Extraction, Allocation, and the Rise and Decline of States: A Simulation Analysis of Two-Level...

Extraction, Allocation, and the Rise and Decline of States: A Simulation Analysis of Two-LevelSecurity ManagementAuthor(s): Marc V. Simon and Harvey StarrReviewed work(s):Source: The Journal of Conflict Resolution, Vol. 40, No. 2 (Jun., 1996), pp. 272-297Published by: Sage Publications, Inc.Stable URL: http://www.jstor.org/stable/174353 .Accessed: 26/10/2012 12:15

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Extraction, Allocation, and the Rise and Decline of States

A SIMULATION ANALYSIS OF TWO-LEVEL SECURITY MANAGEMENT

MARC V. SIMON

Bowling Green State University

HARVEY STARR

University of South Carolina

Using realist models of international politics that deemphasize the two-level security game that states play, most analyses of hegemonic decline argue that decline is caused by the differential growth of power between hegemons and challenging states. The authors argue that decline is affected highly by states' resource extraction and allocation decisions, and that the international and domestic consequences of these decisions must be analyzed. A model of how states respond to external and internal security threats is outlined and analyzed via computer simulation. The authors find that states are likely to decline if they overemphasize increasing capabilities to deter threats instead of allocating resources to reduce opponents' willingness to attack. In addition, a more "dovish" allocation strategy can be very effective against internal threats. Thus the decline of hegemons and rise of challengers is determined as much by strategies as by constraints posed by the system structure.

INTRODUCTION

This article, which is part of a larger project regarding two-level security management, addresses the question of the causes of the rise and decline of states in the international system, particularly hegemonic powers. As outlined in Starr (1994), major theories of system change and hegemonic decline (e.g., Kennedy 1988; Olson 1982; Gilpin 1981; Organski and Kugler 1981; Doran 1989) assume that system change is driven by differential growth in power between hegemonic and challenging states; this is quite similar to the explanation provided by rational models of civil conflict (e.g., Tilly 1978; Oberschall 1973) for revolution. With the deemphasis of civil conflict in most realist models, there has been little attempt to integrate the war and revolution literatures to analyze the effects of this dual security threat to states.

AUTHORS' NOTE: An earlier version of this article was presented at the 28th North American Meeting of the Peace Science Society (International), November 1994, Urbana, IL. We would like to thank Bruce Bueno de Mesquita and Michael McGinnis for their comments.

JOURNAL OF CONFLICT RESOLUTION, Vol. 40 No. 2, June 1996 272-297 ? 1996 Sage Publications, Inc.

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Simon, Starr/TWO-LEVEL SECURITY MANAGEMENT 273

Most and Starr (1989), Starr (1994), and Starr and McGinnis (1992) have outlined a framework that captures the common logic of decisions that states must make as they face threats to security from the domestic and international arenas. We expand this into a model of governments' security management decisions. The model assumes states are unitary actors that make policy choices under conditions of bounded rationality. Actors do not have complete information about many factors related to security but do use available information to make subjective estimates of the probability that other actors will go to war or intensify a rebellion. We assume that bureaucratic constraints deny actors the ability to calculate the long-term effects of their policy choices on other actors; they therefore use simple decision rules to address their immediate security needs. This leaves open the possibility that states may pursue policies that maximize their short-term security but produce unexpected and unfavorable outcomes in the long run. We then examine the model via computer simulation to evaluate its appropriate- ness and to explore its implications for the factors that generate the rise and fall of nations over time. The simulation tests the plausibility of our assumptions by generating implications for a hypothetical system of states.

Assuming that system change and hegemonic decline are largely a result of differential rates of growth in power, we use our model to understand the various factors-system level, state level, and domestic-which contribute to these growth rates. Only by evaluating their effects in an integrated model (including both of Starr's concepts of opportunity and willingness) can we really understand either their relative importance or the processes by which they operate. Our evaluation of the relative effects of these factors will focus on whether factors related to choice are of equal or

greater importance than systemic or other factors affecting the rise and decline of states. By choice, we are referring to basic resource allocation decisions that government policy makers make to address domestic and external threats. All states must use resources to address both types of threats; they can choose to build resources to deter their threats, or to spend resources to improve the status quo and make opponents less willing to attack or rebel. This choice of allocation strategies-in both the domestic and external arenas-has a potent effect on power growth and may be the true engine behind the rise and decline of states.

MODELING THE COMMON LOGIC OF SOCIAL CONFLICT

Our framework is concerned with analyzing government policy decisions in the context of threats to the viability of the government from internal and/or external sources. The model of this internal-external linkage begins with four components of a common logic of decision (Most and Starr, 1989, chap. 5):

Ci = state i's defense capacity against external threats; Ri = the external risks faced by state i in the international system; Si = state i's domestic defense capacity, that is, the strength of the government in the face of

domestic opposition; and Ti = the internal risk (threat) to the government from domestic sources.

274 JOURNAL OF CONFLICTRESOLUTION

Each of these components affects decision makers' perceptions of their state's viability or security. Viability is gauged in two arenas-external risk (R) and internal threat (T)-each of which can have political, military, and/or economic components (see Bueno de Mesquita, Siverson, and Woller 1992). Risk and threat are conceptually measured against the state's defense capacities-C (external capabilities) and S (domestic strength)-which reflect the military, coercive, economic, and political resources it can use against external challengers or internal opponents.

This C-R-S-T framework implies simple sets of governmental goals: to strive to make C > R, and S > T, and make sure that the magnitude of the C/R and S/T ratios is maintained or increased over time. We assume that when decision makers perceive that C < R, S < T, or that the C/R or S/T ratios are getting worse over time, they will feel vulnerable and take action to remedy the situation. These four conditions are, in Schelling's (1978) terms, micromotives, which, if triggered, become the motors that drive decision processes. These triggers and the decisions that affect them are linked via the two-level (Putnam 1988) or nested games (Tsebelis 1990) that decision makers play. Decisions to lessen a C < R problem have consequences for S and T; actions taken to address an S < T situation may exacerbate a concurrent C < R problem.

In sorting out these consequences, decision makers must consider the effect of their actions for both domestic opponents and international challengers; further, those opponents and challengers then make their own calculations about the relative utility of the status quo, the likelihood that they might win a revolution, and the probability of war. International challengers are also faced with C, R, S, and T conditions of their own, adding a layer of complexity that makes it hard for decision makers to know the full consequences of their policies. However, although our model assumes that decision makers do not have complete information, they can make reasonable, subjective estimates of other actors' expected utility of war or revolution and use these to estimate their own risk and threat. In short, the model assumes that these players are Bayesian rational actors.1

Traditional realist models of war and much writing on revolution have neglected this linkage between internal and external security (Starr 1994). The theoretical model developed and explored here attempts to uncover the effects of this complexity on state survival and security. (See appendix for an overview of the model.)

As a first cut, we have chosen to evaluate this model and explore its implications using a computer simulation. Other scholars have used simulations effectively in conflict research (e.g. Cusack and Stoll 1990, 1994; Most and Starr 1989, chap. 6; Salert and Sprague 1980). We have taken note of the strengths and weaknesses of each of these endeavors, and we understand the limits of what simulations can tell us.

1. For further justification of this Bayesian approach to game theory, see McGinnis (1991, 1992) and McGinnis and Williams (1991, 1992, 1993). Our approach is also driven by theoretically grounded assumptions about the constraints that bureaucracies place on decision makers, (e.g., Steinbrunner 1974). Thus our model places limits on the computational abilities of actors. We assume that all states react to simple decision triggers (such as C < R, and S < T), and that they share this knowledge of their limited information. (In fact, McGinnis [1992] argues it would be irrational for actors to ignore such knowledge by assuming that their adversaries were fully rational.) This bounded rational approach, prevalent in cognitive approaches to the study of foreign policy (Mintz 1993) and prospect theory (Levy 1992), is more easily amenable to empirical applications and has even been integrated into several formal game theory models (for citations and examples, see Kreps 1990; McGinnis 1992, 452-3).

Simon, Starr / TWO-LEVEL SECURITY MANAGEMENT 275

However, with complex models that are not easily amenable to empirical application, evaluation by simulation is preferable to the alternatives. Statistical analysis of the model in its present form would be nearly impossible, because our variables are

grounded in perceptions and thus difficult to measure. Moreover, a purely analytical evaluation of the model would likely yield mathematical relationships that would be difficult to interpret and even harder to apply empirically. Simulations are an initial means of checking whether a model has any internal inconsistencies, as well as of

exploring the nonobvious implications of the model that might later be examined in cases. In a sense, we use simulation as what Eckstein (1975) called a "plausibility probe" to determine what kind of empirical work is warranted.

THE SIMULATION MODEL

COMPONENTS OF THE SIMULATION MODEL

Defense Capacity (C) and Domestic Strength (S)

These capabilities denote a state's ability to resist external attack (C) or domestic

opponents (S). Both can be conceived as the outputs of production functions that transform resources, both tangible (materials, troops, etc.) and intangible (ideology, leadership) into capability levels. Resources extracted by i can be applied to either C or S. Although the simulation treats C and S as separate capabilities, in principle, these

capability levels are complements: increases in C should bring about increases (at a lower rate) in S, and vice versa. One advantage of separating C and S conceptually is that this allows each to be subject to a law of diminishing marginal returns, thus it costs more to increase C and S the larger they become.2

The capabilities and strength of states in the system are rough measures; to

approximate real systems, we have consulted power indexes (Taber 1989). Because most indexes are normalized with the major power (or the United States) assigned 100, that is the metric we use in assigning initial values for our state system.3

Interaction Opportunities (p) and Willingness (w, r)

Following Most and Starr (1989), in assessing threats, states consider the probability that other actors will have both the opportunity (p) and willingness (w, r) to

2. The simulation calculates diminishing marginal returns by weighing increases in C and S based on the baseline value for a major power in the system. The formula for the weight (given for C below) allows the actual increment in C or S to vary from 75% to 125% of its face value depending on how high C is compared to the baseline. New C = Old C + 0.5 + increment x 0.5 x ([baseline C] / [Old C + baseline C] + 0.5).

3. It must be stressed that the choice of a metric for C, R, S, and T (as well as other model parameters) is not that important, because our theoretical model assumes that states are concerned with the four security ratios and their relative capabilities. Likewise, though we began with willingness values of approximately 0.02-0.10 for w and 0.01-0.10 for r, calculated using Correlates of War data for the likelihood that a state will be involved in a nation-month of war in a given year (Small and Singer 1982, 129, 263), this metric is not crucial to our analysis.

276 JOURNAL OF CONFLICT RESOLUTION

initiate war or escalate rebellion. Some states interact more frequently than others and are more likely to have conflicts. To assess threats to its viability, government i considers the likelihood that it will have interactions over contentious issues with other states j and internal opposition groups k. The parameter p is i's view of the probability that an issue will arise where j or k might prefer to start a war or revolution with i. If p is low, then i's current relationship with j does not present many opportunities for violent conflict. In the simulation, we begin with p uniform across states; thus the systems being modeled consist of tightly networked sets of frequently interacting states.

Government i also estimates whether in its interactions, j or k will be willing to initiate a war or intensify a revolution. This "probability of willingness" is affected by i's opinion of the "disposition" of the other players with regard to risk, hawkishness, and the like.

In the domestic arena, willingness (r) is a bit different than in the international arena (w) but still fits within the common framework. The problem is that, unlike states, rebel groups by definition are always willing to rebel-they exist to rebel. Applying the resource-mobilization perspective (Tilly 1978) as the major rational explanation for opposition group behavior, rebel groups grow and decay, succeed and fail based on their ability to mobilize resources from society (much as government i extracts them). In contrast to deprivation theories (e.g., Gurr 1970), this perspective assumes that societal grievances, which are necessary for rebellion, are usually present, and so the ability to mobilize is the key for successful rebellion. The rebels are choosing strategies that are aimed at increasing their control over resources, because this determines the success or failure of their rebellion. If they fail to get resources, they will be unable to overcome the free-rider problem (Lichbach 1995) and their rebellion will cease, regardless of the leadership's willingness to continue. So, for oppositions, we conceive of willingness (r) as the government's estimate of the intensity and scope of societal grievances and the rebels' willingness to apply effective mobilization strategies-not their willingness to rebel.

Other rational analyses of rebellion (DeNardo, 1985; Lichbach, 1995) as well as empirical work (Tilly 1975) reveal that government policies and levels of repression do affect the relative success of various rebel strategies of mobilization. In our framework, different strength ratios (s) as well as extraction and allocation decisions, discussed later, affect the degree of threat posed by the opposition's willingness to intensify (r) their rebellion.4

Calculations of Risk (R) and Threat (T)

The formulas for risk and threat are shown below:

Ri = S pijwiCi

4. Lichbach (1995) outlines over two dozen strategies used to overcome the free-rider problem to create conditions for the growth of rebellion. In his terms (see pp. 22-6), improvements in strength ratios help the rebels mobilize by increasing the probability of winning (p. 62); extraction decisions help reduce the size of the public good (p. 62); allocation decisions increase resources (p. 48), increase benefits (p. 35), and lower costs (p. 36) to those who might join the opposition.


Ti = PikrikSik

In the simulation, we assign each state (i) an interaction vector (Pij, Pik) denoting i's perception of the probability that an issue will arise in its interaction with some other state j or opposition k that will precipitate a war or revolution. State (i) is also assigned a willingness vector (wij) containing its perception of the likelihood that opposing states will initiate war, and a similar vector (rik) for its perception of the likelihood that existing rebel groups will escalate their rebellion. The value of each element wij and rk is between 0 and 1. Finally, by comparing its capabilities (Ci, Si) to those of other actors in the system, (Cj, Sk) state i estimates the likelihood that it would lose a war to j (ci) or revolution to k (Sik) should that event occur. These strength ratios (ci, sik) are calculated as the ratio of state i's capabilities to state j's capabilities, and the ratio of i's strength to rebel group k's strength. To represent them as probabilities in the simulation, they are normalized to a range of 0 to 1 as shown below:

ij = 1 - (Ci /(Ci + Cj)

Sik = 1- (Si/ (Si + Sk)

Baseline values for all parameters are listed in the appendix.5

DYNAMICS OF THE SIMULATION

Criterion Function (z)

We have explained how a state arrives at an estimate of the profile of threats it faces, but what does it do about those threats? Practically, a state cannot eliminate all threats, so what profile of threats should be considered optimal? Perhaps state i minimizes the sum of all its threats, but this might produce one very large threat and several small ones, or a set of equally menacing medium-sized threats. Most states would rather have the second option. But rather than impose some ideal threat distribution as the goal of state action, we focus on their decision process as implied by bureaucratic politics and realist models of balancing behavior.

Looking at classic treatments of the balance of power, one plausible interpretation of such models is "minimize the maximum threat." That is, the deterrence-based processes on which the balance of power is built were aimed primarily at stopping drives toward hegemony. To achieve the aims represented by the rules of Kaplan's (1957) balance of power system, the power of the strongest state had to be counter-

5. In the simulation, because p, w, r, c, and s vary from 0 to 1, the value of risk (1) and threat (2) for state i versus state j or opposition k will also vary from 0 to 1; to convert this to a metric comparable to that which we will assign to C and S, we multiply R and T by an appropriate constant (1,000). We wish to reiterate, as in note 3, that the metric we arbitrarily choose for representing capabilities/strength and risk/threat does not affect our results. It is only important that C, R, S, and T are represented in comparable metrics and calculated consistently. We have chosen metrics that allow the possibility that C > R, R > C, S > T, or T > S, which reflects the reality that states are sometimes vulnerable and sometimes secure.


balanced.6 Balance of power models that were particularly concerned with the role of a balancer (almost always identified as Great Britain) also could be interpreted as models that call for the balancer to throw its weight against the most powerful state (or alliance). This would hold for both power and threat. Walt (1987) argues that states form alliances in response to threat, not simply some measure of power. For Walt, threat derives from aggregate power, proximity, offensive capability, and offensive intentions. If Walt is correct that his formulation more adequately captures alliance formation and the dynamics of the balance of power (in terms of both balancing and bandwagoning), then we have a solid theoretical foundation for assuming that states move to minimize the maximum threat-looking not only at military capability but at proximity and intention as well (that is, opportunity and willingness). Although neither the classic balance of power literature nor Walt specifically calls for the strategy of minimizing the maximum threat, such a strategy is implicit in these formulations.

Moreover, this strategy also minimizes decision costs for actors, consistent with bureaucratic politics and cybernetic models (Steinbrunner 1974; Allison 1971; King- don 1984) that motivate our assumption that decision makers act under bounded rationality. The nature of governments as complex organizations suggests a fairly simple decision rule that requires actors to focus their attention on only a small number of threats at a time, perhaps on only their single most pressing threat.7 Thus our criterion function is based on the conceptual rule "minimize the maximum threat": state i tries to minimize the maximum value of all external risks (Rj) and domestic threats (Tk).

This rule assumes that government i can rank other governments and rebel groups according to the overall threat they pose, and that i will concentrate its attention on reducing the threat posed by the actor most likely to have both the opportunity and willingness to attack and defeat i. However, this rule does not eliminate the strong possibility that efforts to reduce one threat may tend to augment other threats, the essence of the two-level security problem. If states are successful in sequentially reducing their most menacing threat, this might result in a system of equally capable and threatened states or an equal distribution of power. If some states are more successful than others, however, we should see a more accurate system of states with various threat profiles.

We have now outlined the basic structure of the simulation (see Figure 1). In each round of the simulation, each state in the system examines its threat profile, finds the maximum threat (be it external or domestic), and takes some action to reduce that threat. This is done simultaneously for all states in the system. After each state has acted, new levels of capabilities (C, S, c, s), willingness (w, r), and interaction (p) are calculated for each state, and the process repeats. The key to changes in the system,

6. Kaplan presents six principles characterizing a stable balance of power system (1957, chap. 2), including: oppose any coalition or single nation that tends to become predominant within the system; oppose any nation that promotes an ideology of subordination of nation-states to some higher authority.

7. In reading the memoirs of high-level decision makers, one is struck by the extent to which the flow of daily events dictated policy and choice, by the limited number of issues that could be attended to at any one time, and by the constant attention to "putting out fires" as they arose. See Kissinger (1979) and, especially, Acheson (1969).


C START

/Assign C,S,SOC,w,r,p and other values

i Begin Round: Calculate R and T for each State

.

- Next State i Noany ba [ ̂C/R or S/ratios?

Yes v

Domesi Identify greatest current threat nternationa

< xtract to build S o Extract to build C or Allocate to redue r cate to reduce w

Calculate impact of extraction or allocation on C,S,SOC,w,r,p

No as ast state ii^ system acted?

Yes v

Replace old C,S,SOC,w,r,p with new values for all states

Round Over

Figure 1: Basic Simulation Algorithm

then, lies in our model of the effects of these "actions" to reduce threat, which we describe as the extraction and allocation of resources.

Resource Extraction and Allocation

In the following sections, we represent the outcomes of extraction and allocation as specified by various, sometimes competing theories. Rather than imposing optimal strategies of extraction and allocation, we use the simulation to evaluate the long-term consequences of such strategies-consequences, we argue, that decision makers


cannot necessarily foresee and account for in their choices of short-term policies to deal with immediate threats to viability.8

Extraction. Extraction is a key process that links apparently disparate studies of revolution and war (Starr 1994). Governments under stress (whether from war or revolution) search for additional resources. They can extract those resources from society or from other states. A major theme in the revolution literature is that war weakens legitimacy and promotes opposition and dissent because it forces the government to extend and deepen its extraction of societal resources. On the other hand, extraction from society might create a cohesion effect from shared sacrifice in the face of an external (or separatist internal) threat (Levy 1989; Stein 1976). External extraction of resources can lead to increased interaction opportunities (p) for generating conflict. It can also lead to more interdependence, predictability, and trust as the mutual gain from trade relations improves both countries' economies. The challenge for governments is to maximize the acquisition of resources from society and international actors while minimizing the costs associated with that extraction.

The extraction and allocation behavior of rebel groups is quite similar to that of the state, especially as portrayed by the resource-mobilization perspective on revolutions and social movements. The simulation allows states to extract and allocate resources, but for simplicity, it models rebel groups as reactive. We apply rational actor theories of rebellion (Tilly 1978; Lichbach 1995) to specify how rebels are affected by state extraction and allocation decisions, government legitimacy, the balance of resources between the state and rebels, and the rebels' current resource endowment. This is described in a later section.

In the simulation, states can extract from three sources: from societal resources, from the capabilities of other states, or by transferring resources between C and S. The simulation defines a pool of societal resources (SOC) for each state. Conceptually, SOC includes those assets not already part of C and S: for example, the size of the economy from which a state gets revenue, and the level of government legitimacy or popular support. Both the government and rebels compete for these resources (Lich- bach 1995, chap. 7); this competition is treated as zero sum. The resource base (SOC) is assumed in the simulation to grow at a fixed rate (1%) for each round, which represents economic growth over time. The size and growth rate of SOC is highly affected by extraction and allocation decisions outlined below.

Allocation. Because we are primarily concerned with threat management, we assume two basic targets for allocation of resources. They can be added to capabilities

8. One might argue that a Bayesian rational actor could formulate an expectation regarding other states' propensity to extract or allocate, and then could make its own extraction or allocation decision so as to maximize its own security gain. However, in addition to the cognitive limitations that we impose on decision makers, we are agnostic regarding the relative utility of extraction versus allocation; it is not clear to us that one approach is empirically better than another in any given situation. We have therefore represented the short-term impact on security of extraction versus allocation as roughly similar. Furthermore, in our baseline system, states randomly extract and allocate about 50% of the time; thus the Bayesian actor in this situation expects other states to be neutral. This method allows us to use the simulation to explore the relative effects of extraction versus allocation without knowing in advance what the result will be.


or strength, making the state stronger in the face of international or domestic challengers, or they can be allocated to those challengers in ways that improve the value of the status quo, making the challengers less likely to be willing to start a war (w) or intensify a rebellion (r). In essence, we assume that a state either deters or buys off its potential opponents. By using these methods, states can reshape the profile of security threats they face, making some actors more threatening while making others less threatening.

Hawks and doves. How does a state decide whether to buy off opponents or build capabilities? Based on empirical discussions by Ikle (1971) and Barnet (1972), Simon (1994) has argued that governments have general dispositions toward either hawkish or dovish methods of solving their security problems. We label accommodating states that attempt to buy off their foes as doves, and extracting states that seek to build capabilities as hawks. In the simulation, rather than impose an optimal strategy, we assign states a "hawkishness" value (H), referring to the probability that they will extract or allocate in any given interaction. Because states need not treat internal and external threats the same, we include a separate hawkishness value for external and domestic opponents. If Hi = 1, then the state always extracts; Hi = 0 means the state always allocates. In practice, most states employ a mixed strategy (0 < H < 1). We have purposely made the short-term impact of hawkish and dovish strategies on security fairly similar, allowing us to explore the long-term and unanticipated consequences of various levels of hawkishness and dovishness with the simulation.

Effects of allocation. Allocations are made to the state (or rebel group) that currently poses the most risk (or threat), following our "minimize the maximum threat" rule. When states allocate, they are spending their capability and strength resources to make opposing states less willing to go to war and rebel groups less willing to rebel. Therefore an allocation decision directly reduces Ci (or Si) and also reduces wij (or r,i), i's perception of j's willingness to go to war (or k's willingness to intensify revolt). In the simulation, the amount of resources spent in an allocation decision is arbitrarily set to 3% of the current total of C or S; the effect on willingness, wij or ri, is a 3% drop. The reduction in willingness produced by allocation can be seen as states moving toward alliances with each other, or rebel groups becoming more like challengers operating within what Tilly (1978) called the "polity"-groups working for policy changes from within the political system.

Domestically, an allocation decision should bring economic benefits, because extracting resources to build (military) capabilities is generally taken to be a drag on the economy (see Mintz and Huang 1991; Russett 1970; Ward, Davis, and Lofdahl 1995; Mintz and Stevenson 1995). To account for this, if a state allocates in a given round, it always receives the full 1% rise in societal resources (SOC) at the end of each round of interaction, though extracting states may receive less.

Effects of extraction to build capabilities. Resources can be extracted from society (SOC), allies, or transferred from domestic strength (S). In the simulation, in half of its extraction decisions, a state extracts from S and SOC, and in the other half, from S, SOC, and an ally. In the first case, a state transfers 1.5% of its current resources in


SOC, combined with 1.5% of its S, to defense capabilities (C). The transfer from S worsens the state's S/T ratio but has few important effects beyond this.

Extraction from society reduces the amount of societal resources, which, in the absence of extraction, are assumed to grow at 1% per round. And, as previously noted, societal extraction may increase the mobilization of rebel groups or may increase internal cohesion. If the number of rebels grows, this further reduces the pool of societal resources available for future extraction; if internal cohesion increases, societal resources are increased.

To represent these processes, states are assigned a variable (V) that specifies the growth rate (2%) of opposition groups that occurs after each extraction. This is based on the resource mobilization assumption that rebels grow based partly on their current endowment of resources. We use another dispositional variable, G (for government legitimacy), to capture the mobilization/cohesion effect on SOC. Highly legitimate states get a small boost in SOC when they extract (cohesion); less legitimate ones see a further drain in SOC (mobilization). The effect is weighted by 1/(C/R), because very secure states are assumed to get less benefit than those facing more ominous external threats; similarly, rebel growth is assumed higher when a state faces a serious threat to viability. The baseline value of G is neutral (zero).

When a state extracts additional resources from an ally, it receives 3% of the defense capabilities (C) of its closest ally in the system (lowest wij). Because alliances enmesh states in the geopolitical web and can also act as conduits for the spread and amplification of conflict (e.g., see Siverson and Starr 1991), state i's extraction increases its exposure (p) to all states in the system by 3%, thereby increasing its total risk (R).9 The costs of the extraction to the ally j are assumed to be negligible, because although the ally gives up resources, it also may gain from increased cooperation with state i.

Effects of extraction for domestic strength. Extraction to build S involves similar processes as extraction for C; a fixed amount of resources can be extracted from external defense capabilities (C), society (SOC), or allies. As above, in half the extraction rounds, state i transfers 1.5% of C to S, and 1.5% of SOC to S; in the other rounds, state i extracts 3% of its ally's C. Extracting from SOC and from allies involves trade-offs similar to those discussed under extraction for defense capabilities (simply substitute S/T for C/R in the discussion above).

OVERVIEW OF THE SIMULATION

We have now outlined the basic assumptions and formulas used to create the computer simulation of state behavior in the context of two-level security threats. Figure 2 illustrates the design of the simulation in a flow chart format, which we hope will clarify any ambiguities in the preceding discussion.

The baseline values for all parameters are listed in the appendix. Deviations from these values for particular simulation runs will be noted. Our baseline system will

9. This increase is 3% of the difference between the current p value and 1; thus interaction opportunities are capped and cannot grow indefinitely.


NJext No State i: is C/R or S/T < 1, tate i qo

or worse than last round?

Yes internal Identify extemnal

Identify xtract or Allocate --- Greatest Threat Extrac or Allocat

to i's Viability allocate extract extract allocate

Allocate 3% Transfer 1.5%

Add 1%to Yes. SOC Replace all old C,S,SOC,w,r,p with new values

Figure 2: Simulation Algorithm in Detail

involve 300 rounds, which provides ample opportunity to display the dynamics of the

system but still keeps important parameters (notably p) within defined ranges.10

10. To reiterate, although the (3%) size of extractions, allocations, and the changes in willingness and interaction opportunities are arbitrary-because the simulation is concerned with long-term consequences of security management decisions-changing the size of such variables does not effect the patterns that emerge; it only affects the time (number of iterations) it takes them to emerge.


We have attempted to create a simple system for use as a baseline for comparing the effects of changing levels of these parameters. The baseline system size (10 states) and polarity (3 major powers) were chosen based on analysis of the effects of these variables on security outlined below. We also assume that each state has two rebel groups, based on empirical data on the prevalence of imperiled minorities (Gurr and Scarritt 1989) and on Lichbach's (1995, 18-9) argument about the likelihood of competition between rebel factions.1

EXAMINING THE EFFECTS OF SYSTEM STRUCTURE ON SECURITY

Traditional realist and neorealist models (Waltz 1979) place great emphasis on

system-level attributes as the main determinant of state security. Rational theories of hegemonic decline (Gilpin 1981; Kennedy 1988; Kugler and Organski 1989) empha- size both international and domestic factors as driving the differential growth in power that generates the rise and decline of great powers. In particular, Gilpin (1981, 10-1) explains that states tend to expand until the marginal costs of further expansion are greater than or equal to the marginal benefits. At this equilibrium point, he argues that "the tendency is for the economic costs of maintaining the status quo to rise faster than the economic capacity to support the status quo."

Although there are various explanations as to why these economic costs rise, we feel that these theories, grounded in traditional realism, tend to downplay the impact of the two-level security game that states play. Certainly, hegemonic powers may become prone to fighting costly wars and proxy wars to preserve their position, and this can be a drain. But, the successful hegemon must do a great deal of extraction, both internally and from allies, to reach its position as a great power. This extraction has important domestic costs. Might there be a dynamic that leads certain states under certain conditions to decline due to the trade-offs between maintaining hegemonic status and addressing internal security? If so, do these conditions relate to the structure of the system, or to choices that states make in managing the dual threats to security?

SYSTEM SIZE

We first examine structural issues, holding the extraction/allocation strategy constant. Table 1 illustrates the effect of changing system size on security gains for systems of equal powers.

In each system, values of C, S, and SOC were assigned so as to make initial C/R and S/T ratios similar despite changes in system size. Three trends emerge from

11. Gurr and Scarritt (1989) find that, among the 126 countries in their study, there are 261 "minorities at risk," and that 99 of the 126 countries possess at least one such minority. Thus the average country has 2.1 minorities, and of those with one minority, the average is 2.6. Although the number of minorities varies by region, we felt that given Lichbach's (1995) argument, it made sense to have more than one rebel group per country, but, given empirical data and the need for simplicity in the simulation, it also made sense to limit the number of rebel groups to 2.


TABLE 1

Average Effect of System Size on Security Gains

Change Change Change Average Number of Size of System in C/R in S/T in SOC (%) States Rising as Major Power

20 states -0.33 31.0 207 4.4 15 states 0.13 20.1 208 4.0 10 states 1.05 10.8 206 2.9 5 states 5.71 4.0 201 1.9 3 states 22.01 1.6 207 1.3

NOTE: Results are based on 100 iterations of 300 rounds each. Baseline C (capabilities), S (domestic strength), and SOC (societal resources) were adjusted to hold each state's starting international security (C/R) at 3.06, and domestic security (S/T) at 2.43. Major powers are defined as those possessing 80% of the defense capabilities of the leading state in the system.

Table 1: the more states in the system, the less gain in international security; the more states in the system, the more states gain in domestic security; and the number of states in the system has no impact on the amount of societal resources used to achieve security.

These results basically conform to what we would expect in the real world. With more states in the system, it becomes more difficult to manage the array of threats facing a state internationally. Allocation to buy off an adversary has less effect on total risk (R), because a state can buy off only one adversary at a time. Further, building capabilities creates less relative gain in security in a larger system because the increase in capabilities is smaller relative to the total capabilities in the system; in addition, building capabilities is more likely to stimulate a counter-buildup in a large state system.'2

On the other hand, we might have expected states to do better in improving their international security in a large system, because they would have more potential allies (and thus more ally resources) from which to extract. Moreover, to hold the initial C/R ratios constant across systems, we had to augment the initial level of capabilities of states in the larger systems. For the 20-state case, each state's initial C value was 105; for the 10-state case, C was 50. We conclude that a system with more net capabilities is one in which states have a harder time maintaining security against international threats than a system with fewer capabilities.

As for domestic security, more states in a system helps states to reduce domestic threats. Lichbach (1995, chap. 7) notes that states face their own collective action problem that resources from external allies help to solve; (in part, this was how collective defense alliances such as NATO or the Warsaw Pact were used). Moreover, for domestic threats, additional states represent only potential ally resources, whereas

12. This is fully consistent with the arguments in the literature concerning the level of uncertainty and lack of stability in a multipolar system. Such effects range from Caplow's (1968) discussion of the instability of triads, to the many studies indicating the greater frequency of war in multipolar systems, to the broad theoretical analyses indicating the weaknesses of multipolarity compared to bipolarity by theorists such as Waltz (1964, 1979).


for international threats, they represent both resources and additional threats. This is why domestic security improves when the size of the system increases.'3

On the other hand, given the two-level logic of security, we might have expected states to do worse against domestic threats in large systems where their international security was more precarious. In fact, this did occur to some extent; subsequent runs demonstrate that states with high levels of international security can more effectively build domestic security.

SYSTEM POLARITY

Next, we consider the effect of changing the system's polarity on the security and survival of states as major powers. Based on the results of Table 1, we chose a 10-state system as being the most neutral in its effects on security. We then varied the number of major powers from 0 to 6, and assigned major powers twice the C, S, and SOC resources as minor powers (see appendix). Figure 3 outlines the effect of polarity on domestic and international security gains.

The trends apparent in Figure 3 reflect the conventional wisdom that polarity does matter, and that unipolar, bipolar, and multipolar systems have different implications for security. The unipolar case is most striking for its implication that the major power shows a small loss in security; this tends to support the notion that the two-level security game produces dynamics that cause hegemons to decline. Yet the decline here is a small one relative to the major power's initial C/R ratio of 11.9.

It is interesting that the bipolar system provided the highest average gain in domestic security for both major and minor powers, supporting the familiar argument about the stability of bipolar systems relative to multipolar ones. Yet, for international security, this held true only for minor powers; majors did slightly better in a system with 4 major powers. We also observe a rough correlation between international and domestic security gains. The explanation for such patterns hinges on the trade-off between the advantage of having more major powers from whom capabilities can be extracted, and the disadvantage of the additional threat posed by those major powers.

Although not shown in Figure 3, system polarity had no effect on the level of societal resources (SOC) gained by major and minor powers. Because the leading theories of hegemonic decline argue that states decline because of economic weakness, this is an important finding. Although system-level factors do affect security gains in both arenas, they do not appear to affect security by the mechanisms that theoretically drive hegemonic decline.

We also examined the frequency with which states rise and decline from major power status in each iteration of the simulation. We arbitrarily defined a state as a major

13. One might speculate that increased system size also helps domestic security because we have limited the number of rebel groups to two, thereby limiting the potential growth of rebellion. However, the benefits of ally extraction overwhelm this effect. Each extraction to build domestic strength brings about a 2% increase in total rebel strength (2% for each rebel group, no matter how many groups) and reduces societal resources. Each extraction also increases S by 3% of the resources in C and SOC. Combined with this, in 50% of the rounds, a state extracts an additional 3% of an ally's C. Because the state's own C, SOC, and the ally's C are generally larger than the rebel's S, the extracting state generally gets more resources from extraction than the rebels do with their 2% growth.


18 - S/T domestic security minor power _ 16 -

> 14 -

12 - ST domestic security = 10- major power ? 10-

8-

6 6- w 4- C/R international security

minor power IV 2-

o0 tC/R major power international security -2 I l t t t I I I

0 1 2 3 4 5 6 7 8 9 10

Polarity: Number of Major Powers (10 State System)

Figure 3: Security Change by Polarity of System

power if it had combined defense capabilities and strength (C and S) within 80% of the leading state in the system. Table 2 illustrates our results.

In general, we find that the more major powers in the system, the more volatile it

becomes; also, the more major powers, the more likely that at least one major power declines, even controlling for the number of major powers in the system. Thus, although Figure 3 indicates that on average, major powers do best in international

security in a 4-polar system and best in domestic security in a bipolar system, in any single iteration of the simulation, there is still a 25% (bipolar) or 44% (4-polar) chance that the major power will decline in capabilities to below 80% of what the leading state has. This volatility may be overstated, because, as the next section illustrates, the

powerful effects of extraction and allocation strategies (here the result of random luck) can cause states to rise or fall much faster than the others in a given iteration. Still, Table 2, like Figure 3, shows that in this two-level security context, unipolar systems are susceptible to rising minor powers; it is difficult for major powers to maintain their

huge security and capability leads over other states in the system.14

EXTRACTION, ALLOCATION, AND THE RISE AND DECLINE OF STATES

We now evaluate the effects of these extraction and allocation strategies for major and minor powers on their ability to produce domestic and international security. We chose a system of three major powers and seven minor powers as our baseline system from which to measure the effects of strategic choices, because the tripolar case seemed

14. This result is broadly similar to a result of the Cusack and Stoll (1990, 174-6) simulation, which found, using a very different design, that when civil wars are allowed, "empires" tended to take longer to form, and they then cycled between one dominant power and many powers.


TABLE 2

Polarity Changes and the Rise and Decline of States by System Polarity

Number of Major Powers in System

0 1 2 3 4 5 6

Average polarity change 3.66 0.55 -0.35 -0.92 -1.76 -2.5 -3.18 (100 iterations)

Percentage of iterations 37 58 71 90 94 99 with any polarity change

Probability of a minor power .36 .06 .02 .004 .00 .002 .00

rising to become major Probability of a major power - .01 .25 .32 .44 .50 .53

declining to become minor

NOTE: Based on a 10-state system, 100 iterations of 300 rounds each. Probabilities refer to chances of change in power status after one iteration. A major power is defined as having 80% of the capabilities of the leading power.

most neutral in terms of its effects on security and survival rates discussed above. We used the same initial conditions for major and minor powers as above and varied the probability of building capabilities versus allocation for one state.

As shown in Table 3, extraction and allocation strategies have important effects for the individual state and the system as a whole. A hawkish strategy does very well for major and minor powers in producing security. Both receive significant gains in security and capabilities, to the point where the major power hawk becomes a hegemon, and the minor power hawk becomes a major power. These changes to the system (from tripolar to unipolar and 4-polar) partly account for the effects on other states. Hawks gain security, but at the cost of a severe depletion of societal resources. Further, other states in both systems also register impressive gains in both international and domestic security, and, in the hegemonic case, they do even better than the hawk in domestic security. Also, the other states gain societal resources while the hawk is losing them.

This process conforms extraordinarily well to conventional theories of hegemonic decline. The simulation shows that hegemons provide a stable international environment on which others can free ride; yet the extraction costs of producing such security eventually drain the hegemon while the free riders are building societal resources. Eventually, the hegemon may decline in security and capabilities relative to other, challenger states.

Hawkish, extractive strategies also have the effect of causing other states in the system to respond by building capabilities, creating a system with higher overall capabilities than the baseline case (+135% in the major hawk system, +46% in the minor hawk system). This result conforms to classic descriptions of the security dilemma and balancing strategies, and also fits Maoz's (1990, chap. 8) elegant discussion of the paradox of gaining extra power and how it can hurt a state. Systems with doves, on the contrary, have a lower absolute level of defense capabilities in the system (-17% in the major dove system, -18% in the minor dove system). Allocative

Simon, Starr/TWO-LEVEL SECURITY MANAGEMENT 289

TABLE 3

Security in Systems with One Hawk or One Dove State

C/R Change S/T Change SOC Change

Baseline changesa Major power 1.8 14.7 107.7 Minor power 1.7 14.7 52.9

Systems with one hawkb

Major power hawk 9.9 7.0 -65.6 (-161%) Other major 3.3 11.2 2.2 (2%) Minor power 1.8 15.7 0.2 (0.02%)

Minor power hawk 3.8 6.7 -85.8 (-162%) Major power 1.0 2.3 2.9 (3%) Other minor 0.4 3.5 2.8 (5.3%)

Systems with one dovec

Major power dove -5.5 -2.6 1,032 (958%) Other major 0.9 0.2 0.4 (0.3%) Minor power 0.4 0.5 0.4 (0.07%)

Minor power dove -1.8 -9.4 501.2 (947%) Major power 0.9 -0.1 0.8 (0.7%) Other minor power 0.2 -0.3 0.8 (1.5%)

NOTE: C/R = international security; S/T = domestic security; SOC = societal resources. a. All changes in security levels represent difference from baseline average security changes in a tripolar 10-state system over 300 rounds. In the baseline case, all states extract in 50% of rounds. b. Hawkish state has a 90% probability of resources being used to build capabilities. c. Dovish state has a 10% likelihood of extraction being used to build capabilities.

strategies produce less resources for others to extract, making it less necessary and more difficult for other states to build capabilities by extracting from the dove. Much of this is illustrated by Jordanian foreign policy, 1963-70 (see Friedman 1993).

COMBINATION HAWK/DOVE STRATEGY

From Table 3 and from results in other simulation runs (Simon, Starr, and McGinnis 1994) we found that whereas dovish strategies perform more poorly than hawkish ones in terms of security gains, they tended to work better against domestic opponents than international ones, especially for major powers.15 More significantly, although security

15. This may be partly due to the limitation on the number of rebel groups (two) compared to the number of international opponents (nine) each state faces. Each domestic allocation buys off half (1/2) of the domestic opponents, whereas an international allocation buys off only 1/9 of the threatening states. Even so, as argued in note 11, this limitation is empirically grounded and would hold as long as a state faced fewer domestic threats than international ones. Furthermore, in experimenting with more than 2 rebel groups, it is apparent that the stronger constraint on rebel growth is not the number of groups but the fact that rebels can grow stronger only if the state extracts; whereas in the international context, other states can build capabilities even if state i allocates (see also Lichbach 1995; DeNardo 1985).


TABLE 4

Systems with One International Hawk/Domestic Dove State

C/R Change S/T Change SOC Change

System A: One major power is an international hawk/domestic dovea Major power hawk/dove 5.8 31.7 189.0 (175%) Other major 2.6 7.8 0.8 (0.7%) Minor power 0.9 7.6 0.2 (0.3%)

System B: One minor power is an international hawk/domestic dovec Minor power hawk/dove 2.0 23.1 216.0 (409%) Major power -0.2 0.1 -2.6 (-5%) Other minor -0.1 0.4 -0.9 (1.7%)

NOTE: All changes represent differences from baseline values for a 10-state tripolar system. See Table 3 for baseline values for changes in international security (C/R), domestic security (S/T), and societal resources (SOC). a. The hawk/dove state has a 95% probability of building capabilities to address international threats and a 22% probability of building capabilities to address domestic threats. b. The hawk/dove state has a 95% probability of building capabilities to address international threats and a 15% probability of building capabilities to address domestic threats.

levels do not increase, dovish strategies bring a large improvement to the societal resource base (SOC).

Because allocation tends to build societal resources rather than deplete them, it seems desirable that states pursue a combination strategy: build capabilities to address international threats, and allocate to reduce domestic ones.16 Table 4 shows the results of optimal7 levels of extraction and allocation that produce the best effects-security gains in both arenas, plus the flexibility provided by increased levels of societal resources, and lesser gains by one's opponents in the system.

Table 4 presents several patterns. First, the domestic security gains achieved by this combination strategy were impressive for both major and minor powers. They exceed those of the pure hawkish and dovish strategies. Also, international security gains are a significant improvement over the baseline (50% allocation) strategy. These gains occur because the combination strategy provides societal resources that are effective in reducing domestic threats. In addition, the effects of this combination strategy on other actors in the system are negligible compared to the baseline strategy. Other actors do not gain on the hawk/dove state, allowing major powers to maintain survival levels (and minor powers rising levels) similar to the baseline case (Table 5).18

16. The advantages of the combination strategy are illustrated by the behavior of Jordan, as developed in a case study by Friedman (1993). For example, explicitly drawing on the work of Most and Starr (1989) and Starr (1991a, 19991b), Friedman looks at Jordan's decisions to ally with Egypt in 1967 and to cooperate with Israel in 1970 as two-level games, with the Palestinians as Hussein's internal opposition. Realist models of balancing and bandwagoning as provided by Walt (1987), although supported, were shown to be incomplete by themselves, requiring a two-level analysis to explain Jordanian behavior fully.

17. Optimal values for the likelihood of extraction and allocation were calculated by trial and error, and represent optimality only within the constraints of this tripolar system with all of its particular characteristics.

18. Because a major power is defined by the sum of C and S, a definition that ignores the overall level of societal resources, the hawkish strategy appears highly advantageous and the dovish strategy a hindrance for states wishing to rise to major power status. However, a closer view reveals that hawkish strategies make states vulnerable in the long run because they risk using up societal resources (see Table 3).


TABLE 5

Allocation Strategy and Survival Rates

Average % of Iterations Probability That Probability That Size of with Any Minor Power Major Power

H/HHa Polarity Change Polarity Change Rises (other states) Declines (other states)

.5/.5 baselineb -0.9 71 .004 0.3

Major powerc .9/.9 hawk/hawk -2.0 100 .000 .0 (1.0) .1/.1 dove/dove -1.4 100 .004 1.0 (0.7) .95/.22 hawk/dove -1.1 87 .009 .4 (0.4)

Minor power .9/.9 hawk/hawk -1.6 100 1.0 (.0) .9 .1/.1 dove/dove -1.3 83 .0 (.006) .4 .95/.15 hawk/dove -0.9 67 .0 (.006) .3

a. H and HH refer to the state's probability of building external (H) or internal (HH) capabilities in a given round. All other states play the baseline (.5/.5) strategy. b. Baseline system has 3 major powers and 7 minor powers, for a total of 10 states. c. Major powers are states whose capabilities and strength values are within 80% of those of the leading state after each iteration.

The basic conclusions regarding the combination hawk-dove strategy are that states do much better being dovish to their domestic threats and hawkish to their international ones and that allocation in at least one arena is necessary to maintain or increase societal resources that guarantee long-term security from both external and internal threats. These results have significant implications for both hegemonic decline and the

stability of repressive regimes.

* If the hawk/hawk strategy depletes societal resources, then dictatorships may tend to lose viability over time. If a state is extractive both internationally and domestically, it may gain in the short run, but it becomes vulnerable on both fronts due to the strain on societal resources. As Wintrobe's (1990) model noted, it eventually may make economic sense for dictatorships to turn power over to more legitimate, civilian governments that can manage the economy better (and perhaps treat rebels more dovishly); yet, in these cases (e.g., Brazil, Argentina, Chile), the military is often "bought off" by the civilian government by maintaining huge defense budgets. This approach has the dual effect of keeping the military out of domestic affairs and of maintaining an extractive, hawkish international policy-our hawk/dove strategy.

* The disadvantages of the hawk/hawk strategy fit well with conventional explanations about the decline of the Soviet Union, which arguably played such a strategy. The Soviet government faced strong internal and external threats to viability, and it chose a coercive strategy of maintaining a high defense budget and strong standing army to deal with both threats. The simulation indicates that such a strategy will deplete societal resources over the long run, making the state vulnerable to either internal or external threats. Gorbachev's "new thinking" and perestroika show evidence of learning on the part of the Soviet government, but the lack of societal resources prevented this allocative strategy from improving the status quo enough to contain the domestic threat. The United States, on the other hand, mirrors the hawk/dove strategy well, building capabilities for external threats but using an allocative, less coercive domestic strategy. Thus the United States has ample resources to avoid decline.

292 JOURNAL OF CONFLICTRESOLUTION

- 100 12

10 - 80

S/T domestic security - 70 u 3 8 l _ '~ (major power) A 3 U 6 60 0

2 --^^^^Y^^A. t^^^ \^!!y"^^^ ~- 20 <n - 40

(0

2 (iopw)sitre - 20 C/R international security societal resource 10

(minor power) (major power) 0 . I i

(N ) ' tO Wf - .0 0o 0 ) " )n tW O - ) 0 - N0 C ) t (N 0 ( N v - < u 0a ) ) - I- 0n U o N v eo 0

Round Number (Time)

Figure 4: Change in Security over Time: Hegemon and Challenger in a Unipolar System

Changes in the extraction/allocation strategy also appear to generate larger effects on security and survival than changes in system polarity. This result reinforces the findings of Most and Starr (1989, chap. 6), who argued that the dynamics of willingness drive international politics more than the possibilities and constraints provided by the international structure/environment (opportunity). Therefore, hegemonic decline may not be an inexorable event in the international system; it may result from poor strategic choices by the leading state.

To further explicate the process of rise and decline due to allocation strategy, we illustrate the decline of a hegemon in a unipolar system over time in Figure 4. To encourage decline, we have made this hegemon a domestic hawk and have introduced a small penalty for extraction in the form of lower legitimacy.19

The hegemon in Figure 4 begins with C/R near 10, and S/T near 4; although it maintains domestic viability at that level, its lead in C/R over the other 9 states in the system quickly withers. Near round 60, C/R meets S/T, stimulating some recovery measures (recall that a state's decision rule is to minimize the maximum threat). This results in a temporary resurgence of international security; however, in the context of decreasing societal resources, the hegemon simply cannot maintain such high levels of security.

Eventually, C/R and S/T meet again, and by round 400 the hegemon no longer has a lead in security over other states, which by now have experienced significant growth in both capabilities and security ratios as noted in our earlier discussion of polarity. A hegemon need not decline to become an ordinary power as long as it maintains a base

19. The 10-state system used to produce Figure 4 has 1 major power. Parameters are the same as in the appendix, with the following exceptions: for the major power, HH (frequency of extraction for domestic strength) = 90%; G (mobilization/cohesion effect) = .05. This makes the hegemon a domestic hawk that has lower than average legitimacy; thus the hegemon is penalized for its extractive behavior with additional (small) losses in societal resources (SOC) each time it extracts. This added strain on SOC is what drives the hegemon to decline in international security, SOC, and overall capabilities.


of societal resources from which to recover; however, it is quite difficult, in the face of equally viable and growing minor powers in the system, to maintain its early lead in all facets of capabilities, domestic strength, societal resources, and security ratios if the hegemon pursues a hawkish strategy of building capabilities.20 This is consonant with Maoz's (1990) "paradox of power," and the case of Hapsburg decline in the face of constant, multiple challenges portrayed by Kennedy (1988).

Figure 4 graphically portrays the decline of hegemons or dominant powers, as found in a number of models of system change and cycles of system-changing wars. Although complementary to Kennedy's notion of "overstretch," and the idea of differential growth of power as argued by Gilpin (1981) (or rates at which the power differential closes between states, as argued by Doran [1989]), a principal component of such processes is ignored in those (and other) works: the internal game dealing with domestic viability issues. Again, although the unipolarity of this system hindered the hegemon's international security, our results indicate that the main cause of the decline was an overreliance on extraction and a neglect of allocation in both the international and domestic arenas. If hegemons develop a propensity to extract, and do not pursue allocation, the consequence is a depletion of societal resources and vulnerability to decline. This is a much more complex picture than the one Gilpin (1981, 157) provides concerning the rising costs of maintaining the status quo. Our point is that hegemons do not simply maintain the status quo, they make strategic choices regarding extraction and allocation of resources in a two-level context; these choices can drive costs higher or reduce them, producing decline or stability.

CONCLUSION

This article has outlined a theoretical framework for analyzing the impact of two-level security games that states play. Applying the theoretical ideas of Most and Starr (1989), Starr (1994), and Starr and McGinnis (1992), we have constructed a model and have used a computer simulation to examine the factors that affect the security of states in various international systems. The simulation has helped us to verify the internal consistency of the model by demonstrating that its implications are consistent with much theory and research in international relations, especially that which supplements or fills in gaps left by the inadequacies of realism. It has thus allowed us to find some important results concerning the rise and decline of states that are missed by those focusing on either the domestic or international security game in isolation.

Whereas system structure had important effects on international and especially domestic security, we found that the strategic decision of how often to build capabilities versus allocate-or hawkishness and dovishness-was a more important way for states to improve or lessen their security. Also, states that have serious threats to

20. This effect is exacerbated if the hegemon has low legitimacy, because the state is further penalized for its extractive behavior by greater declines in societal resources and stronger rebellions (Simon, Starr, and McGinnis 1994).


viability must, in the absence of generous allies, find ways to increase the growth of societal resources or face decline.

The significant argument that emerges, and that would be all but ignored by realist analyses, is that security and state survival are highly affected by the extraction and allocation decisions made in the context of the two-level security game. Both weak and strong states can survive threats to viability if they can build and maintain a strong societal resource base. Conventional theories of hegemonic decline recognize this connection between resources and security, but they fail to make the connections between internal and external threats to the state that drive great powers either to maintain their position or decline. What we have shown is that although some systemic factors may encourage decline, the choices that states make to address two-level security threats can override those factors and produce either stability or decline. Thus much depends on the skill of government decision makers. This should lead us to consider issues of learning and policy choice as the factors that drive the pattern of

hegemonic rise and decline that has been demonstrated over the past 5 centuries.

APPENDIX Baseline Values for Simulation Parameters

Major Power Parameter Minor Power (where different)

Defense capabilities C = 50 C = 100 Domestic strength S = 50 S = 100 Societal resources SOC = 50 SOC = 100 Interaction opportunity p = 0.07

Willingness of major power to attack w = 0.10 w = 0.08

Willingness of minor power to attack w = 0.07 w = 0.04

Willingness of rebels to intensify r = 0.06

Capabilities ratio (defense capabilities) (calculated in simulation) c = 1 - (Ci/[Ci + Cj])

Capabilities ratio (domestic strength) (calculated in simulation) s = 1 - (Si/[Si + Sk])

Initial rebel group strength S(reb) = 20 S(reb) = 40 Rebel mobilization rate V = 0.02

Probability of extraction for increasing defense capabilities H = 0.5

Probability of extraction for increasing domestic strength HH = 0.5

Scapegoating/legitimacy G = 0.00 (no effect) Frequency of ally extraction E = 0.5 (50% of rounds)


Government i's Relative Perception

Previous Capability of Others' Plays Levels Utility

Subjective Probability

Terms Threat Criterion Levels .Function

Appendix Figure: Summary of Functional Relationships in the Model

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