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Does Punishing Sanctions Busters Work? Sanctions Enforcement and U.S. Trade with
Sanctioned States
Bryan R. Early
University at Albany-SUNY
bearly@albany.edu
Timothy M. Peterson
Arizona State University
tim@timothypeterson.org
Note: Accepted for publication in Political Research Quarterly. A complete replication archive
can be found at: https://www.dropbox.com/s/owk5si5fzo5a8po/Enforcement_PRQ_Replica-
tion.zip?dl=1!
Abstract
How can the government agencies responsible for enforcing economic sanctions enhance their
effectiveness? This study explains how and why sanctions enforcement actions undertaken by
sender governments can discourage their firms from trading with the states they sanction. Specif-
ically, we examine how the penalties imposed against sanctions violators by the U.S. Department
of Treasury’s Office of Foreign Asset Control (OFAC) affect U.S. firms’ trade with target states.
We argue that, because U.S. firms are responsive to the risk being penalized and the disruptions
that penalties create, U.S. trade with sanctioned states will be lower in the aftermath of OFAC
enforcement actions. The penalties’ frequency and severity will magnify those negative effects.
We hypothesize that OFAC enforcement actions taken against both U.S. and foreign sanctions
violators will negatively impact U.S. trade with targets. Analyzing data from 2003-2015, we find
that OFAC’s sanctions enforcement actions decrease U.S. trade with sanctioned states in numer-
ous ways.
2
Introduction
Given the scarce resources that governments devote to implementing economic sanctions,
how can the agencies responsible for enforcing sanctions enhance their effectiveness? The
strategies that sanctions enforcement bodies employ vis-à-vis firms can play an important role in
shaping the severity of the costs that sanctions targets experience. Increasing the consequences
firms face for sanctions violations and their perceived risks of being caught are both mechanisms
by which senders can influence firms’ responses to sanctions (Morgan and Bapat 2003; Early and
Preble 2020b). Sender governments can influence the risks their firms perceive in doing business
with partners in sanctioned states via the penalties they impose against sanctions violators. Im-
portantly, the positive relationship between the economic costs sanctions impose on targets and
the success of sanctioning efforts is one of the strongest empirical findings in the sanctions litera-
ture (Bapat et al. 2013). Improved sanctions enforcement can thus contribute to a higher likeli-
hood of sanctions succeeding. Our study seeks to uncover how the penalties imposed against
sanctions violators by enforcement bodies within sender governments affects sanctions’ disrup-
tive effects on trade with target states.
While intuitive linkages exist between the enforcement, consequences, and effectiveness
of economic sanctions, the topic of enforcement has received surprising little attention (Morgan
and Bapat 2003; Bapat and Kwon 2015). Efforts to study how governments obtain private sector
compliance with their sanctions have provided initial insights into what kinds of enforcement
strategies governments can employ (Morgan and Bapat 2003; Early 2016; Early and Preble
2020a; Bapat et al. 2020). To date, however, no empirical studies have examined how the use of
specific enforcement policies affects the behavior of the private sector actors whose behaviors
1
sanctions are intended to alter. One of the key reasons why enforcement-related variables have
not been included in many of the major sanctions datasets (e.g., Hufbauer et al. 2007; Morgan et
al. 2014) is that few governments make robust investments in enforcing sanctions.
In this study, we explore the impact of the sanctions enforcement strategies employed by
the United States government. The U.S.’s superpower status, its dominant place in the in-
ternational financial system, and its propensity to employ sanctions more than any other govern-
ment (Hufbauer et al. 2007; Morgan et al. 2014; Farrell and Newman 2019) allow and motivate it
to invest in sanctions enforcement more than other countries. Given that the U.S. is responsible
for such a significant proportion of the sanctions adopted, understanding how it implements
sanctions and the consequences they have makes it a critical case to understand within the sanc-
tions literature. While most senders do not currently invest as much as the U.S. in enforcing
sanctions, its strategies could be a model for other greater powers seeking to enhance their sanc-
tions’ effectiveness in the future.
Our study specifically examines the impact that sanctions enforcement actions taken by
U.S. Department of Treasury’s Office of Foreign Asset Control (OFAC) have on U.S. firms’ trade
with the targets of U.S. sanctions. We theorize that more frequent and more severe OFAC en-
forcement actions against sanctions violators will promote greater compliance with sanctions
and, more broadly, discourage U.S. firms from trading with states sanctioned by the U.S. gov-
ernment. Our analysis disaggregates enforcement actions between those that should directly af-
fect U.S. firms’ risk calculus for trading with a target states versus those that will contribute to
their systemic risk evaluations. We expect that U.S. firms will be most sensitive to OFAC en-
2
forcement actions against U.S. firms for violating sanctions against a particular trade partner, but
that their risk assessments will also consider punishments against foreign firms for violating
sanctions with that state. We also theorize that the penalties imposed by OFAC against U.S. firms
for violations of other sanctions regimes will contribute to U.S. firms’ evaluations of the risk
climate for trading with sanctioned states. We expect that OFAC’s financial penalties must be
sufficiently large to negatively impact U.S. trade with sanction states and that, after that thresh-
old is met, larger-sized penalties will generally have stronger and more consistent effects.
We test our theory with a quantitative analysis of U.S. trade with sanctioned states from
2003-2015. While this approach does not give us firm-level insights on how sanctions enforce-
ment actions affect their behavior (e.g., Webb 2020; Allen 2021), it allows us to test the macro-
level implications of our theory using a measure that has salient implications for the aggregate
costs sanctions impose on their targets. Our observations include all states subject to U.S. eco-
nomic sanctions of any magnitude. We employ data on imports and exports between the U.S. and
target states as our dependent variables, combining it with data on the civil financial penalties
imposed on firms as part of OFAC enforcement actions (Early and Preble 2020a; Sanctions-
Alert.com 2018). We explore the impact of OFAC penalties at three different minimum thresh-
olds of severity, $500,000-plus, $1 million-plus, and $25 million-plus, allowing us to evaluate
how penalties’ severity affects their impact. Our analysis reveals that OFAC enforcement actions
have strong, consistently negative effects on U.S. imports from and exports to target states when
OFAC penalizes U.S. firms for violating sanctions against the target. We also find that OFAC
penalties against U.S. firms for violating other sanctions regimes depress U.S. exports to targets.
The impact of penalizing sanctions violators thus reverberates beyond the immediate sanctions
3
regime it involves. Lastly, the results show that, when OFAC imposes $1 million-plus penalties
against third parties for violating a particular sanctions regime, those enforcement actions are
associated with reductions of U.S. imports from that target. In sum, our findings indicate OFAC
enforcement actions serve as force-multipliers that increase the disruptions experienced by and
risks perceived by U.S. firms in doing business with the targets of U.S. sanctions.
Our findings contribute in important ways to the literature on economic coercion and in-
ternational political economy. Via OFAC’s enforcement actions, we find that the U.S. Govern-
ment can improve domestic compliance with its sanctions and lead to so-called “overcompli-
ance” in discouraging allowable trade with sanctioned states. As our analysis uncovers, OFAC
can discourage U.S. trade with the states it sanctions through punishing both U.S. and foreign
firms for their violations. Importantly, our study shows that sanctions enforcement actions also
have broader systemic deterrent effects (Peterson 2013, 2014; Miller 2014). Punishing sanctions
busters for violating sanctions thus appears to be a cost-effective strategy for enhancing the ef-
fectiveness of sanctioning efforts. Our analysis suggests that developing a more nuanced under-
standing of how sender governments—and not just the U.S.—enforce their sanctions represents a
crucial future step for sanctions research (Bapat et al. 2020). Finally, our findings have salient
implications for U.S. policymakers. OFAC’s penalties can make U.S. sanctions more effective
than potentially anticipated, and they can leverage the penalties employed against third-party
sanctions violators to make the domestic effects of their sanctions more severe.
4
The Adverse Economic Effects of Economic Sanctions
Economic sanctions are dual-edged swords that harm the economic welfare of both the
sender governments that impose them and their targets. As Morgan (2015) notes, sender govern-
ments have become steadily better at finding ways to minimize the costs sanctions impose on
themselves; but, even so, meaningful sanctions are almost never costless. Indeed, Martin (1992)
argues that the costs senders bear in imposing sanctions help demonstrate the government’s re-
solve in a sanctions dispute. Hufbauer, Schott, Elliot, and Oegg (2007) estimate that the costs of
economic sanctions to senders such as the U.S. can amount to tens of billions of dollars. Huf-
bauer, Elliot, Cyrus, and Winston (1997) also show that economic sanctions cost the U.S. econ-
omy as many as 200,000 jobs in the late 1990s. In addition to the direct losses caused by reduced
market access, contemporary U.S. sanctioning policies place a compliance burden on companies
(Arnold 2016). Companies are responsible for ensuring they comply with sanctions, and increas-
ingly treat sanctions as another form of government regulation requiring investments in compli-
ance and risk management. Sanctions thus impose additional costs of doing business on firms,
which can vary depending on the nature of a company’s business activities. Finally, sender gov-
ernments also incur broad costs associated with investments in creating the regulatory and insti-
tutional infrastructure necessary to implement sanctions, as well as the ongoing costs associated
with monitoring compliance and punishing violations (Morgan and Bapat 2003). Resources for
managing sanctions are generally scarce (Early 2016); and governments may make strategic de-
cisions about the particular sanctioning efforts they want to invest more in enforcing (Bapat and
Kwan 2015; Early and Preble 2020b).
5
The onset of sanctions imposes disruption costs on their targets, severing otherwise prof-
itable business relationships and forcing parties in target states to find new commercial partners.
Beyond the initial disruption, sanctions weaken the target states’ terms of trade, forcing parties in
the target to pay more for imports they used to acquire from the sender, while receiving less for
the exports they must redirect to new customers (Kaempfer and Lowenberg 1999). While parties
1
in the target states may be able to forge new relationships in third-party states (Early 2015; Barry
and Kleinberg 2015), those new trade relationships will almost always be less profitable for tar-
gets. Economic sanctions have thus been found generally to have a significant negative effect on
their targets’ economies, especially in the case of U.S. and United Nations (UN) Security Council
sanctions (Neuenkirch and Neumeier 2015). Economic sanctions increase the likelihood of target
states experiencing financial crises (Peksen and Son 2015), and can increase growth of targets’
illicit economies (Andreas 2005; Early and Peksen 2019).
Research has shown that economic sanctions can have significant and lasting negative
effects on the commercial relationships between sender and target states. Estimates suggest that
economic sanctions have disrupted billions of dollars-worth of potential trade between the U.S.
and the states it has sanctioned (Hufbauer et al. 1997; Hufbauer 2007). Afesorgbor (2019) finds
that imposed economic sanctions have a negative effect on trade between sender and target
states. Finally, Lektzian and Souva (2003) show that trade flows between senders and targets do
not recover immediately after sanctions are removed, and that political factors such as regime
type can influence the time until recovery.
6
Firms within targets and senders whose commerce is affected by sanctions have several
options to prevent the loss of profitable relationships: they can try to exploit legal loopholes in
sanctions policies, continue their trade via smuggling or illicit relationships, or forge sanctions-
busting relationships via third-party intermediaries (Early 2015; 2016; Barry and Kleinberg
2015). The continued interest of sender firms in doing business with target states is at heart of the
compliance challenges associated with sanctions. Sanctions increase costs and enhance the risks
that sender firms face for continuing business with partners in target states. If firms perceive the
profitability of transactions to be sufficiently high, and the risks and/or penalties of being caught
are low, they may circumvent sanctions on behalf of partners in target states. They will use legal
channels or loopholes when possible or illicit methods if necessary (Early 2015; 2016; Early and
Peksen 2018). Sender governments thus face a dilemma in determining how to allocate resources
in implementing and enforcing their sanctions in order to convince private sector actors to com-
ply (Morgan and Bapat 2003; Early and Preble 2020a; 2020b). While Early (2015: 214) advises
that “[h]arsh, credible, and consistently employed penalties will likely be needed to deter firms
from engaging in the otherwise highly lucrative business of sanctions-busting,” understanding
how to use scarce resources to do that represents a significant challenge.
How Enforcement Actions Shape Firms’ Response to Sanctions
Economic sanctions disrupt commerce by restricting or prohibiting otherwise profitable
transactions, creating uncertainty in commercial relationships, and increasing the transaction
costs associated with doing business. Due to the latter two effects, economic sanctions can harm
commercial transactions far beyond the specific types of transactions they forbid. Yet, the prima-
7
ry effects of sanctions centers on their ability to convince private sector actors that they must
stop doing business with commercial partners subject to economic restrictions. The incentive
structures facing firms and governments with respect to sanctions creates both complementary
and diverging interests. Governments wish to make their sanctions effective while imposing as
few costs on their own businesses as possible (Bapat and Kwon 2015). Firms want to survive and
retain profitability. To the extent they can do so via complying with governmental regulations
and policies, they will generally seek to comply with them. In this section, we present our expla-
nation for how and why government investments in sanctions enforcement alter firm’s incentives
to comply with sanctions.
Economic sanctions rarely achieve success immediately (van Bergeijk and Marrewijk
1995), partly because achieving high levels of domestic sanctions compliance may not occur
immediately—or at all. Sanctions enforcement actions can play a key role in bringing firms’ be-
havior in line with sanctions policies. Punishing sanctions violators to promote compliance is
crucial to imposing meaningful costs on sanction targets. As such, sanctions enforcement actions
are not necessarily a sign that a sanctioning effort is failing or will fail; rather, they are often a
steppingstone towards making ongoing sanctioning efforts maximally effective. Not all govern-
ments possess the resources or political incentives to enforce their economic sanctions proactive-
ly, though. It takes resources to enforce sanctions, and punishing firms for non-compliance may
engender broader political resentment against sanctioning efforts. Thus, even governments that
have the prerogative to engage in robust enforcement of their sanctions have incentives to mini-
mize potential political backlash against those actions.
8
In the U.S., OFAC is charged with the responsibility to implement U.S. sanctions and
take civil enforcement actions against parties that violate them. OFAC has broad discretion in
investigating both domestic and foreign sanctions violations and in determining the nature of
penalties imposed for sanctions violations it uncovers (Early and Preble 2020a; 2020b). It em-
ploys sanctions enforcement actions strategically to raise awareness of compliance obligations
and to influence firm risk perceptions for sanctions violations. Since 2003, the OFAC has pub-
lished summaries of its sanctions enforcement actions online. When sanctions infractions be-
come news stories, it can raise awareness among relevant parties about sanctions requirements
and provide OFAC with an opportunity to share lessons-learned from those cases. The imposi-
tion of large financial penalties (Early and Preble 2020a; 2020b) can also be leveraged by en-
forcement bodies to scare companies into reevaluating the perceived risks of non-compliance
with sanctions requirements.
OFAC"s sanctions enforcement strategies have evolved over the past two-decades. During
the early and mid-2000s, OFAC employed an “fishing” strategy that emphasized catching a lot of
small-time violators that, on average, yielded small civil penalties as punishments. Starting in
2009, though, OFAC shifted towards more of a #whale-hunting” strategy that focused more on
targeting foreign financial institutions that violated U.S. sanctions [the whales] and imposing
massive fines against them (Early and Preble 2020a). This strategic shift suggests that OFAC re-
alized that simply penalizing more violators was not necessarily better. Focusing on a smaller
number of high-profile cases was viewed as a more efficient and effective means of raising
awareness of U.S. sanctions requirements and deterring violations. Examples of #whale-hunting”
9
penalties include OFAC enforcement actions taken against Credit Suisse (2009), ING Bank N.V.
(2012), HSBC Holdings (2012), and BNP Paribas SA (2014) that all resulted in $400 million-
plus fines. Targeting foreign sanctions violators was also advantageous for OFAC because such
fines did not directly harm U.S. firms while still potentially generating similar awareness-raising
and deterrent effects. It remains an open empirical question, however, if penalizing foreign sanc-
tions violators actually does influence the trade behavior of U.S. firms.
We assume that firms are complex organizations whose personnel are generally rational
and united in the pursuit of profits but that have a range of different risk tolerances and individ-
ual goals. This means that the leaders of firms may face principal-agent challenges in securing
full buy-in for corporate policies and that the individuals within firms may engage in behaviors
not fully in their firms’ interests. When the U.S. government adopts sanctions policies that dis-
rupt a firm’s business, the firm’s leaders could ignore the sanctions, direct their employees to
find ways of circumventing them, or commit to having their companies comply with the sanc-
tions. Irrespective of stated corporate policies, individual members of a firm may violate sanc-
tions out of ignorance about the policy requirements or because they see opportunities for indi-
vidual gains (i.e., commissions or performance bonuses) via sanctions-busting activities. In 2014,
for example, OFAC settled apparent violations with Sea Tel for exporting 16 marine antenna sys-
tems for use on shipping vessels owned by the sanctioned National Iranian Tanker Company
(NITC). While the company had some sanctions compliance policies in place, “a Sea Tel sales
manager had reason to know that the antenna systems were destined for NITC and [still] autho-
rized the shipments” (OFAC 2014: 1). Firms that want to ensure their entire organizations com-
ply with sanctions policies must make investments in corporate compliance procedures and per-
10
sonnel. The recent rise of consultant services (such as, Kharon and Deloitte) and law practices
(for example, Gibson Dunn) that specialize in corporate sanctions compliance illustrate the major
investments that U.S. businesses have made in this area. Investments in sanctions compliance
increase the transaction costs of doing business but help inoculate firms from the reputational
risks and costs associated with potentially violating sanctions.
OFAC expects that other firms will observe and glean information from its sanctions en-
forcement actions—even if those firms are in other economic sectors, the violations involve oth-
er sanctions programs, or the penalized firms are based in foreign countries (e.g., Gacki 2019).
Yet, at present, the extent to which the deterrent effects of enforcement actions transfer across
sectors, commercial flows, and internationally remains an open empirical question. We think that
firms involved in trading goods, for example, could have their risk-perceptions about complying
with sanctions altered by penalties assessed against financial institutions. As well, many major
multinational firms have corporate presences in numerous countries beyond where they are
headquartered. Many large U.S. firms, for example, have foreign subsidiaries operating in other
locations that may also be required to comply with U.S. sanctions. For example, OFAC (2013)
imposed a $91 settlement with the U.S.-based oil company Weatherford International Ltd and
two of its foreign subsidiaries for apparent violations of U.S. sanctions against Cuba, Iran, and
Sudan in 2013. Similarly, foreign-owned businesses may have corporate presences in the U.S.
that must fully comply with U.S. sanctions policies. This suggests that firms operating within the
U.S. may also be sensitive to sanctions enforcement actions taken against foreign sanctions vio-
lators.
11
We theorize that firms will adjust their assessments of risk associated with violating U.S.
sanctions as a function of the number and severity of enforcement actions by OFAC. While en-
forcement actions resulting in enormous fines can yield significant publicity and deterrent ef-
fects, such cases arise infrequently and require substantial investments of time and resources by
OFAC to pursue (Early and Preble 2020b). Rosenberg and Tama (2019: 11) argue that it is valu-
able to pursue enforcement involving both large and smaller-sized penalties to communicate that
all firms are expected to comply with U.S. sanctions. For the purpose of raising awareness and
deterring violations, we expect that OFAC penalties will still have to be fairly significant to gen-
erate publicity and serve as powerful enough deterrents to discourage trade with the targets of
U.S. sanctions. If the penalties are sufficiently large, though, we theorize that the number of en-
forcement actions that OFAC takes should factor into firms’ risk calculus. When OFAC more
stridently enforces U.S. sanctions, it will disincentive business leaders from deliberately engag-
ing in illegal sanctions-busting activities and encourage them to invest in corporate sanctions
compliance policies to reduce their risks of unintentional violations. Increased levels of domestic
compliance with U.S. economic sanctions will have the aggregate effect of reducing U.S. trade
with sanctioned states.
Beyond the pressure OFAC enforcement actions place on firms to comply with U.S.
sanction policies, they can also have a broader chilling effect on U.S. trade with sanctioned
states. Fears over OFAC enforcement may contribute to higher levels of risk-aversion about do-
ing business with partners in sanctioned states (Early and Preble 2020b). Even targeted sanctions
against specific actors (individuals, businesses, or government agencies) will increase the risk of
doing business with their entire states they are a part of, as firms will have to ensure their trans-
12
actions do not involve any sanctioned parties. This means that even when many transactions with
target states are still allowed, doing business in those states become costlier and riskier. For some
firms, the potential downside risks of doing business in sanctioned states will lead them to volun-
tarily cease operating in or doing business with parties from those states altogether. This practice
is known as “de-risking” or “over-compliance.” It has become prevalent in the financial sector
and has spread elsewhere, like the IT sector (Flores 2019).
Foreign firms’ responses to OFAC enforcement actions can also increase U.S. firms’ costs
of doing business with target states. For example, the substantial penalties OFAC imposed
against foreign banks for violating U.S. sanctions have increased the difficulty that U.S. firms
have in obtaining financing for commercial transactions with partners in target states. By target-
ing the financial institutions that facilitate international trade with sanctioned states, OFAC can
make it harder for both illicit sanctions-busting trade and legal trade with those states. Increasing
the sanctions compliance levels of specific economic sectors, like the financial industry, can thus
raise the transaction costs for all the sectors that depend upon them. Ferrell and Newman (2019)
have argued that the U.S. Government’s “weaponization” of its dominant status in the in-
ternational financial networks has given it substantial leverage in forcing firms to comply with
U.S. sanctions. As they note (2019: 67-68), this leverage helped freeze Iranian banks out of the
international financial system in the early 2010s—making it substantially harder for Iranian
companies to finance commercial transactions with foreign partners. By focusing its enforcement
on this “choke-point” in how international trade occurs (Ferrell and Newman 2019), OFAC sub-
stantially raised the difficulty of conducting both sanctions-violating and legitimate trade with
Iran (such as, pharmaceuticals, medical equipment, and food). This complementary mechanism
13
of making trade with targets more costly and difficult reinforces the deterrent effects that
OFAC’s enforcement actions have. It also highlights how OFAC enforcement actions in non-
trade related sectors can affect decisions made by U.S. firms about trading with sanctioned states.
Hypothesizing the Direct and Systemic Effects of OFAC Enforcement Actions
OFAC enforcement actions imposed against firms for sanctions violating involving a par-
ticular target should constitute a direct deterrent to other firms trading with that target, but other
OFAC enforcement actions can also have deterrent effects. We classify OFAC enforcement ac-
tions into three categories that U.S.-based firms should consider when deciding whether to do
business with a target state. The first category involves enforcement actions against U.S. firms
for violating sanctions against that specific trade partner, which should directly affect U.S. firms’
risk calculus for trading with that state. The second category involves OFAC enforcement actions
that punish third-party firms for violating sanctions against a target with which U.S. firms are
considering trading. In the last category, U.S. firms may be influenced by OFAC’s enforcement
actions punishing U.S. firms for violations involving other sanctions regimes. We expect that
enforcement actions from the first category will have the strongest and most consistent effect on
U.S. firms trade with sanctioned target states, but that enforcement actions in the latter two cate-
gories can also discourage trade with target states.
U.S. firms evaluating the risks of doing business with a sanctioned trade partner should
be most cautious when OFAC enforcement actions were taken against U.S.-based firms for vio-
lating sanctions against that state. For example, U.S.-based PanAmerican Seed Company settled
14
an OFAC enforcement action in 2016 over apparent violations of the “Iranian Transactions and
Sanctions Regulations” for $4,320,000 (OFAC 2016). A simple Google search (“PanAmerican
Seed Company sanctions violations”) reveals that information about the enforcement action was
publicized in the U.S. news media, U.S. legal blogs, and relevant U.S. trade journals and web-
sites. U.S. companies considering doing business with Iran would thus have ample exposure to
information about this case, which should directly affect their perceptions of the risks involved in
doing business with Iran. The more that firms observe such penalties and the greater those penal-
ties are, the greater the risks they will ascribe to doing business with the particular target state.
Based on this logic, we would expect that the enforcement action would have a negative effect
on other U.S. firms’ trade with Iran.
Hypothesis 1: The more frequently OFAC imposes sufficiently large financial penalties
for sanctions violations against U.S. firms over commerce with a U.S.-sanctioned target,
the lower the subsequent U.S. trade with that state will be.
OFAC enforcement actions taken against foreign firms that do business with a particular
target state can also inform U.S. firms’ risk perceptions about trading with it, albeit less directly
(Peterson 2013, 2014). These penalties can provide U.S.-based firms with information about
OFAC’s aggressiveness in pursuing enforcement actions related to specific sanctions programs.
Indeed, research shows that the extent to which OFAC imposes penalties associated with particu-
lar sanctions varies by presidential administration (Early and Preble 2020a; 2021). Large multi-
national firms with corporate presences in the third-party states where the enforcement actions
are imposed may be especially sensitive to the implications of those penalties for their U.S.-
based operations. Enforcement actions against third-party firms for violating the U.S. sanctions
15
against a target will also increase the transaction costs and uncertainty that U.S. firms face in do-
ing business with that state. According to this logic, OFAC’s $375 million settlement with the
United Kingdom’s HSBC Holdings for apparent violations of U.S. sanctions against Iran would
diminish U.S. firms’ trade with Iran as well (OFAC 2012b).
This type of enforcement action has particular value, as OFAC can make foreign firms
pay the costs associated with deterring sanctions violations and hurt the foreign firms’ competi-
tiveness relative to their U.S. rivals. Imposing penalties against foreign firms also minimizes the
amount of domestic political backlash OFAC could otherwise experience for punishing U.S.
firms severely for violating U.S. sanctions. Along those lines, Early and Preble (2020a: 31) find
that OFAC imposes significantly higher financial penalties against foreign firms than against
U.S. firms. Punishing foreign sanctions violators may thus allow the U.S. to realize the benefits
of imposing harsh penalties against violators while minimizing the domestic resentment such ac-
tions would engender if taken against U.S. firms. This logic suggests that extra-territorial sanc-
tions provisions have valuable benefits that sender governments can exploit for enforcement pur-
poses.
Hypothesis 2: The more frequently OFAC imposes sufficiently large financial penalties
for sanctions violations against non-U.S. firms over commerce with a U.S.-sanctioned
target, the lower the subsequent U.S. trade with that state will be.
OFAC enforcement actions can also affect the perception of the systemic risks involved
in trading with sanctioned states. We theorize that U.S. firms will also pay attention to OFAC
enforcement actions taken against U.S. firms for sanctions violations involving other target states
16
besides the one with which they are considering trading. The willingness of OFAC to punish
U.S. firms for violating other sanctions regimes, and how much those penalties are for, signal the
general risks associated with trading with any target of U.S. sanctions. Such cases provide U.S.-
based firms with information about OFAC’s general enforcement practices, such as the size of
the penalties OFAC is willing to impose, that offer additional insight into the risks involved in
trading with sanctioned states. According to this logic, the $7,772,102 settlement that OFAC
reached with U.S.-based Zoltek Companies, Inc. in 2018 for apparent violations of the U.S.’s
“Belarus Sanctions Regulations” would have a chilling effect on U.S. trade with entities in other
sanctioned states (OFAC 2018). This implies that any enforcement action taken against U.S.
firms for sanctions violations should have a systemic effect on the sanctions-related risks that all
other U.S. firms perceive about doing business sanctioned states.
Hypothesis 3: The more frequently that OFAC imposes sufficiently large financial penal-
ties against U.S. firms for violating sanctions with other states sanctioned by the U.S., the
lower the subsequent U.S. trade with a particular target will be.
Research Design
Our research design focuses on analyzing the macro-level implications of our theory
rather than on how sanctions enforcement actions affect the behaviors of individual firms (e.g.,
Webb 2020). While this approach does not enable us to distinguish between the effects of the
complementary compliance-based and deterrence-based mechanisms of our theory, it will allow
us to assess whether—and in what circumstances—firm-level research is needed to parse the in-
17
dividual effects of our theoretical mechanisms. As such, we test our hypotheses with yearly data
(2003-2015) on U.S. trade with all states subject to U.S. sanctions of any magnitude. Our data
2
set begins in 2003 because that is the first year OFAC began publishing its sanctions enforce-
ment penalties and ends in 2015 due to the availability of our control variables. Our unit of
analysis is the U.S.-dyad, where we pair each state in the system with the U.S. under the condi-
tion that U.S. sanctions are ongoing against that state.
3
Our dependent variable captures bilateral trade. We use data from the Atlas of Economic
Complexity (AEC) (The Growth Lab at Harvard University 2019). The AEC takes raw data on
trade in goods from the United Nations Comtrade database and cleans it to account for inconsis-
tencies in reporting. We code separate DVs for imports to the U.S. from the sanctioned state and
exports from the U.S. to the sanctioned state. We log the trade variables after first adding one to
preserve the observations involving no trade. A priori, we do not have any theoretical expecta-
tions for how sanctions enforcement actions could affect U.S. imports and exports differently.
4
Using the disaggregated trade data will provide finer-grained results, giving our findings more
policy-relevance and providing insights that can contribute to more nuanced theory-building in
the future.
Our primary explanatory variables capture the magnitude of civil penalties for violations
of U.S.-imposed sanctions. One of the trends linked to greater investment in sanctions compli-
ance is the substantial increase in the size of OFAC penalties for sanctions violations starting in
2009 (Early and Preble 2020a). While the number of OFAC civil penalties declined significantly
in recent years, the average size of the penalties increased dramatically. According to Early and
18
Preble (2020), this change reflects OFAC’s strategic shift to a “whale-hunting” strategy that em-
phasized the pursuit of a smaller number of high-profile cases that could result in larger penal-
ties. Given this history, we contend that it is necessary to evaluate the magnitude as well as the
frequency of the penalties OFAC employed in order to fully understand the impact of the
agency’s enforcement actions. We assume that firms’ behaviors will not be affected by smaller-
sized penalties and leave out penalties imposed for under $500,000 from our analysis.
We take data on civil penalties from OFAC, coding the state receiving the penalty (i.e.,
the home-state of firms that violated U.S. sanctions) as well as the U.S.-sanctioned state with
which illicit trade was conducted. To test hypotheses 1-3, we code variables that capture OFAC
enforcement actions across the three specific categories highlighted by our theory. First, we
count dyadic penalties: those imposed on U.S. firms for sanctions violating transactions with a
specific target—i.e., country 2 (c2) in the U.S.-c2 dyad. There are fewer of these penalties in
comparison to our other categories. To test hypothesis 2, we count penalties imposed against
non-U.S. (henceforth foreign) firms for sanctions violating transactions with c2 in the U.S.-c2
dyad. To test hypothesis 3, we count penalties specifically imposed on U.S. firms for sanctions
violating transactions with a U.S.-sanctioned state other than c2 in the U.S.-c2 dyad. Given that
5
larger penalties might be more salient to firms, we code this aggregate variable at three different
penalty thresholds: $500,000, $1 million, and $25 million. Figure 1 presents counts of OFAC
6
enforcement actions for each penalty threshold from 2003 to 2015. It separately depicts penalties
imposed on firms in the U.S. vs. those paid by foreign firms and color-codes the various penalty
sizes.
19
[Figure 1 about here]
We control for factors that could otherwise induce spurious correlation, and for gravity
covariates that (also) improve model fit. First, we control for political affinity with two dummy
variables. Specifically, we recode the Peace Scale (Klein, Goertz and Diehl 2008) such that val-
ues less than 0.5 are coded as an adversarial dyadic relationship and values above 0.5 are coded
as dyadic friendship. Values equal to 0.5—defined by the authors as negative peace—compose
the reference category. As such, these control variables account for underlying political relation
7-
ships that likely influence both the likelihood that sanctions exist and are enforced, and business
expectations regarding the sustainability of trade. Similarly, given that regime type could influ
8-
ence the extent of enforcement and the broader trading environment, also code a variable equal
to 1 when c2 is a consolidated liberal democracy, defined as scoring 7 or above on the Polity IV
combined revised democracy score.
We also control for the most common gravity indicators, using data from CEPII (Mayer
and Zignago 2011). Specifically, we include a measure of the logged, average (population-
weighted) distance between the U.S. and c2, as well as a dummy variable indicating direct conti-
guity. To capture demographic proximity, we include dummy variables for common language
and colonial history. We also control for each state’s logged GDP (in constant dollars). To cap-
ture membership in economic institutions, we include dummy variables indicating c2’s member-
ship status in GATT/WTO and the European Union.
9
We estimate auto-distributed lag (ADL) models with heteroskedasticity-consistent stan-
dard errors. We use the following process to determine the optimal lag length for the dependent
10
20
variable, our key explanatory variables, as well as the GDP variables (which are the only control
variables to demonstrate considerable variation within a given dyad over time). First, we use
11
code to run models with every combination of lags up to four, saving the model output. Second,
we conduct Breusch-Godfrey (BG) tests for serial correlation of orders 1 through 4. Third,
among the subset of models where we fail to reject the BG null hypotheses of white noise resid-
uals, we select the model with minimum AIC. All models are estimated in R version 4.0.4 using
12
the plm package version 2.2-4. The supplemental appendix presents additional information about
these models as well as alternate specifications
Analysis
We find strong evidence that OFAC civil penalties are associated with subsequently low-
er U.S. trade with U.S.-sanctioned states (c2 in the U.S.-c2 dyad). Table 1 presents models exam-
ining the association between OFAC civil penalties and U.S. imports from sanctioned states. The
three models represent three different thresholds of penalty size. Each model includes a number
of lags, but we focus on the sign and statistical significance of the contemporaneous (year t) key
explanatory variables. Regardless of the threshold, results look consistent: the coefficient for
13
dyadic penalty count (i.e., the number of penalties imposed on U.S. firms for violation of sanc-
tions against c2) is negative and statistically significant in all three models. Conversely, the coef-
ficient for count of U.S.-firm penalties with respect to third-party sanctions regimes (not c2 in
the U.S.-c2 dyad) is not significant in any of models 1-3. Notably, the coefficients for the count
of enforcement actions against foreign firms for sanctions violations against c2 are negative and
21
significant in two of the three models in Table 1—only failing to attain statistical significance
when the variable counts smaller penalties (with a threshold of $500,000 or more). This finding
suggests that U.S. firms considering imports from a given U.S.-sanctioned state might reconsider
if foreign firms have faced OFAC scrutiny for similar behavior.
[Table 1 about here]
Table 2 replicates the analysis from Table 1 but uses exports to the U.S.-sanctioned state
(c2) as the dependent variable. Once again, we find largely consistent results across the three
models, though the results differ from those examining U.S. imports. We once again find that
dyadic penalties (of at least $1 million in the case of exports) are associated with lower trade.
The impact of the other categories of enforcement actions is different for exports, though. En-
forcement actions against foreign firms for violating U.S. sanctions against c2 have no statistical-
ly significant effects on U.S. exports to c2. Yet, when OFAC penalized U.S. firms for sanction
violations with respect to third-party sanctions regimes (not c2), we find a consistently negative
association with U.S. exports to c2. This result suggests firms pay more attention to the overall
domestic risk environment created by OFAC penalties for sanctions violations when considering
whether to export to a specific U.S.-sanctioned state.
[Table 2 about here]
In order to illustrate our substantive results, Figure 2 plots the immediate impact of an
OFAC civil penalty on U.S.-target trade, using estimates from Models 1-6. We plot estimates
along with 90% and 95% confidence intervals, the former indicated by the whisker closer to the
estimate. Given that our dependent variables are logged, we can calculate the predicted percent-
22
age deviation from baseline U.S.-target imports or exports associated with the presence of recent
penalties using the formula: exp(β×count) -1 × 100. Estimates and confidence intervals are
14
graphed on the y-axis, while the x-axis indicates the relevant penalty threshold, separately for
U.S. imports and exports. We color-code the three different penalty types. Black estimates and
confidence intervals reflect the predicted percentage deviation from baseline U.S.-target trade
following from a single dyadic penalty (i.e., count = 1). Red indicates the presence of a single
U.S. firm penalty for violation of a sanction against a third party; and blue indicates a single for-
eign-firm penalty for violating sanctions against this particular sanction target—i.e., c2 in the
U.S.-c2 dyad.
[Figure 2 about here]
A few notable patterns emerge. First, predicted reductions in imports tends to be greater
than predicted reductions in exports (though, confidence bounds are also wider with respect to
imports). For five of the six cases, dyadic penalties are associated with a negative and significant
reduction in predicted trade—nearing a 100% reduction in imports when OFAC penalties are at
least $25 million. Conversely, predicted exports are lower only by approximately 25% averaged
across models 4-6. Penalties against foreign firms for violating sanctions against c2 are associat-
ed with reductions in imports from c2 averaging over 50%. Mirroring this finding, penalties
against U.S. firms for violation of sanctions against some third party are associated with approx-
imately 20% lower exports to c2. From a policy perspective, those latter results show that OFAC
enforcement actions that punish violations outside a particular U.S.-target dyad also can discour-
age trade within that dyad. This means that OFAC enforcement actions taken to penalize viola-
23
tions of a particular sanctions regime serve as force-magnifiers that strengthen sanctions’ nega-
tive impact on U.S. trade (most consistently exports) with other sanctioned states.
Our results also suggest that the size of financial penalties imposed as part of OFAC’s
enforcement actions influences their impact on U.S. trade with sanctioned states. For the cate-
gories of enforcement actions that are significant in any of the threshold analyses, their effects
are more consistently statistically significant when higher penalties are imposed. There were very
few dyadic OFAC enforcement actions involving $25 million-plus penalties, but they had potent,
negative effects on U.S. exports and imports with c2. When lower penalty-threshold cases were
incorporated into that dependent variable at $500k-level, the variable’s effect washed out. As
well, OFAC enforcement actions against foreign firms only had a negative impact on U.S. im-
ports from c2 when restricting the pool of cases to those that involved larger-sized penalties. In-
deed, our research design is premised on the notion that small penalties (less than $500k) do not
have widespread deterrent effects and, as such, did not warrant inclusion in our analysis. To con-
firm, we re-ran our analysis using a variable that includes penalties of any size. The results in-
cluded in the appendix show that we find no consistent association between OFAC enforcement
actions that include smaller-sized penalties and U.S.-c2 trade. Our findings indicate that en-
forcement actions involving higher penalties have a more consistently negative impact on U.S.
trade with sanctioned target states than ones involving smaller financial penalties. This suggests
that OFAC would not benefit from simply maximizing the number of penalties it could take
against violators without taking into consideration how large the resulting financial penalties as-
sociated with them are.
24
In summary, our findings suggest that OFAC’s enforcement actions play a powerful role
in supplementing the impact and potential effectiveness of U.S. sanctions policies. Our results
offer the strongest support for our first hypothesis that OFAC enforcement actions will discour-
age U.S. trade with a target when they penalize U.S. firms for violations of that sanctions regime.
The results provide weaker but still meaningful support for hypothesis 2, revealing that OFAC
enforcement actions taken against third-party firms for violating sanctions against a target dimin-
ish U.S. imports to that target when the penalties are over $1 million. Notably, this indicates that
OFAC obtains some domestic benefits from punishing foreign firms. Finally, our analysis indi-
cates that OFAC enforcement actions against U.S. firms for all other sanctions regimes have a
systemic effect on discouraging U.S. exports to particular sanctioned states. While the latter two
effects are not as strong or consistent as dyadic penalties against targets, they indicate that OFAC
enforcement actions also affect firms’ behavior in other sanctions regimes and countries. OFAC’s
enforcement actions thus exacerbate the negative economic effects that U.S. sanctions have on
their targets’ trade in a myriad of ways.
Conclusion
Our findings demonstrate that OFAC can increase the potency of U.S. sanctions by pun-
ishing firms that violate sanctions—both domestically and in third-party states. Our study
demonstrates that sanctions enforcement actions meaningfully changes the trade behavior of
firms and enhance the adverse economic impact they have on target states. We find that, while
even one OFAC penalty could influence firm behavior and hold consequences for aggregate
trade volumes, repeated penalties amplify this effect. While taking enforcement actions against a
25
U.S. firm for violating sanctions involving a particular target have the strongest negative effects
on U.S. trade with that state, OFAC penalties against foreign firms and against U.S. firms for vi-
olating other sanctions regimes also can diminish some trade flows. Our analysis further indi-
cates that that larger-sized penalties have more consistently strong, negative effects than smaller-
sized ones. In sum, OFAC enforcement actions appear to be a potent tool for enhancing the ef-
fectiveness of U.S. sanctions policies.
Our findings contribute in important ways to understanding how and why economic sanc-
tions work, and the strategies sender governments can adopt to make them more effective. Our
study reveals that the degree to which the U.S. government follows through with enforcing its
sanctions influences how severely they disrupt U.S. trade with targets. More than that, we show
that firms appear to reference OFAC’s overall level of sanctions enforcement not just with re-
spect to the specific sanctioned state they are considering doing business. How much senders’
enforcement bodies penalize firms for violations also matters. Sanctions enforcement strategies
that emphasize pursuing cases that result in larger-sized penalties appear as if they will be more
effective than ones that penalize small-time violations. Senders’ enforcement actions need not all
be “whale-hunting”-sized penalties (e.g., Early and Preble 2020a; 2020b), but our analysis sug-
gests that at least around $500,000 to $1 million appears to where penalties become meaningful.
For policymakers, our findings suggest that sender governments receive a significant return on
their investments in enforcing sanctions. Sender governments that want to make their sanctioning
efforts more effective should not just broaden their sanctions’ scope on paper, but also invest
more in enforcing existing sanctions. Importantly, the trade-reducing effects of sanctions en-
26
forcement actions affect both specific sanctions programs and other sanctions programs more
broadly.
Our study suggests numerous paths for additional research on sanctions enforcement. As
a follow-on to our macro-level study, we think that future research conducted at the firm-level
would provide greater nuance in understanding the mechanisms by which sanctions enforcement
actions affect firm behavior. Our analysis further confirms the reputation effects associated with
U.S. sanctions (Peterson 2013, 2014), illustrating that U.S. firms’ behavior is influenced by en-
forcement actions taken against foreign sanctions violators or violators of other sanctions pro-
grams. For OFAC, the effects of being tough on sanctions violations in other contexts carries
over. An important extension of this project could explore the impact of OFAC enforcement ac-
tions on third-party trade with the targets of U.S. sanctions. If OFAC enforcement actions can
also deter third-party trade with the targets of U.S. sanctions, they would be markedly more
powerful than even our analysis suggests. !
27
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Bio statements:
Bryan R. Early is an Associate Professor of Political Science and the Associate Dean for Re-
search at the University at Albany, SUNY’s Rockefeller College of Public Affairs Policy. Dr.
Early is also the founding director of the Project on International Security, Commerce, and Eco-
nomic Statecraft (PISCES). He has published 30 peer-reviewed articles on economic sanctions,
strategic technologies, shadow economies, and political violence. His book Busted Sanctions:
Explaining Why Economic Sanctions Fail (Stanford University Press, 2015) explores the causes
and consequences of sanctions-busting behavior.
Timothy M. Peterson is an Associate Professor in the School of Politics and Global Studies at
Arizona State University. His research spans the topics of foreign policy, international political
economy, armed conflict, and human rights. Research topics include the use and consequences of
sanctions, the link between international economic ties and politics, and the effects of variation
in democratic institutional design. His first book was been published by Stanford University
Press; and his work can be found in journals including British Journal of Political Science, Jour-
nal of Conflict Resolution, and Journal of Peace Research.
Address:
Coor Hall 6664
976 S. Forest Mall
Tempe, AZ 85281
Email: tim@timothypeterson.org!
32
Table 1: Coefficients and 95 percent confidence intervals for ADL models with heteroskedasticity-consistent
standard errors: DV = log U.S. imports
DV = log U.S. imports
Model 1: 500k threshold
Model 2: 1m threshold
Model 3: 25m threshold
LDV t-1
0.69*** (0.44, 0.95)
0.63*** (0.25, 1.00)
0.54* (-0.03, 1.11)
LDV t-2
-0.07 (-0.61, 0.46)
-0.11 (-0.61, 0.39)
0.02 (-0.64, 0.69)
LDV t-3
0.32** (0.07, 0.57)
0.39*** (0.20, 0.59)
0.32*** (0.13, 0.51)
Dyadic penalty t
-1.38*** (-2.15, -0.61)
-1.33** (-2.46, -0.19)
-4.51*** (-7.75, -1.27)
Dyadic penalty t-1
0.58 (-0.83, 1.99)
1.30 (-0.56, 3.16)
-2.92 (-8.30, 2.46)
Dyadic penalty t-2
0.48 (-2.36, 3.32)
-2.56* (-5.20, 0.08)
Dyadic penalty t-3
-3.10*** (-5.30, -0.89)
-2.10*** (-3.52, -0.68)
Dyadic penalty t-4
1.41*** (0.40, 2.42)
2.20* (-0.03, 4.42)
US-third penalty t
0.02 (-0.02, 0.05)
0.01 (-0.08, 0.09)
0.01 (-0.03, 0.05)
US-third penalty t-1
0.05 (-0.02, 0.11)
Foreign-c2 penalty t
-0.33 (-1.05, 0.39)
-1.16*** (-1.99, -0.33)
-0.95* (-1.97, 0.07)
Foreign-c2 penalty t-1
0.89 (-0.49, 2.27)
1.28** (0.13, 2.43)
Foreign-c2 penalty t-2
0.33 (-0.38, 1.04)
0.01 (-0.49, 0.52)
Foreign-c2 penalty t-3
0.21 (-0.48, 0.89)
1.08** (0.07, 2.08)
Foreign-c2 penalty t-4
-2.03*** (-2.95, -1.11)
-2.10** (-3.77, -0.42)
US GDP t
6.17*** (2.02, 10.33)
5.62 (-1.29, 12.53)
6.89** (0.08, 13.70)
US GDP t-1
-9.38** (-16.67, -2.08)
-9.57* (-20.87, 1.74)
-10.31* (-20.69, 0.06)
C2 GDP t
0.25 (-0.61, 1.11)
-0.17 (-1.14, 0.81)
0.06 (-0.98, 1.11)
C2 GDP t-1
0.31 (-0.79, 1.41)
1.08 (-0.67, 2.83)
0.66 (-1.39, 2.71)
C2 GDP t-2
-0.74 (-1.76, 0.28)
-0.74 (-1.93, 0.44)
-0.60 (-2.16, 0.96)
C2 GDP t-3
0.66* (-0.03, 1.34)
0.31 (-0.56, 1.18)
0.06 (-0.80, 0.92)
C2 GDP t-4
-0.39 (-1.29, 0.52)
-0.37 (-1.31, 0.57)
-0.06 (-1.23, 1.12)
US ally
0.09 (-0.09, 0.27)
0.11 (-0.09, 0.32)
0.10 (-0.10, 0.30)
US rival
-0.04 (-0.27, 0.20)
0.02 (-0.24, 0.28)
-0.05 (-0.39, 0.29)
C2 democracy
0.09 (-0.06, 0.25)
0.10 (-0.06, 0.26)
0.06 (-0.10, 0.22)
log Distance
0.23 (-0.12, 0.57)
0.16 (-0.13, 0.45)
0.17 (-0.14, 0.48)
Contiguity
0.39* (-0.04, 0.82)
0.35* (-0.06, 0.75)
0.41* (-0.03, 0.86)
C2 EU
0.02 (-0.08, 0.13)
0.02 (-0.10, 0.15)
-0.01 (-0.18, 0.16)
C2 GATT/WTO
0.01 (-0.13, 0.15)
0.09 (-0.04, 0.21)
0.13 (-0.07, 0.32)
Common language
-0.01 (-0.12, 0.09)
0.00 (-0.12, 0.12)
0.00 (-0.15, 0.15)
Constant
72.09* (-6.80, 150.98)
90.09 (-19.60, 199.79)
78.21 (-17.03, 173.45)
Observations
604
604
604
Adjusted R2
0.933
0.932
0.908
Breusch–Godfrey: order 1
1.07 (p = 0.3)
0.36 (p = 0.55)
0.42 (p = 0.51)
Breusch–Godfrey: order 2
1.1 (p = 0.58)
1.04 (p = 0.59)
2.1 (p = 0.35)
Breusch–Godfrey: order 3
5.54 (p = 0.14)
1.56 (p = 0.67)
7.42 (p = 0.06)
Breusch–Godfrey: order 4
6.15 (p = 0.19)
2.06 (p = 0.72)
7.71 (p = 0.1)
* p less than 0.1, ** p less than 0.05, *** p less than 0.01
33
Table 2: Coefficients and 95 percent confidence intervals for ADL models with heteroskedasticity-consistent
standard errors: DV = log U.S. exports!
DV = log U.S. exports
Model 4: 500k threshold
Model 5: 1m threshold
Model 6: 25m threshold
LDV t-1
0.80*** (0.68, 0.93)
0.82*** (0.70, 0.94)
0.82*** (0.70, 0.93)
LDV t-2
0.12** (0.01, 0.24)
0.10 (-0.03, 0.22)
0.10 (-0.02, 0.22)
LDV t-3
-0.04 (-0.18, 0.10)
-0.03 (-0.17, 0.11)
-0.04 (-0.18, 0.10)
LDV t-4
0.09* (-0.01, 0.19)
0.09* (-0.01, 0.18)
0.09* (-0.01, 0.19)
Dyadic penalty t
-0.07 (-0.19, 0.05)
-0.65*** (-0.84, -0.45)
-0.25*** (-0.38, -0.12)
Dyadic penalty t-1
-0.01 (-0.12, 0.09)
-0.33*** (-0.52, -0.14)
Dyadic penalty t-2
-0.09 (-0.28, 0.09)
Dyadic penalty t-3
-0.28*** (-0.47, -0.08)
US-third penalty t
-0.15*** (-0.25, -0.06)
-0.40*** (-0.59, -0.22)
-0.14*** (-0.19, -0.09)
US-third penalty t-1
0.01 (-0.01, 0.03)
-0.28*** (-0.41, -0.15)
0.09** (0.01, 0.17)
US-third penalty t-2
0.14*** (0.05, 0.24)
0.12*** (0.06, 0.18)
0.27*** (0.07, 0.47)
US-third penalty t-3
-0.12*** (-0.18, -0.06)
0.16 (-0.06, 0.38)
US-third penalty t-4
0.30* (-0.03, 0.62)
Foreign-c2 penalty t
0.00 (-0.05, 0.06)
-0.01 (-0.13, 0.10)
-0.05 (-0.19, 0.09)
Foreign-c2 penalty t-1
0.10* (-0.00, 0.20)
0.10 (-0.02, 0.22)
0.17*** (0.07, 0.26)
Foreign-c2 penalty t-2
0.04 (-0.13, 0.21)
0.00 (-0.12, 0.13)
0.01 (-0.12, 0.13)
Foreign-c2 penalty t-3
0.18*** (0.09, 0.27)
0.19*** (0.09, 0.28)
0.18*** (0.05, 0.32)
US GDP t
-17.20*** (-28.99, -5.42)
0.25 (-1.88, 2.39)
-17.45*** (-29.53, -5.37)
US GDP t-1
47.01*** (21.43, 72.60)
3.23* (-0.09, 6.54)
17.88*** (11.70, 24.06)
US GDP t-2
-52.98*** (-77.97, -27.98)
-31.50*** (-42.56, -20.45)
-36.13*** (-50.47, -21.80)
US GDP t-3
19.26*** (9.80, 28.72)
15.25*** (8.09, 22.41)
9.86*** (5.90, 13.82)
US GDP t-4
15.40*** (6.83, 23.97)
C2 GDP t
0.50*** (0.25, 0.74)
0.48*** (0.24, 0.72)
0.49*** (0.25, 0.72)
C2 GDP t-1
-0.33** (-0.59, -0.06)
-0.32** (-0.58, -0.06)
-0.36** (-0.63, -0.08)
C2 GDP t-2
-0.13 (-0.41, 0.15)
-0.09 (-0.35, 0.18)
-0.08 (-0.35, 0.19)
C2 GDP t-3
0.27** (0.00, 0.54)
0.21 (-0.06, 0.49)
0.24* (-0.02, 0.51)
C2 GDP t-4
-0.27** (-0.53, -0.01)
-0.24* (-0.51, 0.03)
-0.26* (-0.52, 0.01)
US ally
-0.01 (-0.06, 0.04)
-0.01 (-0.06, 0.04)
-0.01 (-0.06, 0.04)
US rival
-0.03 (-0.10, 0.05)
0.00 (-0.10, 0.10)
-0.04 (-0.11, 0.03)
C2 democracy
0.02 (-0.03, 0.08)
0.02 (-0.03, 0.07)
0.02 (-0.03, 0.07)
log Distance
-0.02 (-0.07, 0.04)
-0.03 (-0.09, 0.02)
-0.02 (-0.07, 0.04)
Contiguity
0.06 (-0.03, 0.14)
0.04 (-0.04, 0.12)
0.06 (-0.03, 0.14)
C2 EU
-0.02 (-0.08, 0.04)
-0.02 (-0.08, 0.04)
-0.01 (-0.08, 0.05)
C2 GATT/WTO
-0.03 (-0.08, 0.02)
-0.02 (-0.07, 0.03)
-0.03 (-0.08, 0.03)
Common language
0.04 (-0.02, 0.10)
0.04 (-0.01, 0.10)
0.04 (-0.01, 0.10)
Constant
91.59*** (28.52, 154.65)
-59.09* (-122.89, 4.71)
602.79** (73.36, 1,132.21)
Observations
604
604
604
Adjusted R2
0.986
0.986
0.985
Breusch–Godfrey: order 1
0.35 (p = 0.55)
0.56 (p = 0.46)
0.39 (p = 0.53)
Breusch–Godfrey: order 2
2.33 (p = 0.31)
2.02 (p = 0.36)
1.97 (p = 0.37)
Breusch–Godfrey: order 3
2.34 (p = 0.51)
2.03 (p = 0.57)
2 (p = 0.57)
Breusch–Godfrey: order 4
4.42 (p = 0.35)
3.41 (p = 0.49)
4.21 (p = 0.38)
* p less than 0.1, ** p less than 0.05, *** p less than 0.01
1
Figure 1: Yearly counts of OFAC civil penalties
2
Figure 2: Predictions from Models 1-6 1 with 90% (narrower whiskers) and 95% (wider
whiskers) confidence intervals
3
Endnotes
The opportunity costs facing targets (and senders) vary, with consequences for underlying leverage and vulnerabil
1-
ity (Crescenzi 2003, Peterson 2020).
Financial sanctions likely compose the strongest and farthest-reaching lever of U.S. coercion, with the ability to
2
disrupt all forms of commerce. We thus include them in our analysis because we expect they also affect firms’ ability
to participate in international trade.
Given that the commonly used sanctions data are unavailable after 2005 (Morgan, Bapat and Kobayashi 2014), we
3
identify U.S.-sanctioned states using the ICEWS events data (Boschee et al. 2015). To convert ICEWS events into
early indicators of sanction presence, we code running counts of code 163: “Impose embargo, boycott, or sanction”
for all cases where the source is the U.S. government and the target is the target government. We also code running
count of code 085: “Ease economic sanctions, boycotts, or embargoes.” The appendix provides further details.
McLean and Whang (2014) show that the public—which would likely be consumers of imports—might have a
4
role in putting sanctions on the U.S. government’s agenda. Firms—particularly export firms—might be better able to
overcome collective action problems to lobby for trade policy that protects their bottom line.
The appendix includes models that aggregate these three penalty types to create a single, yearly measure of OFAC
5
penalty counts.
These thresholds follow from consideration of common penalty sizes in the OFAC data, along with author judge
6-
ment regarding penalty magnitudes that would capture firm attention. We operationalize penalty counts because we
do not expect linear relationship between each dollar in penalties and the subsequent level of U.S. trade with its
sanctioned states. We think that the frequency of OFAC enforcement actions also matters beyond total observed
penalty. The appendix presents additional models with a $50 million threshold, with which we find consistent re-
sults.
While these variables do not account for dyadic alliances per se, the authors note that the highest values of positive
7
peace capture common membership in a security community.
One might consider the lack of a variable for sanction severity to be a problem given that more severe sanctions
8
might lead both to more OFAC enforcement and a greater reduction in U.S.-target trade; this would constitute a clas-
sic instance of spurious correlation. Ultimately, a yearly measure of severity is difficult to obtain. For example, TIES
costs variables are coded holistically for the entire duration of the episode and thus are analytically post-treatment
for our study. However, our political affinity measure could reduce the prospect of this spurious correlation given
that, as Drezner (1998) notes, sanctions would be most successful—and yet are least likely to be employed—against
friendlier states. The appendix presents models including the frequency of ICEWS sanctions mentions as a measure
of sanction severity against c2.
U.S. values are constant for level of democracy, GATT/WTO membership, EU membership, and land area, and so
9
we omit these indicators from the models.
For all models, we reject the null hypothesis of constant error variance in Breusch-Pagan tests.
10
Given that trade composes part of GDP, simultaneity could be an issue in our models. However, results were gen
11 -
erally consistent in alternate models where we lagged all explanatory variables by one period.
We also compare BIC across models. Often, the model with the lowest AIC also has the lowest BIC. When in
12
disagreement, it is always the case that the minimum BIC favors models with fewer lags. We prefer to minimize AIC
given that, particularly with our small sample size, BIC might penalize added lags that are useful to capture the dy-
namics underling our the relationship between OFAC penalties and trade.
We do not have theoretical reasons to expect a long-run equilibrium between OFAC penalties and trade flows.
13
However, we do calculate the long-run multiplier for each model in the appendix.
1
