CUMULATION AND ITC DECISION-MAKING: THE SUM OF THEPARTS IS GREATER THAN THE WHOLE

WENDY L. HANSEN and THOMAS J. PRUSA*

In 1984 Congress amended the antidumping and countervailing duty laws, man-dating that the International Trade Commission (ITC) "cumulate" imports acrosscountries when determining injury. We estimate that cumulation increases the prob-ability of an affirmative injury determination by 20 to 30 percent and has changedthe ITC’s decision (from negative to affirmative)for about one-third of cumulatedcases. We also show that the protective effect of cumulation increases as the numberof countries involved increases, holding import market share constant. That is, cumu-lated imports have a super-additive effect on ITC decision-making.

I. INTRODUCTION

In recent decades, the rise in interna-tional competition has led many U.S. firmsto seek protection from foreign imports.Particularly noteworthy in the 1980s wasthe increased use of the U.S. "unfair" tradelaws. Two popular trade statutes, the an-tidumping law and the countervailingduty law, allow U.S. firms or industries toseek protection from alleged unfair tradepractices, namely dumping and subsidiza-tion.

Under these laws, U.S. firms or indus-tries apply simultaneously to the Depart-ment of Commerce and the U.S. Interna-tional Trade Commission (ITC); theseagencies have the authority granted byCongress to determine, respectively,whether or not an unfair practice hasoccurred and whether or not the unfairpractice has caused injury to the U.S. in-dustry. Affirmative decisions by both ofthese bodies generally result in the impo-sition of higher tariffs designed to counterthe alleged unfair practice.

* Department of Political Science, University ofNew Mexico and Department of Economics, RutgersUniversity, and NBER. We would like to thank Se Parkfor excellent research assistance. This paper benefitedfrom the comments of participants in the NBER Inter-national Trade and Investment group and also twoanonymous referees.

Since 1974, the U.S. Congress has madea number of major changes to the anti-dumping and countervailing duty laws,largely in response to domestic industrypressures. These amendments were in-tended to either increase the applicabilityof the laws or to make the unfair practiceand injury requirements easier to satisfy.Although Hansen [1990], Moore [1992],and Baldwin and Steagall [1994] have allanalyzed the decision-making process ofthe ITC, none have incorporated the factthat Congress often amends the rules thatdefine how decisions are to be made.There is no empirical evidence of the im-pact of the changes in the statutes on tradepolicy. Authors such as Bello and Holmer[1985], Lande and VanGrasstek [19861, andHorlick and Oliver [1989] who do discussthe amendments tend to focus on legalissues and only offer conjectures as to theconsequences of the revisions. Althoughsome observers cite the increased inci-dence of affirmative antidumping andcountervailing duty decisions as de factoevidence of the effect of the amendments,this type of casual empiricism is not reli-able. Many possible explanations forchanges in ITC behavior--masroeconomicslowdown, election year political pres-sures, etc.--have nothing to do with thechanges in the statutes. Without careful

Economic Inquiry(ISSN 0095-2583)Vol. XXXIV, October 1996, 746-769

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@Western Economic Association International

HANSEN & PRUSA: CUMULATION AND ITC DECISIONS 747

econometric analysis, attributing observedchanges in protection to statutory changeswill almost surely misrepresent the trueeffect of the amendments.

The main purposes of this paper are toprovide such an econometric analysis andto quantify the protective effect of perhapsthe most important amendment to theantidumping and countervailing dutystatutes during the 1980s: mandatory cu-mulation. Enacted in the Trade and TariffAct of 1984, this provision requires the ITCto cumulate imports when a trade disputeinvolves imports from multiple sources.Without cumulation, imports are evalu-ated on a country-by-country basis; whencumulation is applied, the rrc aggregatesall "like" imports from all countries underinvestigation and assesses the combinedimpact upon the domestic industry. With-out cumulation, the volume from any onecountry is less likely to comprise a signif-icant share of the domestic market andtherefore is less likely to cause injury. Onthe other hand, if the imports from indi-vidual foreign competitors are aggregated,the impact of foreign competition will bemore significant, making it more likelythat the ITC will decide that the domesticindustry has suffered material injury byreason of unfairly traded imports.

In order to measure the impact, if any,of the cumulation provision we must con-trol for any other economic and politicalfactors that also explain ITC decision mak-ing. Therefore, in addition to empiricallyanalyzing the impact of cumulation, weoffer a broad characterization of the fac-tors that determine antidumping andcountervailing duty outcomes. Thus, ourresults have general implications for eval-uating the efficacy of the rrc’s decisionmaking. For example, our estimates allowus to compare the importance of statuto-rily mandated requirements, such as eco-nomic measures of injury, with unofficialinfluences, such as political pressure frommembers of Congress who have a vested

interest in seeing an industry receive afavorable ITC decision.

Our explicit consideration of politicalpressure is another unique aspect of ourresearch. Most previous research has fo-cused solely on the impact of statutoryrequirements on rrc outcomes (Finger etal. [1982], Moore [1992], Baldwin andSteagall [1994]). By contrast, our estimatesshow that political pressure, via both di-rect representation and PAC contribu-tions, significantly influences decisionsmade by the ITC, a supposedly apoliticaldecision-making agency.

However, while our model allows us toaddress these broader issues, our primarygoal is to measure the significance of cu-mulation on trade policy outcomes. Usingdata on antidumping and countervailingduty cases filed between 1980 and 1988,we find that cumulation has had a dra-matic impact on ITC decision making.Specifically, after controlling for other eco-nomic and political factors we find thatcumulated cases are 20-40 percent morelikely to result in duties than non-cumu-lated cases. Our results also imply thatone-third to one-half of the cumulatedcases that resulted in duties would havebeen denied protection were cumulationnot mandated.

Most interestingly, our results implythat cumulated imports have a super-ad-ditive effect on ITC decisions. That is, therrc perceives cumulated imports as moreinjurious than an equivalent amount ofnamed country imports. In other words,under cumulation the domestic industryhas a greater chance of protection by filingagainst two countries each with, say, 20percent of the import market than againsta single country with a 40 percent importmarket share. Further, the super-additiveeffect of cumulation becomes more pro-nounced the larger the number of coun-tries being cumulated. Holding the totalimport share under investigation constant,the probability of an affirmative decisionwhen imports from five countries are cu-

748 ECONOMIC INQUIRY

mulated is greater than the probabilitywhen imports from only two countries arecumulated, which in turn is greater thanthe probability when a single country isbeing investigated. At least with respect toITC decision making, it appears that thesum of the parts is greater than the whole.

The remainder of the paper is organizedas follows. In the next section, we examineITC decision making and its use of thecumulation provision both before andafter the 1984 mandate. In sections III andIV, we econometrically analyze the deci-sion-making behavior of the ITC. In sec-tion V we provide a variety of quantitativemeasures of the impact of mandated cu-mulation on ITC decision making. In sec-tion VI we conclude with some additionalinterpretations and extensions of our re-suits.

II. BACKGROUND

Generally speaking, there are three pos-sible outcomes for an antidumping orcountervailing duty petition. First, a casecan be rejected. For instance, if the Depart-ment of Commerce makes a negative rulingin its final investigation, the case is dis-missed; no protection is granted and nofinal ITC determination is made. A case isalso dismissed if either the ITC’s prelimi-nary or final investigation is negative. Sec-ond, if both bureaucratic agencies’ final de-terminations are affirmative, then a duty(tariff) is levied on the named country’s im-ports; the size of the duty is determined bythe Department of Commerce in its inves-tigation of the alleged unfair practice. Fi-nally, a case can be withdrawn. As dis-cussed in Prusa [1992] and Finger and Mur-ray [1990], cases are generally withdrawnonly after some type of agreement (e.g., anorderly marketing arrangement, the for-eign firms agree to raise their prices andstop dumping, the foreign governmentagrees to remove the subsidy, etc.). Notethat since the focus of this paper is actualITC decision making, we exclude with-drawn cases from our analysis.

If the ITC makes an affirmative deci-sion, duties are only levied against thecountry named as an unfair trader in thepetition. As Hansen and Prusa [1995] doc-ument, such protection is quite porous; 90percent of the reduction in trade from thenamed country is merely diverted to otherforeign suppliers. As a result, a domesticindustry often files petitions against mul-tiple exporting countries. Note, however,that the ITC always makes its decisions ona country-by-country basis, even if im-ports from a set of countries are cumu-lated. For example, if seven countries arenamed in the petition, the ITC makesseven separate injury decisions.

Prior to 1984, it was left to the ITCcommissioners’ discretion whether or notto cumulate. However, by incorporatingthe cumulation provision into the Tradeand Tariff Act of 1984 (EL. No. 98-573),Congress required that the ITC cumulatewhenever like products from multiplecountries were subject to investigation. Inparticular, the 1984 amendment stipulatesthat imports from multiple sources mustbe cumulated when three criteria are sat-isfied: (1) the imports must compete withone another and the domestic product, (2)the imports must be marketed within areasonably coincidental period, and (3) theimports must be under investigation.Thus, the 1984 amendment clearly definedwhen cases should be cumulated, andthereby removed almost all of the ITC’sdiscretion regarding cumulation.

Table I gives an example of how thecumulation provision works in practice. InMarch 1986, the U.S. brass sheet and stripindustry filed an antidumping petitionagainst firms located in seven differentcountries. West German firms dominatedthe U.S. import market, accounting forover 20 percent of all U.S. brass sheet andstrip imports and more than half of theallegedly dumped imports. The next larg-est named country, Brazil, accounted forless than 5 percent of the overall importmarket. In January 1987 the Department

HANSEN & PRUSA: CUMULATION AND ITC DECISIONS

TABLE IExample of Cumulation

Brass Sheet and Strip (Cases #311-317)Market Share of Less-Than-

Import Market Cumulated Other Named Fair-Value

Country Share Market Share Countries Duty

West Germany 21.27% 38.35% 17.08% 8.87%

Brazil 4.81% 38.35% 33.54% 40.62%

France 3.78% 38.35% 34.57% 42.24%

Italy 3.27% 38.35% 35.08% 12.08%

South Korea 2.20% 38.35% 36.15% 7.17%

Canada 1.83% 38.35% 36.51% 8.10%

Sweden 1.20% 38.35% 37.15% 9.49%

749

of Commerce determined that each of thecountries had indeed engaged in "lessthan fair value" sales, implying that dutieswould be levied against any countrywhose imports were deemed by the ITC tohave materially injured the U.S. industry.Since the cases were subject to cumulation,the ITC was required to assess the injuri-ous impact of the imports from all namedcountries. For example, when determiningwhether dumped imports from Francematerially injured the U.S. industry, theITC could not merely evaluate the injuri-ous effects of France’s 3.78 percent marketshare, but was required to factor in theadditional 34.57 percent market sharefrom the other named countries. In Febru-ary 1987, the ITC found that imports fromeach of the seven countries had injured theU.S. industry.

The central issue in this study iswhether or not cumulation alters the out-comes. For example, in the brass sheet andstrip cases above, had cumulation notbeen mandated, would any of the seveninjury decisions have been negative? Be-tween 1980 and 1984, fifty-one antidump-ing cases were filed where the namedcountry had an import market share ofless than 5 percent; in only seven of thesecases (14 percent) did the ITC find mate-rial injury. In contrast, during the sametime period approximately 30 percent ofcases filed against countries with import

market shares greater than 5 percent re-suited in duties. This discrepancy suggeststhat cumulation may have changed theoutcome for six of the seven countries inthe brass sheet and strip petition. On theother hand, it is also possible that cumu-lation simply strengthened the U.S.industry’s already strong hand. With itslarge workforce and with production facil-ities located in a number of trade over-sight committee members" districts, thesteel industry’s political clout islegendary.Moreover, profits and employment in theindustry had fallen during the years pre-ceding the petition, indicating possibleinjury. Finally, the large less-than-fair-value margins also may have contributedto the ITC’s determination. Together thesefactors suggest that injury would havebeen found without cumulation.

In Table II we give a breakdown of casesby outcome and whether or not cumula-tion was used both before and after the1984 Trade Act. Title VII cases include bothantidumping and countervailing duty pe-titions (’Tire VII" refers to the section oftrade law where the statutes appear). Inaddition, we report the breakdown forantidumping cases alone, where cumula-tion seems to have had a disproportionateimpact.

A review of the data makes it clear thatonce Congress mandated cumulation,cases involving cumulation became the

75OECONOMIC INQUIRY

TABLE IITitle VII Case Summary

Number of Cases Filed with and without Cumulation, 1980-1988"

Tire VII CasesPre-1984 Post-1984 All YearsOutcome Cum. No Cum. Cum. No Cum. Cum. No Cum.

Negative DOC 2 32 8 9 10 41(3%) (8%) (5%) (7%) (5%) (7%)Negative 1TC 37 126 30 45 67 171(62%) (2~v) (20%) (35%) (32%) (31%)Affirmative 9 123 95 41 104 164(15%) (28%) (64%) (32%) (50%) (29%)Withdrawn 12 152 16 33 28 185(20%) (35%) (11%) (26%) (13%) (33%)Total 60 433 149 128 209 561Antidumping CasesNegative DOC 2 15 3 4 5 19(7%) (7%) (3%) (6%) (4%) (7%)Negative ITC 10 65 21 33 31 98(33%) (32%) (19%) (46%) (22%) (36%)Affirmative 9 43 78 18 87 61(30%) (21%) (71%) (25%) (62%) (22%)Withdrawn 9 81 8 16 17 97(30%) (40%) (7%) (23%) (12%) (35%)Total 30 204 110 71 140 275

*Numbers in parentheses denote percent of column total

norm rather than the expectation. Between1980 and 1984 (i.e., prior to mandatedcumulation) only 60 cases out of 493 TitleVII petitions (12 percent) involved cumu-lation. And, of the 60 cumulated cases,only 15 percent resulted in affirmative ITCdecisions. In contrast, of the 433 petitionsthat were not cumulated, 28 percent re-ceived an affirmative ITC decision. Thus,prior to 1984, not only was cumulationrarely used, but when it was used it ap-parently did not enhance an industry’schance of receiving protection.

Compare the pre-1984 Trade Act num-bers with the patterns post-1984. Between1985 and 1988, 149 of 277 Title VII cases(54 percent) involved cumulation. And, ofthe 149 cumulated cases, a remarkable 64percent were granted relief; in contrast,only 32 percent of the non-cumulatedcases received favorable ITC decisions.From 1985 onwards, it appears that cumu-lation was leading the ITC to be moreprotective.

The patterns in Table II warrant severalcomments. Most notable is the fact thatprior to the 1984 Trade Act cumulatedcases seem to fare worse than non-cumu-fated cases. Given the near unilateral sup-port that the cumulation provision re-ceived from import-competing industriesin congressional hearings and debatesleading up to the passage of the 1984Trade Act, this appears somewhat anoma-lous. This paradox can be attributed toseveral factors. First, prior to the 1984Trade Act the decision of whether or notcumulate was left to the discretion of ITCcommissioners. W~flson [1989, 277-94] andShapiro [1988] have argued that ITC com-missioners prefer not to have their deci-sion overturned by the Court of Interna-tional Trade. Given that during the 1980sthe court reversed nearly 50 percent ofantidumping appeals, and over one-thirdof all cases appealed (Hansen, Johnson,and Unah [1995]), agency concerns aboutreversal are well founded. Given the un-

HANSEN & PRUSA: CUMULATION AND ITC DECISIONS 751

certainty surrounding the legal status ofcumulating imports, it may be that the ITCcommissioners chose to cumulate onlywhen it was clear that doing so would notaffect the ultimate outcome, and thereforewould not be the basis for a Court ofInternational Trade reversal.

A closer examination of the voting andcumulation decisions of the individualcommissioners on the cases cumulatedprior to 1985 seems to support this conjec-ture. Among the sixty cases involving cu-mulation, two cases ended with negativeDepartment of Commerce final decisionsand twelve cases were withdrawn. Thesecases are excluded from our analysis sincethey did not involve ITC decisions. Of theremaining forty-six cases, forty-one wereunanimous decisions (thirty-seven nega-tive), and only five cases involved splitvoting behavior. Clearly, the vast majorityof cumulated cases prior to the 1984amendment were unanimous decisions,supporting the hypothesis that cumula-tion occurred almost always in clear-cutcases where the outcome was determinedby other factors.

Second, even when the ITC chose tocumulate, individual commissioners oftendisagreed over whether a set of petitionsshould be cumulated. Often, several com-missioners would cumulate while the oth-ers would not. Since the ITC makes anaffirmative determination if at least half ofthe commissioners find injury, it may bethe case that cumulation did not have anymeasurable impact on the official outcomein these "split" cases.1 On the other hand,the fact that only one or two commission-ers cumulated imports does not imply thatcumulation did not have an importanteffect on the outcome. For instance, if theother commissioners were split on injury,the overall 1TC decision could change if asingle commissioner cumulated, since asingle vote can change the majority deci-

1. If the commissioners are evenly divided on acase, the determination of the Commission is affirma-five.

sion.2 We believe that the most sensible(and conservative) approach is to classifya case as being cumulated if at least onecommissioner cumulated imports. If thereis a bias inherent in this classificationscheme, it would be that we understate thesignificance of cumulation (since we maybe classifying some non-cumulated casesas cumulated) and this may be what weare seeing in Table II.3

Comparing cumulated cases pre- andpost-1984 suggests that Congress’s man-dating of cumulation did indeed changeITC behavior. In particular, only 15 percentof cumulated cases were affirmatively de-cided when cumulation was discretionaryas compared with 64 percent once cumu-lation was mandated. In addition to thepossible explanations discussed above,this result might also simply reflect thatITC commissioners viewed Congress’smandate as a signal to be more protec-tionist.

The data also indicate that cumulationhas been a more important provision forantidumping cases. Pre-1984 antidumpingcases account for one-half of cumulatedTitle VII cases, while post-1984, antidump-ing cases account for almost three-quar-ters of cumulated cases. Note howeverthat antidumping cases account for abouthalf of non-cumulated Title VII cases bothpre- and post-1984. It is not clear whycumulation would be more important forantidumping cases, although part of theexplanation lies in the fact that an injurydetermination is not required for counter-

2. See Moore [1992] and Baldwin and SteagaIl[1994] for discussions of individual commissioner vot-ing.

3. In particular, Mock [1986] states that there wereno cumulated countervailing duty cases prior to the1984 Trade Act. In contrast, our review of ITC proceea-ings indicates that thirty countervailing duty cases ~n-volved at least one commissioner cumulating imports.However, twenty-seven of the thirty p~e-1984 counter-vailing duty cases that we cl .assify as .c.un~..ulated .wererejected by the ITC. While it ts not enhrely clear ~omthe text, Mock’s discussion suggests that he conslaersa case to be cumulated only if a majority of ITC com-missioners cumulated imports.

752 ECONOMIC INQUIRY

vailing duty cases filed against countriesthat have not signed the GATT subsidycode. Since there is no need to prove injuryagainst firms from these countries, there isless of a need to rely on cumulation. Cu-mulation also seems to have had a moresignificant effect on antidumping out-comes. Cumulated antidumping cases arealmost three times as likely to result induties as non-cumulated cases; in contrastcumulated and non-cumulated counter-vailing duty cases were about equallylikely to receive protection (especiallyafter 1984).

When Congress was debating whetheror not to mandate cumulation, one argu-ment repeatedly made was that the sourceof the dumped or subsidized imports wasirrelevant. What mattered was that thecumulated volume was injurious. This ar-gument in favor of cumulation has beenreferred to as the "hammering effect" hy-pothesis, since according to industries andtheir representatives,

a domestic industry that suffers materialinjury by reason of 100,000 tons of un-fairly traded imports from a single coun-try is injured to the same degree by20,000 tons of unfairly traded importsfrom each of five different countries.(Suder [1983])

Whether or not the "hammering effect"theory is valid, one could hypothesize thatindustries would respond to mandated cu-mulation by (a) filing more multiple-coun-try petitions and (b) filing more casesagainst countries with smaller importmarket shares.

In order to address the first issue wetallied the number of multiple-country pe-titions and found that 22 percent of pre-1984 petitions and 33 percent of post-1984petitions involved firms located in morethan one country, suggesting that man-dated cumulation has led to a 50 percentincrease in multiple petition filings. Onthe other hand, there is virtually no differ-ence in the average number of countriesper filing pre- and post-1984. Of course,the large scale steel industry filings in 1982

and 1984 might explain the similarity. Ifwe exclude the steel industry filings in1982 and 1984, we find that the averageTitle VII pre-1984 petition involved 1.3countries while post-1984 petitions in-volved an average of 1.8 countries--abouta 40 percent increase. Thus, there is somesupport for the claim that cumulation in-creases the number of multiple-countrypetitions.

To address the second issue, we calcu-lated the average import market shareheld by the country named as the unfairtrader in the Title VII petition. Overall wefound an average import market share of11 percent when cumulation was used, ascompared with 17 percent when cumula-tion was not used. This suggests that casesinvolving cumulation are indeed filedagainst countries with smaller marketshares.

Of course, these cross tabulations alonedo not adequately measure the effect ofcumulation since they do not control for awide variety of other economic and polit-ical variables that might also be influenc-ing the ITC’s decision making. For in-stance, if cases with cumulation were alsocases where the domestic industry hadexperienced significant loss in profits,large layoffs, decreased capital utilization,and the like, one should not attributechanging patterns of protection to cumu-lation alone. In order to more fully addressthese concerns, we develop a more formalmodel of bureaucratic decision making inthe next section.

III. MODELLING ITC DECISION MAKING

In this section we model the decision-making behavior of the ITC. During thepast decade the ITC has been the subjectof a growing body of empirical research.Takacs [1981], Hansen [1990], and Fingeret al. [1982] focused on determinants ofthe annual number of petitions filed withthe ITC, either in conjunction with orinstead of the determinants of ITC deci-sions, while Baldwin [1985], Moore [1992],

HANSEN & PRUSA: CUMULATION AND ITC DECISIONS 753

and Baldwin and Steagall [1994] morenarrowly focus on ITC decision making.However, none of the previous researchhas analyzed how a specific amendmentaffects decision making nor do these pa-pers offer as precise measures of politicalpressure as we do.

We incorporate both economic and po-litical factors that may affect whether ornot a Title VII petition receives protection.Clearly, we expect measures of economicinjury to be positively related to affirma-tive ITC decisions, since this is stipulatedin the statutes. However, it is widelyagreed that political and more generaleconomic pressures also influence ITC de-cision making. For instance, the U.S.’slarge and growing trade deficit mightraise the public’s ire over trade-relatedproblems, and thereby create substantialpressure for more affirmative 1TC deci-sions, regardless of whether or not theless-than-fair-value imports have statuto-rily caused injury. Or, a petition filed byan industry with production facilities lo-cated in districts of representatives who siton trade oversight committees might havemore success than a petition filed by anindustry that does not have a representa-tive who will lobby the commission on itsbehalf. Below we discuss the variablesused to measure these influences. A moredetailed description of the variables usedin our model is provided in the appendix.

Economic Measures of InjuryBy statute, the 1TC is directed to take

into account the economic situation of anindustry in determining injury. Thus evi-dence of economic hardship or declineshould be important to the decision-mak-ing behavior of the Commission. In ourmodel percentage changes in industry ca-pacity utilization and shipments are usedto measure recent industry performance-4

4. We could have also included the percentage

is highly correlated w~th the change m smpm -

One would expect that the greater the fallin each variable, the greater the likelihoodof an affirmative decision.

Even though 1TC commissioners arenot required to consider the less-than-fair-value margin when making their injurydetermination, it would not be surprisingto find a relationship between the less-than-fair-value margin and the likelihoodof injury. Palmeter [1987] argues that theITC relies more on the volume of less-than-fair-value imports rather than theless-than-fair-value margin. We investi-gate both hypotheses and include both theless-than-fair-value margin and thenamed country’s import market share asindependent variables-s

Cumulation is the economic criterion inwhich we are most interested. We use twodifferent measures of the cumulation pro-vision. One measure is a dummy variable(= 1 when the case is cumulated). Whilethis is a straightforward measure, it doesnot capture the fact that cumulation islikely to have a more significant effect onthe outcome for named countries withsmall market shares. For instance, in thebrass sheet and strip example discussedabove, West German firms had over 20percent of the import market, and it islikely that they would have been found tohave caused injury with or without cumu-lation. On the other hand, Canada andSweden, with tiny market shares, wouldmore likely have not been found to havecaused injury. In other words, one would

expect the market share contributed by th.eother named countries to be important mtheir injury decision. Our second measure,the market share of the other named coun-tries, captures the fact that cumulation islikely to be more important for countrieswith small import market shares.

5. We use the term "less-than-fair-value" marginto refer to both the dumping margin and also the sub-sidy margin.

754 ECONOMIC

Title VII Protection As Compensation forLost Protection

Baldwin [1985], Hoekman and Leidy[1989], and Hansen and Prusa [1995] haveargued that administered protection oftenserves to substitute for the more tradi-tional, but GATT-constrained mode of pro-tection, namely tariffs. Formally, there isno statutory requirement that there be aconnection between increased imports andtariff concessions. However, followingFinger, Hall, and Nelson’s [1982] argumentthat administered protection serves as a"poor man’s escape clause," we hypoth-esize that the pleas of industries that havelow levels of protection--or have lost pro-tection--will be more successful. In otherwords, the lower the current tariff, themore likely bureaucrats will use Title VIIduties to compensate for lost protection.

Similarly, while Title VII protection issupposed to be granted in response toinjury caused by a particular unfair tradeaction, it may be more appropriatelythought of as compensation for overallmarket share gains by foreign rivals. Inother words, Tire VII may serve to protectthose industries that have experienced thegreatest overall import competition. As ameasure of general import gains, we con-struct an industry-level measure of foreignpenetration [imports/(output + imports -exports)]. Note that foreign penetration isa far more aggregated index than the mea-sures of import gains reported in the ITC’sreports and thus is capturing general in-dustry-wide trends rather than the marketshare gains by the named importers. If thishypothesis is correct, increased foreignpenetration makes it easier for the ITC tomake an affirmative injury decision.

Macroeconomic InfluencesTrends in the aggregate economy are

also likely to influence the ITC. We use thepercentage change in the U.S. trade deficitto capture macroeconomic trends in theflow of imports and exports. We expect a

INQUIRY

positive relationship between the changein the deficit and ITC decisions.6

We also control for additional aggregatetrends with dummy variables for each ofthe years included in our data (with 1980as the base year of comparison). For in-stance, changes in the composition of theITC might lead all cases filed in someyears to be more successful.

Political Pressure

Besides the condition of U.S. industriesand the overall economy, research has alsodemonstrated the importance of politicalfactors in explaining ITC decisions. Onemanifestation of political impact on bu-reaucratic decision making is the princi-pal-agent relationship between Congressand the ITC (Weingast [1984]). As dis-cussed in Baldwin [1985] and empiricallyexamined in Hansen [1990], congressionaloversight committees can exert a greatdeal of pressure on ITC commissioners notonly via direct lobbying but also throughbudgetary control. If this notion is correct,and if members of Congress take actionsin order to keep their constituencieshappy, then industries located in districts(or states) of oversight committee mem-bers would be more likely to receive traderelief than those that do not have suchrepresentation.

The House Ways and Means Committeeand Senate Finance Committee have juris-diction over the ITC in their respectivehouses. In order to measure these commit-tees potential political influence, we firstdetermined which SIC industries had op-erations in oversight members" districts.Our first measure is simply the number ofoversight committee members’ districts inwhich the domestic industry operates.Our second measure weights each com-mittee member by the number of employ-

6. We also included the national unemploymentrate as a control. Since the regression results are vir-tually identical with either measure, we only ~portregressions with the trade deficit.

HANSEN & PRUSA: CUMULATION AND ITC DECISIONS 755

ees in the industry in each district. Thuswith this second measure, (i) large indus-tries and (ii) industries located in manyoversight districts are more influential.

A second manifestation of political im-pact on ITC decision making is interestgroup influence. As a measure, we usePolitical Action Committee (PAC) contri-butions to congressional oversight mem-bers.7 The hypothesis is that industries(via their PACs) contribute to the over-sight members’ campaigns and that morepressure will be exerted on the ITC onbehalf of those industries that made largercontributions.

Another measure of interest group in-fluence is an industry’s size. For any TitleVII case, the larger the petitioning indus-try is, the greater its electoral impact maybe; hence, larger industries can exertgreater political pressure either directly onthe ITC or indirectly through powerfulsenators and representatives. Employ-ment and output are two alternative mea-sures of industry size. Since the variablesare highly correlated and the estimationresults are quite similar using either mea-sure, we present the estimates using em-ployment as the measure of industry size.

The ability of an interest group to influ-ence policy may also be affected by itsability to effectively organize. An industrywith a large number of small producersmay find the benefits of protection toodispersed and the costs of lobbying notworth bearing. We use the four-firm con-centration ratio as a proxy for this notionof an industry’s ability to organize andpressure policymakers.

Countryflndustry Biases

Evidence suggests that the identity ofthe named country in a antidumping orcountervailing duty petition influencesITC decisions. We control for country-spe-

7. See Grossman and Helpman [1994] for a modelhighlighting the importance of political contributionsto the policymaking process.

cific differences by including dummy vari-ables for petitions against each of thefollowing: Japan, newly industrializedcountries, West European countries, andnon-market economies. Petitions againstJapan might be treated differently in ITCdecision making because of the over-whelming negative attention that Japanreceived during the 1980s in trade-relatedmatters. Given its situation, one mightexpect that petitions against Japan wouldbe more likely to receive a positive ITCruling. Similarly, the rapid export-orientedgrowth of the newly industrialized coun-tries might hurt them in ITC hearings. Onthe other hand, the historically strong re-lationship and trade ties between Europeand the U.S. may lead to more favorabletreatment for their industries. Finally,cases filed against non-market economiesmay tend to be more successful, bothbecause of cold-war suspicions and alsobecause of the heavy reliance on "con-structed value" measures of home marketperformance when non-market economiesare involved (see Tharakan [1991] for adiscussion).

Finally, we also control for the fact thatsteel and steel-related industries were byfar the largest users of Title VII lawsduring the 1980s. The notion here is thatpetitions filed by steel and steel-relatedindustries are more successful due to thisindustry’s frequency of filing (i.e., learn-ing-by-doing) or the inordinate amount ofpublic attention steel cases tend to receive.

IV. ESTIMATING ITC DECISION MAKING

Our data set is comprised of the 770Title VII cases filed between 1980 and1988. We drop cases rejected by the Com-merce Department (since the ITC nevermakes a final decision when no unfairpractice is found). We also drop with-drawn cases which receive no official ITCdetermination. In addition, since most ofour measures of economic criteria are un-available for the agricultural sector, werestrict our sample to manufacturing in-

756 ECONOMIC INQUIRY

dustries. We also drop countervailing dutycases against industries located in coun-tries that have not signed the GATr sub-sidy code since an injury decision is notrequired for these countries. After drop-ping these cases, we have data for 317 ITCdecisions. We estimate the ITC decisionfunction for all Title VII cases, and sepa-rately for just antidumping cases.8

Our probit estimates are given in TableIII and IV. In Table III we present fourspecifications of the estimated ITC deci-sion function, allowing for different mea-sures of political pressure and cumula-tion.9 In Table IV we test whether discre-tionary and mandated cumulation haddifferent effects on the ITC.

General Findings

Several general findings emerge fromthe estimations. First, we find that politi-cal pressure has an important influence onITC decisions. Second, petitions are morelikely to result in duties when the case isfiled against non-market economies andless likely when filed against Europeancountries. Third, we find that the U.S. steelindustry has fared particularly well in ITCdecisions. Finally, cumulation crucially in-fluences the ITC. Below we briefly discussthe results. An extended discussion of theimportance of the estimated effect of cu-mulation is contained in section V.

Political Pressure. Supporting the findingsof Hansen [1990], industries with repre-sentatives on the Ways and Means Com-mittee have a greater chance of receivingprotection; Senate Finance oversight rep-resentation, however, appears to be ume-lated to ITC decision making. It is not sur-prising that the House oversight influence

8. We also estimate rite ITC decision function forlast countervailing duty cases, but to ~ the paperreasonable lengfla, we do not pre~ent the results here.

~t.T~e~ ~essions are available upon request from the

9. Year dummies are included but not reportedclue to space limitations. They are available upon re-quest.

is more significant because House mem-bers have a much more geographicallynarrow constituency and therefore morenarrowly defined interests; a firm filing atrade petition will surely affect a largerfraction of a House member "s constituentsthan a senator’s.

PAC contributions also appear to bepositively related to an industry’s pros-pects for protection. In all four specffica-tions and for both the antidumping-onlydata set and the entire Title VII data set,the impact of PAC contributions is posi-tive, but it is significant only for anti-dumping cases.

Economic Criteria. The percentage changein capacity utilization and the percentagechange in shipments are proxies forchanges in the industry’s economic health.While both variables have the expectedsign (i.e., increases in either capacity utili-zation or shipments lowers the chance ofprotection) neither is significant. AlthoughHansen [1990] and Moore [1992] find somesupport for economic decline predicting1TC decisions, we feel that the insignifi-cance of the economic criteria reflects thegreat degree of latitude that the ITC hasin making its decisions--statutory guide-lines, which define the factors that deter-mine injury and what level of injury con-stitutes "material" injury are extremelyvague. This also explains why well-de-fined political pressure variables playsuch an important role.

Import market share has a positive andsignificant effect on 1TC decisions. Thisimplies that the larger a country’s importmarket share, the more likely the ITC willfind injury. Given domestic industries" tes-timony preceding the cumulation amend-ment, this finding was expected.

Country- and Industry-Spec~c Effects. Im-portantly, we find the existence of coun-try- and industry-specific biases. For in-stance the European dummy is consis-tently negative and significant, suggesting

HANSEN & PRUSA: CUMULATION AND ITC DECISIONS 757

that the ITC is reluctant to find injurywhen imports are from the U.S.’s Euro-pean allies. In contrast, cases against non-market economies fare particularly well;the coefficient on the non-market dummyis large, positive, and significant. We findthat there is no significant country effectfor Japan and newly industrialized coun-tries. We do find, however, that the steelindustry, the largest single user of Title VIIlaw, does quite well at the ITC: the steeldummy is consistently positive and signif-icant.

Estimating Pre- and Post-1984 CumulationEffect

The data presented in Table II suggestthat cumulation had a more protectiveeffect once Congress mandated its use.The most straightforward way to test forthis is to simply add a regressor thatcaptures the post-1984 cumulation effect.In specification E (Table IV) we estimate

Outcomei = (z + ~lXi + 71Ci + ¥2(D~i) + (PYi,

where Xi is a vector of all variables in themodel except the cumulation effect, Ci,and year dummies, Yi; Di is a post-1984dummy variable. Thus, ¥i is the pre-1984and T1 + T2 the post-1984 cumulation effect.

Specification E can be applied to any ofthe four specifications estimated in TableIII; the results in Table IV should be com-pared with specification A. As in Table III,we omit year dummies from the table. Inaddition, to conserve space, we do notpresent t-statistics, but rather only Indi-cate which variables are significant.1°

The estimates suggest that once cumu-lation was mandated, it had a greaterimpact on rrc decision making. For boththe Title VII and antidumping-only datasets, 72 is positive and significant, while

10. Complete estimation results are available uponrequest.

71 is insignificant. However, in neitherdata set is the estimate of T2 statisticallydifferent from the cumulation effect esti-mated in specification A.

As discussed above, the ITC may haveinterpreted the passage of the Trade andTariff Act of 1984 as a signal to becomemore protectionist, and this change in be-havior may manifest itself in all of theexogenous variables. If this is indeed thecase, we need to estimate a function thatallows for more general structural changesin ITC decision making post-1984. In spec-ification F we estimate

Outcom~ = vt + ~lXi + 71Ci + 6lDi

+ 1~2(DiXi) + 72(D~i) + ~PYi"

Once again, we report estimates thatshould be compared with those in modelA. While a number of the exogenous vari-ables have significant post-1984 effects,the most important finding for our pur-poses is that cumulation has a statisticallygreater effect after 1984. However, as wasthe case for specification E, the estimatedpost-1984 effects are not statistically dif-ferent from those reported in specificationA.

We perform a chi-squared test in orderto investigate the overall significance ofthis more general model (specification Fvs. A). We find that for the antidumping-only data set there is no evidence of ageneral change in ITC behavior (at the 95percent confidence level). However, forthe Title VII data set, there is evidence thatthe 1984 trade act may have caused theITC to become more protectionist.

V. SIGNIFICANCE OF CUMULATION

Most relevant to this work is the factthat cumulation is positive and statisti-cally significant across all specificationsfor both the Title VII and antidumping-only data sets. In Table V we presentseveral measures of the importance of the

Constant

TABLE IIIProbit Estimation*

Title VII CasesSpecification

A B C D-0.676 -0.704 -0.669 -1.228(-0.885) (-0.922) (-0.878) (-1.873)

# Representatives 0.146 0.114 0.133Ways & Means Districts (2.292) (1.744) (1.985)# Representatives -0.056 -0.064 -0.057Senate Finance States (-1.190) (-1.384) (-1.245)Emplo _yment inOversight Districts -0.280

(-1.145)Employment -0.945 -0.599 -0.415

(-0.789) (-0.491) (-0.330)PAC 0.745 0.675 0.683 0.915Contributions (1.262) (1.145) (1.172) (1.558)Concentration -0.546 -0.759 -0.690 -0.898Ratio (-0,663) (-0.926) (-0,856) (-1.351)Tariff -2.537 -2.921 -2.373 -2.582(-0.797) (-0.924) (-0.749) (--0.889)Foreign 0.047 -0.056 0.082 -0.079Penetration (0.065) (-0.077) (0.114) (-0,112)% Change 1.997 -0.835 0.805 -3.703Trade Deficit (0.403) (-0.173) (0.163) (-1.031)% Change -0.554 -0.609 -0.628 -0.891Capacity Utilization (-0.950) (-1.023) (-1.067) (-1.518)% Change -0.017 -0.106 -0.024 -0.581Shipments (-0,020) (-0.126) (-0.029) (-0.709)Named Country’s 1.974 1.943 1,839 1.686Market Share (3.936) (3.882) (3.701) (3.425)Less-Than-Fair-ValueDuty 0.582 0,612 0.699 0.665(1.754) (1.802) (2.030) (1.978)

Non-Market 0.965 0.939 0.903 0.908Dummy (2.319) (2.191) (2.141) (2.067)

A

Antidumping CasesSpecificationB C D

-0.389 -0.290 -0.413 -1.085(-0,414) (-0.310) (-0.440) (-1.333)0.197 0.149 0.161(2.844) (2.102) (2.225)-0.052 -0.062 -0.056(-1.029) (-1.218) (-1.106)

-0.125(-0,444)

-1.419 -0,740 -0.568(-1.064) (-0.536) (-0.397)

1.160 1.069 1.040 1.186(1.791) (1.654) (1.623) (1.835)-0.047 -0.232 -0.305 --0.702(-0.052) (-0.256) (-0.343) (-0.944)-1.610 -2.474 -1,948 -2.465(-0.451) (-0.695) (-0.544) (-0.743)0.094 --0.024 0.175 0.064(0.119) (-0.030) (0.222) (0.083)7.656 5.005 5.306 -1.243(1.341) (0.905) (0.947) (-0.289)

-0.637 -0.785 -0.735 -0.935(-0.961) (-1.148) (-1.083) (-1.387)0,749 0.658 0.567 -0.107(0.702) (0.620) (0.536) (-0.104)1.591 1.492 1.487 1.365(2.815) (2.669) (2.655) (2.457)

0.604 0.669 0.743 0.728(1.721) (1.854) (2.025) (2.040)0.993 0.940 0.958 0.974(2.284) (2.077) (2.138) (2.118)

TABLE III continuedProbit Estimation*

Title VII CasesSpecification

A B C D

Europe -0.498 -0.570 -0.473 -0.576Dummy (-2.245) (-2.526) (-2.035) (-2.485)

Newly Indus. Country 0.068 0.139 0.123 0.244Dummy (0.233) (0.486) (0.426) (0.854)JaPi~nm -0.116 -0.092 -0.137 -0,127

y (-0.383) (-0.303) (-0.443) (-0.424)

Steel Industry 0.811 0.876 0.424 0.754Dummy (3.169) (3.404) (1.450) (2.492)

Cumulation 0.670Dummy (2.969)Other Named Countries’ 2.121 1.292 1.945Cumulated Market Share (2.834) (1,608) (2.767)

Cumulation x Steel 0.994 0.817(3.132) (2.617)

Antidumping CasesSpecification

A B C D

--0.453 -0.616 -0.478 -0.555(-1.626) (-2.116) (-1.592) (-1.873)

0.081 0.151 0.164 0.271(0.253) (0.473) (0.509) (0.854)-0.051 -0.054 -0.060 -0,068(-0.158) (-0.168) (-0,184) (-0.216)

0,781 0.846 0.417 0.671(2.773) (2.977) (1.249) (1.927)0.805(3.103)

3.126 2.263 2,807(3.280) (2,256) (3.166)

0.866 0.731(2.399) (2.055)

Log Likelihood -159.646 -159.807 -154.738 -156.874Chi-Squared Test 114,232 113.909 124.047 125.553# Observations 313 313 313 317# Observations Positive 151 151 151 155% Observations Positive 48,2% 48.2% 48.2% 48.9%

% Correctly Predicted 76.0% 74.8% 78.3% 76.7%

-114.396 -113.032 -110.095 -113.02488.645 91.374 97.247 96.274

230 230 230 234124 124 124 12853.9% 53.9% 53.9% 54.7%75.7% 75.2% 76.5% 75.2%

*t-statistics ~por~ed in parentheses

HANSEN & PRUSA: CUMULATION AND 1TC DECISIONS 761760 ECONOMIC INQUIRY

TABLE IVPre- and Post-1984 Effect

Title VII Cases Antidumping CasesSpecification SpecificationE F E F

-0.527 -1.324 -0.541 -1.6030.122" 0.057 0.164"* 0.145

Constant# Representatives Ways & Means Districts# Representatives Ways & Means Districts x

Post-1984 Dummy-# Representatives Senate Finance States# Representatives Senate Finance States x

Post-1984 DummyEmploymentEmployment x Post-1984 DummyPAC ContributionsPAC Contributions x Post-1984 DummyConcentration RatioConcentration Ratio x Post-1984 DummyTariffTariff x Post 1984-DummyForeign PenetrationForeign Penetration x Post-1984 Dummy% Change Trade Deficit% Change Trade Deficit x Post-1984 Dummy% Change Capacity Utilization% Change Capacity Utilization x Post-1984 Dummy% Change Shipments% Change Shipments x Post-1984 DummyNamed Country’s Market ShareNamed Country’s Market Share x Post-1984 DummyLess-Than-Fair-Value DutyLess-Than-Fair-Value Duty x Post-1984 DummyNon-Market DummyNon-Market Dummy x Post-1984 DummyEurope DummyEurope Dummy x Post-1984 DummyNewly Indus. Country DummyNewly Indus. Country Dummy x Post-1984 DummyJapan DummyJapan Dummy x Post-1984 DummySteel Industry DummySteel Industry Dummy x Post-1984 DummyCumulation DummyCumulation Dummy x Post-1984 DummyPost-1984 Dummy

0.22 0.12-0.027 0.092 -0.019 0.072

-0.271"* -0.223-0.92 -1.08 -1.363 -2.597

-0.435 1.6670.842 0.782 1.168" 0.926

-0.723 -0.972-0.316 -1.609 -0.001 -1.483

4.524** 4.243*-3.288 -0.779 -1.926 2.023

-5.659 -5.5870.04 .2.054** 0.17 2.056*

--4.548"* -3.996**5.218 0.657 8.644 -0.061

1.095 2.981-0.561 0.007 -0.618 0.076

-1.606 -1.8910.038 -0.828 0.429 0.662

1.881 -0.6621.931"* 1.331" 1.562"* 1.350"

1.8O8 1.2380.632* 0.165 0.635* 0.497

0.77 0.2470.894** 0.696 0.956** 0.701

0.264 0.26-0.560** -0.373 -0.505* -0.284

-0.818 -0.7510.117 -0.227 0.134 0.029

0.396 0.064-0.126 -0.118 -0.056 0.079

-0.252 -0.3720.782** 0.045 0.732** 0.312

1.055" 0.493-0.034 0.004 0.232 0.09

1.152"* 1.196"* 0.949* 1.238"0.212 0.51

Log Likelihood -156.671 -138.935 -112.975 -100.245Chi-Squared Test 120.181 155.653 91.488 116.948# Observations 313 313 230 230# Observations Positive 151 151 124 124% Observations Positive 48.2% 48.2% 53.9% 53.9%% Correctly Predicted 77.0% 77.6% 77.0% 79.6%

*denotes significance at 10% level, ** significance at 5% level (two-tailed tests)

I

762 ~ECONOM!C INQUIRY HANSEN & PRUSA: CUMULATION AND 1TC DECISIONS 763

cumulation provision on ITC decisions.Using the parameter estimates presentedin Tables III and IV we calculate thechange in the probability of protection dueto cumulation evaluated at the mean valueof the other independent variables. Theestimates imply that not only is cumula-tion significant, but also it has a substan-tial effect on outcomes. For instance, forall Title VII cases, cumulation increasesthe probability of protection by more than20 percent, while for antidumping cases,cumulation increases the probability ofprotection by about 30 percent.

Given this dramatic effect on the prob-ability of protection, it is not surprisingthat cumulation crucially determineswhether or not protection is granted in alarge number of cases. For instance, for thedata set induding all Title VII cases (spec-ification C), 112 of the 313 observationswere cumulated. Based on our parameterestimates, of these 112 cumulated cases, 38(34 percent) would have been negativelydecided without cumulation, but were af-firmatively decided with cumulation. Thepercentage of cumulated cases where theoutcome changes due to cumulation var-ies according to the specification (from 18percent to almost 50 percent for the anti-dumping-only data set), but is always asizable number.

Further, note that changing the out-come of cases is only the immediate im-pact of cumulation; ultimately, the affir-mative ITC decision leads to the imposi-tion of a duty and therefore an effect ontrade. In the last row of Table V we reportthe average duty for cases where cumula-tion changes the predicted outcome. Asevidenced, duties are quite large for thesecases, averaging about 20 percent per case.Given that the average tariff level is about4 percent, the additional protection due tocumulation is substantial.

Most interestingly, our results implythat cumulated imports have a super-ad-ditive effect on ITC decisions. To illustratethis point, in Figure 1 we plot the esti-

mated probability of an affirmative anti-dumping decision as a function of the totalmarket share of imports under investiga-tion. All other independent variables arevalued at the sample mean and the coeffi-cients are from specification C. We plotthree hypothetical scenarios. First, weimagine the petition is filed against asingle country. Second, we suppose thatthe domestic industry files antidumpingpetitions against two countries, assumingthat each country accounts for half theimports under investigation. Finally, wesuppose that the domestic industry filesmultiple antidumping petitions againstfive countries, each accounting for 1/5 ofthe imports under investigation.

The figure makes the protective effectof cumulation clear. Even though equiva-lent amounts of imports are under inves-tigation in each of the scenarios, the casesinvolving cumulation have a greater prob-ability of succeeding. Furthermore, theeffect of cumulation becomes more pro-nounced the greater is the share of importsunder investigation accounted for byother named countries. That is, for alllevels of market share the probability ofan affirmative decision when importsfrom five countries are cumulated liesabove that for two countries, which inturn lies above the probability when onlya single country is being investigated.

Consider for instance, the probability ofan affirmative decision when 40 percent ofimports are under investigation. If the caseinvolves a single country, the probabilityof an affirmative decision is estimated tobe 0.60. If petitions are filed against twocountries, each with 20 percent of theimport market (yielding a cumulated mar-ket share of 40 percent) the estimatedprobability of an affirmative decisionjumps to 0.72. If petitions are filed againstfive countries, each with 8 percent of theimport market the estimated probabilityof an affirmative decision is 0.78.

This is a startling result. Under the 1984statute the 1TC should treat each of the

90%

80%

70%

60%

50%-

FIGURE 1

5 Firms(115 from named country,

415 from cumulated countries)

2 Firmsl,/// /" (1/2 from named country,/ / / I/2 from cumulated countries)

/~.-/--,,

30%"0% 20% 40% 60% 80%

Market Share of All Importers Under Investigation

scenarios identically. Forty percent of theimport market is under investigation ineach scenario. If anything, one might ex-pect the ITC to perceive an equivalentamount of cumulated imports as less inju-rious, since commissioners might not beinclined to punish small countries for thetransgressions of others. To the contrary,our estimates imply that the ITC perceivescumulated imports as substantially moreinjurious.

In order for a case against a singlecountry to be as likely to receive protec-tion as when two countries (each with 20percent of the import market) are underinvestigation, that single country wouldhave to account for 62 percent of theimport market; for a case against a singlecountry to be as likely to receive protec-tion as when five countries (each with 8percent of the import market) are underinvestigation, that single country wouldhave to account for 75 percent of theimport market. In other words, cumulated

imports have a super-additive effect onITC decisions. This surprising findingleads us to conclude that at least withrespect to ITC decision making the sum ofthe parts is greater than the whole.

Table VI presents the effect of cumula-tion on predicted outcomes for severalselected antidumping cases which hadpositive ITC decisions. For instance, con-sider again the "Brass sheet and strip"antidumping petition discussed above inTable I. The import market share for thesecountries ranged from West Germany’s 21percent to Sweden’s 1 percent, and thecumulated import market share was 38percent. With the cumulation provision ineffect the ITC found that each of the sevennamed countries had caused injury to theU.S. industry and thus import duties of 7percent to 42 percent were levied on brasssheet and strip imports. Without cumula-tion, however, some of the countrieswould not have been subject to duties. Forinstance, under the parameter estimates

TAB

LE V

IP

redi

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Out

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es w

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t Cum

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Mar

ket

Less

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AB

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Pot

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126

Spa

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49.7

2%21

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5.49

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5P

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21.8

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.72%

27.8

3%39

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AA

AA

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Col

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levi

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rs13

4S

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.29%

56.9

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13.9

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AA

AA

A13

5Ta

iwan

25.7

0%56

.98%

31.2

9%5,

46%

NN

NA

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Iron

con

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dia

28.7

3%68

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40.1

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90%

AN

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263

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19.4

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49.3

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.20%

AN

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262

Bra

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12.6

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56.2

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265

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81%

38.3

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40.6

2%A

AA

AA

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3Fr

ance

3.78

%38

.35%

34.5

7%42

.24%

AA

NN

NN

314

Italy

3.27

%38

.35%

35.0

8%12

.08%

NN

NN

NN

315

Sou

th K

orea

2.20

%38

,35%

36.1

5%7.

17%

AA

AA

AA

312

Can

ada

1.83

%38

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36.5

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AA

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NA

316

Sw

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1.20

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37.1

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386

Japa

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29.9

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29.9

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46.4

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410

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82%

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bass

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426

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9.43

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28.7

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427

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nega

tive.

766 ECONOMIC INQUIRY HANSEN & PRUSA: CUMULATION AND ITC DECISIONS 767

the likelihood that the other named coun-tries are also sanctioned. In a noncoopera-tive game, each country’s profits will behigher if the other named countries arealso subject to duties. If each country actsstrategically, the final outcome might in-volve all of the countries being disadvan-taged (as compared to when the countriesare not cumulated).

There are several empirical concernsthat should be mentioned. For example,occasionally cases are cumulated withcases that had been previously filed. AU.S. industry might file an antidumpingpetition against Taiwan and Brazil, andthen several months later file another pe-tition against Korea. In this circumstance,all three cases could be cumulated as longas the three criteria stipulated in the 1984amendment are satisfied, even though thecases were not filed simultaneously. How-ever, suppose that some information from.the Taiwan and Brazil investigations hasbeen revealed (e.g., say, a preliminary af-firmative decision), then the likelihood ofan affirmative decision against Koreamight be affected. In the results presented,we would attribute the "increased proba-bility" entirely to cumulation, where infact the higher probability may be due inpart to the sequential nature of the filings.In fact, even without the cumulation pro-vision the cases might be linked due to theinformation revealed about the ITC’sopinion on the health of the domesticindustry. To check for this possibility, wedrop cumulated cases that were cumu-lated with previously filed cases and esti-mate the model. Not surprisingly, sinceonly seven cases were dropped, the pa-rameter estimates are almost identical tothose presented in Tables III and IV.

Another issue is the fact that a numberof ITC commissioners have used "bifur-cated analysis" when making their injurydecisions. A commissioner choosing to usea bifurcated approach essentially makes atwo-stage injury decision (see Kaplan[1991] for a discussion). First, the commis-

sioner decides if injury exists. If so, thenthe commissioner decides whether or notimports are the cause. Under a bifurcatedapproach, cumulation would only affectthe outcome if the test gets to the secondstage. Thus, potentially our estimates ofthe cumulation effect might be biased ifthe following four criteria are met: (i) thecase was cumulated, (ii) ITC commission-ers used a bifurcated approach in makingtheir injury decision (iii) the ITC’s decisionis negative, and (iv) the case was negativeat the first stage of the bifurcated analysis.

However, we expect our parameter es-timates to be robust whether or not abifurcated approach was used since ourexogenous variables control for bothstages of the decision process. Nonethe-less, we estimated our model dropping thepotentially problematic cases (onlytwenty-one cases satisfied the above fourcriteria). The parameter estimates are es-sentially unchanged.

Finally, we should note that the 1984Trade Act made a number of changes toTitle VII statutes in addition to the cumu-lation provision. Allowing upstream sub-sidies to be countervailable and the ex-panded definition of "like" product weretwo of the more significant amendments.While it is conceivable that part of theprotective effect that we attribute to thecumulation provision might be due theseother amendments, we believe our estima-tion has identified the cumulation effectsince the circumstances when these otheramendments are relevant are unlikely tosystematically coincide with cases thatwere cumulated.

In conclusion, we hope that our re-search draws increased attention to theprotective effects of congressional amend-ments to the U.S. trade statutes. Otherstatutory and procedural amendmentshave likely also had a significant impacton the overall level of protection in theU.S. For instance, allowing the use of ’~vestinformation available," making upstreamsubsidies countervailable, and expanding

768 ECONOMIC INQUIRY

the definition of "like product" are allexamples of revisions that were intendedby Congress to make Title VII laws moreprotective, but whose ultimate impact isunknown.

We also hope that our research drawsattention to the apparent movement to-wards procedural protectionism. While inrecent years Congress has largely resistedthe rising pressures from U.S. industriesto grant them direct protection from for-eign imports, it has in fact moved the U.S.towards a policy of greater protectionism.To appease U.S. industries, Congressamended existing U.S. trade laws in orderto make them more accessible to indus-tries subject to trade pressures. As theresults of this paper indicate, theseamendments may have unforeseen im-pacts on policy outcomes and interna-tional patterns of trade.

DATA APPENDIXBasic Case Information: Case outcome, date ofinitiation, subject, and named country is avail-able in the Fed-Track Guide to Antidumping andCountervailing Duty Findings and Orders. Im-ports subject to investigation are identified inthe Federal Register by their TSUSA (line-itemtariff) code. The less-than-fair-value duty isalso found in the Federal Register. The four-digitSIC code corresponding to the TSUSA code canbe found in U.S. Foreign Trade Statistics, Sched-ule 6.

Cumulation Data: The public ITC case reportscontain information on which countries’ im-ports were cumulated. Not all multiple countryfilings are cumulated. For example, due toquality differences some imports in multiple-country petitions were determined not to com-pete with one another, and thus were not cu-mulated. Petition filing data in the Fed-Trackguides helped us construct the experiment in-volving mandatory cumulation for all pre-1984multiple country petitions.Capacity Utilization (practical rate) at the four-digit SIC level by year was obtained from theU.S. Bureau of the Census Current Industrial Re-ports, Survey of Plant Capacity.

Shipments and Employment at the four-digit SIClevel by year was obtained from the U.S. Bu-

reau of the Census Census of Manufactures, Sub-ject Series.

Concentration Ratio at the four-digit SIC levelby year was obtained from the U.S. Bureau ofthe Census Census of Manufactures, Industry Se-ries.

Civilian Unemployment Rate is given in the Eco-nomic Report of the President. The merchandisetrade deficit (millions of dollars) is also givenin the Economic Report of the President.

Oversight Committee Data was measured bymatching four-digit SIC industry location withcongressional districts. Typically, each product(which is identified by a SIC code) is producedin a number of locations across the country. Ifa product is produced in a district whose con-gressional representative (House or Senate) isa member of the Trade Subcommittee of theHouse Ways and Means Committee or the In-ternational Trade Subcommittee of the SenateFinance Committee, then the industry is be-lieved to have a greater ability to influence ITCpolicymaking through its political pressure.The Almanac of American Politics was used todetermine subcommittee membership. Datafor industry location (and employment) by dis-trict and year at the four-digit SIC level wereobtained from the Census of Manufactures, Geo-graphic Area Series.

PAC Contributions to oversight members wereconstructed using the Federal Electioncommission’s publicly available Campaign Ex-penditures in the United States Reports on FinancialActivity (RFA) data. The Federal Election Com-mission reports conh-ibutions by each PAC toeach representative and each registered candi-date. Each PAC is also coded with a (self-re-ported) "special interest group" classification.The major task is to construct a concordance be-tween PACs and SIC industry definitions with-out biasing the estimation procedure. The Fed-eral Election Commission’s special interestgroup classification is inadequate, offering onlya handful of different codes. In order to create aconcordance we used the Center for ResponsivePolitics PAC coding scheme (Makinson [1989]).The Center for Responsive Politics assigns eachPAC one or more category codes which denotethe industry and/or groups the committee rep-resents. The first category is the PAC’s primaryindustry affiliation, the second is the next mostimportant, etc. The Center’s categories are rela-tively detailed, offering almost 400 category

HANSEN & PRUSA: CUMULATION AND ITC DECISIONS 769

codes and greatly help in identifying what in-dustry is represented by which PACs. Unfortu-nately, the Center’s categories were not devel-oped with the aim of mapping into SIC industrycodes, and so the classification process is stillsomewhat arbitrary. Where possible we as-signed the Center’s categories a four-digit SICcode, but it was often difficult to go beyond two-digit SIC codes. The results reported in thispaper are based on PAC contribution at the two-digit SIC level. PAC data is coded in millions ofdollars.

Country and Steel Dummies: Non-market econo-mies are defined as East Germany, Czechoslo-vakia, Hungary, Estonia, Latvia, Lithuania, Po-land, USSR, Yugoslavia, Romania, BulgariaVietnam, People’s Republic of China, andNorth Korea. West European economies are de-fined as the United Kingdom, Ireland, theNetherlands, Belgium, Luxembourg, France,West Germany, Austria, Switzerland, Spain,Portugal, and Italy. The newly industrializedeconomies are defined as Singapore, SouthKorea, Hong Kong, and Taiwan (China). Thesteel industry was defined to include the follow-ing four-digit SIC codes: 3312, 3321, 3334, 3339,3351, 3357, 3432, 3441, 3494, 3496, 3519, 3523,3557, 3562.

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