Target, Information, and Trade Preferences: Evidence
from a Survey Experiment in East Asia
Sung Eun Kim Korea University
Jong Hee Park Seoul National University
Inbok Rhee KDI School of Public Policy and Management
Joonseok Yang
Sungkyunkwan University
Abstract: Protectionist measures often have target countries, and public support for such measures depends on who thetargets are. We identify such target effects on protectionist sentiments and examine the effects of information in tempering
protectionist sentiments in East Asia. Using an original survey experiment in China, Japan, and South Korea, we test how
providing information about the costs of protectionism changes public attitudes toward targeted protectionist measures. We
found that providing a target country identity increased public support for protectionism by 8.6%. Providing cost information, on the other hand, reduces support for protectionism by 10%. We also found that information and target effects persist
in the presence of the other: Receiving cost information reduces support for both general and targeted protectionism but does
not necessarily mute the target effect. Similarly, when reputation and retaliation costs are associated with protectionism,
knowing a target country identity still increases public support for protectionism.
Verification Materials: The data and materials required to verify the computational reproducibility of the results, procedures and analyses in this article are available on the American Journal of Political Science Dataverse within the Harvard
Dataverse Network, at: https://doi.org/10.7910/DVN/BXPKHG.

E

xisting studies of individual trade preferences
have examined general public sentiments toward government policy on international trade(e.g., Mansfield and Mutz 2009; Scheve and Slaughter2001). But protectionist measures often have either implicit or explicit targets. Especially in the context of the“weaponization” of trade (i.e., the use of trade as a coercive tool in political disputes), citizens’ support for suchprotectionist measures is highly dependent on the identity of the target country.
Despite the importance of target-related factors inpublic support for protectionist policies, few studies haveexamined empirical evidence on the effect of target-

related information on public support for protectionist
policies. Also, to our knowledge, no study has shown
whether the provision of information concerning thecosts of such measures can temper protectionist sentiments toward the target country. In this article, wetackle these questions using an original survey experiment fielded in China, Japan, and South Korea.
The coexistence of deep economic integration andrecurring trade disputes spurred by political tensions inEast Asia provides a unique opportunity to test the effects of target identity and cost-related information on
public support for protectionist measures. East Asia is
one of the most integrated regions in the world, with aSung Eun Kim, Associate Professor, Department of Political Science and International Relations, Korea University, 145 Anam-ro,
Seongbuk-gu, Seoul, Korea, 02841 Jong Hee Park, Professor, Department of Political Science and International Relations, Seoul National University, 1 Gwanakro, Gwanak-gu, Seoul, South Korea, 151-746 Inbok Rhee, Associate Professor, KDI School of Public Policy andManagement, 263 Namsejong-ro, Sejong-Si, South Korea, 30149 Joonseok Yang, Assistant Professor, Department of Political Science andDiplomacy, Sungkyunkwan University, 25-2 Sungkyunkwan-ro, Seoul, South Korea, 03063
We are grateful to Han Il Chang, Brandon Ives, Haillie Na-Kyung Lee, Sijeong Lim, Chungshik Moon, Taehee Whang, Byungwon Woo,and attendees of the Political Economy Workshop in Seoul held in March 2021 for very helpful comments and suggestions. We also thankSeowoo Chung, Sunhee Kim, Sara Lim, Sangyong Son, Junwoo Suh, and Yehzee Ryoo for exceptional research assistance and for the KDI
School of Public Policy and Management for administrative assistance. The authors’ names are in alphabetical order. Authors contributed
equally to this work. This research was supported by the National Research Council for Economics, Humanities and Social Sciences (2020068). Sung Eun Kim was supported by the Korea University Research Grant (K2302471). Jong Hee Park was supported by the Ministry of
Education of the Republic of Korea and the National Research Foundation of Korea (2021S1A5A2A01066158).
American Journal of Political Science, Vol. 0, No. 0, February 2023, Pp. 1–17
© 2023, Midwest Political Science Association.

DOI: 10.1111/ajps.12783

1

significant share of intraregional trade and a high dependence on intermediate trade (Athukorala 2011; Nguyen
and Wu 2020).1 Trade volumes in intermediate goods
have consistently increased over the past two decades,
making countries in the region indispensable trade partners to each other (Obashi and Kimura 2018). However,deep economic integration has not ameliorated political tensions among East Asian countries and instead is“weaponized” at times, with countries responding to political tensions using economic measures.
What makes the case of East Asian countries particularly interesting is the fact that citizens not only show
strong support for trade restrictions but also engage ineconomically costly political actions, such as large-scaleconsumer boycotts against target countries despite theirown country’s economic interdependence with the target(Li and Liu 2017; Vekasi and Nam 2019).
For instance, when the Japanese government restricted exports of semiconductor manufacturing materials to South Korea over historical disputes,2 more than
70% of Japanese citizens favored the government’s export controls.3 Between China and Japan, disputes overthe Diaoyu/Senkaku Islands triggered the mobilizationof Chinese consumer boycotts of Japanese products (Liand Liu 2017). East Asia therefore presents itself as a hardcase for testing the effects of cost-related information on
individual trade preferences.4
In untangling public support for targeted protectionism in East Asia, we first divide the costs ofprotectionist policy into three categories (retaliation
cost, interdependence cost, and reputation cost) andexamine how different types of cost-related information
affect public attitudes toward targeted protectionism.
First, a target country may retaliate against the initiator’s
protectionist policy by restricting trade with the initiator.
This retaliation imposes economic costs on affected industries in the initiating country. Second, a country’s useof protectionist measures can be costly to its own economy due to economic interdependence with the target.
Even without any retaliation from the target, restricting
imports from the target can be economically costly for1

As of 2017, intraregional trade accounted for 36% of total tradein East Asia (statistic from Asia Regional Integration Center, ADB,
accessible at https://aric.adb.org).

2

Ministry of Economy, Trade, and Industry 2019.

3(Cho 2019).

4

Similar trilateral relations exist in every corner of international relations. In social network theory, the triadic relationship is viewed
as a microcosm of a larger network. Thus, examining three countries that share history, culture, and economic transactions canshed light on how information affects protectionist sentiments
against multiple neighboring countries.

SUNG EUN KIM et al.

an initiating country that is dependent on trade with its
target. Lastly, an initiating country may pay reputationalcosts for violating World Trade Organization (WTO)
rules. The targeted country may file a complaint with
the WTO accusing the initiator of adopting protectionist
measures, which can cause a loss of reputation.
To estimate the effects of different types of costrelated information on public support for targeted
protectionism, we designed a survey experiment using
respondents in China, Japan, and South Korea (2,259
subjects from China, 2,392 subjects from Japan, and2,101 subjects from South Korea). Our survey experiment randomly switches (1) the information on the costof protectionism and (2) the main target of the trade
restriction measures planned by respondents’ homecountries. More specifically, we assigned survey respondents to one of four hypothetical cases that specify thecost condition (no information, retaliation cost, economic interdependence cost, and reputation cost) andthree different targets (an unnamed foreign country andtwo neighboring countries). We were able to estimate thedistinct effects of target information (e.g., the effect ofknowing who the target country is) and cost information(e.g., the effect of knowing the cost of a protectionist
policy), as well as the effects of target-specific information (e.g., the effect of reputation cost information froma protectionist policy aimed at a specific target country),using this factorial design.
The results of our experiment reveal that knowing
about a target country identity as one of two neighboring countries raised public support for protectionism
by 8.6% among Chinese, Japanese, and South Korean
respondents, compared to not knowing about a target
country identity. Providing cost information (economic
interdependence, reputation, or retaliation), on the other
hand, reduces public support for protectionism by 10%,compared to not knowing about costs accompanied byprotectionist measures. Our findings suggest that individuals weigh a variety of costs and benefits in forming
their trade preferences: individuals take into account not
only cost-related information but also a target country
identity, which existing research on public support for
trade policies have paid scant attention to.
Our findings also allow us to investigate the conditional effects of target (cost) information when cost
(target) information is provided. These conditional
effects help us better grasp how “persistent” the impactsof each knowledge are. We found that information effects
and target effects are sticky in the sense that receiving
cost (target) information decreases (increases) support
for both general and targeted protectionism but does notnecessarily mute the effect of target (cost) information.

15405907, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/ajps.12783 by Korea University Library, Wiley Online Library on [09/04/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License2More specifically, knowing a target country identity still
increases public support for protectionism either when
no information is provided or when reputation and retaliation costs are associated with protectionism. Also,
knowing cost information still decreases public support
for protectionism either when no target identity is provided or when China and South Korea are presented astarget countries. When we decompose these effects at thecountry level, we found that the average effect of cost information is driven by respondents in Japan and South
Korea, while Chinese respondents do not show statistically significant preference shifts away from targeted protectionism after receiving cost information.

Trade Partners, Information, andIndividual Attitudes toward Trade
Existing accounts of individual trade preferences examine public attitudes toward international trade in general,
without considering specific trade partners. The interestbased explanations consider the distributive effects oftrade liberalization (e.g., Mayda and Rodrik 2005).
However, a series of studies provide evidence that
individual trade preferences are not necessarily consistent with the predictions of standard economic models(Hafner-Burton et al. 2017; Rho and Tomz 2015). Rho
and Tomz (2017) suggest that economic ignorance accounts for the gap between economic self-interest andtrade preferences, and this gap can be bridged by providing information on the distributional consequencesof international trade. Studies indeed find that individual citizens can learn about trade policies’ implications
for their own well-being via personal experience or fromcoworkers, politicians, or labor unions and align theirpreferences with their material interests (e.g., Dür andSchlipphak 2021; Fordham and Kleinberg 2012; Margalit
2011; Naoi and Urata 2013).
One trend in this literature on individual tradepreferences is the increasing use of survey experiments.5
Hiscox (2006) was one of the first to examine the effects
of issue framing on trade preferences. The study findsthat individuals are sensitive to information on thepossibility of job losses from international trade, whichmakes them far less likely to support international trade,
whereas protrade information has no discernable effecton public attitudes.
Another line of studies examines how individuals
consider the effects of international trade on their national economy. For instance, Mansfield and Mutz (2009)5

For a comprehensive overview, see Kuo and Naoi (2015) and Naoi
(2020).

show that individuals form attitudes toward international trade based on their understanding of how theircountry as a whole is affected by it. In a similar vein,
Schaffer and Spilker (2019) examine how information on
the effects of international trade on a country as a wholeshapes individual preferences. They find that individuals are more sensitive to egocentric information, whereassociotropic information only amplifies the existing egocentric effect.
Following this line of research, we further examine
how individuals consider trade policy’s impact on theirtrading partners’ economies in addition to their own
economy. One country’s protectionist policy against another country may incur costs for both the initiator andthe target due to economic interdependence. We examine
how information about different types of costs of protectionism affects individual trade preferences toward specific trade partners.

Target Effects and Information Effects on
Support for Protectionism
In this article, we assume that public support for targeted
protectionism is subject to two theoretically distinct factors: target effects and information effects. First, individual
support for a protectionist policy may change dependingon who the target country is; we call this “target effects.”
A country’s protectionist policy often has explicit or
implicit targets. For example, on January 23, 2018, US
President Trump announced that he had imposed tariffs
on solar panels and washing machines. At that moment,
most citizens did not realize which country these tariffs
targeted. However, the next day, the media reported thatthe action “prompted outcry from China and South
Korea, the primary targets of the measure.”6 By reading
this news article, voters learned the potential target of the
Trump administration’s protectionism. In this example,
target effects would refer to the extent to which voters’
attitudes towards the Trump administration’s protectionism change when they learned which countries werebeing targeted by the policy.
Second, “information effects” refer to the extent towhich individuals change their attitudes toward a protectionist policy after receiving information. Such information can come from various sources, including government agencies, interest groups, think tanks, experts,
or news organizations. Here, we focus on the contents
of information about the cost or benefit of protectionist
6BBC, “Trump says no trade war despite Asia outcry over tariffs,”
January 23, 2018. https://www.bbc.com/news/world-42786995.

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3

TARGET, INFORMATION, AND TRADE PREFERENCESSUNG EUN KIM et al.

measures. On August 7, 2020, Canada announced thatit had imposed $3.6B in tariffs in retaliation for Trump’s
aluminum tariff.7 The information of Canada’s retaliatory tariff provides important information about the costof the Trump administration’s protectionist policy, which
could affect some voters’ attitudes toward the protectionist measure. We highlight that finding empirical evidence
that indicates what type of information is most effective
in changing voters’ support for protectionism has important implications, both theoretically and in practice.

trade partners. DiGiuseppe and Kleinberg (2019) findthat individuals were less likely to support trade agreements not only with a rival, but also with a rival of therival or a country that cooperates with the rival. Carnegie
and Gaikwad (2022) also find that citizens prefer tradingwith allies over adversaries, which provides microlevel
evidence for the security externality hypothesis. Buildingon these findings, we further contribute to the discussion
by demonstrating how provision of information affects
individual support for targeted protectionism and how
the effects depend on the targets.

Target Effects: Trade Preferences toward
Partner Countries
The formation of individual trade preferences depends
on the consideration of who the target country is. In
other words, one’s interest-based calculation or feelingsbased preferences may significantly vary depending on
trade partners. Indeed, debates on trade policy in the realworld often center on whether to expand or reduce tradewith specific countries. For example, a recent Pew Research Center poll shows that Americans who view economic ties with China as bad are “much more likely thanthose who think the nations have good economic ties
to have overall unfavorable views of China (71% versus47%).”8
Recently, a few studies began to examine whichcountries are preferred as partners for preferential trade
agreements. For example, Spilker, Bernauer, and Umaña(2018) asked respondents in Costa Rica, Nicaragua, andVietnam to choose between two hypothetical preferential
trade agreements that varied with regard to membership, scope of liberalization, environmental and labor
standards, and labor market access. The findings of theirconjoint experiment show that feelings such as sympathy
or antipathy toward particular countries are the mostimportant factor shaping people’s trade preferences in all
three countries. In all three countries, individuals were
far less likely to prefer trade agreements that include
India as a trade partner, compared to those that include
the European Union as a trade partner.
Another strand of research examines how trade preferences change depending on political relationships with
7

CBC, “Canada to impose $3.6B in tariffs in response to
Trump’s move against Canadian aluminum,” August 8, 2020
(https://www.cbc.ca/news/politics/freeland-aluminum-importstariffs-trump-1.5677757).

8

Pew Research Center, “U.S. Views of China Turn
Sharply Negative Amid Trade Tensions” August 13, 2019(https://www.pewresearch.org/global/2019/08/13/u-s-views-ofchina-turn-sharply-negative-amid-trade-tensions/).

Information Effects: Retaliation,
Interdependence, and Reputation
We consider three types of costs the initiator of a protectionist policy can incur. The first is retaliation. A
targeted country may take retaliatory actions against
the initiator’s protectionist policy. Retaliation, broadly
speaking, can take two forms—“government-driven”(or top-down) or “grassroots” (or bottom-up) retaliation. Government-driven retaliation is when a targeted
government takes counteractions to coerce the initiating
government to change the protectionist policy. Various types of retaliatory actions are available, including
antidumping and countervailing duties, export regulations, countertariffs, and noneconomic measures suchas diplomatic sanctions. For example, in response to
the Japanese government’s restriction on exports of key
semiconductor manufacturing materials to South Korea
in 2019, citizens in South Korea actively mobilized consumer boycotts against Japanese products. The Japanese
economy incurred substantial costs as a result of theboycott, mainly due to a drastic decline in sales of a wide
range of Japanese consumer goods in Korea.9
The second type of significant cost due to targeted
protectionism comes from economic interdependence. As
noted by Hirschman (1945), a high level of economic
interdependence can be an effective means of exerting
political pressure and coercion because economic interdependence is usually asymmetrical. However, the useof economic interdependence as a political strategy canhurt the economy of the initiating country, and its citizens (and firms) may oppose the measure once theyknow the full cost of the action. Moreover, the use of economic interdependence as a political strategy takes the9

See Justin McCurry "South Korean boycott of Japanese
goods hits beer and carmakers," The Guardian, September
4, 2019 (https://www.theguardian.com/world/2019/sep/04/southkorea-boycott-japanese-goods-beer-car-sales, Accessed April 12,2021).

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4

form of cutting or downsizing existing trade relations
with the target country, which can produce unexpected
outcomes such as benefiting a third country, weakening
the competitiveness of the initiating country’s firms or
economy, or disrupting world trade. For instance, Japan’s
export restriction on key semiconductor manufacturing
materials to South Korea, intended to hurt South Korea’s
semiconductor industry, also imposed economic costs
on Japanese industries independent of the impact of theconsumer boycotts, as Japanese companies lost an important exporting market.10
One important fact about economic interdependence is that citizens can anticipate the economic costsof a protectionist action coming from interdependence
rather easily without further information about target’s
responses. Moreover, if citizens and interest groups are
informed that they will bear main costs of forgoing economic interdependence due to a protectionist action, citizens and interest groups can protest their governments
to refrain from the planned protectionist move (Carnegie
and Gaikwad 2022). In this regard, we expect that when
individuals are informed about the economic interdependence with a foreign country, they may become morereluctant in supporting the use of protectionist measuresagainst the target country.
The last type of significant cost due to targeted protectionism is a cost to reputation. Targeted protectionism
can taint the initiator’s national reputation in various
ways. The immediate reactions to the protectionist action
from the global media and the target country’s government would be the first stage of reputational sanction. In
this stage, the initiating country argues for the necessityof the protectionist measure, defending its position, andreputational loss is not obvious. We argue that the mostsignificant blow to the national reputation of the initiator
comes from the WTO’s dispute settlement mechanism(DSM). If the targeted country files a complaint with
the WTO and wins the case, it becomes obvious that theinitiator’s action was illegal. Previous studies have shownthat when a country reneges on international commitments, it can be branded a violator of international law,undermining its reputation as a law-abiding memberof the international community (Simmons 2000; Tomz2008). In the realm of international trade, scholars argue
that the WTO’s DSM heightens the reputational costs ofnoncompliance by serving as an independent arbitrator
and by disseminating information about compliance
10“Korean semi-conductor industries make a smoothtransition to depart from Japan.” The Nikkei. February 7, 2021. Available at https://www.nikkei.com/article/
DGKKZO68906810W1A200C2EA5000/. Accessed on April
13, 2012.

(Dai 2007; Kono 2007). The authoritative third-party
rulings by standing DSM tribunals are viewed as legitimate and are less politicized than the judgments ofother ad hoc tribunals and are thought of as representing
the “will of the international community” (Kono 2007;
Simmons 2010). Thus, once ruling is made by the WTO,
the defendant can face significant reputational costs thatcan weaken the country’s future bargaining positionin later disputes or in trade negotiations (Bechtel and
Sattler 2015).
If citizens care about reputation costs to their country, they will punish leaders who pursue foreign policythat may damage the country’s international reputation(Abbott and Snidal 1998; Brutger and Kertzer 2018). This
raises the question of whether the anticipation of legal defeat in the WTO DSM deters ordinary voters in the initiating country from supporting a protectionist policy. That is,what we are interested in is not the ex post punishment
mechanism but the ex ante punishment mechanism via
citizens’ anticipation of legal outcomes at the WTO.
Recently, scholars of international political economy
have increasingly paid attention to the reputational effects of legal defeats in formal WTO rulings. Pelc (2013),
for example, shows that US citizens were concerned
about their country’s reputation when it was involved in a
WTO dispute. Moreover, using a survey experiment witha hypothetical trade dispute, Chaudoin (2014) shows thatcitizens tend to disapprove of the trade practices that canbe subjected to adjudication at the WTO due to reputational concerns. We thus expect that individuals would
be less likely to support targeted protectionist measureswhen they are informed about the possibility of an international dispute at the WTO and related reputation
losses.

Experimental Design
It is difficult to disentangle target and information effects in an observational study because in reality, these
two effects are intermingled. For example, the samenews article about tariffs on solar panels and washingmachines cited above also informed readers of decisions
by China and South Korea to bring the case to the World
Trade Organization. Thus, readers of this news article areexposed to two treatments at the same time. Moreover,reading this article is a voluntary decision that cannot be
captured in an observational setting.
To untangle target effects from the three types of
information effects, we designed a survey experiment
for subjects in China, Japan, and South Korea to assess
the factors that change their support for a protectionist

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5

TARGET, INFORMATION, AND TRADE PREFERENCES

policy.11 Among various protectionist tools available togovernment, we focus on import restrictions—economic
policies that restrict imports to protect domestic industries from foreign competition, following earlier experimental studies on public attitudes toward protectionism(e.g., Bearce and Moya 2020; Wu 2019).
Using a private polling company (Qualtrics), we
recruited samples of 2,259 respondents in China, 2,392
respondents in Japan, and 2,101 respondents in South
Korea.12 The Qualtrics recruited survey participants
via quota sampling in terms of the population’s gender and age (18–24, 25–34, 35–44, 45–54, 55–64, andabove).13 The subjects participated in an online survey inNovember 2020. See Section A in the online supporting
information for our sampling strategy and descriptive
statistics of the demographic characteristics of survey
participants.
In our experiment, all respondents were provided
with a hypothetical scenario in which their country is
considering import restriction measures to protect theirdomestic industry in the face of the economic downturn due to COVID-19. As all three countries had alreadysuffered from economic recessions due to the pandemic
at the time of the survey, we referred to COVID-19 to
make the scenario as realistic as possible. By referring
to COVID-19, we also try to avoid presenting a scenario
in which a country would violate the rules of the WTO.
During the COVID-19 pandemic, the WTO members
are allowed more flexibility in adopting “trade measuresdeemed necessary to protect public health and publicwelfare (including import and export bans, quantitative
restrictions on imports and exports, and non-automatic
import licensing).”14 Moreover, our focus on the eco11

We have registered a preanalysis plan (PAP) on a commonly used
repository, but we are unable to provide the details due to confidentiality in the blind review process. We are happy to provide
more details of the PAP as needed or upon request.
12
Our estimations are in fact based only on attentive respondents.
For more details, see Section A in the online supporting information. Tables A1 and A2 show the summary statistics of demographic characteristics of the survey respondents and the distribution of age, respectively (pp. 3–4).
13
As we rely on online survey, our sample overrepresents younger
population especially in China. However, the Qualtric’s quota sampling allows us to better capture older population compared toother crowdsourcing online surveys such as Zhubajie (Li, Shi, andZhu 2018).
14
For details, see https://www.wto.org/english/tratop_e/covid19_
e/faqcovid19_e.htm. While our scenario focuses on the use of protectionist measures during COVID-19, our findings are also applicable to other contexts because member countries use a different
set of vague protectionist’s measures even during the normal circumstances and do not necessarily strictly adhere to the rules of theWTO. Also, the use of antidumping measures can be another ex-

SUNG EUN KIM et al.

nomic downturn was intended to prime respondents tofocus on the economic logic of protectionism, relative totheir feelings toward a particular country. Thus, any findings of target effects in this experiment could arguably beconsidered as conservative estimates.
Our experimental treatments follow a 4×3 factorial
design, which randomly flips (1) the information on thecosts of protectionism and (2) the main target of the imports restrictions. Respondents are randomly assigned to
12 groups of approximately 150–244 respondents each.
The first dimension is designed to examine whether
different types of information reduce public support fora protectionist policy. The second dimension is designed
to capture whether the public support for protectionism
varies depending on the target country. With the twodimensions combined, the factorial design allows us
to estimate target effects separately from information
effects and also examine their joint effects.
In the following section, we briefly explain the sequence of our experiment. First, we assigned respondents
into four groups—a control group that was not provided
any information about costs and three groups of randomly assigned participants that were each provided
information on one of the three types of potential costs
associated with protectionist policies, namely potential
retaliation from the target country, mutual economic
costs due to interdependence, and reputational costs.
Table 1 presents the exact treatment information
provided to respondents using the experimental conditions in South Korea as an example. Examples of thetreatment information that the respondents in China,
Japan, and South Korea received are presented in Figures
A1–A3 (pp. 5–7). Respondents in China and Japan wererespectively provided with hypothetical scenarios inwhich their own respective country is considering ways
to reduce imports. In the control group, respondents
read a simple description that said their country is
considering ways to reduce imports due to the economic
downturn, while the other three groups received the
additional information on the potential costs of suchprotectionist measures. The retaliation treatment examines whether individual support for protectionism
decreases when a respondent recognizes the possibilityof a tit-for-tat response from the target country thatwould also hurt their own country’s economy. The interdependence treatment also provides information on thecosts of protectionist measures on the national economy,
but with a focus on the economic interdependence of
ample that closely resembles this scenario in that the WTO members are allowed to invoke antidumping measures that can target
specific products from specific countries.

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6

TABLE 1 Experimental Conditions, by Information on Costs of Protectionism
Control Group
Korea is considering ways to reduce imports from [a foreign country/China/Japan] to protect the domestic industry in
the face of the economic downturn due to COVID-19.
Retaliation Treatment Group
Korea is considering ways to reduce imports from [a foreign country/China/Japan] to protect the domestic industry in
the face of the economic downturn due to COVID-19. However, taking such measure is likely to hurt the Korean
exports, as [the foreign country/China/Japan] may take a retaliatory action.
Interdependence Treatment Group
Korea is considering ways to reduce imports from [a foreign country/China/Japan] to protect the domestic industry in
the face of the economic downturn due to COVID-19. However, taking such measure is likely to hurt the exports of both
Korea and [the foreign country/China/Japan], as the two countries’ economies re closely connected.
Reputation Treatment Group
Korea is considering ways to reduce imports from [a foreign country/China/Japan] to protect the domestic industry in
the face of the economic downturn due to COVID-19. However, taking such measure is likely to hurt Korea’s
international reputation, as it can lead to a defeat in the WTO panel
Notes: Table presents the exact treatment information provided to respondents using the experimental conditions in South Korea as an
example.

their own country and the target country. While the two
conditions both provide information on the potential
costs to the initiating country’s exports, they differ in themechanisms through which such costs are incurred. The
two conditions also differ in that the interdependence
treatment emphasizes the costs to the target country as
well. This allows us to examine whether citizens respondsimply to the costs information or respond more strongly
to either the retaliation or the interdependence information. The reputation treatment examines whether
citizens are concerned about a possible WTO disputeand their country’s international reputation.15 If citizens
are concerned about a defeat at the WTO panel and theassociated reputational costs, they may become less likely
to support their government’s protectionist measures.
Second, we randomly assign information about thetarget country. As we are interested in examining whether
citizens’ support for protectionist measures depends on
the target country, we randomly flip the information on
the target among a hypothetical foreign country and each
15
The effects of a WTO ruling can be multifaceted, including not
only reputational risks but also potential retaliation by other member countries that can shape public opinion toward the trade measures. While it is difficult to clearly unbundle those two different
mechanisms, in this article, we aim to capture the reputational effects of the WTO adjudication by explicitly providing an informational cue about potential reputational consequences.

of the two specific neighboring countries. For instance,
Chinese survey respondents were randomly presented
with three scenarios in which their government is considering import restriction measures against (1) an unnamed foreign country, (2) Japan, or (3) South Korea.
Likewise, Japanese respondents were randomly assigned
scenarios in which import restriction measures were targeted against (1) an unnamed foreign country, (2) China,or (3) South Korea.16
After presenting a hypothetical scenario, we ask respondents about their support for their own country’s
use of protectionist measures as follows:• How much do you support or oppose your government’s consideration of such measures to reduce imports?
Answers to this question were measured on a 5-point
scale as follows: (1) strongly oppose, (2) oppose, (3) neither support nor oppose, (4) support, and (5) strongly
16
Existing literature (e.g., Levendusky and Horowitz 2012; Tomz
2007) suggests that the use of generic country best provides thenecessary control over the scenarios to isolate the causal impact
while preventing some idiosyncratic features driving the results.
Nonetheless, we conduct a follow-up experiment in April 2022 totest whether if our results are driven by such use of generic namein the control. The results and the related discussion presented in
Section H of the online supporting information show findings
consistent with the results from the original experiment.

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7

TARGET, INFORMATION, AND TRADE PREFERENCESSUNG EUN KIM et al.

support. Throughout the analysis, we use a binary measure that classified the top two categories on the 5-point
scale (strongly support and support) as support for protectionist measures.
One potential concern in our factorial design is the
sample imbalance between treatment arms. Covariatebalance test results, available in Figures A10 through A12
in the online supporting information (pp. 15–17), show
some persistent signs of covariate imbalance between thecontrol and the treatment groups. To adjust this observed
imbalance between the groups, we use the covariate balancing propensity score (CBPS) method, which models
treatment assignment while optimizing the covariate balance (Fong, Hazlett, and Imai 2018; Imai and Ratkovic
2014, 2015).17 CBPS computes weights that maximize
the covariate balance and the prediction of treatment
assignments at the same time. Using these weights, we
can compute the average treatment effects in the form of
weighted regression estimates. We included 29 covariates
covering basic demographic information, ideology, andsocioeconomic status: age, gender, income, employment
status (7 categories), industry (11 categories), and ideology (8 categories). Detailed information is available
in Section D in the online supporting information. We
highlight that all of these covariates were collected prior
to the random assignment to experiment arms to avoid
posttreatment bias (Acharya, Blackwell, and Sen 2016;
King and Zeng 2006; Montgomery, Nyhan, and Torres
2018). The results of CBPS analysis are presented in
Figures A13–A15 (pp. 18–20).
Our estimations are based only on attentive responses. Our sample excludes any respondents who did
not pass the Qualtric’s quality checks. We also included
our own question that asked respondents to skip and not
to click any numbers between one and nine. We excluded
those respondents who chose any random numbers between one and nine despite the instruction.

Results
Does the provision of cost information change public
support for general and targeted protectionism? Does
knowing which country is the target alter the effect of
cost information on public17 support for protectionism?
In this section, we provide the findings of our experiment to these questions. First, we report the average
effect of target identity and cost information. Then we
discuss how the cost-related information affects public attitudes toward targeted protectionism differently
across countries, targets, and information types.
17

We also present the average treatment effects in Figures A4-A9 in
the supplementary appendix (pp. 8–13).

Average Target and Information Effects
The first four columns and the first four rows ofTable 2 summarize the main results of the experiment.
We report the standard error of information effects
and target effects in Table A5 (pp. 22). The numbers
indicate the proportion of public support for protectionist policies averaged over the three sample countries.
The numbers in parentheses are standard error. Column Control shows the mean level of public support
for protectionism when no cost-related information isprovided. Columns Retaliation, Interdependence, andReputation show the mean levels of public support forprotectionism when specific cost-related information
is provided. Each row contains the target specification,with “Foreign” denoting an unnamed target, and theremainder denoting targets of China, Japan, and South
Korea, respectively. The last column shows information
effects for each target country, and the last row shows
target effects for each information condition.
The information effects given a specific target h is defined as 
E E Y1i jh − Y0i jh |H = h
⎞
⎛
1 
1 
1⎝ 
yi jh,k ⎠ −yi jh,k=(1) , (1)=3 k∈{(2),(3),(4)} Nk i
N(1) iwhere i denotes individual respondents, j denotes i’scountry, and k indicates the assigned cost information.
In words, the information effect measures the magnitudeof the change in public support for targeted protectionism when (one of the three types of) cost information isprovided. Note that the effects are averaged over individuals, countries, and information treatments, conditional
upon the target information.18
We define the target effects given a specific cost information k similarly: E E Y1i jk − Y0i jk |K = k
⎛
⎞
1 
1 
1⎝ 
=
yi jk,h ⎠ −yi jk,h=(a) .
2
Nh i
N(a) i(2)h∈{(b),(c)}18The standard error of information effects is computed by combining standard error of each group, which can be calculated by
iteratively applying the following formula (Tatebe 2005).

Average SE of group i and group j=

Ni2 − Ni 2 N j2 − N j 2 Ni N j µi − µ j
s + 2
s +
N2 − N i
N −N j(N 3 − N 2 )2,where Ni is the sample size of group i and Ni + Nj = N . µi and si
are the mean and standard deviation of group i.

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8

TABLE 2 Decomposition of Causal Effects
Control

Treatment

Information Effects

No information

Retaliation

Interdependence

Reputation

Foreign

0.587(0.021)0.519(0.022)0.490(0.021)0.450(0.020)−0.100(0.025)

China

0.613
(0.026)0.448(0.027)0.554(0.025)0.433(0.025)−0.135(0.030)

Japan

0.708
(0.024)0.648(0.026)0.638(0.024)0.683(0.025)−0.052(0.029)South Korea

0.699(0.024)0.614(0.025)0.612(0.026)0.579(0.025)−0.097(0.029)Target effects

0.086(0.026)0.051(0.027)0.111(0.026)0.115(0.025)

Notes: Each cell presents the mean support for a protectionist policy in each experimental group. Information effects and target effects aredefined in Equations (1) and (2), respectively.

In words, the target effects measure the magnitude of
the change in public support for targeted protectionism
when the target is clearly identified.
The last column of Table 2 shows that the provisionof cost-related information reduces public support forprotectionism by 10% when a target identity is not provided. Except the case of Japan as a target country, the information effects are all negative and statistically significant, indicating that providing cost-related information
significantly decreases public support for protectionism.
The size of information effects is largest when the target
country is identified as China, indicating the common
concern among Japanese and South Korean respondents
toward China as a target.
On the other hand, the last row of Table 2 shows thatthe provision of a target identity increases public support forprotectionism by 8.6% when cost information is not provided. The target effects are still statistically significant
and positive when cost information related to interdependence and reputation is provided. Interestingly, when
respondents are informed about retaliation cost, the provision of a target identity does not make a statisticallymeaningful change in public support for protectionism.
To better understand sources of target and information effects, we disaggregate target effects by country, as
shown in Table 3. It is clear that positive target effects
are driven by respondents from Japan and South Korea. When reminded of the interdependent cost borne byprotectionist policies, Chinese respondents reduced theirsupport for protectionism by 9.1%. By contrast, Japanese
respondents increased their support for protectionism

when the target country information switches from a foreign country into either China or South Korea, regardlessof the type of cost information. South Korean respondents increased their support for protectionism when
the target country information switches from a foreigncountry into either China or Japan, only in the context
of interdependence or reputation cost information. Also,
Japan and South Korea have quite different reactions to

TABLE 3 Target Effects by Country
Control

Treatment

(1)

(2)

(3)

(4)

China

−0.051(0.033)−0.091(0.035)0.068(0.038)0.041(0.039)

Japan

0.184
(0.043)0.170(0.043)0.131(0.042)0.101(0.038)South Korea

0.090(0.046)0.033(0.047)0.121(0.045)0.192(0.045)

Notes: Each cell presents the estimated treatment effects and standard errors in parentheses. Column (1) presents the target effects for the control group, while columns (2), (3), and (4) report the target effects of retaliation, interdependence, and reputation cost information, respectively. Target effects are estimatedfrom different combinations of target countries among China,
Japan, and South Korea. For example, Chinese respondents intreatment groups receive target information of South Korea andJapan, whereas Japanese respondents in treatment groups receive
target information of China and South Korea. Thus, effects must
be compared across countries with caution.

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9

TARGET, INFORMATION, AND TRADE PREFERENCESSUNG EUN KIM et al.

FIGURE 1 Information Effects Given an
Unnamed Target

target information and cost information. South Korean
respondents show the largest target effect in the presenceof reputation information, whereas Japanese respondents
show the largest target effect when there is no cost information. Note that the country-level target effects areaveraged over different target countries. Thus, it is ournext step to examine target-specific information effects(or conditional effects of information given a target identity) to better understand public sentiments toward targeted protectionism.

Target-Specific Information Effects
Target-specific information effects measure the extent towhich respondents of a home country (e.g., Chinese respondents) change their attitudes on targeted protectionism against a target country (e.g., South Korea) after theyreceive specific information about the cost of targeted
protectionism (e.g., retaliation cost). Because there aremany moving parts in our discussion of target-specificinformation effects, we use a simple diagram that summarizes the main findings of our experiment.
We begin with the baseline case, in which respondents do not know which country is being targeted.
Figure 1 summarizes our findings from general protectionism by odds ratio changes.19 More detailed information is presented in Table A3 in the online supporting
information.20 The arrow lines in Figure 1 indicate that
respondents in a sender country are likely to decrease
their support for protectionist policies if they learn either
retaliation, interdependence, or the reputation cost ofprotectionist policies. Figure 1 clearly demonstrates thatthe cost information of protectionist policies significantly decrease the support for protectionism in all three
countries. Only the cost of interdependence shows a consistent effect across three countries, demonstrating that
respondents from three East Asian countries generally
value economic interdependence, and they are willingto change their protectionist positions if the measure is
expected to disrupt
economic interdependence. Interestingly, information on costs due to interdependence has the largest
19
Odds (Supporting Protectionism | Specific Cost Information)
Odds (Supporting Protectionism | No Cost Information).
20

We developed a simple bingo card table√to effectively summarize
the statistically significant joint effects ( ) across the three treatment information groups and two of the three target identities. t
indicates an insignificant effect, and an empty cell indicates that noexperiments were conducted on the given combination, for casesthat correspond to the nonsensical scenario of self-targeting protectionism. Regression results are summarized in the right side of
the table.

Notes: Reported numbers are quasibinomial logistic estimates. An arrow indicates that respondents in the sendercountry are willing to withdraw protectionist support if they
were informed protection brings either retaliation, interdependence, or reputation cost with regard to the unknown target country.

effect among Chinese respondents. Also, the effect of
reputation cost information has the largest effect among
Chinese respondents. These findings imply that Chinese
citizens are more concerned about the economic andreputational effects of domestic trade policy than withthe political ones.
Figure 2 reports the findings of target-specific information effects when a target country is identified.21 One of
the most prominent differences from the unnamed target
case in Figure 1 is the lack of significant responses to cost
information from Chinese respondents. If we consider
the diagrams in Figure 2 as a social network, China iseither an isolated (interdependence) or absorbing (retaliation and reputation) node while Japan and South Korea interact with each other by one of cost-information
paths.
21

Numerical results are available in Table A4 in the online supporting information (p. 21).

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10

FIGURE 2 Target-Specific Information Effects

Notes: An arrow indicates that respondents in the sender country are willing to withdraw protectionist support if they were informed
protection brings either retaliation, interdependence, or reputation cost with regard to the target country.

We interpret the results in more details starting fromthe top panel in Figure 2. Retaliation cost information
decreases the odds ratio of supporting targeted protectionism only for Korean respondents by 68% toward
China and 47% toward Japan. Two factors can explain
South Korean respondents’ sensitivity to retaliation cost
information. The first factor is historical. South Korea isthe only country that recently received targeted protectionism from the two neighboring countries. China hassanctioned South Korea for the deployment of THAAD
since 2015, and Japan has sanctioned South Korea since2019 for the South Korean court’s decision on the case
filed by victims of forced labor during Japan’s colonial
rule over Korea. The sensitivity to retaliation information among South Korean respondents must reflect these
two ongoing sanctions by China and Japan. The size ofthe economy is the second factor. The economy of South
Korea is smaller than that of China or Japan, creating a
sense of vulnerability and insecurity (Hirschman 1945;
Keohane and Nye 1989). As of 2019, China’s economy
was more than seven times larger than that of South Korea’s, and Japan’s economy was four times larger than thatof South Korea’s. Also, South Korea’s trade dependence(trade as a share of GDP) is significantly higher (69%)
than that of both China (31%) and Japan (34%) as of2020 according to the World Development Indicator.22
The top-right panel of Table A4 (pp. 21) in the
online supporting information shows the effects ofinterdependence cost information on public support
for targeted protectionism against a named neighborcountry. Interdependence cost information changes
public attitudes of respondents in both Japan and South
Korea. Holding other covariates constant, the provi22

https://data.worldbank.org/indicator/NE.TRD.GNFS.ZS?
locations=CN-JP-KR.

sion of interdependence cost information decreases theodds that respondents from Japan will support targeted
protectionism against South Korea by 63% and that
respondents from South Korea will support targeted
protectionism against Japan by 43%. That is, respondents from Japan and South Korea are willing to rethinktheir support for targeted protectionism against eachother when they learn about the potential costs due tothe economic interdependence of the two countries.
The symmetrical efficacy of information on interdependence costs in modifying the attitudes of respondents
from Japan and South Korea has significant policy implications for how the two countries’ policymakers might
address bilateral issues. The findings imply that domestic
audiences’ support for targeted protectionism toward
one another can be tempered by the detailed information
on how intertwined their trade patterns and economies
are. It is interesting to find that despite their substantial
economic connection with China, neither Japanese nor
South Korean respondents demonstrate significant shifts
in attitude when informed that their economies are inextricably linked to China and that targeted protectionism
will harm both countries. Although additional data areneeded to validate this, this finding suggests that citizens of democracies are more likely to value economic
interdependence with another democracy than with
nondemocracies as noted by Russett and Oneal (2001).
Lastly, the bottom panel of Table A4 shows theeffects of reputation-cost information on public support
for targeted protectionism directed at a specific neighboring country. Similar to the case of interdependence
cost information, reputation-cost information modifies
respondents’ protectionist attitudes only in Japan andSouth Korea. Keeping other factors constant, providing
knowledge about reputation costs reduces the odds
of supporting protectionist policies by 43% (against

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11

TARGET, INFORMATION, AND TRADE PREFERENCESSUNG EUN KIM et al.

China) and 57% (against South Korea) among Japanese
respondents. Provision of information on reputation
costs reduces South Korean respondents’ odds of supporting targeted protectionism by 50% (against China).
The presence of reputation effects among South Korean
and Japanese respondents could be another indicationof democracy effect in international litigation. Existingstudies have shown that voters in democratic countries
are more likely to respect the international legal process
and worry about maintaining their reputation countries
where the “rule of law” is followed compared to theircounterparts in nondemocracies (Dixon 1993; Gaubatz
1996). Citizens of democracies do not wish to hurt theirreputation by taking unlawful actions against a neighboring country. Although the information of losing
a case at the WTO deters Japanese respondents fromsupporting targeted protectionism regardless of whom
the target country, we could not find a corresponding
effect from South Korean responses toward Japan asa target country. South Korean respondents withdrew
their support for targeted protectionism only when theylearned the prospect of losing a WTO case against China.
The findings of the South Korean respondents must be
linked to South Korea’s recent WTO complaint against
Japan’s export control of semiconductor materials, which
was filed in 2019. The case drew a lot of attention fromthe South Korean press.23 The findings from the South
Korean case show that loss of reputation due to a defeat
in the litigation may not be a significant deterrent when
the litigation with the target country is considered tohave a high stake. Instead, even if the chances of winninga case are low, Koreans may believe that legal proceedings
with Japan should not be avoided.24

Individual-Level Analysis
In this section, we analyze treatment effects at the individual respondent level using various demographic information. We emphasize that the demographic data forthis analysis were obtained prior to the random assignment of participants to experiment arms, and so there isno possibility that respondents changed their responses
as a result of the information supplied in the experiment.
First, we examine the determinants of support fortargeted protectionism using the logistic regression
model and the support for protectionism as the dependent variable. Responses of “Support” or “Strongly Support” are coded as 1, and otherwise as 0. We use observations from the control group to check the baseline support for targeted protectionism.25 Figure 3 summarizes
the logistic regression results. Starting with the pooled
country sample in the first panel, we notice that acrossthe three countries in our sample, respondents who
are female, have less education, have a higher income,have greater nationalistic sentiment, or who work in the
manufacturing sector are more likely to support protectionist measures across three countries in our sample.26
However, there are some noticeable variations across thethree countries. For instance, female respondents are
more protectionist than male respondents in China andSouth Korea, but not in Japan. While holding a college
degree is statistically significant in the pooled sample, it
is not a statistically significant predictor of protectionism
in any of the country-level samples. Higher levels ofnationalism, on the other hand, are consistently found to
be statistically significant across all three countries, at theconventional 95% significance level in China and Japan,
and at the 90% significance level as in South Korea.
Focusing on this last factor of nationalism, we next
turn to examine whether nationalistic individuals respond to cost information differently from how others
respond. The reason we focus on nationalistic individuals is clear. They are the group expected to most strongly
advocate for protectionism aimed at a particular country
and the group that has the smallest information effect.
Furthermore, the provision of information can lead tounpredictable reactions among these individuals.
Due to the small subgroup-level sample sizes, here
we pool the information across target countries. The
results, shown in Figure 4, reveal an interesting pattern
between the level of nationalism and the effect of information treatments. Respondents with higher levels ofnationalism (in China and Japan) are more responsive tothe treatment providing information about reputation

23

Between 2019 and 2022, the total number of South Korea’s domestic news articles containing the terms “Japan, WTO, and export
control” is 8,434. The search was conducted using an online searchengine of Korean newspaper (https://www.bigkinds.or.kr/).
24
In 2019, South Korea won the WTO dispute over import bans
imposed on Japanese seafood in the wake of the 2011 Fukushima
nuclear disaster when the WTO Appellate Body ruled against apanel decision that had initially found in favor of Japan’s position.
This event was hailed as a national victory against Japan. The caseinformation is available at https://www.wto.org/english/tratop_e/
dispu_e/cases_e/ds495_e.htm.

25

The respective sample size for each of the columns are as follows:
Pooled (N = 1,626), China (N = 536), Japan (N = 583), and South
Korea (N = 507).
26

The income variable is based on self-reported income level from
1 to 8. The nationalism variable utilizes the response to the question, “How proud are you to be a Chinese/Japanese/Korean?” The respondents could choose between very proud, quite proud, not very
proud, and not at all proud. We collapse these responses into a binary code where 0 indicates not proud, and 1 indicates proud.

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12

FIGURE 3 Individual Characteristics and Support for Protectionism, by Survey Countries

Notes: Solid dots are coefficients of logistic regression models and horizontal bars are 95% confidence interval based onheteroskedasticity-consistent standard error (MacKinnon and White 1985). Reference Category for Industry and Employment
are “Unemployed.”costs, whereas less nationalistic respondents (in Japanand South Korea) are more responsive to the treatmentthat provides information about retaliation costs. One
possible explanation is that individuals with high levelsof nationalism may care more about maintaining their“national honor” with regard to keeping an international
agreement and may respond more strongly to treatment information concerning reputation. These typesof citizens tend to believe that inconsistent decisions
by policymakers, such as a failure to follow throughon international commitments, damage the country’s
honor and reputation (Brutger and Kertzer 2018; Fearon
1994; Kertzer and Brutger 2016; Nomikos and Sambanis2019). In contrast, those with weak nationalist sentimentconsider the economic costs of retaliation as significant
as or more significant than sovereignty and national
honor. Strong nationalists worry about the damage froma legal defeat at the WTO because they may believe that alegal defeat at the WTO is a national humiliation hurtingthe country’s image and credibility in international
affairs (Chaudoin 2014).

Conclusion
In this study, we investigated the formation of public
preferences for targeted protectionism in East Asia us-

ing the concept of target and information effects. We
estimated average and conditional effects of target andcost information among respondents of China, Japan,
and South Korea using a survey experiment that assigns
respondents into various information settings for target
identities and cost information.
Our experiment demonstrates that both target
identities and cost information affect popular support
for targeted protectionism, although the effects varyacross target identities, cost information types, andrespondents’ nationalities. Most surprisingly, when we
examined information effects directed towards an unnamed target country, we discovered that respondents
from all three countries were not significantly different:
cost information reduces public support for targeted
protectionism. We also found that information effects
and target effects are “persistent” in the presence of theother in the sense that receiving cost information reduces
support for both general and targeted protectionism but
does not necessarily mute the effect of target information. Similarly, when reputation and retaliation costs areassociated with protectionism, knowing a target country
identity still increases public support for protectionism.
It is when the target country is identified as one of twoneighboring countries that the cross-country differences
become pronounced. While Chinese respondents did

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TARGET, INFORMATION, AND TRADE PREFERENCESSUNG EUN KIM et al.

FIGURE 4 Support for Protectionism, by Survey Countries

Notes: The estimation method is the quasi-binomial logistic regression model weighted by the CBPS method.

not shift their support for targeted protectionism significantly in response to cost information, respondents inJapan and South Korea significantly withdrew support
for targeted protectionism after learning about the costs
associated with targeted protectionism against one of theneighboring countries.
Although the evidence in our experiment comesfrom three East Asian countries, our findings have several broader implications beyond East Asia. First, an
increasing number of studies have examined nonmaterial sources of trade preferences, such as other-regarding
preferences (Lü, Scheve, and Slaughter 2012), nationalism, and ethnocentrism (Mansfield and Mutz 2013;
Margalit 2012). In these studies, feelings of ingroupfavoritism, national superiority, or patriotism are consistently found to be the key sources of individual tradepreferences (Mutz and Kim 2017; Rankin 2004). According to our findings, individual support for protectionism
can be mitigated if voters are provided information on

the costs of targeted protectionism. While individuals’
feelings toward specific countries are an important
determinant of their trade attitudes, these feelings do
not necessarily trump cost-related calculations. When
individuals are informed about the material and reputational costs of protectionist measures, they become lesssupportive of protectionism. In particular, although theeffects depend on the target and the type of information,
we find that the median respondents in Japan and South
Korea tend to withdraw their support for targeted protectionist measures when informed about the economic
interdependence between their own country and thetarget and the potential loss of reputation that could
result from targeted protectionist actions.
Second, the findings of our article demonstrate how
and under what conditions cost-related information
successfully reshapes citizens’ views and feelings towardtargeted protectionism. Given citizens’ low levels ofknowledge about trade policy and its consequences,

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14

previous studies have largely focused on the role of information in bridging the disconnect between personal
interests and policy preferences. For instance, Rho andTomz (2017) find that individuals’ trade preferences
become more aligned with their self-interests when
the individuals are informed about the distributional
consequences of trade liberalization. Similarly, Schaffer
and Spilker (2019) show that individuals are less likely
to support trade liberalization when they are exposed to
information regarding its negative impact on their own
industries. In this article, we show that individuals not
only respond to information about their self-interests
but also to information concerning sociotropic concerns,
such as the expected economic and reputational costs ofprotectionism to their country as a whole.
Third, individual citizens are highly concerned withprotecting their country’s international reputation as arule-abiding country. Informing citizens in Japan and
Korea about the possibility of a WTO dispute significantly reduces their support for the use of targeted
protectionist measures against their neighbors (with the
exception of Korea targeting Japan). This highlights theimportant role of the WTO as an independent arbitrator(Dai 2007; Kono 2007). Along with previous findingsthat have shown that the public pays attention to the
WTO disputes and disapproves of trade practices that
may be subject to disputes (Chaudoin 2014; Pelc 2013),
we add further evidence that citizens are less willingto support targeted protectionism when informed thatit may lead to a WTO dispute. It is also notable thatthese effects are more pronounced among nationalistic
individuals, who are often considered to be more supportive of “weaponizing” economic interdependence
during periods of political disputes. The results imply
that the WTO, as an authoritative third party, can mitigate public support for protectionism and discouragecountries from using protectionist policy as a coercive
tool.
Finally, our study sheds important light on theextent to which public support for protectionist measures is based on political tensions with trade partners
and in what ways public support for protectionism canbe mitigated by providing information on the costs ofprotectionism. So far, the literature on political tensions
and international trade has mostly focused on aggregatelevel trade flows and consumer boycotts (e.g., Davis andMeunier 2011; Pandya and Venkatesan 2016). We believethat recent events, such as China’s export regulation ofrare earth products to Japan, the trade war between the
United States and China, and Japan’s export regulationsof semiconductor supplies to South Korea, clearly showthat the nexus between political tensions and interna-

tional trade is an emerging fault line in international
politics.
The evidence we presented suggests that raisingawareness about the interdependent nature of the global
economy can significantly contribute to tempering targeted protectionism in East Asia and between Japanand South Korea in particular. As citizens of democratic
countries, respondents in Japan and South Korea appear
more responsive to information about economic interdependence than to information about possible retaliation. While individuals tend to view trade in terms of“us-versus-them” terms and favor “winning more thanthem” in a trade relationship (Mutz and Kim 2017), information about economic interdependence may weaken
this attitude by highlighting the linked fates of the twoneighboring countries.

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Supporting Information
Additional supporting information may be found online
in the Supporting Information section at the end of thearticle.
Appendix A: Survey Sample
Appendix B: Treatment Texts
Appendix C: Average Treatment EffectAppendix D: Balance Test Results for Subgroups
Appendix E: Results of CBPS Analysis
Appendix F: Target-Specific Information Effects
Appendix G: Standard Error of information Effects andtarget Effects
Appendix H: Generic Country Names as a Control
Condition

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