Power,proximity,and democracy

States cannot engage in gunboat diplomacy without gunboats

To understand why coercive bargaining occurs, we need to first understand why states acquire and project military power. Why would some states choose to bargain over their interests in the shadow of military power (Powell, 1999), while others choose to bargain without the threat of military coercion? States that operate within competitive geopolitical environments are incentivized to build power projection capabilities, whereas states within cooperative geopolitical environments can safeguard their interests and bargain effectively without relying on power projection capabilities. Thus, states stop experiencing bargaining failure that leads to war because they stop employing military coercion when bargaining. Today, states in North and South America and most of Europe bargain with one another over a variety of contentious issues; however, military coercion is rarely used in these interactions. Since these bargains do not involve military coercion, they cannot end in war.

We seek to build a theory that can explain this first step in the causal chain of coercive bargaining and conflict: a state’s choice to build the capabilities necessary to coercively bargain over its interests. We argue that economically powerful states, when faced with a competitive geopolitical environment, are more likely to build power projection capabilities. We define a state’s geopolitical environment as the set of countries with whom it can interact. Geopolitical competition is defined as the potential for coercive bargaining interactions between each state and the other states in its geopolitical environment. For each state, as the potential for coercive bargaining interactions increases, so does the level of geopolitical competition. Operationally, the level of geopolitical competition that each state faces is defined by a function that combines three components: the geographic position of the state, relative to other states; the relative economic power of each other state; and the degree to which it has compatible interests with each other state. The higher the level of geopolitical competition a state faces, the greater its incentive to invest in power projection capabilities. States expect that if they do not invest in these capabilities, they will be outgunned by other states when coercively bargaining.

We make three contributions in this article. First, we develop a state-level theory of why states find their strategic environment threatening and how they respond to geopolitical competition. Second, we construct a unique measure of the level of geopolitical competition that each state faces in the international system. Third, we apply the measure to explain why only some powerful states invest in the capabilities to project military force. Our approach represents an improvement over existing explanations, such as structural realism and democratic peace theory, because it can make predictions regarding whether individual states like China, Russia, India, or Brazil will choose to develop power projection capabilities.

Below, we discuss existing explanations and how our theory addresses shortcomings with these competing theories. We then develop the logical foundations of our theory and our measure of geopolitical competition. Next, we provide empirical evidence for our claim that economically powerful states, when faced with a competitive geopolitical environment, develop power projection capabilities. We conclude with a discussion on the theoretical and policy implications of our findings.

Missing pieces: Geography and regime type

What is needed is a theory that explains when the nature of the geopolitical environment will be threatening to individual states and when it will not. We assume that threat is a function of geopolitical competition. Geopolitical competition occurs when states possess the economic power to develop and the political will to deploy military forces capable of threatening other’s interests. Our model offers a counterpoint to structural realism, which focuses on power and proximity, and theories of the democratic peace that privilege political will (i.e. regime type, which is a type of interest compatibility) and ignore the distribution of power and geography. By incorporating insights from both schools of thought, we develop a theory of threat that begins with a state’s assessment of the economic power and geographic proximity of other states and is conditioned by their regime type. In our model, regime type determines the level of interest compatibility between states, which conditions the effect of economic power and proximity on perceptions of threat.

A theory of geopolitical competition: Combining insights from structural realism and the democratic peace

Our theory of geopolitical competition incorporates insights from both (1) structural realism, which focuses on how geographic proximity and changes in the distribution of power influence the level of geopolitical competition in the system, and (2) democratic peace theory, which focuses on how domestic political institutions affect the level of interest compatibility between states.

We argue that two variables influence the degree to which states choose to build power projection capabilities: the relative size of their economy and the level of geopolitical competition they face. As the size of the state’s economy grows, the more geographically expansive its economic interests become. Economically powerful states tend to trade and interact at greater distances. A larger economy is also likely to be associated with the ability to afford expensive power projection capabilities. However, even if a state has a large economy and geographically distant interests, it will only be incentivized to invest in power projection capabilities if the geopolitical environment threatens its interests. The higher the level of geopolitical competition, the more likely that such states will build power projection capabilities. The level of geopolitical competition a state faces is determined by three components: the relative economic power of other states, their geographic proximity, and the degree to which they possess compatible interests. The level of geopolitical competition a state faces will be higher when other states are more economically powerful, proximate, and possess incompatible interests. Next, we define the three components that collectively determine the level of geopolitical competition faced by individual states.

The distribution of economic power

The level of geopolitical competition is partially a function of the relative economic power of other states in the system. The more economically powerful other states are, the greater their ability to invest in military forces that are capable of threatening others. The more powerful countries a state faces, the more threatening they will find their geopolitical environment. Because economic multipolarity does not necessarily result in military multipolarity, this relationship is conditioned by two additional components, the geographic proximity of other states and the degree to which they possess compatible interests.

Geographic proximity

Distance influences the degree to which states must consider the interests and capabilities of other states in the international system. Research on military competition and conflict has concentrated on the relationship between geographic proximity and conflict. ² As distance increases, relative power decreases, because of the loss of strength gradient (Boulding, 1962). Russett & Oneal demonstrate that ‘distance is the most important constraint’ on power projection (2001: 87). Thus, geographic proximity conditions the distribution of potential power. States that are close to one another should be more concerned about each other’s intentions relative to distant states.

The rise of German economic power in the 19th century illustrates this dynamic. Germany’s economic rise threatened Britain because British economic and strategic interests were increasingly within reach of Germany’s potential power. Were Germany to build a powerful navy, it would be able to threaten British access to sea-lanes and its trading empire. Japan’s economic rise posed less of a threat to Britain’s core interests because it was a distant nation. Japan did eventually threaten Britain’s colonies, but it could not mount a blockade of the British Isles. Therefore, London constructed a naval force structure and foreign policy doctrine designed to counter Germany instead of Japan.

The more geographically proximate states are, the greater the potential competition between them, and the heavier they weigh in each state’s strategic calculation of the nature of their geopolitical environment. We are not arguing that rising German power was the only factor that motivated Britain to invest in further augmenting its power projection capabilities. We argue only that German economic growth threatened Britain when the two states had interests that threatened one another. Today, Britain and Germany have interests that are less threatening to each other and therefore have lower levels of geopolitical competition.

Interest compatibility

We define interest compatibility as the degree to which states possess interests that are not inherently threatening to one another. The less the interests of a given state threaten other states, the more compatible their interests and vice versa. It is important to clarify that we do not consider interest compatibility to necessarily mean that states have identical interests, but only that their interests are not threatening. States that possess compatible interests with other states in their geopolitical environment face lower levels of geopolitical competition. In contrast, states with interests that are incompatible with the other states in their geopolitical environment face higher levels of geopolitical competition.

Though there are many factors that influence whether states have compatible interests, there is theoretical and empirical reason to expect that pairs of democracies tend to have interests that are more compatible than pairs of countries that include at least one autocracy. Thus, we assume that pairs of democracies possess compatible interests. We are not suggesting that all democracies have the same interests, but only that they tend to not threaten one another’s interests. We do not view interest compatibility between democracies as an ironclad law; rather, we believe that regime type is a useful starting point for developing a measure that incorporates the degree to which states find one another threatening. Additionally, we are not claiming that the finding that democracies do not fight one another is necessarily caused by democracy alone. As previous research suggests, there are other factors that co-vary or interact with democracy such as trade, financial integration and economic interdependence, and domestic economic structure and development (Gartzke, 2007; McDonald, 2009).

Despite these limitations, we believe that regime type represents a fruitful starting point for three reasons. First, rigorous theory suggests that states should perceive autocracies as more threatening because of their preference to seek rents through territorial expansion. Second, a large body of research on the relationship between regime type and conflict suggests that democracies should be less likely to engage in coercive bargaining and conflict with one another. Third, regime type is one of the only publicly available measures of states’ interests with the temporal data coverage needed to test the validity of our measure over a long time period. However, as we discuss in greater detail in the conclusion, regime type is a starting point and future research will be able to incorporate more sophisticated estimates of interest compatibility into our measure of geopolitical competition.

Scholars working in the democratic peace literature have produced several explanations for why democracies do not fight one another. We focus on explanations for why democracies have fewer serious disagreements with one another – disagreements that could lead to war – rather than why their disagreements are less likely to end in war. Two sets of explanations have used interests to justify why democratic dyads have fewer significant disagreements. The first relies on democratic political institutions (Lake, 1992; Bueno de Mesquita et al., 2003) and the second on shared norms (Tomz & Weeks, 2013). We focus on the institutional explanation to illustrate why democracies will have more compatible interests, but we recognize that there is empirical support for both sets of explanations and this article does not assess which is superior.

Research suggests that democratic political institutions influence states’ foreign policy interests in two ways: first, by constraining incentives to pursue rents and territory (Lake, 1992) and second, by shifting preferences to pursue public goods rather than private goods (Bueno de Mesquita et al., 2003). Both mechanisms make it costlier for democracies to engage in threatening conflict: wars of conquest and expansion for material gain. States that share a weaker preference to predate others’ goods, such as territory, should also find each other less threatening and subsequently have more compatible interests. In contrast, states that have a strong preference to take goods from one another should have less compatible interests. It is important to note that we do not assume that democracies have the same interests or that they will never go to war, but only that their interests are less threatened by one another in general.

Lake argues that democratic political institutions explain why autocracies are less constrained in their rent-seeking than democracies. Democratic states that engage in rent-seeking that harms society are punished via electoral institutions, while autocrats face no such constraints (Lake, 1992). Democratic states must maintain the support of broad sections of society. Thus, they have stronger incentives to distribute goods broadly. Public or club goods are more efficient at achieving this policy goal.

Governments in autocratic states, in contrast, seek to maintain the support of a small number of individuals, which makes private goods a more efficient means for delivering benefits to supporters of the regime. The degree to which a regime seeks rents or private goods matters for two reasons: first, it affects their propensity to pursue territory as a source of land rents (Lake, 1992) and private goods (Bueno de Mesquita et al., 2003), and second, it affects their propensity to pursue exclusionary policies to extract monopoly rents by restricting economic competition. Theoretical work on the effect of democratic political institutions suggests that democracies should be less likely than autocracies to pursue territory because the private goods generated from conquest are more likely to dilute when redistributed to a larger winning coalition (Bueno de Mesquita et al., 2003). Empirical work finds that democracies are indeed less likely to pursue expansionist policies to take territory (Bueno de Mesquita et al., 2003; Huth & Allee, 2003; Lake, 1992; Wright & Diehl, 2016).

Research also finds that pairs of democracies are more likely to maintain free trade with one another in comparison to dyads that include autocracies (Mansfield, Milner & Rosendorff, 2000). Thus, because democracies have stronger incentives for securing non-rival goods, such as sea-lanes, or goods that can be positive sum, such as trade, they should be more likely to pursue foreign policies designed to generate such goods. Once sea-lanes have been secured, their consumption is non-rival for citizens of a state. Market access is a similar, if less pure, form of public good, in that its consumption is sometimes rival. However, market access benefits society at large, as consumers have access to cheaper goods and producers have more customers for their exported products.

Generally, it is easier for states to cooperate over the provision of non-rival and positive sum goods in comparison to rival and zero-sum goods. Non-rival goods are easier to share because their benefits do not decrease as they are consumed by a larger number of individuals. Positive sum goods increase incentives to cooperate because they generate surpluses that can be redistributed to make both parties better off. In comparison, private goods that are zero-sum, such as control over territory, resources, or rents, increase the incentives to compete, as one side’s gain necessitates another side’s loss. Democracies have stronger incentives to cooperate over the provision of non-rival or positive-sum goods and weaker incentives to exclude one another from accessing markets or sea-lanes when compared to autocracies (Graham, Gartzke & Fariss, 2015). Thus, economic multipolarity will not result in military competition between these states because democratic states have compatible interests.

In contrast, autocratic states possess stronger incentives to pursue exclusionary foreign policies and these policies are inherently threatening to all other states. Autocratic states possess domestic political institutions that incentivize them to seek rents by excluding other states from markets and sea-lanes (monopoly rents), or directly controlling territory or resources (land rents). Because these states have stronger incentives to pursue exclusionary policies, they pose a greater threat to the interests of all other states. The presence of autocratic states in the international system increases the incentives of all states to invest in power projection capabilities. Thus, if the only powerful states in the region are democratic, then the geopolitical environment should be less threatening to other democratic states. This is because democratic states are less likely to employ military force to exclude one another from accessing territory, markets, and resources.

For democratic states, if no other state seeks to limit their access to goods, then maintaining power projection capabilities is a costly burden rather than a valuable asset for achieving policy objectives. European powers, because of their high level of interest compatibility, do not find each other, or the United States, threatening. These states happily free-ride off the security provided by Washington, rather than building their own capabilities. Many of the goods that European states want are already being provided by the foreign policy of Washington, which is why a return to economic multipolarity in Europe is not associated with European states investing the capabilities to project power. Even if states are powerful and geographically proximate, they should not necessarily find one another threatening. For the security dilemma to obtain, states must have incompatible interests (i.e. differences that are great enough to lead to disagreements that could end in war). If states have compatible interests and can identify this compatibility ex ante, then they will have little incentive to waste valuable resources investing in the capabilities to project power against one another (Glaser, 2010). Interest incompatibility lies at the heart of security dilemma (Glaser, 2010). Without interest incompatibility, there should be no security dilemma, and thus changes in relative power should not be associated with changes in the level of geopolitical competition between states.

The level of geopolitical competition each state faces is a function of the relative economic power, geographic proximity, and interest compatibility with other states. The level of geopolitical competition influences states’ incentives to build power projection capabilities. From this set of assumptions, we derive the following hypothesis:

Competitive geopolitical environment hypothesis: The more competitive a state’s geopolitical environment, the more likely it will be to build power projection capabilities.

Next, we operationalize these theoretical constructs to evaluate this hypothesis.

Measuring geopolitical competition

To operationalize the Competition_it variable, let i = {1, …, N} index countries, j = {1, …, J} index all states in country i’s geopolitical environment (no matter the distance between i and j), and t = {1816, …, 2010} index years. Competition_it is a country-year variable which makes use of information from all of the other states in the international system in a given year, indexed by j. The information from each of the other j states is weighted by the distance from a specific state i.

d_ijt measures the distance between the capital city of state i and the capital city of state j in year t. Note that i ≠ j; that is, we do not consider the influence of a country on itself. d_ijt is defined for each country-year pair in each year using the longitude and latitude coordinates for each state’s capital city. The equation d i j t = acos ( sin ( l a t i t ) * sin ( l a t j t ) + cos ( l a t i t ) * cos ( l a t j t ) * cos ( l o n i t − l o n j t ) ) * r a d i u s captures the shortest distance over the globe. lat_i, lat_j, lon_i, and lon_j are the latitude and longitude locations for state i and state j, respectively. These data are from the Distance Between Capital Cities dataset (Gleditsch & Ward, 2001a; Gleditsch & Ward, 2001b).

Close states are more threatening than states that are far away because of the loss of strength gradient, which results in power dissipating over distance (e.g. Boulding, 1962; Markowitz & Fariss, 2013). The inverse distance creates a weight, w_ijt, which captures this intuition. It is defined as w i j t = 1 ln ( d i j t ) . In words, w_ijt is the inverse of the natural log of distance d_ijt in km between state i and state j in year t. The measure operationalizes the insight that states that are geographically proximate to country i are more influential on the behavior of that country than states that are far away.

Only certain states are potentially threatening to others: two democratic states are not threatening to one another, which follows from the argument put forth above (we consider other measures of interest compatibility in the context of our measure of geopolitical competition in another article). We therefore define p_ijt as 0 if state i and its neighbor, state j, are both democracies in year t. p_ijt is otherwise coded as 1 when this is not the case. A coding of 1 captures potentially threatening relationships between democracy-autocracy dyad-years and autocracy-autocracy dyad-years. To operationalize this component, we use the Polity scores of the country-year pairs. If both states have a Polity score greater than 6, then they have compatible interests and are not threatening to one another and are thus coded 0. ³ All other country-year pairs are considered potentially threatening and coded 1.

States with the largest economies in the system are the most potentially threatening adversaries to other states because they can develop and deploy power projection capabilities. Conversely, states with small economies do not have such potential and are relatively less threatening. To express this as a component of the measure, we define g_jt as the potentially threatening state’s economic capacity measured by gross domestic product (GDP) in year t.

Economic power is measured using GDP data from the World Development Indicators (World Bank, 2016), and supplemented with historic GDP data developed by Gleditsch (2002) and the Maddis on-Project (2013). These three measures of GDP are highly correlated over the period when all data series exist (1960–2010). We use a Bayesian measurement model to estimate a GDP series that covers the entire period of observation 1816–2011 (Fariss et al., 2017). For this component of the Competition_it variable, we transform the total GDP of each of state i’s j neighbors into a proportion by dividing it by ∑ j g j t , which is the total GDP of all other j states in a given year t. This captures the relative importance of large economies consistently over time. For example, proportionally large economies like Imperial Japan or contemporary China are potentially threatening to their contemporaries in the system but not across several decades.

Geographic competition for country i in year t, based on all other j states in the international system is defined as

C o m p e t i t i o n i t = ∑ j ( g j t ∑ j g j t * p i j t * w i j t ) ∑ j w i j t

1

In other words, Competition_it captures the geographic proximity of economically powerful states that have incompatible interests with state i in year t. If a given state is not a democracy, then all economically powerful states are potentially threatening. China today considers potential threats from democracies such as Japan and the United States and autocracies like Russia. However, if the state is a democracy, then only non-democracies are of concern. Contemporary Japan considers potential threats from China and Russia, but not the United States. Figure 1 shows the values of the Competition_it variable each year. In the next section, we assess the explanatory power of this variable using a measure of power projection. In the Online appendix, we provide some additional discussion of why we developed country-level, rather than dyad-level of geopolitical competition.

Geopolitical competition and the development of power projection capabilities

The dependent variable of the analysis is the relative power projection capability of a state. Following previous research (Bolks & Stoll, 2000; Lemke, 2002), we use a state’s naval capabilities as a proxy measure for its choice to invest in power projection capabilities. We recognize that there are other measures of power projection, especially in the contemporary era. Due to space constraints and data availability, we focus on naval capabilities. In other research, we focus on how the level of geopolitical competition explains the choice to build other weapons systems that are associated with power projection, such as aircraft, missiles, and nuclear weapons. Focusing on naval capabilities has limitations, but it is still a useful and informative indicator for several reasons.

First, measuring naval capabilities provides several advantages for cross-national comparison. States vary in OPEN IN VIEWER

Second, the concept that we are fundamentally interested in measuring is a state’s choice to invest in the capabilities to inflict harm on other states by projecting military force. No state has ever projected a substantial amount of power globally without first building the capabilities to project power over water. A state’s decision to build and maintain naval forces is a costly signal that they seek to build the capabilities to project military force beyond their immediate borders.

Third, ships, unlike land armies, are much less useful for domestic security and repression. We might observe states investing in their armies and conclude that their decision was driven by their geopolitical environment, when their primary motive was domestic suppression, an especially relevant concern with autocracies. By focusing on capabilities that are more useful for projecting power outside the state, rather than within the state, we alleviate a potential confounding factor that might otherwise bias the results in our favor.

The fourth reason is substantive. Oceans have increased in importance over time due to increased maritime trade and discovery of deep-sea maritime resources. The result has been heightened competition over maritime space, as in the Arctic and South China Sea. As territorial borders stabilize and the number and intensity of maritime disputes increase, predicting which states will be likely to enhance their naval capabilities will have important implications for governance of global commons.

One potential downside of a naval measure is that it may underestimate the power projection investments of land powers relative to sea powers. In the Online appendix, we discuss this potential bias in detail, and describe why, to the extent bias exists, it makes it more difficult for us to find support for our theory.

Following Lemke (2002), we use data on naval ship tonnage as an operational measure for power projection capabilities. For data on naval ship tonnage, we use a dataset on naval power developed by Crisher & Souva (2014). The dataset records the naval tonnage for all states possessing at least one frigate class ship or submarine of at least 1,000 tons. Seventy-three countries enter the dataset from 1865–2011.

We also run our analysis using the number of capital ships that a state builds. We estimate eight models in which the dependent variable is operationalized as a count of the number of capital ships a state possesses (see Table I and Figure 1 in the Online appendix). Our results are generally robust when using Modelski & Thompson’s (1988) and Crisher & Souva’s (2014) data on capital ships. For the main results (see Table II), we have opted to use Crisher and Souva’s (2014) tonnage data because they provide naval tonnage for a broader set of states and the data extend to 2011, as opposed to Modelski & Thompson’s (1988) data, which end in 1993.

Each ship’s tonnage is recorded if it possesses a minimum level of armament, is deployable to areas beyond the state’s own littoral waters, and surpasses the minimum level of tonnage. This minimum criterion changes over time to consider changes in naval technology. For more on the selection criteria, see Crisher & Souva (2014). We recognize that this is an imperfect measure, as a heavier navy is not necessarily a more capable one, however, a ship’s capabilities and tonnage tend to be highly correlated.

We measure a state’s relative level of tonnage compared to its total GDP by dividing the level of tonnage in that year by the GDP. This transformation creates an index in which values represent the number of tons of naval equipment in service per unit of GDP generated in that same year. The GDP values are in constant 2011 purchasing power parity dollars. Thus, larger values indicate a relative increase in the economic capacity being devoted to a state’s naval capabilities. These values are useful for comparisons over many decades and across different states, as seen in Figure 2.

If we look at absolute levels of Chinese military spending, they appear to be growing at break-neck pace, however, military spending as a percentage of GDP has remained relatively constant at around 2.5% of GDP over the past decade. Similarly, China’s absolute naval tonnage has been increasing. However, considering this metric alone would bias towards finding a relationship between the level of geopolitical competition and this variable. Hence, we examine whether states such as China are increasing their naval tonnage relative to their economic power. We find that from the end of the Cold War in 1991 to 2011, the total naval tonnage for China grew from 173,491 tons to 447,280 tons, which represents approximately a 250% increase in China’s total tonnage. However, during the same period, the economy of China grew by 265% (Gleditsch, 2002). Thus, while China’s absolute tonnage is growing and its ability to project power has increased, its tonnage to GDP ratio has fallen. The fact that we still find these results, despite using this more conservative measure of a state’s choice to build power projection capabilities, increases the robustness of our findings.

In comparison, Japan’s navy grew from 212,065 tons in 1991 to 312,890 tons in 2011, an increase of approximately 50%, while its economy increased by approximately 40% over the same period (Gleditsch, 2002). Thus, Japan’s total tonnage increased faster than its GDP, indicating its GDP ratio has increased, consistent with our theoretical predictions. This reflects Japan’s prioritization of its navy even during a period of economic hardship, suggesting that China’s economic rise should increase the level of geopolitical competition that Japan faces (and it does, increasing by approximately 24% from 1991 to 2011).

The contrast in this ratio is especially clear when looking at Europe. European states have witnessed a decrease in total tonnage while their economies have grown. For example, Britain’s navy decreased from 422,477 tons in 1991 to 177,108 tons in 2011 – a decrease of approximately 58.0% – while its economy increased by approximately 23.5% over the same period. Consistent with our theory, the tonnage to GDP ratio of European states has fallen much more steeply than in Asia, suggesting that European states decline to invest in power projection capabilities because their geopolitical

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Table I.

Negative binomial count models for capital ships, using geopolitical competition, the natural log of GDP, and a lagged dependent variable as controls

	Dependent variable
	Pre-Dreadnoughts	Dreadnoughts	Aircraft carriers	Battleships	Aircraft carriers	Diesel submarines	Nuclear attack submarines	Ballistic submarines
	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
Geopolitical competitioni,t−1	205.18***	185.49***	102.76***	297.62***	50.50***	8.05	157.41***	55.41***
	(4.44)	(4.62)	(9.23)	(13.20)	(13.74)	(6.69)	(6.38)	(9.93)
ln GPDi,t−	0.82***	0.93***	0.91***	0.60***	0.91***	0.32***	1.05***	1.16***
	(0.02)	(0.02)	(0.03)	(0.04)	(0.04)	(0.02)	(0.02)	(0.02)
Pre Dreadnoughtsi,t−	0.13***
	(0.001)
Dreadnoughtsi,t−		0.15***
		(0.001)
Aircraft carriersi,t−			0.18***
			(0.003)
Battleshipsi,t−				0.34***
				(0.01)
Aircraft carriersi,t−					0.19***
					(0.004)
Diesel submarinesi,t−						0.05***
						(0.001)
Nuclear attack submarinesi,t−							0.04***
							(0.0005)
Ballistic submarinesi,t−								0.05***
								(0.001)
Constant	−13.58***	−14.58***	−14.40***	−11.83***	−13.16***	−3.17***	−14.99***	−16.53***
	(0.29)	(0.27)	(0.40)	(0.51)	(0.53)	(0.24)	(0.26)	(0.33)
Data	MT	MT	MT	CS	CS	CS	CS	CS
Observations	10,907	10,907	10,907	4,806	4,806	4,806	4,806	4,806
Log likelihood	−3,242.43	−3,297.80	−1,735.09	−2,054.95	−2,433.88	−10,287.65	−3,697.85	−2,258.15

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Table II.

Linear regression models (1865–2011)

	Dependent variable
	ln Naval tonnageindexi,t
	Panel linear								OLS
	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)	(11)	(12)
ln Competitioni,t−1	1.06***	1.23***	1.23***	1.22***	0.43***	0.36***	0.38***	0.35***	0.06***	0.10***	0.10***	0.10***
	(0.02)	(0.02)	(0.02)	(0.02)	(0.03)	(0.04)	(0.04)	(0.04)	(0.01)	(0.01)	(0.01)	(0.01)
Democracyi,t−1		0.03***	0.03***	0.03***		−0.01	−0.005	−0.004		0.005***	0.005***	0.005***
		(0.003)	(0.003)	(0.003)		(0.004)	(0.004)	(0.004)		(0.001)	(0.001)	(0.001)
GDPi,t−1			5.28***				2.45**				0.19
			(0.84)				(0.79)				(0.11)
ln GDP ratioi,t−1				−0.22***				−0.26***				0.004
				(0.04)				(0.04)				(0.003)
ln Naval tonnage indexi,t−1									0.97***	0.96***	0.96***	0.96***
									(0.003)	(0.004)	(0.004)	(0.004)
Constant									0.27***	0.45***	0.43***	0.46***
									(0.03)	(0.05)	(0.05)	(0.05)
Fixed effects	C	C	C	C	C-Y	C-Y	C-Y	C-Y	None	None	None	None
Observations	4,518	4,449	4,449	4,449	4,518	4,449	4,449	4,449	4,423	4,354	4,354	4,354
Adjusted R2	0.46	0.48	0.48	0.48	−0.01	−0.02	−0.01	−0.005	0.97	0.97	0.97	0.97

*p < 0.05, **p < 0.01, *** p <0.001. Geopolitical competition is associated with statistically significantly higher levels of investment in power projection capabilities across all models. The estimated size of the effect varies with the model that is used in the estimation. A 10% increase in the level of geopolitical competition that a country faces is associated with on average 1% (including a lagged dependent variable), 3.8% (for the model with country and year (C-Y) fixed effects), to 12.3% (using just country (C) fixed effects) increase in the naval tonnage index for a model with the Polity 2 score and the GDP ratio as controls.

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Figure 2.

Yearly estimates of each state’s relative level tonnage compared to its total GDP in that year