Geopolitical Competition

The concept of geostrategic concern was measured across four dimensions.

1. 1. Security Community: A dummy variable was created to represent whether state A and state B were part of the same security community at the time of the deal in question. A security community is generally defined here in accordance with Adler and Barnett (Reference Adler and Barnett1998), who argue that the formation of a common identity between states can eventually lead to the development of a norm of non-violence among those states. The result is a community in which participating states resolve their disputes with one another solely through the use of non-violent means, causing a sense of “we-ness” to develop (Adler & Barnett Reference Adler and Barnett1998, 7).² For the purposes of coding the database, security communities are more strictly defined as those in which this norm of non-violence has been demonstrated to be historically robust, whether through the existence of the highest level of mutual security agreements, such as the North Atlantic Treaty Organization (NATO), through the existence of treaties providing for the sharing of the highest levels of intelligence, such as the American, British, Canadian, Australian and New Zealand Multilateral Master Information Exchange Treaty (ABCANZ), or through membership in a highly integrated political and economic union, such as the EU. These communities are uncommon, and may not always take exactly the same form.

2. 2. Relative Military Power: This variable roughly approximates the relative military power differential between both states involved in the transaction. Its purpose is to shed light on the extent to which state A might have felt threatened by state B, and to indicate when military power differentials might have played a role in causing a given state to seek alternative forms of balancing. It represents the ratio of the military expenditure of state B to that of state A.

3. 3. Resource Dependency: This variable measures the general resource dependency of state A.³ It was calculated in accordance with the method used by the International Energy Agency (IEA),⁴ utilizing the yearly ratio of state A's energy imports to its energy supply.

4. 4. Inward Foreign Direct Investments (IFDI): This variable is meant to proxy the relative economic power position of state A by representing its IFDI. This measure is used because many political economists argue that it is the rapid or sudden increase in IFDI, rather than changes its net FDI position, that causes a state to react negatively – through protectionism or other means – to conspicuous foreign investment in its country (see e.g., Tyson Reference Tyson1992).

Economic Nationalism

1. 1. Nationalism: A variable measuring the level of nationalism in state A has been included for two reasons. First, nationalism is often a strong component of economic nationalism. The author strongly agrees with Helleiner and Pickel “that economic nationalism, like political or cultural nationalism, can be understood only if it is analyzed in the context of nation and nationalism in general, rather than as just another economic doctrine or ideology (the conventional economistic view)” (Helleiner & Pickel Reference Helleiner and Pickel2005, 12, emphasis in original). Second, comparable cross-national data on economic nationalism per se do not yet exist for many countries outside of the EU, and even within the EU, data are neither yearly nor complete. This variable, therefore, helps to round out an understanding of the theoretical concept of economic nationalism, while providing truly comparable data. Specifically, it represents the percentage of those survey respondents in a given state who said that they were “very proud” of their nationality (see WVS 2001–04).⁵

2. 2. Pro-Globalization Sentiment: This represents the level of pro-globalization sentiment in state A. As high levels of anti-globalization feeling in a state are often associated with higher levels of economic nationalism, this variable acts as an excellent proxy for the latter concept. Furthermore, anti-globalization attitudes are often identified with the particular form of state action examined in this study, as state intervention into foreign takeovers is often associated with a desire to protect so-called “national champions.” This variable thus represents the level to which respondents (business elites in state A) believed that “attitudes towards globalization [were] generally positive in [their] economy” (IMD 2007a, 6).⁶

Economic Competition

1. 1. Economic Competition I: In the primary hypothesis, this variable is meant to control for the possibility that a foreign takeover may be blocked on competition, rather than national security, grounds. Data were not readily available for this variable on a case-by-case basis for all countries and within the limits of the author's resources. Moreover, it is a concept for which the creation of a single dummy variable would be inadequate to represent the complexities of the competition review process. The author thus leaves the detailed examination of this concept to the case study section, where it is more appropriately applied.

2. 2. Economic Competition II: This variable seeks to control for a different theoretical concept, which also falls under the rubric of the word “competition.” This is the extent to which state A is believed to be “competitive” in the international market as a state open to liberal economic business practices and foreign investment. Given the nature of the hypothesis, this variable offers another important statistical control to the data being examined here. Thus, an index of the perceived economic competitiveness of state A was made in order to create this variable. This index was formed by taking the average of twelve different measures of economic competitiveness provided by the IMD World Competitiveness Yearbook, which obtains these rankings by conducting a large-n survey of business elites worldwide on a yearly basis (see IMD 2007b, 2016). The IMD measures indexed for the purposes of this dataset are presented in Figure 13.

Interest Group Presence

1. 1. Interest Group Position Index: The case study method is used in the following chapters to determine the presence of interest groups, as well as their effectiveness in blocking foreign takeovers, in each of the critical cases. Yet, such an investigation is not practical for the dataset, due to the lack of readily available and comparable data. The index variable used here, however, provides a useful approximation of the concept of interest group presence by measuring the general influence of relevant interest groups within state A. This was achieved by taking the average value of two separate measures of interest group position within these societies, again from the IMD World Competitiveness Yearbook (see IMD 2007b). These measures, outlined in Figure 14, arguably address two of the most critical interest groups involved in cross-border mergers and acquisitions. These are labor unions and shareholders: labor unions because they tend to be one of the more effective groups in voicing their opposition to takeovers and opposing them in costly ways, i.e., through strikes or negotiations, and shareholders for their ability to directly influence the outcome of public takeovers.

MNLM I

The first MNLM tests the primary hypothesis that state A's intervention in the foreign takeovers of companies in its national security sectors will depend primarily on geopolitical competition and economic nationalism, controlling for economic competition and interest group presence. As previously specified, the independent variables tested as part of MNLM I are: security community, relative military power, resource dependency, nationalism, pro-globalization sentiment, economic competitiveness, inward FDI, and interest group position. The dependent variable in MNLM I represents the type of intervention, i.e., the form of non-military internal balancing, that state A chooses to utilize vis-à-vis the foreign takeover in question. This dependent variable, labeled intervention type (Y₁), has four value categories, as defined in Figure 15.

It should also be noted here that the category of bounded intervention has been divided into two parts: high-bounded and low-bounded intervention (see Figure 15). Parsimony demands that the broader category of bounded intervention is retained within the theory, because governments use both these sub-categories to mitigate rather than block foreign takeovers. However, these sub-categories of bounded intervention utilize different methods, or in some cases the same method to different degrees, to achieve the goal of bounded intervention and modify a specified transaction in state A's favor. Thus, while there are conceptual benefits to maintaining the broader concept of bounded intervention as a whole, these sub-categories are distinct enough to offer valuable insights into the explanation of the puzzle when examined statistically. In addition, a Hausman Test of the independence of irrelevant alternatives (IIA) confirms that all four categories of the dependent variable are statistically distinct and useful.⁷

It should be the case that the variables representing economic nationalism and geopolitical competition concerns play a significantly larger role than those controlling for interest group presence and economic competition concerns in MNLM I.

MNLM II and MNLM III

MNLM II restricts the cases analyzed to those in which the cross-border M&A deal takes place within the context of a security community. MNLM III restricts the number of cases tested to those that occur outside of that same context. It should be noted here that the independent variable of “resource dependency” drops out of MNLM III for purely statistical reasons: namely, there is insufficient variance on the variable within the population of cases under consideration.⁸

The purpose behind these additional tests is to determine whether or not the behavior of state A varied significantly under these diverse conditions. If it did, then these models should indicate which independent variables are associated with a higher probability that state A will pursue these different types of intervention vis-à-vis their closest allies. Such information would help explain the puzzle behind this work to a great extent.

MNLM IV

The MNLM IV tests the second hypothesis that the outcome of a foreign takeover is largely determined by the form that state A's intervention takes. The dependent variable of the first three models (intervention type) thus becomes the independent variable in this model. The dependent variable of MNLM IV, labeled deal outcome (Y₂), represents the actual outcome of the deal in question, and takes on the values noted in Figure 16. The results of MNLM IV are expected strongly to support the secondary hypothesis.

MNLM I

The results of the first MNLM show clear support for the argument that economic nationalism and geopolitical competition are the primary motivations behind non-military internal balancing of this type. The impact of these variables on the probability of state A engaging in either bounded or unbounded intervention – versus the base outcome of no intervention at all – does vary, however.

For example, it can be said with 90% confidence that state A is significantly more likely to use a higher or lower form of bounded intervention, rather than no intervention, as the level of nationalism within state A increases. In general, this finding supports the idea that higher levels of economic nationalism in state A will lead to that state's desire to protect its national interests through such measures. An increase of one standard deviation in nationalism increases the probability that state A will engage in low-bounded intervention by 11.6% and high-bounded intervention by 7.9%. As nationalism increases from its minimum to maximum value, the chance of being in these categories increases by 16.7% and 11.7%, respectively. Figure 20 summarizes the effect of these variables on probability change in MNLM I (see Appendix B for the complete marginal effect tables).

Three indicators of geopolitical competition between states A and B – relative military power, resource dependency, and IFDI – approach significance in heightening the probability that state A will engage in high-bounded intervention. Increases in the IFDI and resource dependency of state A may therefore play a role in determining state behavior. Interestingly, so may a decrease in the relative power of state B. The results of MNLMs II and III, discussed in the next two sections, indicate that, under certain conditions (namely within security communities), state A may feel more comfortable imposing domestic barriers to foreign takeovers when it is in an advantaged power position versus state B. Yet, it is also clear that when state A is in a position of weakness versus state B, state A will be more likely to engage in unbounded intervention.

Thus, when trying to understand what factors generally motivate states to engage in bounded forms of intervention, nationalism appears to be the most important determining factor. Geopolitical factors may also play a role, though their impact is less clearly defined.

In regard to unbounded intervention, MNLM I indicates that geopolitical competition and nationalism are the chief motivating factors in determining the behavior of state A. In fact, it can be said with 95% confidence that those deals occurring outside of the security community context were significantly more likely to result in state A engaging in unbounded intervention, rather than no intervention at all. For example, when states A and B are members of the same security community, the probability of state A engaging in unbounded intervention decreases by 11.4%. Furthermore, it can be said with 90% confidence that as the military power of state B increases relative to state A, state A is significantly more likely to employ a tool of unbounded intervention to block a foreign takeover. An increase of one standard deviation in the relative military power of state B increases the probability of state A using this category of intervention by 4.5%, but as relative military power moves from its minimum to maximum value, the probability of A engaging in unbounded intervention is raised to 46.3%. Together, these figures provide positive evidence that the motivations behind the behavior of state A will vary in accordance with its alliance relationship to state B.

In terms of economic nationalism, MNLM I also illustrates that a decrease in pro-globalization sentiment will significantly increase the likelihood of state A engaging in unbounded intervention, rather than no intervention at all. An increase of one standard deviation in the value of pro-globalization sentiment decreases the probability of unbounded intervention by 9.3%. In other words, as anti-globalization sentiment increases, the probability of unbounded intervention into foreign takeovers rises by 57.5%.

On the whole, therefore, elements of geopolitical competition and economic nationalism are found to play a clear role in motivating states to engage in this type of non-military internal balancing. Notably, none of the control variables registered as having a significant impact on any level of intervention that state A was likely to choose, indicating that the alternative explanations of interest groups and economic competition concerns cannot necessarily explain state behavior in this model.

MNLM II

Interestingly, none of the variables explored in MNLM II provide insight into why a state would be likely to pursue lower forms of bounded intervention. This phenomenon is likely to be explained by two factors. First, many cases of even low-bounded intervention are classified. Second, low-bounded interventions that occur within the confines of a security community are often not leaked to, or mentioned in, the press. This is because M&A activity is so frequent and regularized between these countries that the companies involved in these transactions see the government's actions as standard operating procedures, and may not feel the need to publicize them of their own accord.

It can be said at the 90% confidence level, however, that high-bounded interventions are significantly more likely to occur when the resource dependency of the target state is high and its levels of nationalism are high. This outcome suggests that elements of economic nationalism and geopolitical competition are again motivating factors for state behavior. The marginal effect of higher levels of resource dependency in state A resulting in high-bounded intervention is 13.2%, and a move from that variable's minimum to maximum value leads to a 44.4% increase in the probability of this form of non-military internal balancing. For nationalism, these numbers are 15.6% and 8.9%, respectively (see Figure 21; for the complete marginal effect tables, see Appendix B). Notably, as in MNLM I, relative military power is significant in the negative direction, indicating that stronger target states are likely to feel they have sufficient power to impose such mitigation measures on their allies.

Furthermore, it can be said with 99% confidence that unbounded intervention into foreign takeovers within security communities is significantly more probable than no intervention when there are lower levels of pro-globalization sentiment in the target state. (A one standard deviation change in this variable decreases the probability of state A engaging in this behavior by approximately 2.7%.) There is a great difference, however, in the value of this variable across countries.¹⁰ Thus, it is important to note that as pro-globalization sentiment goes from its minimum to maximum value, the probability of state A engaging in unbounded intervention within a security community decreases by 72.0%. In other words, as anti-globalization sentiment increases (or economic nationalism rises) within state A, it is increasingly likely that state A will utilize a tool of unbounded intervention vis-à-vis a takeover deal emanating from within its own security community. This is in line with the expectation that economic nationalism will play a larger role within security communities, where geopolitical competition is clearly lower.

MNLM III

For the non-security cases examined in MNLM III, nationalism again proves to be a significant factor in increasing the likelihood that a state will engage in either low- or high-bounded intervention. For example, a one standard deviation increase in the value of this variable results in a 13.8% increase in the probability that state A will engage in low-bounded intervention, and a 9.7% increased probability that it will pursue high-bounded intervention (see Figure 22 and Appendix B). A change from the minimum to maximum value of the nationalism variable increases the chances of state A being in these categories by 33.6% and 10.9%, respectively. It is not surprising that this variable, which may be considered a precursor of economic nationalism, plays a role in state behavior here – especially when it is recalled that higher levels of nationalism in state A were associated with a significantly increased likelihood of high-bounded intervention in both MNLMs I and II, and of low-bounded intervention in MNLM I. Clearly, nationalism is associated with states that seek to protect their economic and national security interests by altering or mitigating cross-border deals in their favor.

Most significantly, however, MNLM III demonstrates the greater importance placed on the geopolitical relationship of states A and B in determining intervention type for non-security community cross-border deals. To begin with, it can be said with 90% confidence that higher levels of IFDI in state A significantly increase the likelihood that state A will utilize low-bounded intervention in non-security community deals, rather than no intervention at all. Indeed, a one standard deviation increase in the level of IFDI in state A increases the probability that state A will use this tool of intervention by 16.6%. This, of course, illustrates the heightened importance that the relative economic power positions of states A and B play in determining even the lesser forms of intervention that occur outside of the security community context.

As with MNLM II, state A is significantly more likely to engage in high-bounded intervention as its military power relative to state B increases. Initially, this seems contradictory. As mentioned already, however, the likely explanation is that as state A's power increases relative to state B, it may feel more comfortable engaging in a form of intervention that simply seeks to impose changes to a deal, rather than blocking it. In such a situation, state A may feel both that it is easier to impose conditions on a transaction that involves a weaker non-allied state and that more severe measures are unnecessary because of the less threatening nature of such a state.

In the category of unbounded intervention, we see that the theory is again borne out. If the acquirer's state (state B) has a higher level of military power relative to the target company's state (state A), then it can be said with 95% confidence that the target state's government is significantly more likely to intervene in this most strenuous of ways, rather than not at all. In fact, a one standard deviation increase in the military power of state B relative to state A increases the probability of unbounded intervention on the part of state A by 25.1%. An increase from the minimum to the maximum value of the military power of state B relative to state A raises the probability of unbounded intervention on the part of state A by an astounding 94.3%.

Relative economic power proves to be an important element of geopolitical competition here as well, as higher levels of IFDI are shown to be significant in determining the probability of this course of action on the part of state A. A one standard deviation increase in the IFDI of state A raises the probability of unbounded intervention by 33.6%. On the whole, therefore, it does seem clear that outside of the security community context, foreign takeovers are more likely to be barred on the basis of geopolitical concerns.

MNLM IV

MNLM IV tests the effect of government intervention on the outcome of cross-border deals. Here, intervention type now acts as the independent variable, and the dependent variable is deal outcome, i.e., deal, changed deal, or no deal. Out of the 209 cases in the database, 104 deals went through with no apparent changes imposed by governments, 48 were mitigated in some way by the state in question, and 57 resulted in “no deal” (see Figure 23).

Figure 23

Cross-border deal breakdown by deal outcome 2001–07

Significantly, the results of MNLM IV show clear evidence that the type of government intervention employed by state A will affect the outcome of the foreign takeover in question (see Figure 24). It may be said with 99.9% confidence that intervention type significantly affects the likely outcome of the dependent variable across each of its categories. Furthermore, as the level of government intervention increases, so do the chances that the deal will be barred or mitigated. For example, a one-unit increase in intervention type – i.e., an increase from no intervention to low-bounded intervention, or from high-bounded intervention to unbounded intervention – decreases the probability of an unaltered deal outcome by 111.3% (see Figure 25). Such a one-unit increase in the level of intervention, then, concurrently increases the probability of a “changed deal” outcome by 53.8% and raises the probability of a “no deal” outcome by 57.5%.