price should go down immediately upon receiving such

news. In addition, we looked at long-term performance. Specifically, we examined the stock returns

and accounting performances of these firms up to three years after the imposition of AD measures.

These investigations can help to quantify the effect of AD on Chinese firms and also have important

implications for the market participants. Furthermore, we investigated whether government subsidies

to relevant firms change after the imposition of AD duties, which is an interesting issue. According to

Capital Trade Incorporated (2008), it has been widely perceived in the west that the Chinese

government subsidizes exporters. The imposition of AD duties on Chinese firms offers a good

opportunity to test whether the Chinese government gives more subsidies to help these firms when

they are in the midst of difficulties.

We also looked at several related issues. First, the Chinese economy is in transition with many

state-owned enterprises (SOEs). A common view is that the Chinese government gives more favorable

treatment to SOEs (Eckaus, 2006; Lee et al., 2014). It is interesting to see if this is indeed the case

when AD measures are imposed on SOEs. Second, under the mounting pressure from its trading

partners, especially the US and EU, the Chinese government started to allow its RMB to appreciate

gradually in July 2005 from RMB 8.27 per US Dollar to about RMB 6.15 per US Dollar at the end of

2013. It is also interesting to see if AD investigations and measures have more negative effects on

Chinese firms after July 2005 when the RMB has been appreciating. Third, although AD

investigations and measures are largely consistent across WTO member countries, there are still some

differences in the US and EU. Hence, the influence of AD cases initiated and AD measures

implemented in the two places may have some systematic differences in their effects on Chinese firms.

We investigated this issue. Finally, it is reasonable to expect that firms affected by AD measures in

their recent past will react more negatively to new AD measures due to the compounding effect. We

further examined this possibility.

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Our major findings are summarized below. First, AD decisions, especially final decisions,

were value relevant. The stock returns of AD affected firms declined around the decision day, and the

three-year buy-and-hold returns of these firms were also negative relative to their peers after the

imposition of AD duties. Second, in general, there was no significant stock return difference between

the SOEs and non-SOEs across different exchange regimes, and between the firms that had received

AD measures in the previous three years and those that had not. Third, AD duties had a negative effect

on the profitability of AD affected firms. However, there was only limited evidence that AD affected

firms underperform compared with their matched peers, and the underperformance seems more

concentrated in AD affected non-SOEs. Finally, while there was no evidence that AD affected firms

received more government subsidies than their matched peers, there was some evidence that AD

affected non-SOEs received less subsidies from the government than AD affected SOEs after the

imposition of AD duties. These findings have both theoretical and practical implications.

The next section provides background information for AD initiations and AD measures

against Chinese firms. Section 3 reviews the literature. Section 4 examines the stock price response of

Chinese firms to AD news, and Section 5 investigates the long-term stock return of firms sanctioned

by the AD measures. Section 6 further studies whether AD measures affect the profitability of Chinese

firms and the government subsidies these firms received up to three years following the AD sanctions.

Section 7 concludes this study.

2. BACKGROUND INFORMATION

The US and EU are China’s two largest trading partners. Table 1 presents the relevant annual

trading statistics from 1995 to 2012 for China, the US, and the EU. It is clear from the table that China

runs huge trade surpluses with both the US and the EU year after year. Such trade imbalances hurt the

import-competing firms in the US and EU, which in turn has fostered the protectionist sentiment

against Chinese producers.

(Insert Table 1 here)

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Many import competing firms and other interest groups in the US and EU accuse Chinese

firms of engaging in “unfair trading practices” and seek protections from their respective governments.

WTO allows its member countries to erect some temporary trade barriers (TTBs) to provide relief to

the industries injured by “unfair trading practices.” AD litigations are the most popular TTBs. Nearly

90% of TTBs worldwide consist of AD cases (Vandenbussche & Viegelahn, 2011). Under GATT

Article VI and the WTO’s Antidumping Agreement, member countries are permitted to impose

discriminatory tariffs on goods sold by foreign producers at prices that are deemed to be less than fair

value (LTFV), if these sales result in material injury to the domestic industry.

As a condition to join WTO, China agreed to be treated as a non-market economy (NME) for

15 years until 2016. Petitioners do not need to use Chinese domestic input prices in determining the

cost of producing an investigated product. This gives more discretionary power to petitioners and

investigators in the US and the EU seeking evidence for Chinese products selling at LTFV, and thus,

may have increased the use of AD litigations against China.

Table 2 lists the total number of AD initiations and measures against China from 1995 to 2012.

There were a total of 4,230 AD investigations initiated globally during this period. Of these

investigations, 916 cases (21.65%) were against exports from China, which made China the world’s

largest recipient of AD investigations. Of all AD investigations against China, 565 cases (62%) were

sanctioned with AD tariffs or duties.


Table 3 lists the top five countries that issued AD litigations against China during the period

from 1995–2012. India, the US, and the EU ranked as the top three both in terms of AD initiations

(154, 112, and 111, respectively) and AD measures (126, 93, and 73, respectively). However, the

trading volume between India and China has been small.


AD laws in the US are jointly administered by the Department of Commerce (DoC) and the

International Trade Commission (ITC). The former is in charge of investigating whether there is a

dumping of imported goods in the US, while the latter investigates whether domestic industries are

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injured by alleged dumping. Individual firms, groups of firms, trade chambers/industry associations, or

labor unions may file an AD petition with the ITC alleging that an industry in the US is materially

injured or threatened with material injury by imports that are, or are likely to be, sold at LTFV.

The ITC starts its preliminary investigation after receiving a petition and should determine

whether there is a reasonable indication of injury to the domestic industry 45 days after the filing of a

petition. If the ITC finding is negative, then the case is terminated. Otherwise, the DoC performs its

preliminary investigation to determine whether the imported goods named in the petition are sold at

LTFV. The determination has to be made between 115 and 165 days after the ITC preliminary finding,

depending on the complexity of the investigation. If the DoC preliminary finding is positive, then the

importers of the goods must post a bond equivalent to the estimated dumping margin to guarantee that

AD duty will be paid upon assessment. Whether the determination is positive or not, the DoC will

continue its final investigation of the case, and the final DoC determination on whether dumping exists

has to be made between 75 and 135 days after the preliminary DoC determination. Again, if the

finding is negative, the case will be terminated. Otherwise, the ITC will conduct its final investigation

and make a final determination on whether the domestic industry is injured 45 days after the DoC’s

final determination. If the decision is affirmative, the DoC will issue an order to impose AD duty on

the imported products. The whole process usually takes 280 to 390 days.iv

From Table 3, we see that out of 112 US initiated AD investigations against China, 93 (83%)

resulted in sanction measures. The AD duty is meant to be temporary and usually expires in five years,

but it may be extended after a formal review by the ITC and the DoC.

AD cases in the EU are handled by the EU Commission. Similar to the US, an interest party

may file an AD petition with the EU Commission, and the commission must launch the investigation

within 45 days of the filing if the petition is credible. The overall process must be completed within 15

months after the beginning of the investigation. However, a provisional finding must be published

within the first nine months and be open for comments to all interested parties. If the finding is

positive and the imported products are found being sold at LTFV and causing injury to EU industries,

provisional AD measures (AD duties) will be imposed on the relevant imported products. The final

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decision has to be made within the following six months. If the final ruling on dumping is affirmative,

then definitive measures will be imposed. However, the rate could be lower than the one specified in

the provisional measure. The duration of AD duty in the EU is also five years. It may be extended if a

formal review determines that it is necessary. From Table 3, we see that out of 111 EU initiated AD

investigations against China, 79 (70%) end with definitive AD measures.

The AD petition is product specific both in the US and the EU and it can involve producers in

one or several countries. However, there are some differences in administering AD laws between the

EU and the US. For example, in addition to considering whether there is a presence of dumping and

whether there is an injury to EU industries, the EU Commission must consider the EU’s community

interests when it decides to impose AD duties on imported products. For example, the price of the

likely products should not rise dramatically after the imposition of AD duties. This is not a required

consideration in the US. The implication is that AD measures imposed by the EU may be less severe

than those imposed by the US.

3. LITERATURE REVIEW

There is a vast amount of literature on the effect of trade protection. We will first review

papers on the stock price response to trade protection news. We will then review papers on how trade

protection measures, especially AD duties, affect trade volume, profitability, productivity, and

employment of the relevant firms/industries a few years after the protection measures are imposed.

Finally, we will further review papers on government subsidies to firms.

3.1 Stock Price Responses to Trade Protection News

In theory, trade protection, especially in the form of tariffs or dutiesv, should benefit the

protection seekers and hurt foreign producers that are targeted by protection measures. Hartigan, Perry,

and Kamma (1986) used the capital market approach to investigate trade restriction effects on the

protection seeking firms’ stock prices. They focused on the protection decision effects of the escape

clause (Section 201) petitions filed under the Trade Act of 1974 with the ITC in the US. The authors

identified 65 petition firms from 19 industries involved in Section 201 petitions and looked at the ITC

and presidential decision effects on those industries. They found that the effect on import-competing

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industries is insignificant, i.e., the petition industries’ stock returns did not respond to the administered

protection.

A more relevant study was done by Marsh (1998), which used event study to examine whether

AD petitions and measures in the US are effective at improving the performance of US firms.

Specifically, Marsh hypothesized that (1) filing an AD petition has a positive effect on the stock price

of petitioning firms, regardless of the outcome of the petition; and (2) affirmative AD decisions by the

ITC at the preliminary and final determinations have positive effects on the performance of the

petitioning firms and vice versa. Using a sample of 134 petitions filed by listed firms during the period

from 1980–1992 and daily stock return data, Marsh found that the three-day average abnormal return

of petitioning firms around the AD petition filing date was positive and significant. However, the

affirmative ITC preliminary and final decisions did not generate abnormal returns for the petitioning

firms, but negative ITC final decisions generated a negative and significant abnormal return for the

relevant petitioning firms. A possible explanation for these findings is that affirmative ITC rulings are

expected whereas negative rulings are not. Overall, Marsh concluded that AD laws increase returns of

US firms pursuing AD protection.

Brander (1991), Hartigan, Perry, and Kamma (1989), Mahdavi and Bhagwati (1994), Rehbein

and Starks (1995), and Hughes, Lenway, and Rayburn (1997) all used event study to examine the

effect of AD or Section 201 petitions and measures on protection-seeking firms in the US, especially

in the steel and semi-conductor industries. The authors found some mild evidence that AD petitions

and positive ITC rulings increase the stock price of protection seeking firms.

Melvin and Sun (1997) examined the effect of U.S. trade restriction news on the stock prices

of affected firms in Taiwan and Korea in the late 1980s. They found that the effect was generally

insignificant. However, their sample size was small. Parsons (2005) investigated the effect of anti-

dumping actions by the US on Japanese firms with mixed results.

No study thus far has examined the stock price response of Chinese firms to trade restriction.

In addition, no study has examined the effect of AD measures on long-term stock price movement,

whether for the protection-seeking firms or for the firms sanctioned by AD measures. We will fill this

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void with our study. Our relatively large and more concentrated sample is also better suited for a test

of the AD effect on export firms, given the importance of the US and EU markets to the Chinese

economy.

3.2 Trade Protection Effect on Firm Performance Measures

Holding other things constant, AD measures should have a negative effect on the sales,

profitability, and employment of targeted exporters and cause trade depression and/or trade diversion.

Trade depression means that AD measures depress exports of the named country or firms, while trade

diversion means these reduced exports are offset, either fully or partially, by an increase in exports to

other countries. Bown and Crowley (2010) investigated how US and EU initiated AD duties affect

exports from Chinese firms. They found that trade depression effects were weak but trade diversion

effects were strong.

Konings and Vandenbussche (2008) examined how antidumping protection in the EU affects

the productivity of domestic import-competing firms and found that AD measures do help improve

productivity but mostly for low productivity firms. Pierce (2011) also found that anti-dumping duties

are associated with an increase in revenue productivity of protection-seeking firms in the US.

However, this is mainly due to the increase in product prices and markups while the physical

productivity actually falls.

Li and Whalley (2010) empirically investigated how AD measures affect Chinese exporting

industries. Using panel data from 1997 to 2007, they found that antidumping measures negatively

affected profit, employment, firm numbers, and exports of the relevant industry. They also found that

antidumping measures from the US have more negative effect than those from EU countries.

Furthermore, they found that antidumping measures have less negative effect on SOEs than on other

firms in China. Chandra and Long (2013) also found that US AD duties led to a significant drop in

both labor productivity and total factor productivity of Chinese export-oriented firms.

Lu, Tao, and Zhang (2013) focused on how AD investigations initiated in the US affect the

exporting volume of Chinese firms and the number of Chinese exporting firms exiting the US market.

Using Chinese customs data that covered monthly transactions of all Chinese exporters during the

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period from 2000 to 2006, they found that the negative effect was mainly manifested through the exit

of Chinese exporting firms from the US market.

3.3 Government Subsidies

Schwartz and Clements (1991) pointed out that subsidies are tools used by governments

around the world to pursue social policy objectives. Desai and Hines (2008) and Ishikawa and Spencer

(1999), among others, documented that subsidies are often used to improve export competitiveness.

Lee, Walker, and Zeng (2014) found that on average 68% of listed companies in China received

government subsidies in various forms during the period from 2002 to 2008, and the subsidies were

value relevant to these firms. However, there has been no study on whether the government subsidies

given to a firm changed in response to AD measures.

4. STOCK PRICE RESPONSES TO AD NEWS

If AD news, such as AD petitions and AD protection decisions, is expected to have a negative

effect on Chinese export-oriented firms, then their stock prices should go down upon receiving the

news. Using the event study methodology, we examined how US and EU AD initiated news affects

the stock returns of these Chinese firms.

4.1 Data

We first identified AD events from the Global Antidumping Database (GAD) compiled by the

World Bank. There were a total of 108 completed AD cases against Chinese firms in the EU and 113

in the US.vi We then identified Chinese listed firms affected by the AD cases. Since AD is product

specific, all exporters of the same product from the accused country are affected. Following previous

authors (e.g., Konings & Vandenbussche, 2008), we used the six-digit Harmonization System (HS)

code provided in GAD to match firms that produce the same product and are also listed on the

Shanghai Stock Exchange (SSE) and Shenzhen Stock Exchange (SZE). The firms included in our

sample must have been listed in the stock market one year before the AD petition date. We excluded

AD events with no qualified listing firms producing the same six-digit HS code products.vii Our final

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samples on the petition day included 68 events and 187 affected firms for the US initiated AD cases

and 64 events and 135 firms for the EU initiated AD cases (See Table 4).viii

For EU initiated AD cases, there are three event days: petition day, preliminary decision day,

and the final decision day. We examined the abnormal returns around all three events. However, for

the US cases, there are five event days: petition day, ITC preliminary decision day, DoC preliminary

decision day, DoC final decision day, and ITC final decision day. Following previous authors (e.g.,

Marsh, 1998; Hartigan, Perry, & Kamma, 1989), we only focused on the petition day and the ITC

decision days, as DoC investigations almost always find that foreign firms sell at LTFV in the US.

(Insert Table 4 Here)

Table 4 details the sample size for each event day in the EU (Panel A) and the US (Panel B),

respectively. For EU cases, there were 64 AD petitions associated with a sample of 135 firms, 42

preliminary affirmative decisions with 92 firms, 49 affirmative final decisions with 112 firms, and 15

negative final decisions with 23 firms. There were fewer preliminary decisions than final decisions

because the EU allows accelerated investigations for some cases. In such circumstances, preliminary

decisions are skipped and the first decision becomes the final decision. For US cases, there were 68

petitions associated with a sample size of 187 firms, 64 ITC affirmative preliminary decisions with

175 firms, 55 affirmative final ITC decisions with 150 firms, and 8 negative ITC final decisions with

27 firms. We also classified the sample firms associated with each event into SOEs versus non-SOEs,

firms sanctioned with AD measures in the previous three years either in the US or EU versus those

without, and firms associated with AD events that occurred before July 2005 when the Chinese Yuan

started to appreciate versus those that occurred after. As the sample size associated with negative

decision events was small, we focused on affirmative decision events in our empirical tests. The

average AD duty rate for each US case in our sample ranged from 4% to 274% with the mean of 80%,

while for EU cases, it was much lower and ranged from 7.5% to 90.6% with the mean of 34%. The

much lower average AD duty rate in the EU is consistent with the European Commission policy that

AD duties should not dramatically increase the price of products.

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4.2 Methodologyix

We used event study to examine the stock price response to an AD event surrounding the

event day (day 0 or t = 0). The daily stock return data obtained from the CSMAR Database were used

to estimate the market model:

Rit = αi + βiRmt + εit (1)

where Rit is the return for firm i on day t, Rmt is the market (including all A-shares in SSE and SZE)

return on day t, and εit is the residual. The estimation period was 140 days, from 150 trading days

before the event day to 11 days before, i.e., (-150, -11). The Scholes-Williams (1977) method was

applied in the estimation of β. We then computed the abnormal return for firm i on day t in the event

window surrounding the event day:

ARit = Rit − αi

− β

i

Rmt (2)

where αi

− β

i

Rmt is the benchmark return generated by using the estimated parameters α

i

and β

i

in equation (1).

CARit1,t2= ∑ ARit

t2t=t1

(3)

where CARit1,t2 is the cumulative abnormal returns of firm i during the event window from t1 to t2. The

cross-sectional t-statistic for CAR is given below:

(4)

In addition to testing the significance of the mean CAR, we also reported and tested the

significance of the median CAR using the Wilcoxon statistics to rule out the possible influence of

CAR outliers.

1

2

1 1

1

1 1[ ]

( 1)

M

jt

j

M M

jt jt

j j

CARM

t

CAR CARM M M

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Since the EU and US are 7–13 hours behind Beijing, we set the event day (t = 0) as the first

trading day in China after the AD petition or decision had been made.x We examined six windows for

each event: (-5, 5), (-3, 3), (-1, 1), (0, 1), (0, 3) and (0, 5).

The estimation window was a bit complicated as the petition day and decision days are not

very far apart. To avoid the problem of overlapping, we set the estimation period for approximately

140 trading days. For the petition day, the estimation period was (-150, -11). Since the preliminary

ITC decision day is only 45 days after the petition, we applied the same estimation window from the

petition to the preliminary ITC decision. There are at least 235 days between the preliminary and final

ITC decisions. However, there are two DoC decision days in between. We excluded the two periods (-

10, 10) surrounding the DoC preliminary and final decision days in the estimation period, but still

made the total number of days in the event window equal to 140. For example, the window can be

started from day -192 and end on day -11 but with 42 days surrounding the two DoC decisions omitted.

Similar methods were used to set the estimation period for EU preliminary and final decisions.

As hypothesized in Marsh (1998), we expected that filing an AD petition would have a

negative effect on the stock price of Chinese export-oriented firms, regardless of the outcome of the

petition, and an affirmative AD decision by the ITC or EU Commission at the end of the preliminary

and final investigations would also have negative effects on the stock price of Chinese export-oriented

firms.

4.3 Event Study Results

Table 5 presents the results for the EU in Panel A and the US in Panel B. Several observations

are worth noting. First, the petition event did not generate any significantly negative CAR for both EU

and US cases across all six event windows. This is surprising given the fact that 70–80% of the

petitions led to the imposition of protection measures. Second, the mean CARs were statistically

insignificant for all event windows surrounding the preliminary ITC ruling that the relevant domestic

industry was materially injured by imports from China. However, the EU initiated affirmative

preliminary decision does have a negative effect on stock prices for the (0, 1) window. The two-day

mean CAR was -0.9%, which significant at the 5% level. That is, the negative effect of the EU

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affirmative AD preliminary decision was concentrated in the two-day event window (0, 1) only. Third,

regarding the ITC’s final decision to impose AD duties, the mean CARs were about -1% and

statistically significantly across all windows. For the EU, the final decision to impose AD duties

generated negative CAR for Chinese firms. Again, the effect was concentrated in the short windows

surrounding the decision day. Both CAR (-1, 1) and CAR (0, 1) were -0.7% and significant at the 10%

and 5% levels, respectively. The median CAR and the associated Wilcoxon z-statistics were consistent

with the mean CAR tests.

(Insert Table 5 Here)

Overall, our event study results indicated that AD cases do have a negative effect on the stock

prices of Chinese export-oriented firms. However, Chinese investors seem to respond only when US

initiated AD duties are imposed. While investors also respond to the preliminary AD ruling for EU

cases, abnormal returns are concentrated in the days immediately surrounding the event day (-1, 1) and

particularly in the (0, 1) window.

4.4 Regression Analysis of CAR

We further completed a regression analysis of CARs to examine whether the stock return

response to AD news was different between SOEs and non-SOEs, over different sample periods or

different exchange rage regimes, and across the firms that received AD sanctions in the past three

years and those that did not. Since the stock price response to AD petitions and preliminary decisions

were largely insignificant, we focused our analysis on the CARs around EU and ITC final decisions.

The regression model was specified as follows:

CAR(t1,t2) = a + b*SOE + c*Multiple + d*post2005 + f*post2005*SOE + g*post2005*multiple + e

(6)

where CAR(t1,t2) is the mean cumulative abnormal return for the window from t1 to t2 of each firm;

SOE is a dummy that takes the value of 1 if a firm is controlled by the government, and zero otherwise;

Multiple is a dummy that takes the value of 1 if the firm received one or more AD investigations in the

previous three years, and zero otherwise; post2005 is another dummy that is set to 1 if the observation

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occurs in the period after July 2005, and zero otherwise. Post2005*SOE and post2005*multiple are

interactive dummies. If SOEs received more favorable treatment from the government after the AD

sanctions, the coefficient b should be significantly positive. If the firm has received AD measures

before, the new AD duty may make things even worse for the firm. Hence, the coefficient c is

expected to be significantly negative. If a firm received AD sanction after July 2005, the consequence

of the current AD sanction may be more serious for the affected firm as the RMB appreciation has

already made life more difficult for Chinese exporters. If this is the case, then the coefficient d should

be significantly negative. The interactive dummies post2005*SOE and post2005*Multiple were

included to examine if AD sanctions have a different effect on SOEs and firms previously sanctioned

with AD measures across the two exchange rate regimes. Following the logic that RMB appreciation

makes life more difficult for exporters, both coefficients f and g should be significantly negative.


The regression results of equation (6) are presented in Table 6. Surprisingly, the estimated

coefficients are unanimously insignificant except the coefficient for SOE in the CAR (0,3) regression,

which is negative and significant at the 10% level. The results seem to suggest that when facing AD

sanctions, SOEs are not perceived by investors to be in a better position than non-SOEs to deal with

the possible negative effect. This indicates that either the government does not give special favors to

SOEs when they face AD tariffs/duties or that the favor SOEs received from the government was not

enough to give them advantages over non-SOEs. Additionally, the CAR response does not differ

across the two exchange rate regimes. One possible explanation is the RMB appreciation effect has

been taken into consideration when the AD duty rate is determined by the EU Commission or the US

DoC. The indifferent CAR response to AD sanction news between the first-time recipient and

recurring recipients indicates that there is not a strong compounding effect across AD measures

against the same firm.

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5. LONG-TERM STOCK RETURN MOVEMENT AFTER AD MEASURES

5.1 Long Term Stock Returns

Next, we examined whether AD measures affect long-term stock performance as the full

effect of AD duties may reveal over time. We computed the buy-and-hold abnormal return (BHAR)

for AD affected firms up to three years after the imposition of AD measures.

BHAR𝑖𝑇 = ∏ (1 + 𝑅𝑖,𝑡) − ∏ (1 + 𝑅𝐵𝑒𝑛𝑐ℎ𝑚𝑎𝑟𝑘𝑖,𝑡)𝑇𝑡=0

𝑇𝑡=0 (7)

where BHARiT is the buy-and-hold abnormal return for firm i up to time T; Rit is the stock return for

firm i in month t; and RBenchmarki,t is the benchmark return for firm i in month t. Since we employed

monthly data, T extends up to 36 (or three years). We used two alternative benchmarks to compute

BHAR. The first is the A-share market return, the same as the market proxy used in the event study.

The second is the equal-weighted portfolio return of all listed firms producing unaffected HS-6 digit

products within the same HS-4 digit category in which the affected product belongs. This is similar to

the method used by Konings and Vandenbussche (2008) and Lu, Tao, and Zhang (2011) to form a

control group. There is a matched group of firms for each event, and the number of firms included in

the group varies across AD events. Out of 49 EU cases, no matched firm could be found for six cases.

For the remaining 43 cases, there were 106 AD affected firms and 272 matched firms.xi The number of

matched firms ranged from 2–36 for each case with a mean (median) of 6.36 (6). We found matched

firms for 50 out of the 55 US cases. There were 105 AD affected firms and 370 matched firms. The

number of matched firms for each AD event ranges from 2–38 with a mean (median) of 7.4 (5). We

dropped the cases for which no matched firms could be found. If AD duties have a long-term effect on

sanctioned firms, we expect that the BHARs will be negative in the years following the imposition of

AD measures.


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Table 7 presents the cross-sectional mean BHARs and associated t-statistics up to three years

after the imposition of AD duties. BHARs shown in Panel A are obtained using the market return as

the benchmark. It is clear that the BHAR is insignificantly different from zero for both EU and US

initiated cases up to three years after the imposition of AD duties.

Panel B reports the BHAR obtained by using the matched firms as the benchmark. The one-

year and two-year BHARs are still insignificantly different from zero for both EU and US cases.

However, the three-year BHAR is significant for both EU and US cases. BHAR is -10.58% for EU

cases, which is significant at the 10% level, while for US cases it is -8.86%, which is significant at the

5% level. Overall, the results indicate that AD affected firms do not underperform compared with the

overall market up to three years after the AD duties are imposed upon them, but their

underperformance compared with their peers shows up in the three-year BHAR. Hence, the AD

measures have a negative effect not only on the short-term CARs of AD affected firms but also on

their long-term BHARs when compared with their peers.

5.2 Regression Analysis of BHAR

We further examined whether BHAR is different between SOEs and non-SOEs, over different

sample periods or different exchange rate regimes, and across the firms that received AD sanctions in

the past three years and those that did not. The regression model is similar to the one used for the CAR

regression analysis:

BHARiT = a + b*SOE + c*Multiple + d*post2005 + f*post2005*SOE + g*post2005*multiple + e (8)

where BHARi is the buy-and-hold abnormal returns of each AD affected firm after the imposition of

AD duties. All other variables are defined the same as those in Equation (6). We only focus on the two

three-year BHARs relative to their peers, as all other BHARs shown in Table 7 are statistically

insignificant. Table 8 presents the regression results.


18

Similar to the regression analysis of CARs, the estimated coefficients for all independent

variables are statistically insignificant. The results indicate that BHARs are unaffected by a firm’s

SOE status, different exchange regimes, and whether a firm had previously received AD measures.

6. PROFITABILITY AND SUBSIDIES AFTER AD MEASURES

Li and Whalley (2010) found that AD duties have a negative effect on the profitability of

Chinese export firms. We examined the effect of AD duties on different profitability measures.

Specifically, we performed two regression analyses, (1) to compare the profitability and subsidies of

AD affected firms before and after the imposition of AD duties, and (2) to compare the change of

profitability and subsidies of AD affected firms with that of their peers before and after the imposition

of AD duties.

6.1 Changes in Profitability and Subsidies Before and After the Imposition of AD Duties

To compare the profitability of and subsidies given to the AD affected firms against their own

history, we used six yearly observations of profitability and subsidies for each AD affected firm; three

yearly observations before the filing of AD petitions and three yearly observations after the imposition

of AD duties. xii We used the following panel analysis model:

PPit(or subsidyit) = const + a*SOE + b*Afti + c*SOE*Afti + d*Exrateit + f*GDPit + eit (9)

where PPit is the profitability proxy of firm i in year t; Afti is a dummy set at 1 for firm i starting from

the year after the final AD decision and zero otherwise; SOE is a dummy set to 1 if the AD affected

firm is state-controlled. Exrate is the yearly average USD per RMB or EURO per RMB rate, GDP is

the yearly GDP growth rate to capture the time specific effect; eit is the residual for firm i in year t. To

control for firm fixed-effect, all the time series variables used in the regression except for dummies

were demeaned for each firm. While the constant captures the average profitability of non-SOE firms

before the imposition of AD duties, Afti measures the average AD effect on PP for non-SOE firms in

the years after the duty imposition. The SOE dummy captures the average profitability of SOE firms

19

relative to non-SOE firms before the imposition of AD duties, while the interactive term, SOE*Aft,

measures the effect of AD duties on SOEs relative to non-SOEs in the years after the imposition of

AD duties.

In total, we used six profitability measures and two subsidy measures. If AD duties have a

negative effect on profitability, the dummy Aft should be significantly negative. If the government

provides more subsidies to AD affected firms after the imposition of AD duties, then Aft should be

significantly positive. We first looked at the EBIT over total assets (EBIT/TA) to gauge if overall

earning power declines after the imposition of AD duties. We then looked at EBT over total assets

(EBT/TA); if EBT declines less than EBIT/TA, then we may infer that the firm pays less interest than

before and one possibility is that it pays a concessionary rate on its borrowings. We further examined

return on asset (ROA); if it declines less than EBT/TA, then it is likely that the firm gets some tax

rebate from the government. We also looked at alternative profitability measures, EBIT/Sales,

EBT/Sales, and return on sales (ROS). In addition, we constructed two government subsidy variables:

Subsidies/TA and Subsidies/Sales for each firm. We then tested whether firms receive more or less

subsidies after the imposition of AD duties. All these data were obtained from the CSMAR Database

except for the EURO/RMB rate, which was obtained from EUROSTAT’s EURO/RMB nominal

effective exchange rate (NEER). The subsidies we obtained from the database are the overall subsidies

a firm received from the government because there were no detailed classifications of subsidies in the

annual report of listed companies until 2008. The analysis is preliminary as interest and tax may be

affected by other factors during the sample period, and the subsidies may be given for reasons

unrelated to AD events. However, if the government wishes to subsidize firms after they are

sanctioned with AD duties, it is very likely that the subsidies were disguised in forms that are

unrelated to exporting to avoid further trade conflicts. Hence, the total amount of subsidies was

considered a reasonable proxy for our test. With our sample observations surrounding the AD event

and controls for firm fixed effect, exchange rate change, and GDP growth, our panel data analysis can

provide some indication of whether the Chinese government provides supports to help AD affected

firms, especially SOEs.

20

To avoid the confounding effect of multiple sanctions received by the same firm within the

comparison period, we included in our sample the firms that were sanctioned by AD duty only once

from three years before the AD investigation to three years after the imposition of AD duties. This

resulted in 65 firms for EU cases, of which 44 were SOEs and 21 were not. For US cases, we included

98 firms, of which 69 were SOEs and 29 were not.


Table 9 presents the estimation results of equation (9). For EU cases presented in Panel A,

there is a clear indication that profitability is negatively affected by AD duties. The estimated

coefficient for Aft is negative for all six profitability regressions and statistically significant at the 5%

level or better. The estimated coefficients of Aft for EBT/Asset and ROA regressions are -0.0272 and -

0.0354, respectively. They are similar or even more negative than the estimated coefficient of Aft in

the EBIT regression (-0.0297). Hence, there is no indication that the AD affected firms pay less

interest or taxes after they get AD sanctions. We also observed that the estimated coefficient of Aft for

EBT/Sales and ROS regressions is more negative than that for EBIT/Sales; the decrease in EBT/Sales

or ROS after the imposition of AD duties is on par or even more severe than that in EBIT/Sales. Of

course, such comparison without a formal test is difficult. However, a further look at the Aft estimates

for subsidy regressions shows that there was no significant increase in government subsidies to AD

affected firms, as they were all statistically insignificant. The estimated coefficients for both SOE and

Aft*SOE are statistically insignificant, indicating that there is no systematic differential in profitability

and subsidies between SOEs and Non-SOEs both before and after the imposition of AD duties.

The estimates for Exrate and GDP growth were statistically insignificant across all

profitability and subsidy regressions, which surprisingly indicates that the general economic condition

and exchange rate has no effect on the profitability of and subsidies to the AD affected firms.

Similarly, the results for US cases in Panel B show that profitability declined after the

imposition of AD duties for AD affected firms as the estimate of Aft was negative and statistically

significant in all profitability regressions. Again, there is no indication that EBT/Asset (EBT/Sales)

and ROA (ROS) decline less than EBIT/Asset (EBIT/Sales). In addition, the Aft estimate for subsidy

21

regressions is statistically insignificant. Hence, there is no evidence that the Chinese government

provides more subsidies for AD affected firms after the imposition of AD duties in general.

Conversely, the estimated coefficient for Aft*SOE is positive and statistically significant in the

Subsidy/Asset regression, showing some evidence that the government may provide more subsidies to

SOEs after the imposition of AD duties. However, the estimates for SOE and Aft*SOE were

statistically insignificant in all other regressions, indicating that there is no systematic difference in

response to AD duty imposition between SOEs and non-SOEs.

In contrast to the results in Panel A, the estimate for GDP growth was positive and statistically

significant in three out of six profitability regressions but negative and statistically significant in the

two subsidy regressions. This is consistent with the intuition that the profitability of AD affected firms

is positively while the subsidies are negatively associated with the overall economic condition.

Although the estimate for exchange rate was insignificant in all profitability regressions, it was

positive and statistically significant in the two subsidy regressions, indicating that a depreciation of

USD leads to an increase of government subsidies for the AD affected firms. This finding is also

consistent with common sense.

On the whole, the results in Table 9 suggest that AD duties have a negative effect on the

profitability of AD affected firms whether duties are imposed by the EU or the US. This is consistent

with the findings of Li and Whalley (2010). Although there is no evidence that the Chinese

government offers more subsidies to AD affected firms in general after the imposition of AD duties,

there is some weak evidence that the government provides more subsidies to SOEs after they are

sanctioned by AD duties. It is possible that the Chinese government refrained from giving more

subsidies to AD affected firms to prevent further trade protection reactions from the EU and the US.

There is also no evidence that SOEs can handle the AD duties better or worse than their private

counterparts.

6.2 Comparison of AD Affected Firms with Their Peers

We examined the effect of AD on the change in profitability and subsidies by comparing the

AD affected firms with their peers, which was similar to a difference-in-differences analysis. The AD

22

affected firms were the same as those used in the equation (9) regressions. The control firms were

identified in a similar way as the method we used to compute BHAR in section 5.2; all listed firms

producing unaffected HS-6 digit products within the same HS-4 digit category to which the affected

product belongs. We did not follow Lu, Tao, and Zhang to further predict which firms in this group

are more likely to be sanctioned because this would reduce our already small sample size, as we could

not find matched firms for all AD affected firms. Our EU sample only included 61 AD affected firms

and 145 matched firms, while the US sample included 84 AD affected firms and 169 matched firms.

The following model was used for our difference-in-differences analysis:

ΔPPit (Δsubsidyit) = Consti + a*ADSOEi + b*ADNonSOEi + c*ΔExratet + d*ΔGDPit + eit (10)

where ΔPPit is defined as the three-year average profitability (or subsidies) of firm i after the

imposition of AD duties minus the three-year profitability (or subsidies) of the same firm before the

AD investigation; ADSOEi is a dummy set to 1 for all AD affected firms that are SOEs, and zero

otherwise; similarly, ADNonSOEi is a dummy set to 1 for all AD affected firms that are non-SOEs,

and zero otherwise; ΔExrate and ΔGDP are the changes in average exchange rate and GDP growth

rate corresponding to each firm and they are used as controls in the regression. Similar to equation (9),

we used six profitability measures and two subsidy measures. If the AD affected SOE (or nonSOE)

firms performed worse than their peers (firms not affected by AD duties), the estimated ADSOE

(ADNonSOE) coefficient should be negative and statistically significant.


Panel A of Table 10 presents the regression results for EU cases. The constant is negative and

mostly significant for all profitability regressions but positive and significant for all subsidy

regressions, indicating a profitability decline and subsidy increase in general for all firms, whether AD

affected or not. However, there was only limited evidence that AD affected firms underperform

compared with their peers. The estimated coefficient for ADSOE was negative for all profitability

regressions but only significant for EBT/Asset regression, and the estimate was insignificant for the

23

two subsidy regressions. These results indicate that the SOE firms affected by the AD duties do not get

more subsidies relative to their controlled peers. Except for ΔEBT/Asset, SOEs generally did not

perform worse than their controlled peers either. For non-SOEs that were affected by AD duties, we

found more evidence of under-performance as the estimated coefficient of ADNonSOE was negative

and significant in both ΔEBT/Sales and ΔROS regressions. The estimate of ADNonSOEs in the two

subsidy regressions was not statistically significant. Overall, we found some weak evidence that AD

affected firms underperform compared with their controlled peers after the imposition of AD duties for

EU cases.

The results for US cases are presented in Panel B. Similar to what we found in Panel A, the

constant term was significantly negative in all six profitability regressions but positive for both

subsidy regressions; however, it was only statistically significant in the ΔSubsidies/Sales regression,

suggesting a profitability decline and subsidy increase in general for all firms. However, we found that

the SOEs neither underperform nor get more subsidies than their matched peers, as the estimated

coefficient of ADSOE was statistically insignificant in all profitability and subsidy regressions. On the

other hand, we found more evidence that non-SOE firms underperform compared with their matched

peers, as the estimated coefficient of ADNonSOE was negative and significant in three out of six

profitability regressions. In one of the two subsidy regressions, the estimated coefficient for

ADNonSOE was also significantly negative, indicating that non-SOEs get less subsidies than their

matched peers after the imposition of AD duties.

The estimated coefficient of ΔGDP was positive and significant in some profitability

regressions for both EU and US cases, indicating that profitability change is positively related to the

change in GDP growth rate in general, which is intuitive. However, the estimate was significantly

positive in subsidy regressions for EU cases but significantly negative for US cases. While the

negative estimate for subsidy regressions is consistent with the results observed in Panel B of Table 9,

which show that a higher economic growth rate leads to lower subsidies given to firms in general, the

positive estimate for EU cases suggests the opposite, which is hard to explain.

24

The estimated coefficient of ΔExrate was positive and significant in two EU regressions and

one US subsidy regression, indicating that RMB appreciation is associated with an increase in

government subsidies to the firms. This is also consistent with the Exrate estimate in Panel B of Table

9. However, the positive and significant estimate of ΔExrate in most profitability regressions in EU

and US cases suggests that the appreciation of RMB is associated with high profitability for Chinese

firms in general, which is inconsistent with the previous findings that indicated exchange rate does not

affect the profitability of AD affected firms.

In summary, there is some evidence that AD affected firms underperform compared with their

matched peers. However, the underperformance seems more concentrated in AD affected non-SOEs.

In addition, there is some evidence that these non-SOEs receive fewer subsidies from the government

after the imposition of AD duties.

7. CONCLUDING REMARKS

During our sample period, China was the largest exporter and the number one recipient of AD

measures in the world. The AD cases initiated in the US and EU against Chinese firms offered a good

setting to examine the effect of AD investigations and measures on the export-oriented firms. Previous

authors have examined the AD effect on Chinese firms in terms of productivity, employment, number

of exporting firms exiting the industry, profitability, and other variables. We extended the literature by

examining how AD investigations and decisions in the EU and US affect the stock price of relevant

Chinese firms. Our empirical analyses showed that the final affirmative AD decisions in the EU and

US have a negative effect on their stock prices. The three-day CARs surrounding the EU and ITC final

affirmative decisions are -0.7% and -1%, respectively. There is also a -0.9% two-day CAR for EU

preliminary affirmative EU decisions. While the three-year buy-and-hold return of AD affected firms

did not underperform compared with the overall market return, it underperformed compared with

matched peers by 10.56% and 8.86% for EU and US cases, respectively. These results indicate that

investors expect the affirmative AD decisions and measures to negatively affect the future prospects of

these firms, and thus they are considered value relevant. However, short-term CARs and long-term

25

BHARs do not differ based on the SOE and non-SOE status of the firm, across different exchange rate

regimes, and over whether the firm has received AD measures more than once. This seems to indicate

that investors do not expect the government to give substantial assistance to SOEs after AD duties are

imposed, or that the assistance may not be useful to help SOEs better handle the AD effect than non-

SOEs. It is possible that the effect of RMB appreciation is endogenized in the AD decisions when

setting the duty rate, and it is also possible that the RMB appreciation effect has been expected by

investors. Hence, the CAR and BHAR are not affected by the change in exchange rate regime. This

further suggests that the marginal effect of additional AD measures may not be larger and may well be

expected.

We further extended the literature by examining the profitability of AD affected firms together

with the subsidies they have received from the government. Our regression analysis using AD affected

firms indicated that the profitability of these firms tends to drop after the imposition of AD duties for

both EU and US cases. This is consistent with the findings by Li and Whalley (2010). However, our

further regression analysis using both AD affected firms and their matched peers showed that the drop

in profitability was not unique for AD affected firms, but also appeared in matched peers. In fact, this

result is consistent with the finding by Li and Whalley (2010), as their industry portfolio based on two-

digital NEIC classification may well include both AD affected firms and the matched peers in our

sample. However, we did find some evidence that AD affected non-SOE firms tend to perform worse

and get less subsidies than their matched peers after the imposition of AD duties, especially for firms

involved in the US cases. In contrast, AD affected SOEs generally do not perform worse or get fewer

government subsidies than their matched peers. This is also consistent with the finding by Li and

Whalley (2010) that SOEs are affected less than non-SOEs by AD duties. Our analysis of government

subsidies indicated no evidence that the government gives more subsidies to AD affected firms. In fact,

the government tends to give less subsidies to non-SOE firms after the imposition of AD duties. This

is understandable if an increase in state subsidies may further escalate trade conflicts. This also shows

that the government may discriminate against non-SOEs. In general, we did not find that US and EU

initiated AD measures generated systematic differential effects on Chinese export firms.

26

Overall, the negative stock price response and non-negative profitability response of AD

affected firms relative to their matched peers suggests that investors expect AD affected firms to

perform better if no AD duties are imposed. Our findings on stock return response complements Bown

and Crowley (2010), who found that the effect of US and EU initiated AD duties on Chinese firms is

primarily manifested via trade diversion rather than trade depression, and the study by Lu, Tao, and

Zhang (2012), which found that the AD effect on Chinese firms is mainly in terms of the number of

firms exiting the US market.

Our study has implications for researchers, trade negotiators, and investors. It can help

researchers use stock price changes to quantify the effect of AD measures on Chinese firms. It

provides useful information regarding Chinese government subsidies for trade negotiators. It also

shows the value relevance of AD news in the stock market, which is meaningful to general investors.

However, there are two caveats. First, our study only examined listed firms. The effect on non-listed

firms may be different, as they are usually small and more vulnerable. Second, as mentioned in

Section 5, the subsidies used for our study were the lump sum of all subsidy types, which may not be

closely related to export assistance.

27

REFERENCES

Brander, A. 1991. Election polls, free trade, and the stock market: Evidence from the 1988 Canadian

general election. Canadian Journal of Economics, 24: 599-620.

Brown, S. J., & Warner, J. B. 1985. Using daily stock returns: The case of event studies. Journal of

Financial Economics, 14(1): 3-31.

Bown, C. P., & Crowley, M. A. 2010. China’s export growth and the China safeguard: Threats to the

world trading system. Canadian Journal of Economics/Revue canadienne d'économique, 43(4):

1353-1388.

Capital Trade Incorporated. 2008. An assessment of China’s subsidies to strategic and heavyweight

industries. Report submitted to US-China Economic and Security Review Committee.

Chandra, P., & Long, C. 2013. Anti-dumping duties and their impact on exporters: Firm level

evidence from China. World Development, 51(5): 169-186.

De Melo, J., & Tarr, D. 1992. A general equilibrium analysis of U.S. foreign trade policy. Cambridge,

MA: MIT Press.

Desai, M., & Hines, J. 2008. Market reactions to export subsidies. Journal of International Economics,

74(2): 459-474.

Eckaus, R. S. 2006. China’s exports, subsidies to state owned enterprises and the WTO. China

Economic Review, 17: 1-13.

Hartigan, J. C., Perry, P. R., & Kamma, S. 1986. The value of administered protection: A capital

market approach. Review of Economics and Statistics, 68(4): 610-17.

Hartigan, J. C., Kamma, S., & Perry, P. R. 1989. The injury determination category and the value of

relief from dumping. Review of Economics and Statistics, 71(1): 183-86.

Hughes, J. S., Lenway, S., & Rayburn, J. 1997. Stock price effects of U.S. trade policy responses to

Japanese trading practices in semi-conductors. Canadian Journal of Economics, 30(4): 922-42.

28

Irwin, D., & Klenow, P. 1996. High-Tech R&D subsidies: Estimating the effects of sametech. Journal

of International Economics, 40(3-4): 323-344.

Konings, J., & Vandenbussche, H. 2008. Heterogeneous responses of firms to trade protection.

Journal of International Economics, 76: 371-383.

Lee, E., Walker, M., & Zeng, C. 2014. Do Chinese government subsidies affect firm value.

Accounting, Organizations and Society, 39: 149-169.

Li, C., & Whalley, J. 2010. Chinese firm and industry reactions to antidumping initiations and

measures. NBER Working Paper, 16446.

Lu, Y., Tao, Z., & Zhang, Y. 2013. How exporters respond to antidumping investigations, Journal of

International Economics, 91: 290-300.

Marsh, S. J. 1998. Creating barriers for foreign competitions: A study of the impact of anti-dumping

actions on the performance of U.S. firms. Strategic Management Journal, 19: 25-37.

Mahdavi, M., & Bhagwati, A. 1994. Stock market data and trade policy: Dumping and the

semiconductor industry. International Trade Journal, 8(2): 207-21.

Melvin, M., & Sun, Q. 1997. U.S. protectionist policy and stock prices of U.S. import-competing and

Korean and Taiwanese export-oriented firms. Pacific-Basin Finance Journal, 5: 25-38.

Moeller, S. B., Schlingemann, F. P., & Stulz, R. M. 2004. Firm size and the gains from acquisitions.

Journal of Financial Economics, 73(2): 201-228.

Parsons, C. 2005. The effect of the semiconductor trade agreement on Japanese firms. The Singapore

Economic Review, 50(1): 117-129.

Pierce, J. R. 2011. Plant-level responses to antidumping duties: Evidence from U.S. manufacturers.

Journal of International Economics, 85: 222-233.

Rehbein, K., & Starks, L. T. 1995. Changes in U.S. trade policies: The wealth effects on Japanese steel

firms. Japan and the World Economy, 7: 309-327.

29

Scholes, M., & Williams, J. 1977. Estimating betas from nonsynchronous data. Journal of Financial

Economics, 5(3): 309-327.

30

Table 1. China’s Bilateral Trading Statistics with the US and EU ($ in billion) (1995–2012)

This table presents China’s bilateral trading statistics with the US and EU.

Total Trade

with US Trade Surplus with the US Total Trade with EU Trade Surplus with EU

1995 40.83 8.59 40.34 -2.16

1996 42.84 10.53 39.70 -0.04

1997 48.99 16.40 43.00 4.62

1998 54.94 21.01 48.86 7.43

1999 61.50 22.53 55.78 4.83

2000 74.51 29.78 69.04 7.34

2001 80.52 28.12 76.60 5.33

2002 97.19 42.73 86.74 9.63

2003 126.39 58.63 125.20 18.96

2004 169.63 80.32 173.75 35.40

2005 211.67 114.20 217.30 70.20

2006 262.74 144.29 272.28 91.57

2007 302.62 162.90 356.27 134.19

2008 333.82 170.83 425.82 160.09

2009 298.37 143.44 364.24 108.45

2010 385.44 181.31 479.83 142.86

2011 446.71 202.42 567.33 144.86

2012 484.88 219.12 546.64 121.59

Source: Wind database

31

Table 2. Antidumping Investigations and Measures Against China

This table presents the total number of antidumping investigations initiated against China, the total

number of antidumping measures imposed on China, and their percentages of the world total.

Year

Initiations

Against

China

Total

Initiations

China/World

(%)

Measures

Against

China

Total

Measures

China/World

(%)

1995 20 157 12.74 26 119 21.85

1996 43 226 19.03 16 92 17.39

1997 33 246 13.41 33 127 25.98

1998 28 266 10.53 24 181 13.26

1999 42 358 11.73 21 190 11.05

2000 44 298 14.77 30 237 12.66

2001 55 372 14.78 32 171 18.71

2002 51 315 16.19 36 218 16.51

2003 53 234 22.65 41 224 18.30

2004 49 220 22.27 44 154 28.57

2005 56 201 27.86 42 138 30.43

2006 72 204 35.29 38 142 26.76

2007 62 165 37.58 48 108 44.44

2008 76 213 35.68 53 139 38.13

2009 77 209 36.84 56 141 39.72

2010 44 172 25.58 53 123 43.09

2011 51 166 30.72 37 98 37.76

2012 60 208 28.85 34 117 29.06

Total 916 4230 21.65 664 2719 24.42

Source: www.wto.org

http://www.wto.org/

32

Table 3. Top Five Antidumping Users Against China (1995–2012)

This table presents the number of antidumping initiations and measures against China by the top five

initiating countries.

Country AD initiations Country AD measures

1 India 154 India 126

2 US 112 US 93

3 EU 111 EU 79

4 Argentina 89 Argentina 67

5 Brazil 62 Turkey 57

All 528 All 422

Source: www.wto.org

http://www.wto.org/

33

Table 4. Events and Sample Sizes (1995–2012)

This table presents the number of various types of US and EU initiated AD events and the corresponding number of firms affected by those events in Panels

A and B, respectively. In addition, the sample firms are further grouped by SOEs and non-SOEs, by events that occurred before July 2005 and after, and by

firms that received AD petitions in the past three years and those that had not.

Panel A: EU Panel B: US

Petition Preliminary

(+)

Final

(+)

Final

(-)

ITC Petition ITC Preliminary

(+)

ITC Final

(+)

ITC Final

(-)

Number of Events

64 42 49 15 68 64 55 8

Number of Firms

Whole Sample

135 96 112 23 187 175 150 27

SOE

98 68 78 20 142 134 110 23

Non-SOE

37 28 34 3 45 41 40 4

Before July 2005 37 25 33 4 84 75 56 15

After July 2005

98 71 79 19 103 100 94 12

First Time in Past Three Years 87 59 70 17 125 114 105 13

More Than Once in Past Three

Years

48 37 42 6 62 61 45 14

Note: For the subgroups “first time in past 3 years” and “more than once in past 3 years,” the sample period is from 1998–2012. In addition, there are 64 ITC

preliminary decision cases. However, we cannot find the exact decision date for one case.

34

Table 5. Event Study Results

This table reports the mean and median cumulative abnormal returns (CARs) associated with various AD event windows in the EU (Panel A) and the US

(Panel B). Events for the EU are AD petition and the Commission’s preliminary and final decisions, while events for the US are AD petition and ITC

preliminary and final decisions. The t- and Wilcoxon Z- statistics are listed in parentheses under the mean and median CARs, respectively.

Panel A: EU Initiated AD Events

(-1, 1) (-3, 3) (-5, 5) (0, 1) (0, 3) (0, 5)

Obs Mean Median Mean Median Mean Median Mean Median Mean Median Mean Median

Petition 135 0.002 0.002 -0.005 -0.006 -0.008 0.000 0.000 -0.001 -0.005 -0.002 -0.005 -0.003

(0.50) (0.18) (-0.99) (-1.40) (-1.16) (-1.00) (0.10) (-0.76) (-1.18) (-1.55) (-1.11) (-1.35)

Preliminary 96

-0.006 -0.002 -0.012 -0.013 -0.002 -0.002 -0.009** -0.008*** -0.005 -0.004 0.004 0.001

(-1.38) (-1.21) -1.04 (-0.72) -0.29 (-0.18) (-2.37) (-2.82) (-0.95) (-1.34) 0.65 (0.57)

Final 112

-0.007* -0.007*

(-1.70)

-0.002 0.000

(-0.67)

-0.001 0.003

(-0.44)

-0.007** -0.008*

(-1.86)

-0.003 -0.012

(-1.04

-0.007 -0.008

(-1.33) (-1.75) (-0.26) (-0.12) (-1.99) (-0.66) (-1.11)

35

Panel B: US Initiated AD Events

(-1, 1) (-3, 3) (-5, 5) (0, 1) (0, 3) (0, 5)

Obs Mean Median Mean Median Mean Median Mean Median Mean Median Mean Median

Petition 187 0.003 -0.002 0.002 0.003 0.006 0.002 0.002 0.001 0.001 -0.003 0.002 -0.001

(1.18) (-0.44) (0.35) (0.30) (0.98) (0.72) (0.84) (0.27) (0.17) (-0.44) (0.61) (-0.07)

Preliminary 175 -0.002 -0.003 0.009 0.007 0.005 -0.002 -0.001 -0.002 0.003 0.001 0.006 -0.001

(-0.51) (-0.66) (1.45) (1.22) (0.72) (-0.01) (-0.37) (-0.24) (0.54) (0.21) (1.04) (0.53)

Final 150 -0.010*** -0.010*** -0.011** -0.012*** -0.011* -0.018*** -0.009*** -0.009*** -0.012*** -0.011*** -0.012*** -0.013***

(-3.21) (-3.96) (-2.27) (-2.96) (-1.71) (-2.73) (-3.51) (-3.73) (-3.24) (-4.00) (-2.8) (-3.30)

Note: *, **, and *** denote statistical significance at the 10%, 5%, and 1% levels, respectively.

36

Table 6. Regression Analysis of CARs

This table reports the cross-section regression analysis for CARs of the final AD decision events in the EU and US. The regression model was specified as

follows:

CAR(t1,t2) = a + b*SOE + c*Multiple + d*post2005 + f*post2005*SOE + g*post2005*multiple + e

where CAR(t1,t2) is the cumulative return for the window from t1 to t2 of each firm; SOE is a dummy that takes the value 1 if the firm is an SOE and zero

otherwise; Multiple is a dummy that takes the value 1 if the firm has received an AD investigation in the previous three years and zero otherwise; post2005 is

another dummy set to 1 if the observation is in the period before July 2005 and zero otherwise. Post2005*SOE and post2005*multiple are interactive

dummies; t-statistics are listed in parentheses.

37

Panel A: EU Final Decision

CAR (-1, 1) CAR (-3, 3) CAR (0, 1) CAR (0, 3)

SOE -0.0113 -0.0331 -0.0176 -0.0459*

(-0.79) (-1.13) (-1.46) (-1.75)

Multiple 0.0028 0.0105 0.0054 0.0166

(0.16) (0.34) (0.30) (0.58)

Post2005 -0.0079 -0.0140 -0.0007 -0.0236

(-0.54) (-0.51) (-0.06) (-0.97)

Post2005*SOE 0.0151 0.0465 0.0153 0.0466

(0.89) (1.41) (1.05) (1.63)

Post2005*multiple -0.0113 -0.0229 -0.0094 -0.0120

(-0.57) (-0.67) (-0.48) (-0.39)

Const. 0.0020 0.0127 -0.0005 0.0213

(0.16) (0.53) (-0.05) (0.97)

N 112 112 112 112

R2 0.085 0.145 0.089 0.135

38

Panel B: US ITC Final Decision

CAR (-1, 1) CAR (-3, 3) CAR (0, 1) CAR (0, 3)

SOE -0.0001 0.0010 -0.0030 -0.0044

(-0.02) (0.09) (-0.49) (-0.41)

Multiple 0.0079 0.0097 0.0021 0.0039

(1.20) (0.83) (0.40) (0.41)

Post2005 0.0006 -0.0021 -0.0033 -0.0095

(0.06) (-0.16) (-0.41) (-0.75)

Post2005*SOE -0.0104 -0.0079 -0.0053 -0.0058

(-0.93) (-0.45) (-0.55) (-0.39)

Post2005*multiple 0.0082 0.0232 0.0009 0.0014

(0.60) (1.09) (0.08) (0.09)

Const. -0.0104* -0.0138 -0.0041 -0.0011

(-1.70) (-1.58) (-0.74) (-0.11)

N 148 148 148 148

R2 0.037 0.043 0.018 0.028

Note: *denotes statistical significance at the 10% level.

39

Table 7. Long-Term Buy-and-Hold Abnormal Returns

This table reports the buy-and-hold abnormal returns (BHAR) up to three years for firms with imposed AD duties. BHAR was computed using the following

formula:

BHAR𝑖𝑇 = ∏(1 + 𝑅𝑖,𝑡) − ∏(1 + 𝑅𝐵𝑒𝑛𝑐ℎ𝑚𝑎𝑟𝑘,𝑡)

𝑇

𝑡=1

𝑇

𝑡=1

where BHARit is the buy-and-hold return for firm i up to month T, Rit is the return for firm i in month t, RBenchmark,t is the benchmark return in month t. We used

two benchmarks in the test. First, the A-share market return, and second, the average return of matched firms corresponding to each affirmative AD final

decision. Below, we report the mean cross-firm BHAR for T = 12, 24, and 36 months (or 1–3 years); t-statistics are listed in parentheses.

Panel A: BHAR using market return as the benchmark

EU (112 firms)

One-year Two-year Three-year

Mean 0.0165 0.0124 0.0041

T-value (1.49) (1.49) (0.34)

US (150 firms)


Mean 0.0014 -0.0085 0.0044

T-value (0.17) (-0.64) (0.58)

40

Panel B: BHAR using matched firms as the benchmark (the matched samples contain 206 and 257 firms for EU and US cases, respectively)

EU (106 firms)


Mean -0.0527 -0.0706 -0.1058*

T-value (-1.53) (-1.03) (-1.85)

US (135 firms)


Mean -0.0206 -0.0130 -0.0886**

T-value (-0.58) (-0.35) (-2.73)


41

Table 8. Regression Analysis of BHARs

This table reports the cross-section regression analysis for BHARs related to the final affirmative AD decision events in the EU and US. The regression model

was specified as follows:

BHARiT = a + b*SOE + c*Multiple + d*post2005 + f*post2005*SOE + g*post2005*multiple + e

where BHARi is the three-year buy-and-hold abnormal return of each firm after the AD duty was imposed and it is computed by using matched firms as the

benchmark; SOE is a dummy that takes the value 1 if the firm is an SOE and zero otherwise; Multiple is a dummy that takes the value 1 if the firm has

received an AD investigation in the previous three years and zero otherwise; post2005 is another dummy set to 1 if the observation occurs in the period before

July 2005 and zero otherwise. Post2005*SOE and post2005*multiple are interactive dummies; t-statistics are listed in parentheses.

42

BHAR (Using matched firms as the benchmark)

EU Cases US Cases

Three-year Three-year

SOE 0.0233 -0.1456

(0.13) (-0.68)

Multiple 0.0336 0.1513

(0.13) (0.90)

Post2005 -0.0060 0.1326

(-0.04) (0.71)

Post2005*SOE 0.0355 0.1689

(0.18) (0.72)

Post2005*Multiple -0.1102 -0.2296

(-0.40) (-1.23)

Cons. -0.1249 -0.1292

(-1.01) (-0.78)

N 67 117

R2 0.005 0.075

43

Table 9. Comparison of Profitability and Subsidies Before and After the Imposition of AD Duties

This table reports the panel data analysis results for the profitability and subsidies of AD affected firms for three years before the AD investigation and three

years after the imposition of AD duties using the following model:

PPit(or subsidyit) = const + aSOE𝑖 + bSOE𝑖 ∗ Aft𝑖 + cAft𝑖 + d ∗ Exratet + f ∗ GDPt + eit

where PPit is the profitability proxy of firm i in year t; Afti is a dummy set to 1 for firm i for three years after the imposition of AD duties, and zero otherwise;

SOE is a dummy that takes the value 1 if the firm is an SOE and zero otherwise; Exrate is the average yearly USD/RMB or EURO/RMB exchange rate; GDP

is the yearly GDP growth rate to capture the time specific effect; eit is the residual for firm i in year t. All variables except for dummies are demeaned to

control for the firm fixed effect; t-statistics are listed in parentheses.

44

Panel A：EU Cases

EBIT/Asset EBT/Asset ROA Subsidy/Asset EBIT/Sales EBT/Sales ROS Subsidy/Sales

SOE 0.0052 0.0086 0.0056 -0.0006 0.0023 0.0040 0.0011 -0.0001

(0.58) (1.07) (0.74) (-0.69) (0.17) (0.25) (0.08) (-0.06)

SOE*Aft -0.0098 -0.0176 -0.0106 0.0014 -0.0074 -0.0112 -0.0056 0.0002

(-0.57) (-1.22) (-0.67) (1.07) (-0.24) (-0.37) (-0.19) (0.06)

Aft -0.0297** -0.0272** -0.0354*** 0.0009 -0.0553** -0.0593** -0.0640*** 0.0020

(-2.41) (-2.53) (-3.08) (0.73) (-2.19) (-2.54) (-2.73) (0.74)

GDP growth 0.0009 0.0002 0.0010 0.0001 -0.0004 -0.0016 -0.0005 0.0000

(0.80) (0.13) (0.83) (0.87) (-0.23) (-0.63) (-0.31) (0.12)

Exrate 0.0005 0.0007 0.0008 0.0000 0.0007 0.0007 0.0008 0.0001

(1.11) (1.32) (1.62) (0.86) (0.84) (0.73) (0.88) (1.26)

Const. -0.0610 -0.0631 -0.0858 -0.0052 -0.0489 -0.0266 -0.0490 -0.0113

(-0.91) (-0.86) (-1.29) (-1.04) (-0.43) (-0.20) (-0.42) (-1.29)

N 374 328 374 362 374 328 374 362

R2 0.044 0.082 0.068 0.036 0.047 0.063 0.059 0.028

45

Panel B: US Cases

EBIT/Asset EBT/Asset ROA Subsidy/Asset EBIT/Sales EBT/Sales ROS Subsidy/Sales

SOE -0.0037 -0.0078 -0.0053 -0.0006 -0.0094 -0.0169 -0.0156 0.0000

(-0.71) (-1.34) (-1.05) (-1.44) (-0.73) (-1.04) (-1.16) (0.01)

SOE*Aft 0.0074 0.0159 0.0111 0.0017*** 0.0245 0.0418 0.0373 0.0010

(0.83) (1.56) (1.31) (2.99) (1.05) (1.45) (1.55) (0.69)

Aft -0.0175** -0.0288*** -0.0209*** -0.0004 -0.0580** -0.0796*** -0.0682*** 0.0010

(-2.12) (-3.04) (-2.64) (-0.77) (-2.54) (-2.86) (-2.92) (0.81)

GDP growth 0.0012*** 0.0014*** 0.0009** -0.0001*** 0.0009 0.0013 0.0011 -0.0003***

(3.14) (2.87) (2.52) (-3.43) (1.05) (0.99) (1.24) (-4.43)

Exrate -0.0016 -0.0018 -0.0013 0.0004*** 0.0004 0.0002 -0.0002 0.0009***

(-0.93) (-0.94) (-0.77) (3.72) (0.09) (0.04) (-0.03) (3.14)

Const. 0.0127 0.0172 0.0147 -0.0041*** 0.0066 0.0133 0.0171 -0.0079**

(0.55) (0.68) (0.65) (-2.60) (0.10) (0.18) (0.27) (-2.08)

N 557 478 563 534 557 478 563 534

R2 0.046 0.072 0.045 0.108 0.039 0.051 0.045 0.097


46

Table 10. Comparison of AD Affected Firms with Their Peers

This table presents the comparison of changes in profitability and subsidies of AD affected firms with their matched peers using the following regression

model:

ΔPPi (Δsubsidyi) = Consti + bSOEi * ADi + cNONSOEi * ADi + d* ΔExratei + f * ΔGDPi + ei

where ΔPPit is defined as the three-year average profitability of firm i after the imposition of AD duties minus the three-year average profitability of the same

firm before the AD investigation; ADi is a dummy set to 1 for all AD affected firms, and zero otherwise; SOE is a dummy that takes the value 1 if the firm is

an SOE and zero otherwise; NONSOE is a dummy that takes the value 1 if the firm is not an SOE and zero otherwise; ΔExrate and ΔGDP are the changes in

average exchange rate (USD/RMB or EURO/RMB) and GDP growth rate corresponding to each firm, used as controls in the regression; ei is the residual for

firm i. Panel A reports the regression results for EU cases, while Panel B reports results for US cases; t-statistics are listed in parentheses.

47

Panel A：EU Cases

ΔEBIT/Asset ΔEBT/Asset ΔROA ΔSubsidy/Asset ΔEEBIT/Sales ΔEBT/Sales ΔROS ΔSubsidy/Sales

SOE*AD -0.0033 -0.0237* -0.0085 0.0010 -0.0133 -0.0394 -0.0191 -0.0000

(-0.26) (-1.93) (-0.85) (1.05) (-0.49) (-1.35) (-0.73) (-0.01)

NONSOE*AD -0.0051 -0.0170 -0.0158 -0.0003 -0.0282 -0.0566** -0.0474* -0.0011

(-0.32) (-1.05) (-1.08) (-0.19) (-1.30) (-1.99) (-1.89) (-0.26)

ΔGDP growth 0.0034** -0.0029 0.0024** 0.0003*** 0.0027 -0.0028 0.0018 0.0005***

(2.36) (-0.68) (1.98) (3.45) (0.95) (-0.38) (0.60) (3.55)

ΔExrate 0.0009* -0.0008 0.0009** 0.0002*** 0.0018* 0.0002 0.0017* 0.0003***

(1.77) (-0.64) (1.99) (4.16) (1.89) (0.11) (1.75) (4.39)

Const. -0.0243*** -0.0088 -0.0229*** 0.0009* -0.0364*** -0.0147 -0.0360** 0.0018*

(-3.66) (-1.13) (-3.96) (1.97) (-2.71) (-0.89) (-2.54) (1.82)

N 206 170 206 206 206 170 206 206

R2 0.041 0.027 0.029 0.088 0.025 0.042 0.035 0.094

Panel B：US Cases

ΔEBIT/Asset ΔEBT/Asset ΔROA ΔSubsidy/Asset ΔEEBIT/Sales ΔEBT/Sales ΔROS ΔSubsidy/Sales

SOE*AD 0.0136 0.0070 0.0073 0.0004 -0.0036 -0.0030 -0.0092 0.0002

(1.40) (0.61) (0.79) (0.48) (-0.18) (-0.11) (-0.44) (0.11)

NONSOE*AD -0.0107 -0.0264* -0.0177 -0.0013* -0.0395 -0.0670** -0.0570* -0.0012

(-0.77) (-1.67) (-1.26) (-1.70) (-1.46) (-1.99) (-1.89) (-0.49)

ΔGDP growth 0.0017** 0.0020 0.0013* -0.0002*** 0.0018 0.0019 0.0021 -0.0005***

(2.09) (1.57) (1.83) (-2.81) (0.95) (0.69) (1.07) (-3.14)

ΔExrate 0.0125** 0.0153** 0.0120** 0.0007* 0.0268** 0.0369** 0.0294** -0.0003

(2.38) (2.03) (2.49) (1.73) (2.34) (2.38) (2.48) (-0.31)

Const. -0.0454*** -0.0478*** -0.0385*** 0.0009 -0.0742*** -0.0965*** -0.0708*** 0.0049**

(-4.25) (-3.34) (-4.11) (1.12) (-3.11) (-3.09) (-2.91) (2.38)

N 253 212 253 253 253 212 253 253

R2 0.036 0.045 0.036 0.089 0.042 0.070 0.057 0.077

48


i Although in terms of the number, India is the champion in using AD litigations against Chinese exporters during the period from 1995-2012 while the US and the EU ranked

second and third, India’s total trading value with China is much smaller than the Sino-US and Sino-EU bilateral trading values. In fact, Chinese firms have never responded to

any of the AD investigations initiated in India. ii For the past 10 years, exporting is about 30% of China’s GDP on average. iii Section 3 provides a literature review. iv Firms in the US can also file a countervailing duty petition if they think imported goods are subsidized by the foreign government. The procedure is similar to that of AD

cases. However, the countervailing duty was considered not applicable to non-market economies before 2007. There have been about 20 countervailing cases against China

since 2007. v Quantitative measures such as voluntary export restrictions (VER) can benefit both protection seekers and foreign exporters due to the price hike resulting from the VER (De

Melo & Tarr (1992). vi There are some slight discrepancies between WTO and GAD statistics. WTO statistics only provide general information regarding the number of AD cases without

providing concrete data for each AD case. Therefore, we obtain all our AD cases from GAD, which is also frequently used in the recent studies. vii Many cases only affected non-listed companies. viii If a firm is involved in two AD cases, then it will be counted twice or as two firms. Unless otherwise mentioned, this method of counting is used throughout the paper. ix For details please refer to Brown and Warner (1985) and Moeller et al. (2004). x We have randomly checked a few cases and found the AD news often appeared in Chinese news media or company websites one or two days after their release in the EU or

US. xi Some firms are included in the matched sample for several AD events. If a firm is included in the matched sample for two events, we will count them as two firms. The

same holds for the AD affected firms. xii For firms sanctioned in 2011 and 2012, we have fewer than three years of post-sanction data. Some firms also have fewer than three years before investigation data.

abstract we examine how the us and eu antidumping (ad...

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