The effect of foreign direct investment on the use and success of US sanctions

Abstract

Although the relationship between trade and the use and success of sanctions is frequently studied in international relations, researchers have generally failed to address the importance of foreign direct investment (FDI) on sanctions despite global capital markets dwarfing the exchange of goods and services. Using panel data for 171 countries from 1971 to 2000, we test the effect of FDI on the use and success of sanctions imposed by the USA. We find evidence that a high level of economic engagement in the form of US FDI as a percentage of the recipient county’s gross domestic product reduces the likelihood of the use of US sanctions. We also find that, when sanctions are imposed, declining US FDI generally has a positive and significant effect on sanctions success. However, if non-US firms offset lost US FDI, the probability of sanctions success decreases. The results show that investors may have an important influence on foreign policy outcomes.

Keywords

FDI globalization sanctions sanctions success

Introduction

When the US government imposes economic sanctions it seeks to increase a target country’s costs for pursuing a policy that the USA finds objectionable. Traditionally, empirical research has focused on how trade relationships between the USA and the targeted country affect the likelihood that sanctions are successful. However, this leaves an important area in political economy, foreign direct investment (FDI), unexplored by the sanctions success literature. The lack of empirical studies is curious given the well-documented importance of foreign capital flows to modern economies (Hufbauer et al., 2007: 47) and the effect of disinvestment and economic sanctions on the collapse of the apartheid regime in South Africa (Brooks, 2002; Kaempfer and Lowenberg, 1986).¹ Disinvestment is also likely to play an increasingly significant role in international relations. Global capital markets are immense when compared with the exchange of goods and services (Gartzke et al., 2001), with FDI expanding about five times as fast as merchandise trade since the mid-1980s (Lairson and Skidmore, 2003: 123–124).

In this paper, we address this gap in the literature by developing and testing arguments about the relationship between FDI and the use and effectiveness of sanctions imposed by the USA. Building on the liberal perspective regarding the potential pacifying effect of trade on conflict,² we expect that increased capital flows raise the costs of sanctions to both the sender and target of sanctions and decrease the likelihood of their use. However, once sanctions are imposed, because of the high costs of targeting countries for severing economic investment ties, we expect that, if US FDI to the target decreases, the probability of their success will increase. Finally, because FDI between the USA and the targeted state could be replaced by other global sources, we not only look at how changes in US FDI affect the success of US sanctions, but also consider the effect of global investment decisions in the target. If increases in global FDI offset departed US FDI, the likelihood of sanctions success is expected to diminish.

The results from our empirical analysis confirm our expectations that, if US FDI declines during sanctions, the likelihood of US success at achieving its policy goals increases significantly. However, if global FDI to the targeted country increases during sanctions, offsetting losses from declining US FDI, the overall success of US sanctions is compromised. We also find that, as the importance of US FDI to other countries increases, the likelihood of disputes with that country rising to the level of formally imposed sanctions decreases significantly.

Our findings have important implications for the study of economic sanctions and FDI. The results back the expectation that investors have a significant effect on the outcome of economic coercion attempts, which has implications for the globalization of FDI. Our findings suggest that even an economic superpower like the USA has its coercive capability tempered by the cumulative decisions of participants in global financial markets. Thus, as others have noted (Evans, 1997; Ferguson and Mansbach, 1999; Keohane and Nye, 1977; Kindleberger, 1969; Mann, 1997; Strange, 1995), the nation-state is not the only actor whose inputs need to be considered in determining outcomes in international relations.

The remainder of the study is presented in the following sections. In the first two sections, we discuss relevant literature and develop hypotheses related to FDI and the use and success of economic sanctions. The research design, methods and results of our empirical analysis are shown next. The last section concludes the paper with a brief discussion showing the important role played by FDI in relations between the USA and Iran and South Africa.

FDI and the effectiveness of US sanctions

An important topic in the economic sanctions literature is the factors associated with sanctions success (Allen, 2005; Dashti-Gibson et al., 1997; Drury, 1998; Marinov, 2005; Nossal, 1989; Pape, 1997; van Bergeijk, 1989). Most research on the success of sanctions takes an instrumental approach (Wallensteen, 1983), focusing on whether the target of sanctions changed its policy to comply with the demands of the sender (Hufbauer et al., 2007; Pape, 1997). The standard explanation for how sanctions achieve success is described by Pape (1997: 93–94) as that sanctions “Seek to lower the aggregate economic welfare of a target state by reducing international trade in order to coerce the target government to change its political behavior”.

The consensus of the sanctions literature has been that they are not very successful in achieving policy goals, mostly because they are unable to generate enough costs to the target country’s leadership to make it change behavior (Askari et al., 2003; Barber, 1979; Doxey, 1971; Lindsay, 1986; Nossal, 1989; Pape, 1997). However, previous research has established a strong correlation between the economic damage to the targeted state’s economy and the political success of sanctions (Dehejia and Wood, 1992; Drury, 1998; Hufbauer et al., 2007: 106). Thus, a main reason proposed for the failure of sanctions is their inability to cut target countries off from alternative sources of goods, resulting in an inability to impose sufficient costs.

The role of costs also figures into FDI and sanctions work (Biglaiser and Lektzian, 2011). The primary connection between FDI and sanctions revolves around the ability of the sending country to increase investment risk and thus raise costs in the targeted country. Much of the FDI literature assesses the effect of risk on MNC decisions, with many arguing that risk tends to lessen investor interest (Biglaiser and DeRouen, 2006; Henisz, 2000; Jensen, 2003, 2006, 2008; Jensen et al., 2012; Li, 2006, 2009; Li and Resnick, 2003; Malesky, 2009). In the case of US multinational corporations (MNCs), the US government has many resources to monitor sanctions infractions and punish violations that increase investor costs (Morgan and Bapat, 2003). The US government also can eliminate incentives that are only available to US MNCs such as access to the Export–Import Bank or the Overseas Private Investment Corporation, which again raises investor costs (Biglaiser and Lektzian, 2011).

Similar to the effect of decreased trade with the target, we expect that disinvestment from the target will result in costly disruptions in targeted economies. Moreover, US MNCs are major suppliers of foreign capital and if US disinvestment occurs it can present difficulties for the targeted country’s economy. Leadership in the targeted states can attempt to develop counter measures to offset the effect of economic losses (Allen, 2005; Bolks and Al-Sowayel, 2000; Galtung, 1967), but because of the importance of foreign capital, declining FDI may pressure state leaders to offer better deals to foreign investment firms to replace departing investment. While traded goods can often be produced domestically, as the history of import substitution industrialization in the 1940s–1970s suggests, a lack of domestic capital reserves is possibly a more difficult problem to overcome (Hufbauer et al., 2007).³ If attracting foreign firms to replace departing investment becomes too costly, the targeted leadership may find that it is better served by placating the demands of the sender nation in order to bring the sanctions to an end. Because of this, we expect declining FDI to targeted nations during sanctions to be positively associated with the ability of the sender to achieve its sanctioning goals.

Thus, our theoretical mechanism linking sanctions to policy change by the target is similar to that proposed in the majority of the sanctions literature. If the cost of resistance is made greater than the cost of compliance, the target will prefer to comply.⁴ US FDI withdrawal owing to sanctions will raise the costs to the target for resisting US government demands and increase the likelihood of policy change by the targeted country. Gartzke and Li (2003: 127) emphasize the importance of “the productive efficiency of markets for their rents and for the political survival of leaders”. If these markets suffer owing to foreign disinvestment linked to sanctions, we expect those leaders to take steps to reduce the incompatibility that brought about the sanctions. Thus, our first testable expectation is that, if US FDI to the target declines during sanctions, the likelihood of their success will increase.

Hypothesis 1: Decreasing levels of US FDI during sanctions will result in an increased probability that the target of sanctions will comply with US demands.

It is important to consider that, while the USA is a major supplier of foreign capital, it is not alone. As noted earlier, when the USA imposes sanctions it has many tools for increasing the risk associated with US-based MNCs investing in the target (Morgan and Bapit, 2003). Globally, however, the USA has far fewer tools for increasing risk for foreign investors. Additionally, existing studies that examine the effect of sanctions on trade (Askari et al., 2003; Caruso, 2003) provide evidence that, under certain circumstances, global trade with the target increases during US sanctions.

Despite efforts by US policy-makers to seek multilateral support for sanctions (Drezner, 2000; Martin, 1992; Miers and Morgan, 2002), a reason commonly voiced for their failure is that they are unsuccessful at isolating the target from alternative trade sources (Haass, 1997, 1998; Pape, 1997; Wallensteen, 1983).⁵ The role of sanctions buster or “black knight” countries that come to the aid of the target (Early, 2009), and the difficulties involved in establishing and maintaining a sanctions coalition (Drezner, 2000; Kaempfter and Lowenberg, 1999; Mansfield, 1995; Martin, 1992; Miers and Morgan, 2002), are frequent topics in the sanctions literature. Hufbauer et al. (2007) maintain that one reason why sanctions may fail is that powerful or wealthy allies of the target come to its aid.⁶ Similarly, Early (2011) looks at how the number of trade-related black knights that come to the target’s aid affects the likelihood of sanctions success. Rather than focus on the decisions of states to promote or discourage sanctions-busting, we follow a liberal perspective (Moravcsik, 1997) and study the incentives at the individual or private firm level.⁷

Globally MNCs are motivated by profit opportunities, but their decisions are tempered by potential risks associated with investing in a sanctioned state (Shambaugh, 1999). Indeed, risk considerations may factor even more in investor decisions than traders because “bankers or investors risk not only legal redress but also losing their capital” (Hufbauer et al., 2007: 47).⁸ The USA can use its considerable influence in the international system to attempt to increase risk to global firms in the targeted state through the inclusion of provisions for secondary sanctions against firms operating outside the USA that violate US sanctions policies.⁹ However, attempts such as those found in the Helms–Burton Act and the Iran–Libya Sanctions Act have met with strong resistance from foreign countries (Boudreau, 1997; Clark and Wang, 2007; Clawson, 1998; Early, 2009; Haass, 1998; Hufbauer et al., 2007; Shambaugh, 1999).¹⁰ In one of the only empirical analyses of this topic, Shambaugh (1999) found that the USA has had limited success in enforcing its export control regime through the use of secondary sanctions directed against foreign firms.¹¹ While global firms are probably influenced by the same risk profile as US firms, and global firms thus may avoid a US-sanctioned country because it seems like a bad bet, US firms may be leaving not because of risk considerations or economic opportunities but more as a result of US government pressure.¹² As Cortright and Lopez (2000: 229) note regarding UN sanctions, firms in third party states surrounding the targeted country will have a strong economic motivation to break sanctions. Without the support of these bordering states, policy-makers and scholars contend that even multilateral efforts like UN sanctions are destined to fail (Doxey, 1997).

If the USA fails to increase the investment risk for global investors in the targeted state, and if US FDI declines, then profit-motivated global investors are likely to increase their investments (Kaempfer and Lowenberg, 1999: 54). Indeed, foreign investors stand to gain based on sales to the domestic market, access to natural resources and the availability of scarce human capital in the host countries. Moreover, if targeted countries lose US FDI, they have an incentive to seek out replacement investment from firms operating outside the US jurisdiction. Gartzke and Li (2003: 127) argue that, in their competition with other states to attract foreign capital, “States, … are more often forced to construct their economic policies to please global investors and transnational firms”. Our expectation, based on arguments made in the sanctions literature, is that, if the USA is unsuccessful in increasing investment risk for global FDI, and targeted states are able to attract global FDI to replace lost US FDI, sanctions are likely to fail in achieving their policy goal.

Hypothesis 2: Increasing levels of global FDI during sanctions will result in a decreased probability that the target of sanctions will comply with US demands.

Our final hypothesis regarding the success of US sanctions is that the effect of changes in US FDI on the success of US sanctions will be conditional, depending on whether global FDI decreases, stays the same or increases during the course of sanctions. We expect that the effect of changes in US FDI on the success of sanctions will be greatest when global investors do not undermine the effect of declining US FDI on the targeted government.

Hypothesis 3: The effect of changes in US FDI on the outcome of sanctions will be greatest when global FDI to the target remains the same or is decreasing.

FDI and the use of US economic sanctions

In the globalization era, countries are more economically linked to each other than ever before. A sneeze in the USA can cause a cold elsewhere. Just-in-time manufacturing and outsourcing suggest the interconnectedness of the global economy. The central logic behind most liberal studies is that this economic engagement makes states less likely to escalate disputes to the military level because increased trade increases the costs of conflict (Blainey, 1988: ch. 2; Doyle, 1997; Gartzke et al., 2001; Polachek, 1980; Schneider et al., 2003). Likewise, it can be argued that sanctions raise the costs of conflict by disrupting economic commerce, and by the same logic sanctions should be less likely to occur when economic engagement between two states is high.

Thus, an intriguing question for this study is whether decreased levels of economic engagement during the course of sanctions will affect future political relations between the USA and the targeted country? If US investment in the targeted country declines during sanctions, we expect that this will increase the probability of achieving the short-term policy objectives connected to the sanctions. However, a longer-term question is how changes in FDI during sanctions might affect future political interaction between the target and sender.

One line of argument is that, if target states anticipate the potential costs of sanctions being higher when the level of US investment in their country is high, it could allow the USA to gain compliance more frequently without the need to impose sanctions. Additionally, as US FDI increases in importance to a potential target of sanctions, it also increases in importance to the USA. Thus, the inhibition to sanctions by the USA and the target is high when US FDI is high and we would expect a decreased likelihood of observed sanctions. A further implication of this expectation is that, if US FDI declines, the USA might face a situation where it imposes more sanctions but actually has less leverage in terms of restricting capital, as is the case in North Korea (Goodman, 2003) and was true in the Soviet Union (Carswell, 1981: 264). Based on the logic stated above, we expect that increased amounts of US FDI will decrease the probability that sanctions will be realized.

Hypothesis 4a: High levels of US FDI will result in a decreased probability of sanctions being imposed.

Hypothesis 4a is based on an opportunity costs argument (Polachek, 1980), where increased levels of economic interaction increase the perceived costs of conflict and result in a decreased probability of conflict occurring. The opportunity costs logic supporting hypothesis 4a is broadly consistent with the logic supporting hypotheses 1–3. The anticipation of high cost sanctions deters states from using them, while the realization of costs, in cases that do make it to the imposition stage, play an important role in determining the outcome of sanctions.

A potential alternative explanation is considered here because of its importance to the trade and conflict literature. Neorealists argue that tensions may arise over how the gains from trade are distributed, offsetting any pacifying effects of trade presumed by liberals (Barbieri, 2002: 28). Additionally, Waltz (1979) argues that as economic interactions between states increase, the opportunity for conflict also increases. Based on this alternative argument, one might expect that, as more multinational firms that are based in the USA locate their investments in a foreign country, there is an increased opportunity for economic or political disagreements that might rise to the level of formalized government sanctions by the USA. Additionally, the USA may see an increased opportunity to coerce economically when there is greater level of economic interaction. When there is little trade or investment between countries, imposing sanctions may not seem like a logical tool of coercion. This line of reasoning leads to the opposite expectation as stated in hypothesis 4a. We state this hypothesis formally here as hypothesis 4b, and test it against our expectation stated in hypothesis 4a.

Hypothesis 4b: High levels of US FDI will result in an increased probability of sanctions being imposed.

Methods and research design

We gathered data for 171 countries on an annual basis from 1971 to 2000 to test our hypotheses.¹³ The basic unit of analysis is the country–year. For the purposes of testing hypotheses 1–3, the main dependent variable is the success of sanctions imposed by the USA in a given year, and the country–years that are analyzed are those where the USA sanctioned a country.¹⁴ After accounting for sample attrition owing to missing data, there are 574 sanctioned country–years.¹⁵

Others have noted that, for sanctions to end successfully, the target country must decide to comply with the sender’s demands (Allen, 2005: 127; McGillivray and Stam, 2004: 157; Smith, 1997). If the target does not comply, then sanctions either continue or they fail, depending on whether or not the sender chooses to quit. Similarly, our primary interest is in how changes in FDI during sanctions affect the target’s decision to resist or comply, thus, we focus on the time until sanctions conclude successfully. Sanctions that fail will be observed up until the time that the sender decides to quit and accept a failed sanction outcome. At that point, they will be treated as censored because we cannot know if the target would have complied had the sanctions remained in place for additional years. Following the above logic, and precedent established by previous studies of sanctions success (Lektzian and Souva, 2007; Nooruddin, 2002; Wallensteen, 1983), success is coded in the year that the sanction ended.

The sanctions success variable used in this analysis is a dichotomous indicator based on Morgan et al.’s (2009) sanction outcome variable. TIES records 11 different non-ordered settlement outcomes of sanctions cases and the start and end date of sanctions and threats of sanctions. We code the success of sanctions as described by Morgan et al. (2009), where the key determinant of whether the sanctions were successful is whether the sender or target achieved more of its objectives. When testing hypothesis 4, the dependent variable is the imposition of sanctions by the USA. This variable is coded 1 in the year that sanctions were imposed by the USA against the country being observed. The data for the sanction imposition variable come from Morgan et al. (2009). After accounting for sample attrition owing to missing data, there are 3047 country–years.¹⁶

Building on work by Nooruddin (2002) and Lektzian and Souva (2007), two-stage Heckman models are also estimated that complement the single equation models. These models are meant to statistically control for issues related to potential selection effects on the outcome of sanctions. If the imposition of sanctions is partially determined by the likelihood of their success, then estimates in the single equation models will be biased (Bushway et al., 2007). The first-stage dependent variable in the Heckman models is the occurrence of a sanction involving the USA as a sender. This variable is coded 1 for each year that the USA imposed one or more sanctions against a country.¹⁷ The second-stage dependent variable is the success of sanctions and it is coded in the same way as in the single equation models with success as the dependent variable.¹⁸

Key independent variables

Our primary interest is the relationship between changes in FDI and sanctions outcomes. We operationalize US FDI to each country using net capital outflow data from the Bureau of Economic Analysis (BEA). These data are measured in current US dollars and converted to billions of dollars for ease of interpretation. The BEA data consist of funds that US parent firms provide to their foreign affiliates net of funds that foreign affiliates provide to their US parents.¹⁹ We use data from the World Bank (2008), to measure global FDI inflows from all countries in the world to each country.²⁰ The global FDI data measure net inflows from all countries, including the USA. We are interested in how the success of sanctions will be affected if US FDI to that target declines and also how the success of sanctions is affected if global competitors increase their FDI flows to the targeted country to offset any losses from US firm disinvestment. Therefore we subtract out US investment from global investment. The US and global FDI data are comparable as both are in current US dollars, both address net inflows and both are measured as a percentage of the recipient’s gross domestic product (GDP).²¹

Others have focused on preexisting trade linkages and reasoned that high trade linkages between the sender and target should increase the likelihood of success (van Bergeijk, 1994). Our argument focuses on costs to the target as a result of lost investment rather than the potential for imposing costs. Therefore, we estimate the effects of changes in FDI on sanctions success by calculating cumulative annual changes in FDI over the course of sanctions. It is important to focus on changes in FDI rather than levels because the target has already considered its pre-sanctions level of dependence on FDI from the sender country when it decided to resist the sender’s sanctions threat.²² For FDI linkages to coerce the target after sanctions are imposed, the target must have initially miscalculated the potential cost of the sanctions when it decided to resist the sender’s original demands (Hovi et al., 2005). Thus, observing the pre-sanctions economic linkages is of less value for studies of the success of sanctions than observing the changes in those linkages over the course of a sanctions episode.

Operationally, we calculate the cumulative change in US and global FDI to the target, beginning with the change from the year prior to the sanction imposition until the first year of the sanctions. Then we add to that the change from the first to the second year, followed by the change from the second to the third year, and so on. This allows us to accumulate the total amount of change over the course of the sanctions episode.

Another important aspect of this operationalization is that, by accumulating changes in FDI over the course of sanctions, it accounts for the importance of sustained economic pressure on targeted governments over time. Baldwin (1985: 111) notes that “Economic statecraft often works slowly, but this is not necessarily the ‘inherent weakness’ it is often made out to be”. Additionally, Schelling (1966: 69) notes, “A given amount of coercive pressure exercised over an extended period of time, allowed to accumulate its own momentum, is a common and effective technique of bypassing somebody’s commitment”.

The main independent variable for testing the initiation of sanctions (hypotheses 4a and 4b) is the level of US FDI in other countries as a percentage of GDP. Theoretically, we expect that, when the potential costs of sanctions to both the sender and target are high, they will be motivated to seek compromises and not disrupt economic interactions. When levels of US FDI as a percentage of a country’s GDP are high, we expect that the cost of disrupting that investment will be high for both the recipient country and for firms in the USA, resulting in a lowered probability of observing sanctions in the dyad. As in the success equation, we operationalize US FDI to each country as a percentage of that country’s GDP using net capital outflow data from the BEA. The difference is that in the success equation we were interested in changes in the amount of US FDI during sanctions, whereas in the onset equation we are interested in the level of US FDI as a percentage of the target state’s GDP. Finally, we also include a variable measuring the importance of US FDI to the overall US economy. We operationalize this variable as US FDI as a percentage of US GDP.

Control variables

Democratic states have been found to engage in fewer sanctions between each other (Cox and Drury, 2006; Lektzian and Souva, 2003) while sanctions against a democracy generally have been found to be more likely to result in successful coercion (Brooks, 2002).²³ Additionally, democratic institutions may affect the amount of FDI flowing to a country (Henisz, 2000; Jensen, 2003, 2006, 2008). Because of this, we control for the presence of democratic institutions in the target of sanctions in the success stage and for all potential targets in the first stage. Data come from the Polity2 variable (Marshall and Jaggers, 2006). The measure is a dichotomous indicator coded 1 when polity is ≥6 and 0 in all other cases.

When an international organization is involved in the sending coalition, this could provide additional credibility to the goals of sanctions (Abbot and Snidal, 1998) and increase the cohesiveness of the coalition (Drezner, 2000; Miers and Morgan, 2002), making them more likely to be successful. The actions of international organizations against the target state might also affect FDI flows to the country (e.g. credit ratings, interest rates, loans). Thus, we control for the presence of an international organization in the equations estimating sanctions success using data from Morgan et al. (2009).

In order to control for changes in the target’s economy during sanctions, which may be correlated with FDI and the success of sanctions, we include the percentage growth in the target’s GDP. Growth data come from the World Bank (2008). When two actors are more distant, it can diminish the ability of one state to influence the actions of the other. Therefore, in the equation estimating the success of sanctions we control for distance using the great circle distance formula, measured from capital to capital.²⁴ Powerful states have a strong international agenda and may be more difficult to influence than lesser states. Additionally, the USA may prefer to engage more powerful states economically rather than militarily, leading to an increased likelihood of US sanctions. Therefore, we control for capabilities in the initiation and success equations. Capabilities data are obtained using EUGene (Bennett and Stam, 2000) and are logged.

Controls are also needed for military force concerns. Lektzian and Sprecher (2007) document a relationship between the use of military force and the use of economic sanctions and Li (2008) shows a relationship between military force and FDI. Thus, we control for the onset of military force when estimating both the occurrence of sanctions and their potential success.²⁵ Because sanctions tend to be used in response to international crises such as civil conflicts, and the presence of civil conflict can affect the risk of FDI, we control for the occurrence of Civil war in the equations estimating the use and success of sanctions by the USA.²⁶

Alliances ties between the sender and target have also been proposed as an important explanatory factor in the success and use of sanctions (Allen, 2005; Drezner, 1999). Alliance data come from the Alliance Treaty Obligations and Provisions dataset (Leeds et al., 2002), and indicate the presence of an alliance between the target and the primary sender of sanctions. Finally, in order to account for temporal dependence in the data, we include a variable measuring the number of years that sanctions were in place (success equation) or the number of years without a sanction (onset equation), and three cubic spline variables (Beck et al., 1998).²⁷

Results

Table 1 presents the results of three models showing the effect of changes in global and US FDI on sanction targets. Model 1 estimates the effect of decreases in US and global FDI flows to the targeted country on the probability of achieving a successful sanctions outcome. A logistic regression model is estimated with standard errors clustered on the country.²⁸

Table 1.

FDI and sanctions onset and success

	Model 1: sanctions success	Model 2	Model 3: sanctions success
Outcome equation
Cumulative Change in US FDI	−0.32*** (−3.49)		−0.18*** (−3.31)
Cumulative Change in Global FDI	−0.10* (−1.83)		−0.06** (−2.54)
Interaction of ΔUS FDI ΔGlobal FDI*	0.01* (1.88)		0.004*** (3.00)
International Organization	0.12 (0.30)		−0.31 (−1.37)
ln(Distance)	−0.32 (−0.65)		−0.35 (−1.22)
MID with USA	0.24 (0.20)		0.19 (0.25)
Civil War	−0.30 (−0.55)		−5.26*** (−12.31)
Democracy	0.12 (0.21)		−0.42 (−1.28)
ln(capabilities)	−0.040 (−0.18)		0.05 (0.50)
GDP Growth (Annual Percentage)	−0.07** (−2.45)		−0.02 (−0.75)
Alliance (USA–Target)	1.13* (1.73)		0.77 (1.64)
Constant	−0.99 (−0.20)		1.85 (0.69)
Selection equation		Sanctions	Sanctions
US FDI as a Percentage of Target GDP		−0.12** (−2.42)	−0.02 (−0.91)
US FDI as a Percentage of US GDP		−4.18 (−1.10)	3.43 (1.11)
MID with USA		0.99 (0.95)	0.56 (1.61)
Civil War		−0.74 (−1.37)	−0.10 (−0.49)
Democracy		0.12 (0.31)	0.25 (1.52)
Alliance (USA–Target)		0.81* (1.85)	0.12 (0.83)
ln(Capabilities)		0.63*** (4.66)	0.16*** (4.77)
Constant		−2.61** (−2.49)	1.76*** (6.67)
ρ			−0.16 (−0.73)
Observations	574	3047	Total: 3015 Uncensored: 250

Robust z statistics in parentheses; *** p < 0.01, ** p < 0.05, * p < 0.1.

A peace–years variable and three cubic splines were included in the estimation but are not reported owing to space considerations.

Model 1 of Table 1 provides support for hypotheses 1–3. As expected in hypothesis 1, cumulative decreases in US FDI, while holding cumulative changes in global FDI constant at no change, produce a positive and significant increase in the probability of sanctions ending successfully. Likewise, as expected by hypothesis 2, when global FDI increases, the probability of sanctions success decreases.²⁹ Model 3 confirms these results in a Heckman selection model where the second stage of the model uses a probit link and standard errors clustered by country. Although the ρ is not significant in model 3, because others have made a compelling theoretical argument for the necessity of including a selection equation in the estimation of sanctions success (Drezner, 2003; Lektzian and Souva, 2007; Nooruddin, 2002; Smith, 1997),³⁰ we present our results both with and without the selection model.³¹ The results vary only slightly between the estimates of model 1 and the results of the Heckman estimates in model 3. The consistent conclusion reached in models 1 and 3 is that, when US or global FDI in states targeted by US sanctions declines, the probability of sanctions being successful increases.

The inclusion of a multiplicative interaction between US and global FDI in both models allows for easy interpretation of the effect of a change in one of these variables while holding the other at any chosen level. Figure 1 plots the marginal effect of a change in US FDI at varying levels of decreases in global FDI, ranging from 1 standard deviation below the mean change in global FDI to 1 standard deviation above the mean.³² Figure 1 shows that a marginal increase in US FDI decreases the probability of sanctions success. For the purposes of this paper, the substantive interpretation is that, when US FDI to the target decreases, the probability of success increases. Substantively, the effect is largest if global FDI is also decreasing. The effect is statistically significant over the range of about a US$6 billion cumulative decrease to about a US$8 billion cumulative increase in global FDI. For the vast majority of sanction cases (as seen in the histogram in Figure 1), cumulative decreases in US FDI to the target during sanctions significantly increase the probability that the USA achieves its sanctions goals.

Figure 1.

Average marginal effect of a change in US FDI on the probability of sanctions success at varying levels of change in global FDI (with 95% confidence interval).³³

In support of hypothesis 3, the results shown in Figure 1 reveal that the effect of decreasing US FDI is greatest when global FDI to the target is also decreasing. When global FDI to the target increases during sanctions, it undermines the efforts of US foreign policy and the marginal effect of decreasing US investment decreases until eventually becoming insignificant when global FDI increases by more than about 0.5 standard deviation above the mean. An implication of this finding is that changes in US investment during sanctions can have policy implications, and can play a role in increasing pressure on countries targeted by US sanctions. However, this affect is attenuated by the behavior of global investors. If global investors come in to replace lost US investment during sanctions, then the marginal effect of changes in US investment will be decreased.

Figure 2 provides a direct view of the substantive effect of changes in US and global FDI on the likelihood of successful US sanctions. First, note that, when global FDI decreases by 1 standard deviation and US FDI also decreases by 1 standard deviation, the probability of sanctions being successful is at its high point, producing approximately a 30% chance of sanctions ending successfully in a given year. Focusing on the top line in Figure 2, we see the rapid decline in the probability of success (from ∼30 to ∼5%) as the cumulative change in US FDI goes from 1 standard deviation below the mean to 1 standard deviation above the mean. If global FDI remains at its mean value or is unchanged, there is a substantial decrease in the likelihood of sanctions being successful. The probability of sanctions ending successful is only about 15% when US FDI decreases by 1 standard deviation and falls to only about 2.5% if US FDI increases by 1 standard deviation. Finally, if global FDI increases during sanctions, the probability of success becomes very low, even if US FDI declines. The probability of success ranges from only about 5% if US FDI decreases by 1 standard deviation to barely 1% if US FDI also increases.

Figure 2.

Change in probability of sanctions success at varying levels of change in US and global FDI.³⁴

The findings demonstrated in Figures 1 and 2 have implications regarding the importance of international cooperation in achieving sanctions success. Drezner (2000: 73) noted that “A common thread in the economic sanctions literature is the assumption that multilateral cooperation among the potential sanctioning states is a necessary and/or sufficient condition for generating a successful outcome”. Our results suggest that, in general, the marginal effect of decreasing US FDI is weakest when global FDI to the target grows during sanctions. Additionally, it appears that the USA will be hard pressed to achieve success in sanctions if it is forced to “go it alone” while global FDI to the target country grows.

The bottom half of Table 2 shows the effect of FDI on the likelihood of sanctions occurring. The results in model 2 provide support for the opportunity costs variant of hypothesis 4a—high levels of US FDI as a percentage of the potential target state’s GDP decrease the likelihood of sanctions occurring.³⁵ This finding supports the expectation that high levels of investment can provide additional incentive for states to settle disputes short of what could be very costly sanctions. While this finding reaches significance for the variable measuring US FDI as a percentage of the potential target’s GDP, it is not significant when considering US FDI as a percentage of US FDI. This is probably due to both the size and diversity of the US economy as well as the greater harm that a loss of capital inflows would impose on governments that are recipients of US FDI.³⁶ Additionally, if sanctions are imposed, as we see in the success equations, decreases in US investment can provide additional leverage to bring about policy change from the target.

Table 2.

FDI and sanctions onset and success with a GEE model including robust standard errors and AR(1) term and a logit link function (see footnote 28)

	Model 1: sanctions success	Model 2: sanctions onset
Outcome equation
Cumulative Change in US FDI	−0.32*** (−3.44)
Cumulative Change in Global FDI	−0.10* (−1.79)
Interaction of ΔUS FDI ΔGlobal FDI*	0.01* (1.85)
International Organization	0.14 (0.33)
ln(Distance)	−0.33 (−0.68)
MID with USA	0.2 (0.16)
Civil War	−0.29 (−0.56)
Democracy	0.10 (0.18)
ln(Capabilities)	−0.03 (−0.16)
GDP Growth (Annual Percentage)	−0.07** (−2.42)
Alliance (USA–Target)	1.09* (1.70)
Constant	−0.70 (−0.14)
Observations	571
Onset equation		Sanctions
US FDI as a Percentage of Target GDP		−0.12** (−2.42)
US FDI as a Percentage of US GDP		−4.22 (−1.104)
MID with USA		0.99 (0.95)
Civil War		−0.74 (−1.37)
Democracy		0.13 (0.31)
Alliance (USA–Target)		0.81* (1.84)
ln(Capabilities)		0.63*** (4.67)
Constant		−2.52** (−2.50)
Observations		3045

Robust z statistics in parentheses; *** p < 0.01, ** p < 0.05, * p < 0.1.

A peace–years variable and three cubic splines were included in the estimation but are not reported owing to space considerations.

Finally, Figure 3 shows the substantive effect of US FDI as a percentage of target GDP on the probability that the USA would impose sanctions on a country. The probability that the USA would impose a sanction against a state in any given year is generally low, about 1.6%, but when the level of US FDI as a percentage of the state’s GDP is high (1 standard deviation above the mean), that probability drops to only about 1%. On the other hand, when US GDP as a percentage of the state’s GDP is at 1 standard deviation below the mean, the probability increases to about 2.4%, which represents about a 50% increase.

Figure 3.

Change in probability of sanctions onset at varying levels of US FDI as a percentage of the potential target’s GDP.³⁷

Summarizing the significant control variables, we see that alliance partners of the USA are more likely to draw sanctions, and that those sanctions tend to be more successful. Additionally, the USA is more likely to impose sanctions against powerful states, although those sanctions are no more or less likely to be successful. We also find that, as economic growth in the target of sanctions declines, targets are more likely to acquiesce to US sanctions, perhaps in an effort to re-establish whatever forms of commerce were disrupted by the sanctions. A final significant variable, from the success stage of the Heckman model, is the presence of a civil war in the targeted state. Sanctions against countries experiencing civil conflict tend to be particularly difficult cases for the achievement of success with sanctions.

Discussion

Anecdotal evidence from Iran and South Africa also helps to trace the working of our theoretical mechanisms in specific cases. In Iran, we see an example identified in hypothesis 2, where US firms follow the wishes of the US government and abandon their investments, only to see global FDI take their place, undermining sanctions success. In South Africa, we see that US and global FDI disinvest, tightening the noose on South Africa, which, as suggested in hypothesis 1, increases US sanctions success.³⁸

Iran is an example of US investors fleeing as a result of sanctions and of global FDI taking their place, helping to undermine US sanctions success. Historically, Iran had been an important country for US oil investment. The abundant oil reserves and great demand for fuel provided many opportunities for US petroleum firms. The fall of the Shah in the late 1970s and the rise of Ayatollah Khomeini ignited much tension between the USA and Iran that precipitated the USA’s imposition of sanctions in the mid 1980s. However, the USA appeared to give a reprieve to US oil producers. While US sanctions affected all Iranian imports, including oil, sanctions did not apply to US foreign subsidiaries so long as Iranian oil never entered the US market. As a result, US subsidiaries continued to operate in Iran, lessening the bite of US sanctions.

In 1995, the Clinton administration attempted to tighten the noose around Iran, enforcing comprehensive sanctions, where US firms could no longer use subsidiaries to explore for Iran’s oil (Rodman, 2001: 122). The USA hoped that, by tightening the sanctions, it could pressure Iran to modify its activities. Much of the tightening also depended on global investors abandoning Iran. However, global investors saw the flight of US firms as an opportunity to earn substantial profits. Indeed, the comprehensive sanctions that forced the US firm Conoco to remove its bid for a contract to develop Iran’s Sirri oil fields immediately led French, German and Russian firms to place bids (Shambaugh, 1999: 185). A French competitor, Total, assisted by the French government, would ultimately win the contract (Rodman, 2001: 125). Currently, US firms still remain blocked from Iran’s oil fields, while companies from Norway, Austria, China and Malaysia develop and explore Iran’s petroleum reserves (Bayefsky, 2007; Ilias, 2009: 30; Jacobson, 2008: 78). The easy replacement of US firms with profit-motivated global MNCs has helped to undermine US sanctions success in Iran.

An additional result of sanctions against Iran was that other countries, particularly other OPEC countries with vulnerabilities similar to those of Iran, observed how the USA was able to effectively freeze US$12 billion in Iranian assets. Carswell (1981: 262) reported that, after the US-led sanctions against Iran were lifted, there was “a noticeable decline in the proportion of OPEC assets held in the form of direct claims against US banks and their major foreign branches. In 1979 about $16.5 billion of the $40 billion OPEC increase in claims against the international banking system was held with US banks. In 1980 only $1.1 billion of the corresponding $44 billion increase was held with US banks”. While noting that there were other potential causes for this change, Carswell (1981: 263) writes that a primary cause may well have been “a reaction to, or fear arising from, the Iranian blocking”. Actions such as these not only hurt the strength of the US dollar and the US economy, but also decreased the USA’s ability to use economic levers as a policy instrument in the future.

Lastly, and unlike in Iran, South Africa is an example where both US and global FDI disinvested, increasing pressure on South Africa’s economy that ultimately led to US sanctions success. The sanctions literature on the South African case is voluminous and we provide a very brief thumbnail sketch. In the 1980s most Western countries stepped up economic sanctions against the apartheid government in South Africa to end political repression of its majority population and to promote democratization. Countries including the USA, the UK, Japan, the European Economic Community and the Commonwealth along with the UN adopted their own sanction policies that relied primarily on trade restrictions (Kaempfer and Ross, 2004: 235).

In addition to trade restrictions, the anti-apartheid movement also involved MNC disinvestment. Two years prior to the enactment of international sanctions in 1986, MNCs had already begun to disinvest because of the risk associated with declining economic conditions and political instability (Rodman, 2001: 210). Pressures from nonstate actors including pension funds, shareholders, universities and state and local governments in the USA and elsewhere, in particular, raised investor risks. However, the force of nonstate actors is not to deny the importance of sanctions for increasing risks to MNCs and lowering business confidence that compelled many to pull out of South Africa. As Rodman (2001: 211) notes in the case of US MNCs, “US companies were confronted with an additional cost after the passage of the Rangel Amendment in December 1987, which denied tax credits to direct investors. Several firms, most prominently Mobil, attributed their departure to this law”. Moreover, MNCs tended to disinvest from three strategic areas (electronics, petrochemicals and automobiles), which added to South Africa’s high costs. US MNCs, which were responsible for much of the strategic investment in electronics that were the lifeblood for the South African military and police, began to heavily disinvest, as did firms from other countries (Mangaliso, 1999: 147–149). South Africa subsequently witnessed falls in GDP growth from an average of 6% in the 1960s, to 3% in the 1970s, to 2% in the 1980s, and negative growth from 1990 to 1992 (World Bank, 2008). Under heavy economic and political pressure, the apartheid regime finally gave way to universal elections in 1994. The decision by many US and global firms to disinvest largely because of the risks attributed to sanctions contributed to sanctions success.

Conclusion

The findings of this paper underscore the role of FDI in international relations in general and US foreign policy more specifically. We find support for our hypotheses regarding the effect of foreign investment decisions on the success of economic sanctions. Our results show that if, during the course of US imposed sanctions, US FDI in the targeted country decreases, sanctions are significantly more likely to be successful. Importantly, however, the actions of US MNCs are not the only determining factor in the success of US sanctions. Rather, the success of sanctions also depends in part on what global firms do. If global FDI increases while US FDI falls, the ability of the USA to punish target countries is undermined and the success of sanctions decreases. Indeed, as we saw during the Cold War, when the USA imposed severe economic sanctions against Cuba, aid from the Soviet Union reduced much hope for sanctions success. Even in the post Cold War years, as the USA attempts to tighten its grip on Cuba, Cuba has found a new patron, in this case Venezuela, to lighten the economic pain.

We also find significant backing for the idea that US FDI decreases the likelihood of disputes rising to the level of formal economic sanctions. This finding extends previous work showing that economic engagement reduces the likelihood of conflict. Our findings are also suggestive of the work of de Vries (1990) and Copeland (1996), demonstrating that high levels of economic engagement tend to magnify the relationship between states, causing states to work harder to find solutions to disputes short of formal sanctions. However, if the economic interactions are threatened, and investment declines, it can leave states vulnerable to coercive demands for political change (Hirschman, 1980).

More work is needed to investigate the role of sanctions on FDI and vice versa. Studies are warranted to determine how FDI responds to sanctions from countries besides the USA. Indeed, a caveat to the analysis presented here is that the focus is only on US sanctions cases. The USA may in fact be unique in its sanctioning actions given its great military and economic power during this period. Thus, we should be cautious in generalizing these results to all sanctions cases. However, given the USA’s prominent position in the international system and its frequent use of sanctions, the study of US sanctions is highly relevant and should be of interest for scholars of international relations and US foreign policy. Future researchers might want to consider whether global FDI would act differently if the sending state were a country other than the USA. Additionally would US investors act as “black knights”, disrupting sanctions attempts by other countries? While there are many interesting questions left for future research, our initial research helps to better understand the importance of investor decisions in determining the outcomes of international disputes.

Footnotes

Acknowledgements

The authors would like to thank Alfred Cooper Drury, Bryan Early, Quan Li and Cliff Morgan for their helpful comments and suggestions.

Funding

This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

Notes

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