tariff liberalisation and dumping 3

The International Trade Journal, 26:418, 2012Copyright Taylor & Francis Group, LLCISSN: 0885-3908 print/1521-0545 onlineDOI: 10.1080/08853908.2012.631866

Tariff Liberalization and the Riseof Anti-dumping Use: Empirical Evidence

from Across World Regions

SASATRA SUDSAWASDSchool of Development Economics, National Institute of Development Administration (NIDA),

Bangkok, Thailand

The relationship between tariff policy and anti-dumping use isempirically examined. Using a panel dataset of 56 countries overthe period of 19952007, the effects of tariff liberalization onanti-dumping use are found to vary across world regions. ForEuropean countries, as well as developed North American andLatin American countries, a lower tariff rate appears to inducemore use of anti-dumping measures, which emerge as a protectiontool among trade liberalization regimes. In contrast, a reduction ina tariff rate leads to lower anti-dumping use in developing NorthAmerican and Latin American countries and in developed Asian,African, and Middle Eastern countries. In terms of initiating antidumping action, developed countries are likely to be more sensitivethan developing countries to tariff policy change in most regions ofthe world.

KEYWORDS anti-dumping, tariff liberalization, world regions

I. INTRODUCTION

The World Trade Organization (WTO) has succeeded in reducing tariff bar-riers among member countries, especially in regards to the use of importtariffs on merchandise trade. Due to this success, many countries haverapidly turned to other forms of non-tariff measures (NTMs) to protect theirimport-competing sectors. Industrial nations were found to rely heavily onthe use of NTMs to regulate trade flows (Clark 1992). The most widespread

Address correspondence to Sasatra Sudsawasd, School of Development Economics,National Institute of Development Administration (NIDA), 118 Seri Thai Road, Bangkok 10240,Thailand. E-mail: [email protected]

4

Tariff Liberalization and the Rise of Anti-dumping 5

type of protection is anti-dumping measures. Since 1980, there have beenmore complaints under the anti-dumping statute than under all other tradelaws combined (Blonigen and Prusa 2003), and the number of anti-dumpinginvestigation filings has increased substantially.1 Hence, the rise of anti-dumping use can be partly regarded as an indication of tariff reductionprocess success.

The patterns of anti-dumping use changed dramatically over the last twodecades. In the early 1980s, only eight countries filed anti-dumping actions,in which more than 97% of the filings were from the major four coun-tries: Australia, Canada, the EU, and the United States.2 Since then, there hasbeen an unprecedented rise in anti-dumping usage in other countries aroundthe world, especially among developing countries. As calculated by Baruah(2007), more than 60% of total anti-dumping disputes in 2003 were initiatedby developing countries. There has been a noticeable shift of anti-dumpingusage from rich to poor countries (Prusa 2005).

For the distribution of anti-dumping use across world regions, the num-ber of anti-dumping initiations has been substantially increased in Asiancountries (Figure 1). There were only 29 cases filed for anti-dumping inves-tigation in 1995, considerably small numbers comparing with 89 cases filedin 2008. North American and Latin American countries experienced a smallreduction in the number of anti-dumping filings from 74 cases to 69 casesduring the same period. On average, the time patterns of anti-dumping usageare distinct across world regions.

The regions share of total world regional anti-dumping filings alsochanged significantly (Figure 2). For instance, Asian countries had notably

FIGURE 1 Number of anti-dumping initiations by world regions (color figure availableonline).

Source: The data are obtained from http://www.wto.org. Note that the European Community is treatedas a single country.

1 For instance, as reported on the WTO website, there were 366 cases reported for anti-dumpinginvestigation in 2001, more than double the 157 cases reported in 1995.2 For a review and discussion on trends in worldwide anti-dumping use, see Prusa (2005).

6 S. Sudsawasd

FIGURE 2 Share of anti-dumping initiations by world regions (color figure available online).

Source: The data are obtained from http://www.wto.org. Note that the European Community is treatedas a single country.

a larger share of anti-dumping initiations over the period 19952008 (from18% in 1995 to almost 43% in 2008). In contrast, the share by North Americanand Latin American countries had declined significantly (from 47% in 1995 to33% in 2008); and the share by European countries region was quite stable(around 22%) during the same period.

Although an analysis of the factors influencing anti-dumping useappears to be one of the most popular international trade topics, most exist-ing research is focused on the experiences of the major four countries (e.g.,Feinberg 1989; Knetter and Prusa 2003).3 It is inappropriate for one to expectthat the findings would be the same for other countries, especially whencomparison countries are quite dissimilar, as well as when political percep-tions on anti-dumping measures are different. Besides, one may expect thata region where a country resides can be one of the factors influencing theuse of anti-dumping measures in each country. Therefore, one of the inter-ests of the current study is to examine what contributing factors underlie theshift of worldwide anti-dumping filing usage in each region.

As stated, the surge in the use of anti-dumping measures is found to beassociated with the success of GATT/WTO in reducing world tariff barriers.Thus, a link between tariff policy and anti-dumping usage would reason-ably be expected. Early attempts to empirically examine the determinantsof macroeconomic factors, including the tariff factor, on anti-dumping fre-quency have been made by Irwin (2005) and Aggarwal (2004). Irwin (2005)focused on various determinations of anti-dumping filings in the UnitedStates and found that an increase in the average tariff rate leads to moreanti-dumping filings. However, his findings are inconsistent with those ofAggarwal (2004), who used panel data for 99 countries over the period of19802000 and found a negative relationship between the average tariff rate

3 For a comprehensive review of the literature on anti-dumping, see Blonigen and Prusa (2003).


and the frequency of anti-dumping use in developing countries, whereas therelationship was found to be insignificant for developed countries.

Aggarwals findings are contrary to the conventional view, in which anti-dumping is considered to be a tool of administered protection used againstthe prevailing trade liberalization. Although a shift in anti-dumping usageaway from developed countries is obvious, developed countries are still themajor users of such measures.4 Hence, a significant relationship betweentariff policy and the number of anti-dumping filings in developed countrieswould be expected.

The current study aims to empirically examine the relationship betweentariff policy and anti-dumping use categorized by a region where countriesreside. A negative binomial model is used for the estimation and the datainclude a panel of 56 countries from 19952007.5 The findings will contributeto better understanding of the change over time in anti-dumping patternsin different world regions. The article is organized as follows. In the nextsection, an empirical model examining the link of tariff policy and the use ofanti-dumping measures is presented; whereas, the data and empirical issuesare discussed in the third section. The fourth section contains the empiricalfindings. And concluding remarks are presented in the final section.

II. MODEL SPECIFICATION

As suggested by Knetter and Prusa (2003), the number of anti-dumpingfilings is determined by real exchange rates, the filing countrys GDP, andthe GDP of the rest of the world. This study augments the standard frame-work by adding the filing countrys trade balance and tariff policy variablesto examine the effects of the countrys trade environment and tariff liberaliza-tion policy on anti-dumping filings. The model specification of anti-dumpingfilings in country i in the year t is therefore:

(?) (?) (-) (-) (?)

ADit = f(REERit,GDPit,WGDPit, TBALit, Tariffit

),

where

ADit = the number of anti-dumping initiations,

4 See Table 3 in Prusa (2005).5 The 56 countries are: Argentina, Australia, Austria, Belgium, Brazil, Bulgaria, Canada, Chile, China,Colombia, Costa Rica, Czech Republic, Denmark, Ecuador, Egypt, Finland, France, Germany, Greece,Guatemala, India, Indonesia, Ireland, Israel, Italy, Jamaica, Japan, Latvia, Lithuania, Luxembourg, Malaysia,Mexico, Netherlands, New Zealand, Nicaragua, Pakistan, Panama, Paraguay, Peru, Philippines, Poland,Portugal, Slovenia, South Africa, South Korea, Spain, Sweden, Taiwan, Thailand, Trinidad and Tobago,Turkey, Ukraine, United Kingdom, United States, Uruguay, and Venezuela.

8 S. Sudsawasd

REERit = the real effective exchange rate,GDPit = the domestic real GDP (in 2000 constant dollars),WGDPit = the real GDP of the rest of the world (in 2000 constant dollars),TBALit = the net trade balance as a ratio of total trade (percentage), andTariffit = average tariff rate (percentage).

There are two basic requirements to pursue anti-dumping lawsuits. First,less than fair value, or LTFV, occurs when foreign exporters are found to setthe price of a product either below the normal price it charges in other mar-kets or below the cost of production plus a normal profit. Second, materialinjury occurs when the domestic industry is found to suffer from dumpedimports. The basic requirement for the determination of such injury is thatthere must be evidence of the volume and price effects of dumped importsand a consequent impact of dumped imports on the domestic industry. Thenumber of anti-dumping filings is presumed to have a positive relation withthe likelihood of affirmative LTFV and injury determinations.

Thus, given those two requirements described above, a change in thereal exchange rate has theoretically ambiguous effects on the number of anti-dumping filings. As shown in Knetter and Prusa (2003), a real appreciationof the domestic currency increases the possibility of material injury, butreduces the chance of LTFV. Using data on the four primary anti-dumpingusers, Knetter and Prusa found a positive relationship between the real effec-tive exchange rate and anti-dumping filings. On the contrary, using U.S. data,Feinberg (1989) found an inverse relationship.

An increase in the domestic import countrys GDP has an ambiguousimpact on the number of filings. Countries in a recession are more likely tofile anti-dumping complaints, as the probability of an affirmative materialinjury increases. In addition, if a foreign firm lowers its price in order tomaintain its level of exports, it is more likely for a foreign firm to be guiltyof the LTFV determination. However, due to differing political pressure, it ispossible that import countries with higher GDP may use more anti-dumpingto protect the domestic industry. Thus, the relationship between the filingcountrys GDP and anti-dumping use is unclear.

An increase in the GDP of the rest of the world is hypothesized to have anegative impact on the use of anti-dumping measures. An exporting foreignfirm in a recession economy may decide to lower its export price in orderto stabilize its excess supplies in the home country. Thus, an increase in thepossibility of LTFV filings would be expected. For the trade balance variable,a widening in the filing countrys trade deficit may increase the probabilityof affirmative material injury determination and the more likely that anti-dumping action will be used (Aggarwal 2004, and Feaver and Wilson 2004).The relationship between the filing countrys trade balance and the numberof anti-dumping filings is expected to be negative.


A change in tariff policy is hypothesized to have ambiguous effects onthe number of anti-dumping filings. A reduction in an import tariff reducesdomestic firms price in the market. As a result, the profits of domesticfirms are likely to decrease. Under such circumstances, the likelihood offilings related to material injury would increase. Hence, tariff liberalizationincreases the possibility of filing for material injury. This is in a line with theview that anti-dumping measures are used to ensure some level of protectionfor the domestic industry against a dramatic surge in import competition.

On the other hand, the effects of a lower tariff rate on the LTFV deter-mination are less clear. Although the export price (the price after includingimport taxes) of a foreign firm is expected to decrease, it is uncertain whethera foreign firm will lower its sale price (the price before including importtaxes). If a foreign firm increases its sale price (since it may possess somemarket power), an affirmative LTFV determination would be less likely.In contrast, if the sale price is decrease, a foreign firm would be more likelyto be guilty of the LTFV determination. Therefore, the overall relationshipbetween tariff policy and anti-dumping usage is theoretically ambiguous.Moreover, it may differ in each world region. It is now a matter of empiricalevidence.

III. DATA AND EMPIRICAL ISSUES

Data on explanatory variables are extracted from the World Banks WorldDevelopment Indicators (WDI)-2009 CD-ROM, and anti-dumping initiationfilings per year are collected from the WTO website (http://www.wto.org).In this analysis, a panel dataset of 56 reporting countries over the period19952007 is employed. For the purpose of a comparative analysis, the56 countries are divided into three regional groups. They are

1. North America and Latin America,2. Europe, and3. Asia, Africa, and the Middle East.6

The choice of regional groups identified in this analysis was determinedby the availability of data for each world region. As stated, it is possible thatthe level of development may have some influences on the number of anti-dumping use in each country. Thus, the estimation results for developed anddeveloping countries could vary substantially. Hence, the model is estimatedseparately for developed and developing countries in each regional groupdataset.

6 The composition of countries in each region follows the region classification used in the WTOsInternational Trade Statistics.

10 S. Sudsawasd

The real effective exchange rate is defined as the nominal exchange rateadjusted for the effects of inflation by multiplying the ratio of the reportingcountrys consumer price index to another major countrys consumer priceindex, where the United States is used as the base country for simplicity.A rise in the real effective exchange rate would indicate an appreciation ofthe real exchange rate of the reporting countrys currency relative to the USdollar.

For the tariff policy variable, an average tariff rate is measured by theratio of customs and other import duties to the total imports of the reportingcountry. As shown in Figure 3, the trends of the average tariff rate havedeclined over time in each world region, especially in Asian, African, andMiddle Eastern countries that experienced a substantial decrease in the tariffrate. Meanwhile, the tariff rate in European countries moved less than thetariff rate in other countries. This is clearly because the tariff rate in Europeancountries was relatively low. Hence, they may be very sensitive to a tariffreduction.

The number of anti-dumping initiation filings is based on non-negativecount data, and the negative binomial model is used for the estimation. Thenegative binomial model is an extension of the Poisson model, which allowsfor an over-dispersion structure, in which the variance of a dependent countvariable is greater than its mean.7 Due to the nature of panel data, both fixed-and random-effects estimators are employed to accommodate heterogeneityacross countries. This study employs the Hausman (1978) specification test todecide between the fixed-effects or random-effects model. The Hausman testdid not reject the null hypothesis in which the estimated coefficients between

FIGURE 3 Average tariff rate (color figure available online).

7 See Greene (2003) and Cameron and Trivedi (1998) for more details on the treatment ofeconometric models for count data.


the two estimators were statistically indifferent. Hence, the random-effectsmodel was chosen as the main estimator for further analysis.8

IV. EMPIRICAL FINDINGS

Tables 14 present the estimation results of factor determinants of anti-dumping filings in each world region, in which the incidence rate ratiosare reported. The incidence rate ratio is defined as the ratio of the expectedcounts where the variable of interest is a one unit increase from its meanvalue and other variables are at their mean values to the expected countswhen all variables are at their mean values.9 Based on the log-likelihoodstatistics, the inclusion of the trade balance and tariff variables in the esti-mate versions of the model without tariffs as in Knetter and Prusa (2003)improves the model fit. The findings can be analyzed as follows:

When the pooled data of all 56 countries are used, the real exchangerate variable is not robustly and significantly related to the number ofanti-dumping filings. Although the estimated coefficient appears positivelysignificant in the regressions without the tariff variable (Equations 1 and 2),indicating more use of anti-dumping measures associated with an apprecia-tion of real exchange rate, it turns insignificant with the inclusion of the tariffvariable (Equation 3). When the model is estimated separately for developedand developing countries (Equations 4 to 9), none of the estimated coeffi-cient of the real exchange rate variable is shown to be significant. In addition,when the model is estimated for each regional group, the insignificance ofthe real exchange rate variable is found most often.

The estimated coefficient of the domestic GDP variable is mostly signif-icant and has a positive sign. 10 The findings indicate that political pressurerelated to anti-dumping use may change with domestic GDP levels. Countrieswith higher GDP have a greater tendency to use anti-dumping measures toprotect their domestic industry from import competition. The GDP of therest of the world variable appears to be negatively related to the numberof anti-dumping initiations when the pooled data of all countries for eachregional group dataset are used (except Asian, African, and Middle Easternregions, in which the estimated coefficient is not significant.) Hence, in arecession, an export country is shown to have a strong tendency to lower itsexport price to less than fair value, resulting to more anti-dumping use in

8 The estimation results of the fixed-effects stimators are available upon request.9 For example, if the reported IRR for the tariff rate is two, it indicates that one unit increase in thetariff rate would increase the expected counts (the number of AD filings) by 100% holding other variablesconstant, comparing with when all variables are at their means.10 Except when the datasets of developed countries were used, the estimated coefficient of the GDPvariable was mostly insignificant.

TABLE

1Determinan

tsoftheNumber

ofAnti-DumpingInitiations(AD

i):Ran

dom-EffectsNegativeBinominal

Model

Allregions

Allcountries

Developed

countries

Developingcountries

12

34

56

78

9

lnREERi

1.1386

1.1308

1.0675

1.0976

1.0774

1.0107

0.9726

0.9646

0.9592

(0.0407)

(0.0408)

(0.0458)

(0.0711)

(0.0721)

(0.0892)

(0.0365)

(0.0368)

(0.0430)

lnGDP

i1.3279

1.3630

1.5902

0.9167

0.9090

1.0137

2.0815

2.1763

2.1084

(0.0862)

(0.0877)

(0.1256)

(0.0661)

(0.0693)

(0.1201)

(0.1545)

(0.1735)

(0.1886)

lnWGDP

i0.3594

0.3580

0.2232

0.2241

0.1938

0.1336

0.6696

0.7853

2.6002

(0.0857)

(0.0863)

(0.0973)

(0.0566)

(0.0519)

(0.0605)

(0.3119)

(0.3746)

(1.9665)

TBAL i

1.0005

1.0022

0.9917

0.9969

0.9919

0.9992

(0.0036)

(0.0048)

(0.0056)

(0.0071)

(0.0051)

(0.0063)

Tariff

i0.9647

0.8396

1.0196

(0.0166)

(0.1232)

(0.0164)

Loglikelihood

1932.33

1906.53

1031.71

1119.71

1099.92

541.07

760.08

754.47

458.34

WaldX

261.53

65.06

57.17

41.43

42.29

22.48

97.98

100.34

84.73

No.ofobs.

713

707

422

325

320

169

388

387

253

Note:Estim

ates

arereported

asinciden

cerate

ratio

s.Standard

errors

arein

paren

theses.

,

,

den

ote

1%,5%

,10%

sign

ificantlevels,respectiv

ely.

12

TABLE

2Determinan

tsoftheNumber


i):Ran


Model

NorthAmerican

andLatin

American

regions

Allcountries

Developed

countries

Developingcountries

1011

1213

1415

1617

18

lnREERi

1.0617

1.0773

0.9780

1.1669

1.8091

0.0327

1.0255

1.0119

0.9964

(0.0673)

(0.0748)

(0.0660)

(0.7307)

(1.8575)

(0.0390)

(0.0556)

(0.0584)

(0.0713)

lnGDP

i1.3603

1.2693

1.7551

1.3428

1.1432

5.0503

2.3395

2.6018

2.5038

(0.1529)

(0.1564)

(0.1522)

(0.2221)

(0.3862)

(2.0748)

(0.2629)

(0.3324)

(0.3496)

lnWGDP

i0.2871

0.3201

0.0593

0.3567

0.3531

0.0010

0.1010

0.1932

0.4770

(0.1286)

(0.1489)

(0.0553)

(0.2387)

(0.2378)

(0.0014)

(0.0580)

(0.1213)

(0.6161)

TBAL i

0.9919

1.0089

0.9898

1.1110

0.9852

0.9883

(0.0063)

(0.0062)

(0.0186)

(0.0342)

(0.0066)

(0.0086)

Tariff

i1.1175

0.5578

1.1437

(0.0539)

(0.1796)

(0.0528)

Loglikelihood

431.19

430.35

244.80

116.63

116.48

71.91

297.75

295.07

157.13

WaldX

228.05

27.16

85.12

58.23

57.70

75.15

82.09

82.06

63.53

No.ofobs.

213

213

128

3939

27174

174

101

Note:Estim

ates

arereported

asinciden

cerate

ratio

s.Standard

errors

arein

paren

theses.

,

,

den

ote

1%,5%

,10%

sign


ely.

13

TABLE

3Determinan

tsoftheNumber


i):Ran


Model

Europeanregion

Allcountries

Developed

countries

Developingcountries

1920

2122

2324

2526

27

lnREERi

0.9409

0.9816

1.2147

0.8990

0.8694

0.8604

2.0111

1.9805

0.5890

(0.1339)

(0.1469)

(0.2252)

(0.1188)

(0.1193)

(0.2317)

(0.4587)

(0.7779)

(0.3886)

lnGDP

i1.3904

1.4854

1.9907

1.0399

1.0756

1.1450

2.1432

2.1488

3.1592

(0.1572)

(0.1650)

(0.2884)

(0.1012)

(0.1111)

(0.2375)

(0.3606)

(0.3802)

(0.9368)

lnWGDP

i0.1857

0.1978

0.0794

0.1609

0.1343

0.1268

3.8600

3.9409

0.0838

(0.0598)

(0.0668)

(0.0399)

(0.0495)

(0.0451)

(0.0675)

(5.5691)

(5.9447)

(0.3576)

TBAL i

1.0077

0.9968

0.9932

0.9953

0.9978

0.8176

(0.0068)

(0.0083)

(0.0067)

(0.0077)

(0.0455)

(0.0788)

Tariff

i0.4300

0.6546

1.5089

(0.1219)

(0.2369)

(0.7606)

Loglikelihood

957.44

936.12

400.25

825.23

805.86

349.75

88.60

88.60

37.46

WaldX

229.92

35.95

69.96

37.55

38.97

16.29

43.99

43.85

18.74

No.ofobs.

299

294

154

221

216

105

7878

49

Note:Estim

ates

arereported

asinciden

cerate

ratio

s.Standard

errors

arein

paren

theses.

,

,

den

ote

1%,5%

,10%

sign


ely.

14

TABLE

4Determinan

tsoftheNumber


i):Ran


Model

Asian

,African

,an

dMiddle

Eastern

regions

Allcountries

Developed

countries

Developingcountries

2829

3031

3233

3435

36

lnREERi

0.9719

0.9735

0.9411

0.9719

0.8809

1.1465

0.9346

0.9265

0.9063

(0.0588)

(0.0620)

(0.0570)

(0.0976)

(0.0989)

(0.0739)

(0.0629)

(0.0651)

(0.0744)

lnGDP

i1.1993

1.1799

1.7964

0.6095

0.6294

1.8299

1.6732

1.7139

1.7770

(0.1715)

(0.1783)

(0.2335)

(0.1521)

(0.1479)

(0.3887)

(0.2024)

(0.2451)

(0.2774)

lnWGDP

i1.5319

1.4777

4.9505

0.2971

0.2897

0.2385

2.2738

2.2327

23.8073

(0.9151)

(0.8960)

(4.4215)

(0.2725)

(0.2680)

(0.3650)

(1.7057)

(1.7034)

27.49

TBAL i

1.0006

1.0080

0.9584

1.0224

0.9959

1.0136

(0.0093)

(0.0122)

(0.0224)

(0.0244)

(0.0097)

(0.0141)

Tariff

i1.0166

1.4932

1.0355

(0.0225)

(0.2438)

(0.0254)

Loglikelihood

522.79

518.10

346.58

164.08

162.47

94.99

347.81

343.18

239.84

WaldX

22.82

2.38

44.07

6.14

10.88

33.55

24.31

23.60

40.18

No.ofobs.

201

200

140

6565

37136

135

103

Note:Estim

ates

arereported

asinciden

cerate

ratio

s.Standard

errors

arein

paren

theses.

,

,

den

ote

1%,5%

,10%

sign


ely.

15

16 S. Sudsawasd

an import country. However, the estimation results for developed and devel-oping countries are very distinct. For instance, the negative and significantrelationship is found only in developed European countries, whereas therelationships for developed countries in other regions are not significant.

Next, the estimated coefficient of the countrys trade balance variableis surprisingly insignificant in most of the model estimations, regardless ofwhich regional group dataset is used. Hence, the results point to which thecountrys trade environment measured by the countrys trade balance is nota significant determinant factor of the anti-dumping use.

For the tariff variable, when the pooled datasets of all countries areused (Equation 3), a tariff rate has a negative impact on anti-dumping use.As indicated, a 1% reduction in a tariff rate leads to a 3.53percentage pointincrease in the number of anti-dumping initiations. These findings are con-sistent with Aggarwal (2004) and suggest that anti-dumping measures havebeen used as a measure to provide protection for the domestic industry fromtariff liberalization policy.

When this study estimates the effects of tariff policy in each worldregion, the estimation results vary widely. In general, the findings are alongthe same lines as Knetter and Prusa (2003), whose findings also vary byuser. Developed countries in the North American and Latin American regionsare found to use more anti-dumping measures when a tariff rate decreases(Equation 15). A 1% reduction in the tariff rate leads to a 44.2percent-age point increase in the anti-dumping cases. The findings point to whichdeveloped countries in these regions used anti-dumping as a substitutionfrom tariff liberalization. In contrast, developing North American and LatinAmerican countries are found to file a 14percentage point less in the numberof anti-dumping initiations with a 1 % reduction in a tariff rate (Equation 18).Hence, tariff liberalization policy has different effects on anti-dumping usagein developed and developing countries in the North American and LatinAmerican regional group.

The estimated coefficient of the tariff variable is negative and significantwhen an all-European countries dataset is used (Equation 21). A one% reduc-tion in a tariff rate leads to a 57 percentage point increase in the number ofanti-dumping initiations. This finding suggests that European countries arevery sensitive to a change in a tariff rate and may respond by a dramaticincrease in the anti-dumping use. This is perhaps because the tariff rate inthis region is already low so that the decline in the tariff rate has a very largeimpact on the anti-dumping measure. However, the estimated coefficient ofthe tariff variable turns insignificant when the model is estimated separatelyfor developing and developed countries datasets.

For developed countries in the Asian, African, and Middle Easternregions, a change in a tariff rate has a significant impact on anti-dumpinguse. A 1% reduction in a tariff rate leads to a 49percentage point decrease in


the number of anti-dumping initiations. Hence, tariff liberalization policy inthese countries does not induce more use of anti-dumping measures.

Finally, when the sizes of the estimated coefficients of the tariff variablefor developed and developing countries are compared, developed countriesappear to be more sensitive than developing countries to a change in a tariffrate. This suggests that the motivations for the use of anti-dumping measureswhen tariff policy changes are likely are stronger in developed countries.

V. CONCLUSION

This study examined empirically how tariff policy influences the likelihoodof anti-dumping filings. The empirical evidence shows that the effects of tariffliberalization on anti-dumping use vary across world regions. For Europeancountries, as well as developed North American and Latin American coun-tries, a lower tariff rate is associated with greater use of anti-dumpingmeasures. Anti-dumping appears to emerge as a protection tool amongregions with trade liberalization regimes.

In contrast, in developing North American and Latin American countries,a decline in the tariff rate leads to a significant reduction in the use of anti-dumping measures. Hence, the findings suggest that these countries havecommitted more to free trade in reducing both tariff and non-tariff barriers.In most regions of the world, developed countries are likely to be more sen-sitive than developing countries to tariff policy changes in terms of initiatinganti-dumping action.

The empirical findings in this study are contrary to the view that devel-oped countries are usually strong advocates of free trade. They are morelikely to be under political pressure to use anti-dumping as a way to pro-tect the domestic industry from a rise in import competition. Clearly, thismay hamper the gains from free trade. Therefore, it is important for eachcountry to make a stronger commitment to free trade and to try to minimizeanti-dumping abuse, especially in European countries, as well as developedNorth American and Latin American countries.

ACKNOWLEDGMENTS

This study was funded by the Thailand Research Fund under contract num-ber MRG5080155. The author would like to thank Dr. Wisarn Pupphavesaand Dr. Robert E. Moore for their constructive comments and VarachatNumchaisri and Siam Sakaew for their outstanding research assistance.

18 S. Sudsawasd

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