Value Differentiation, Policy Change, and Cooperation in International Regime Complexes

Tyler Pratt∗ December 3, 2020

Abstract In many important policy areas, interstate cooperation is governed by a dense net- work of separate but overlapping international institutions. Whether this environment of “regime complexity” strengthens or undermines cooperation is a subject of debate. While some argue that overlapping institutions enhance legitimacy and flexibility, oth- ers claim that opportunistic forum shopping will enable states to escape compliance with rigorous rules. This paper reconciles this debate, demonstrating that regime com- plexity has contrasting effects depending on the degree of value differentiation among institutions. In issue areas where undifferentiated institutions function as substitutes, forum shopping will reduce the regime’s ability to discipline state behavior. However, in issue areas where institutions are differentiated by value—i.e., institutions with deeper rules provide greater benefits—institutional overlap can increase policy change among states. I demonstrate these dynamics formally and provide empirical evidence in a comparative analysis of the development finance and election-monitoring regime complexes.

∗Assistant Professor of Political Science at Yale University ([email protected]). I am grateful to Sarah Bush, Christina Davis, Alex Debs, Randall Henning, Kosuke Imai, Amanda Kennard, Robert Keohane, Nico- las Lampach, Melissa Lee, Julia Morse, Abraham Newman, Kelsey Pratt, Charles Roger, Duncan Snidal, Diana Stanescu, and participants at the July 2020 Workshop on International Regime Complexity for com- ments on earlier drafts.

1 1 Introduction

Rapid growth in the number and scope of multilateral institutions since World War II has transformed the structure of global governance in many issue areas. Instead of a single unified regime, states frequently confront a regime complex: a set of international institutions that operate in a common issue area and the (formal and informal) mechanisms that coordinate them (Henning and Pratt, 2020). Regime complexes feature a dense network of institutions that compete for authority over the same issue area. This environment gives rise to strategic behavior by states, who can select among multiple institutions when crafting new rules or seeking judgments about compliance. Recent scholarship has improved our understanding of how regime complexity shapes interstate bargaining (Alter and Meunier, 2009; Jupille, Mattli, and Snidal, 2013; Morse and Keohane, 2014) and influences power relations among states and institutional actors (Drezner, 2009; Lipscy, 2015; Pratt, 2020; Henning, 2017). However, existing work provides inconsistent answers to the most fundamental question raised by the increasing density of institutions: how does institutional overlap affect international cooperation? Many scholars argue that the fragmentation of governance across multiple institutions harms cooperation by fomenting ambiguity, encouraging rule conflict, and undermining compliance (Raustiala and Victor, 2004; Alter and Meunier, 2009; Struett, Nance, and Armstrong, 2013). Others contend that regime complexes facilitate more effective cooperation: they can increase flex- ibility (Keohane and Victor, 2011), boost legitimacy (Kelley, 2009), and engender greater expertise (Lesage and Van de Graaf, 2013) compared to unified regimes. These contradictory findings have driven calls for conditional theories of regime complex- ity that explain variation across issue areas (Henning and Pratt, 2020). This paper con- tributes to this agenda by introducing a key omitted variable—value differentiation—that moderates the effect of regime complexes on state behavior. Put simply, regime complexes that are value-differentiated can impose discipline and extract meaningful policy adjustment from member states. Undifferentiated regime complexes are significantly weaker in generat- ing policy change.

2 The paper seeks to accomplish three tasks. First, I propose a useful criterion for assessing cooperation in regime complexes: depth of policy adjustment by states. Policy adjustment is a practical, clear, and widely applicable measure of regime complex effectiveness. It is consistent with the fundamental goal of international regimes, as articulated by Keohane (1984). It is also applicable across a wide range of issue areas, facilitating comparisons across distinct regime complexes. Second, I develop a theory of overlapping institutions that explains why some regime complexes outperform others in generating depth of policy adjustment. The theory explains how expected policy adjustment shifts when new institutions are layered onto a particular issue area. In some issue areas—particularly those where international institutions offer near-identical benefits to member states—the emergence of a regime complex will decrease depth of policy adjustment. As states gain the ability to forum shop (Busch, 2007; Alter and Meunier, 2009), they will opportunistically empower institutions with weaker standards and thereby reduce the need for policy change. This dynamic has generated concern, for example, about the proliferation of development aid institutions.1 Because states can obtain similar benefits (e.g., grants or loans) from an array of sources, they select into institutions where policy conditions are more lenient. The ability to forum shop provides states with leverage vis-a-vis multilateral institutions, weakening the ability of the latter to demand policy reforms. In other issue areas, however, regime complexity can have the opposite effect. The presence of overlapping institutions will deepen policy adjustment if institutions are value- differentiated: i.e., the benefits they provide increase as institutional rules become more rigorous. One example is election monitoring bodies, where institutions with strict standards send a stronger signal about the quality of an election. In this issue area, states face more complicated tradeoffs when substituting one institution for another. Selecting into a more lenient election observer lowers the conditions a government must meet to have its election

1While this paper examines overlap among multilateral institutions, studies of aid competition and frag- mentation typically analyze both bilateral and multilateral aid flows (Annen and Kosempel, 2009; Steinwand, 2015; Bueno de Mesquita and Smith, 2016; Brazys, Elkink, and Kelly, 2017; Gehring, Michaelowa, Dreher et al., 2017).

3 certified as compliant. But it simultaneously reduces the benefit of compliance: clearing a lowered bar sends a less favorable message to domestic and international audiences. In these value-differentiated regime complexes, some states will forum shop to more rigorous institutions in order to extract a greater benefit. If the degree of differentiation is sufficiently large, a regime complex can actually generate more policy adjustment than a unified regime with a single institution. The paper first describes the sources of value differentiation and then demonstrates its effect on policy adjustment. The degree of value differentiation in a regime complex is determined by the type of incentives international institutions offer states to encourage com- pliance. Institutions that induce compliance via certification (sending public signals about a government’s behavior) and gatekeeping (granting access to reciprocal policy adjustment by other states) tend to feature high levels of value differentiation. In conducting these ac- tivities, more rigorous institutional standards generate greater rewards. On the other hand, institutions that provide members with private benefits (e.g., aid or technical assistance) tend to have lower levels of value differentiation. Most international institutions perform a mix of these activities. The degree of value differentiation in an issue area is determined by the relative importance of each in motivating compliance with institutional rules. To illustrate the effect of value differentiation on state behavior, I develop a simple model of state compliance with international institutions. The model envisions states as consumers in a “market” for institutional rewards. States decide whether to comply with institutional rules by weighing the costs and benefits. Like consumers, a state’s decision depends on the structure of the market. The creation of a regime complex is equivalent to transitioning from a monopolistic market (one international institution) to an oligopoly (multiple institutions). As states gain additional institutional options, their willingness to comply with each body’s rules depends on the relative costs and benefits of compliance. The model predicts significant differences in state behavior depending on the differentiation of international institutions. If institutions in the issue area are undifferentiated, the emergence of a regime complex de- creases policy adjustment by states. If institutions are value-differentiated, however, regime

4 complexes can actually increase policy adjustment. Finally, I test these expectations by comparing the effect of overlapping institutions in the domains of development finance and election monitoring. These regime complexes are similar in many of the dimensions identified by (Henning and Pratt, 2020). Both display moderate levels of informal hierarchy and feature institutions differentiated by regional focus. They differ, however, in the degree of value differentiation. Development finance institutions induce compliance with policy conditions by offering private benefits to borrowing states, which generates lower levels of value differentiation. Election monitoring organizations reward compliance by certifying the administration of an election. Their signaling function creates value differentiation among organizations with different standards. In each issue area, I leverage dynamic changes in the institutional environment to esti- mate how the addition of overlapping institutions shapes national policies. I find support for the theory in a series of large-N statistical tests. Consistent with the model, the layering of overlapping institutions is associated with deeper policy adjustment in the election mon- itoring regime complex. In the development finance regime complex, however, institutional overlap has no discernible effect on policy adjustment.

2 Cooperation in International Regime Complexes

Much of the existing scholarship on international regime complexity emphasizes the chal- lenges that overlapping institutions create for effective cooperation. Scholars typically high- light the inefficient duplication and coordination problems that arise when multiple institu- tions share jurisdiction.2 Raustiala and Victor (2004), for example, note the tendency for institutions governing plant genetic resources to adopt competing or contradictory rules.3 Struett, Nance, and Armstrong (2013) finds similar conflict in the maritime piracy regime

2Abbott and colleagues summarize the modal perspective on international regime complexity: “Typically, regime complex theory treats the co-existence of multiple governance actors with overlapping mandates as a pathology (‘overlap’ or ‘fragmentation’) that threatens governance effectiveness through redundancy, inconsistency, and conflict” (Abbott, Genschel, Zangl et al. 2015, 7). 3Raustiala and Victor argue more broadly that “legal conflict among overlapping rules...is a recurring and difficult challenge for regime architects” (2004, 300).

5 complex. Hofmann (2009) and Pratt (2018) argue that regime complexes induce additional inefficiencies due to duplication of effort. Alter and Meunier (2009) note that regime complexity allows states to engage in “cross institutional political strategies” which may undermine the goals of the regime. A com- mon strategy is forum shopping, where states selectively engage with particular institutions that favor their policy preferences (Busch, 2007; Alter and Meunier, 2009). Forum shopping enables regulatory arbitrage as opportunistic states avoid costly rules, empower the weak- est institutions, and encourage a race to the bottom (Pratt, 2018; Riles, 2014; Efrat and Newman, 2016). States may also use one forum to directly challenge the rules or authority of another, a strategy known as regime shifting (Helfer, 2004; Morse and Keohane, 2014). These behaviors have the potential to undermine compliance and increase conflict within a regime complex. Alongside the pessimistic view of institutions, some contend that regime complexity brings distinct advantages over unified regimes. Kelley (2009) argues that the presence of overlapping election monitoring organizations can boost legitimacy of international norms and facilitate action that might otherwise be blocked. Keohane and Victor (2011) assert that the climate change regime complex represents a more flexible and adaptable governance sys- tem than a single, comprehensive institution. Lesage and Van de Graaf (2013) explain how institutional overlap in energy and tax governance has reinforced the comparative advantage of individual institutions like the Organisation for Economic Co-operation and Development (OECD). What accounts for these competing perspectives on cooperation in international regime complexes? One likely explanation is that the effect of overlapping institutions is heteroge- neous. In some issue areas, the introduction of multiple institutions has encouraged conflict and non-compliance. In other domains, regime complexity may result in a more flexible and complementary governance system. Recent scholarship acknowledges the divergent tra- jectories of regime complexes (Orsini, Morin, and Young, 2013; Gehring and Faude, 2014; Abbott, Genschel, Zangl et al., 2015; Pratt, 2018). But this work has largely focused on

6 describing and conceptualizing disparate outcomes, rather than explaining their emergence (Henning and Pratt, 2020). I build on these efforts by demonstrating why the proliferation of institutions damages cooperation in some issue areas and improves it in others. A second factor that has stymied progress on this question is the lack of an agreed upon standard for assessing cooperation. Scholars disagree about the effect of overlapping institu- tions, in part, because of the abundance of different metrics that have been used in empirical examinations. Among the outcomes examined in existing work are the degree of rule con- flict in a regime (Raustiala and Victor, 2004), competition among actors (Struett, Nance, and Armstrong, 2013), level of institutional coordination (Gehring and Faude, 2014; Pratt, 2018), adaptability and flexibility (Keohane and Victor, 2011), and strength of norms (Kel- ley, 2009). The examination of different outcomes makes it difficult to draw inferences about heterogeneous effects of overlapping institutions. The next section proposes one reasonable metric for assessing cooperation in regime complexes that can be applied across issue areas.

3 Depth of Policy Adjustment

I argue that cooperation in overlapping institutions should be assessed based on the depth of policy adjustment that the regime induces in member states. There are at least three reasons to privilege policy adjustment as an outcome of interest in international regime complexes. First, it corresponds closely with Keohane’s definition of intergovernmental cooperation as “a process of policy coordination.”4 International institutions are designed, in part, to help states achieve gains through mutual policy adjustment. Their success in facilitating policy adjustment is a natural measure of their efficacy. Second, policy adjustment is widely used in the literature on international cooperation to judge the effectiveness of individual international institutions. Scholars routinely attempt

4In Keohane’s words, “intergovernmental cooperation takes place when the policies actually followed by one government are regarded by its partners as facilitating realization of their own objectives, as the result of a process of policy coordination” (1984, 51-52).

7 to estimate the change in state behavior caused by participation in particular institutions.5 This treatment effect is difficult to identify, given the strategic behavior of states and non- random assignment of institutional membership.6 The fact that scholars persist in the face of these identification challenges attests to the importance of policy adjustment as a primary criterion for judging cooperation in international institutions. Third, depth of policy adjustment is a broadly applicable measure that can be used to assess cooperation in almost all issue areas. While institutions in different issue areas are designed to resolve distinct cooperation problems (Martin, 1992; Koremenos, Lipson, and Snidal, 2001), the underlying goal is to shift state behavior in pursuit of a mutually beneficial outcome. An important question for analysts of regime complexity is whether—and under what circumstances—overlapping institutions support or impede this goal. I define depth of policy adjustment as the total change in states’ national policies induced by a set of international institutions in a particular issue area. In other words, it is the causal effect of an international regime (consisting of one or more international institutions) on state policies. To formalize this quantity, we can envision state policy in an issue area as existing on a continuum from shallow to deep (e.g., from a fully protectionist to completely liberal trade posture). Depth of policy adjustment among N states is then defined as:

N X DPA = E[Policyi|Regime] − E[Policyi|No Regime] i=1

Depth of policy adjustment in the trade regime, for example, can be calculated by aggregating the change in all national tariff levels caused by the World Trade Organization, PTAs, and other trade institutions. The counterfactual is a world with no multilateral trade regime. This definition is similar to the concept of “depth of cooperation,” defined by Downs, Rocke, and Barsoom (1996) as the “extent to which [a treaty] requires states to depart from what they would have done in its absence” (p. 383). The primary difference is that Downs,

5For examples, see Simmons (2000); Rose (2004); Gowa and Kim (2005); Goldstein, Rivers, and Tomz (2007); Young (1999); Breitmeier, Underdal, and Young (2011); Russett and Oneal (2001); Boehmer, Gartzke, and Nordstrom (2004); Hafner-Burton and Montgomery (2006); Johnston (2001); Bearce and Bondanella (2007). 6See Downs, Rocke, and Barsoom (1996); Von Stein (2005); Davis and Pratt (2020).

8 Rocke, and Barsoom focus on the degree of policy adjustment required to be compliant with an institution or treaty, while I emphasize realized policy adjustment. This distinction is important in the context of regime complexity, because the presence of multiple institutions is likely to be systematically related to states’ propensity to comply with particular institutions. As a result, we need to know not only what policy adjustments are required by international institutions, but whether states choose to comply with or ignore those requirements. Depth of policy adjustment is a useful concept because it facilitates analysis of how cooperation changes as international institutions proliferate. It refines the general ques- tion posed by students of regime complexity—are overlapping institutions good or bad for cooperation?—to a more tractable form: does regime complexity increase or decrease depth of policy adjustment, compared to a unified regime? Before turning to this question in sec- tion 5, the next section introduces the concept of value differentiation and its application to international regime complexes.

4 Value-Differentiated Institutions

The concept of product differentiation was developed by scholars of industrial organization to relax the assumption that firms in a given market produce homogeneous products. When products are homogeneous, consumers shop solely on the basis of price. If the market is com- petitive, firms are forced to lower their prices to marginal cost to avoid losing market share. The ability of consumers to select among multiple producers disciplines the behavior of firms, rendering them incapable of extracting excess profit from consumers. Those concerned about the effect of regime complexity worry that the same dynamic constrains the power of inter- national institutions. When states can forum shop among multiple institutions, institutions lose the ability to extract policy concessions from states.7 As Abbott notes, “such forum shopping can create harmful competitive incentives: schemes may compete for adherents by weakening their standards, fueling a ‘race to the bottom”’ (2012, 582). Of course, products are rarely perfectly homogeneous. Firms differentiate products, often

7Lipscy (2017) calls this phenomenon “policy area discipline.”

9 with the express purpose of limiting price competition. In a differentiated market, consumers must compare goods of heterogeneous value; they are no longer willing to substitute one product for another solely on the basis of price. This reduces the competitive pressure on firms to price their products at marginal cost. The main argument of this paper is that international institutions, like products, some- times provide differentiated value to member states. Scholarship on forum shopping often assumes an environment akin to an undifferentiated market, where states freely substitute one institution for another. In many cases, however, institutions are imperfect substitutes. Differentiation allows international institutions to mitigate the competitive pressures that would otherwise weaken their power. As a result, differentiated regime complexes are able to demand more policy adjustment from states than undifferentiated complexes. I focus on a particular type of differentiation in regime complexes in which the benefits of compliance with an institution are correlated with the rigor of its rules—a pattern I call value differentiation.8 To be value-differentiated, a set of international institutions must have two properties. First, the institutions must vary in the policy demands they place on member states. Trade institutions, for example, vary in the degree of liberalization that they call on states to undertake. Second, these differences in rigor must translate into disparate benefits for states. In the trade example, deeper agreements offer members a greater reward in the form of access to other member states’ markets. As a result, trade institutions feature relatively high levels of value differentiation. Defense pacts are another example of value-differentiated institutions. Like trade agree- ments, these institutions offer member states a reward (the promise of military support) in return for a set of policy demands (e.g., maintaining a certain level of military spending). Defense pacts may differ in the severity of obligations they place on potential members, gen- erating disparate membership “costs” across institutions. The benefits of membership also

8Economists often distinguish between horizontal and vertical product differentiation. Horizontal differ- entiation occurs when variation in subjective consumer preferences generates different evaluations of products (e.g., Pepsi vs. Coca-Cola). Vertical differentiation occurs when all consumers share an ordered preference ranking of products (e.g., Kia vs. BMW). Value differentiation is a type of vertical differentiation among international institutions.

10 vary, and they do so in ways that are inextricably linked to costs. Deeper defense pacts— those that demand more in terms of state commitment and military readiness—provide a greater reward in terms of military protection. There is an inherent relationship between the value of the institution and the depth of its rules. Value differentiation is one of many ways in which relevant distinctions can emerge among overlapping institutions in a regime complex. Henning and Pratt (2020), for example, note the potential for functional and geographic specialization among institutions in a regime complex. Trade agreements and defense pacts are differentiated by breadth of membership as well as depth of rules. I emphasize value differentiation for two reasons. First, as I argue in the next section, it is a recurring feature of global governance in many issue areas. Second and more importantly, it has significant implications for institutional competition and policy adjustment in regime complexes.

4.1 The Origins of Value Differentiation

Value differentiation is usefully conceptualized as a continuum, ranging from perfectly sub- stitutable to completely value-differentiated institutions. A regime complex’s placement on the continuum is determined by the type of benefits institutions offer states to incentivize compliance. Because the structure of institutional benefits differs across issue areas, we can generate expectations about the degree of value differentiation in different policy domains. Without a supranational executive to enforce compliance with international commit- ments, institutions must rely on inducements to encourage states to abide by their rules. These inducements vary widely in character and magnitude. I divide them into three broad categories of common institutional reward structures: private goods, gatekeeping, and certi- fication. Institutions that provide private goods incentivize compliance via the transfer of exclud- able, material rewards. Multilateral development banks, which provide developing countries with loans or grants in exchange for policy concessions, are a clear example. Issue areas in which institutions offer aid, technical assistance, or access to technology to member states

11 in good standing also rely on inducement via private goods. These institutions exhibit low levels of value differentiation. Private goods are more homogeneous, and their value does not change as institutional rules become more stringent. As a result, states will more readily substitute one institution for another. Institutions that engage in gatekeeping reward compliance by granting access to recipro- cal policy adjustment by other states. Trade agreements often embody this reward structure: members that comply with the rules of a PTA gain access to export markets in other member states. In gatekeeping institutions, more rigorous rules offer greater benefits. This relation- ship holds because the primary benefit of compliance, from a member state’s perspective, is obtaining reciprocal policy adjustment by others. More stringent rules increase the level of policy adjustment demanded of all members, thereby increasing the rewards of membership. As a result, institutions that use gatekeeping exhibit high levels of value differentiation. Finally, institutions that engage in certification reward compliance by sending positive signals about a government’s behavior. These institutions rely on reputational mechanisms to sustain compliance. Certification provides value by credibly signaling that a state has fulfilled an obligation or met a set of criteria. The more rigorous the criteria, the stronger the value of the signal, as the election monitoring example illustrates. Other examples include human rights bodies and institutions that engage in “scorecard diplomacy” (Kelley, 2017) to reveal information about states’ domestic policies. Certification institutions feature high levels of value differentiation. Many international institutions perform a mix of these activities, though the relative importance of each will vary by issue area. Different issue areas represent distinct strate- gic settings in which states seek to cooperate (Martin, 1992). The cooperation problem that characterizes each issue area necessitates a specific institutional design (Koremenos, Lipson, and Snidal, 2001). As a result, the basic operation of international institutions – and thus the potential for value differentiation – are largely determined by the issue area in which the institutions operate. If international institutions in a given policy domain rely primarily on gatekeeping or certification to encourage compliance, they are likely to be value-

12 Multilateral Development Defense Election Banks Non-proliferation Pacts Trade Monitoring

0 1

Figure 1: Continuum of Value Differentiation: Five issue areas are plotted on a contin- uum of value differentiation, ranging from 0 (no value differentiation) to 1 (complete value differentiated). differentiated. If, instead, they primarily distribute material rewards like aid or technical capacity, they will reside toward the undifferentiated end of the continuum. Figure 1 uses these criteria to situate several empirical regime complexes on the contin- uum of value differentiation. Multilateral development banks lie on the low end, since they rely primarily on private goods to sustain compliance with loan conditions. States seeking funds for development projects can approach an array of development banks. In return for loan programs, development banks often require states to make policy reforms and uphold economic, environmental, and social standards. While the severity of these conditions varies across development banks, the private benefit of compliance—i.e., the funds a state receives after fulfilling the conditions—do not change in value as conditions become more rigorous. A $20 million loan finances the same project whether it comes from the International Bank for Reconstruction and Development (IBRD), Inter-American Development Bank, or the Andean Development Corporation Development banks are not completely lacking in value differentiation, however, because institutions may also serve a secondary certification role. Loans from high profile institutions like the IBRD, for example, may send a broader signal about a government’s commitment to reform and the country’s future economic performance. Non-proliferation institutions exhibit low-to-moderate value differentiation. A major function of these institutions is to certify that states are not developing nuclear weapons programs. They do so via intrusive monitoring procedures, which are often codified in bi-

13 lateral safeguards agreements between states and the International Atomic Energy Agency (IAEA). As in all certification regimes, more stringent rules (e.g., IAEA “Additional Proto- col” agreements) have the potential to send stronger signals about the government’s behav- ior. However, the non-proliferation regime also relies heavily on private goods to encourage compliance. The Treaty on the Non-Proliferation of Nuclear Weapons (NPT) encourages the sharing of peaceful nuclear energy technology with NPT-compliant non-nuclear weapons states. This private benefit is independent of the stringency of NPT rules, reducing the degree of value differentiation in the regime. Trade and defense pacts are primarily gatekeeping institutions, allowing member states in good standing to gain access to favorable policy adjustment by others. Deeper trade agreements provide member states with greater market access, creating the potential for value differentiation. Similarly, more demanding defense pacts enhance the collective strength of the alliance and thus offer greater military protection to each member state. These regimes are located toward the higher end of the value differentiation continuum. Finally, election monitoring bodies are classic certification institutions, approximating the ideal type of highly value-differentiated institutions. These institutions function by certifying the legitimacy of domestic elections. The primary benefit they provide is a signal to domestic and international actors that an election was conducted in accordance with national and international standards. Election monitoring institutions with high standards for compliance, such as the Organization for Security and Cooperation in Europe (OSCE), can provide a stronger signal than institutions with weaker standards, like the Southern African Development Community (SADC). The value of complying with OSCE election standards should therefore be greater than the SADC, making the regime complex value- differentiated.9 Figure 1 characterizes the level of value differentiation in each regime complex, but no-

9See Kelley (2012) for evidence that election monitoring institutions often employ different standards when assessing and certifying elections. Rational parties will take these differing standards into account when updating beliefs about the legitimacy of electoral processes. Bush and Prather (2018) find evidence that election observers may also be horizontally differentiated, since some citizens perceive geographically proximate institutions to be more capable and unbiased.

14 tably does not reflect other types of differentiation that may occur. Both election monitors and multilateral development banks, for example, tend to be differentiated based on geo- graphic region. Institutions may also specialize by topical focus (e.g., development banks’ relative focus on infrastructure vs. public health). These are important dimensions that lie beyond the scope of the present analysis. The next section turns to a formal examination of the effect of value differentiation on policy adjustment in regime complexes.

5 Forum Shopping and Depth of Policy Adjustment

To illustrate the effect of value differentiation, I construct a simple model of states adjusting their national policies in response to an international regime. The model draws an anal- ogy between states navigating a regime complex and consumers in economic markets. Each setting features strategic actors making cost/benefit tradeoffs as they choose among a set of potentially differentiated goods. Like consumers, states must decide whether to “pur- chase” the benefits associated with an international institution by moving their policies into compliance. The model envisions a voluntary reward-for-policy exchange between states and inter- national institutions. Institutions make a set of policy demands from states. They offer a reward to states that choose to comply and withhold it from those that do not.10 In this basic environment, the model examines how regime complexity shapes policy adjustment by predicting how state behavior shifts in response to overlapping institutions. In unified regimes with a single institution, states face a single monopoly “producer.” They choose whether to adjust their national policies to gain the benefits of compliance with a single institution. In regime complexes, states gain the ability to forum shop among multiple in- stitutions. As I demonstrate below, the consequences of this environment depend on the degree of value differentiation among the institutions.

10This simple setup is generalizable to a large class of international institutions that motivate compliance by providing excludable benefits. It excludes one notable class of international regimes: institutions that facilitate public goods provision. In that case, the reward for compliance is non-excludeable and states generally cannot be incentivized to comply.

15 The model is built on three simplifying assumptions. First, I assume that each state has an ideal policy level that it would adopt in the absence of an international regime. Depending on the regime, the ideal policy could represent a state’s preferred tariff level (trade), the quantity of strategic weapons it produces (non-proliferation), or the fairness of its elections (election monitoring). These preferred policy levels are distributed along a spectrum from 0 (lowest possible level) to 1 (highest level) according to a continuous density function, f(). This assumption does not suppose that international institutions only regulate a single issue; most do not. Instead, it simplifies the analysis by decomposing states’ multifaceted interests into a series of specific preferences over individual policy domains. Second, international institutions determine compliance by setting a standard, or floor, for states’ national policies. States with policies above this standard are deemed compliant with the institution and may receive associated benefits. States with policies below this level are non-compliant and gain no reward from the institution. Empirically, there are a wide range of benefits states derive from compliance with international institutions. These include direct rewards, such as financial aid, technical assistance, or market access, as well as more diffuse benefits associated with a state’s reputation. Avoiding penalties imposed on non-compliant states can also be viewed as a benefit of compliance. Third, states find it costly to adjust their national policies away from their ideal levels. In the model, states internalize the costs of policy adjustment, and these costs are increasing in the size of the adjustment. For example, a state that prefers high tariffs finds it more costly to comply with WTO rules than a state that generally favors low tariffs. These three assumptions allow us to analyze state behavior in a range of institutionalized environments. I first consider a scenario where state policies are regulated by a single international institution, and then examine how depth of policy adjustment shifts as states are subject to overlapping institutions of different types.

16 5.1 Unified Regime

In the unified regime scenario, states confront a solitary international institution with an exogenously determined standard for compliance, s. States obtain a reward (α + θ) if they comply with the institution by adopting a policy level ≥ s.11 This reward represents the benefits of compliance with the international institution, as well as the avoidance of non- compliance penalties.

Each state begins with an ideal policy level, pi, and must decide whether to adjust their policies to gain the rewards associated with compliance. In this environment, states are akin to consumers in a monopoly market for institutionalized cooperation. They can “purchase” the benefits of compliance by raising their national policy level to the institutional standard. Notably, states pay heterogeneous costs for this benefit since their ideal policy levels are not identical. Some states require no costly policy adjustment because their ideal policy level is already above the institutional standard. Others must raise their policy level to s or fail to gain the benefits of cooperation. Each state’s utility depends on its decision to comply and the size of the required policy adjustment. Formally, state i has the following payoff schedule:

• 0 if the state chooses not to comply with the institution (non-compliance)

• α + θ if the state complies and its ideal policy level is higher than the institutional

standard (pi ≥ s)(compliance with no adjustment)

• (α + θ)−(s − pi) if the state complies and its ideal policy level is lower than the

institutional standard (pi < s)(compliance with adjustment)

Figure 2 provides a visual depiction of the unified regime scenario. The vertical line represents a continuum of potential policy levels, ranging from 0 to 1. States’ ideal policy levels are distributed on this continuum by the density function f(p). States choose whether to adopt a realized policy level high enough to be compliant with a single international

11α + θ can be considered a single quantity in the context of a unified regime. In a regime complex, the α term is constant across institutions, representing the identical benefits of compliance that can be obtained from every institution. The θ term can depend on the standard for compliance (sj) set by institution j.

17 Unified Regime 1

A. Comply with no policy adjustment

IO 1 B. Comply with policy adjustment

C. Fail to comply with no policy adjustment

0

Figure 2: Unified Regime: States arrayed on a continuum of ideal policy levels choose whether to comply with a standard set by a single international institution. institution (IO 1). Each state makes this choice via a simple cost-benefit calculation. If the benefits of compliance are greater than the costs of policy adjustment, states comply with the institution; otherwise they do not. This process sorts states into three categories. One set of states has ideal policy levels that are above the compliance threshold. These states (set A in Figure 1) do not adjust their national policy but are nonetheless compliant with the institution. A second set of states (B) has ideal policy levels that are below the compliance threshold, but close enough that the costs of policy adjustment are lower than the benefits of compliance. These states choose to move their policies into compliance. Finally, the third set (C) deems the costs of policy adjustment to be too high, and chooses to be noncompliant with no policy adjustment. The figure highlights the difference between depth of policy adjustment and another po- tential measure of cooperation, the rate of compliance with the regime. Sets A and B are both compliant, since their policies meet the minimum institutional standard (s1). But the regime only induces policy adjustment among states in set B. The latter is a more mean- ingful measure of regime effectiveness because compliance rates can be trivially increased by lowering the standard for compliance (Downs, Rocke, and Barsoom, 1996).

18 5.2 Overlapping Institutions

How is cooperation affected once we introduce multiple institutions? To answer this question, consider an environment where two new institutions are added to the issue area.12 For illustrative purposes, suppose one of the new bodies (IO 2) sets a compliance threshold higher than the existing institution, while the other (IO 3) has a lower standard for compliance. I further assume all states are at least potential members of all three institutions.13 We can now examine how policy adjustment changes as states gain the ability to forum shop. Forum shopping occurs when “actors select their international venues based on where they are best able to promote specific policy preferences, with the goal of eliciting a deci- sion that favors their interests” (Alter and Meunier, 2009, 16). The ability to forum shop is a defining feature of regime complexity, where institutions make overlapping authority claims.14 This environment provides discretion for actors to opportunistically select which claim they recognize and thus which institution should have jurisdiction over their behavior. The model incorporates forum shopping by allowing states to choose among multiple institutions when seeking compliance rewards. For example, a state confronting an array of election monitoring organizations can select which body will be invited to judge the quality of a domestic election.15 Similarly, states that are party to multiple human rights institu- tions can selectively recognize the jurisdiction of one institution in specific circumstances.16 This does not entail an assumption that each institution enjoys equal legitimacy or legal status. Indeed, the potential for differentiation among institutions is the key independent variable that shapes depth of policy adjustment in international regime complexes. How-

12Results are consistent with any number of additional institutions. 13In other words, I examine policy adjustment among those states that are subject to multiple, overlapping institutions. Those that are members of only one institution will behave as discussed in the previous section. 14According to Raustiala and Victor, “the defining characteristic of a regime complex is the existence of multiple, overlapping elemental regimes” (2004, 299). 15In practice, states can and often do invite multiple institutions to monitor an election. Though the model only allows states to choose a single institution, it is consistent with a scenario where states select multiple institution and receive a compliance benefit from the most rigorous (highest standard) institution. 16For example, Morse and Pratt (2018) describe the strategic selection of human rights institutions govern- ing the use of torture by the United States and Kyrgyzstan. In each case, countries made selective claims of compliance with weaker institutions that they claimed should have jurisdiction instead of the more rigorous Convention Against Torture.

19 ever, I do assume that membership in multiple institutions provides states with the ability to make selective claims of compliance with particular institutions, whether they are election monitoring bodies, trade agreements, or development banks. As before, states must adopt a policy level equal to or greater than a particular institu- tional standard in order to obtain the benefits of compliance with that institution. If a state adopts a realized policy level that differs from its ideal level, it pays a cost commensurate with the size of the policy adjustment.

5.2.1 Undifferentiated Regime Complex

I first consider the case where institutions provide undifferentiated benefits to compliant states. Each institution offers an identical benefit, α + θ, to states that are compliant with an institution. This makes institutions equivalent to homogeneous goods from the perspective of states: they choose among institutions only on the basis of their relative cost, represented here by the degree of policy adjustment required to comply with each institution. Development finance institutions are close to the ideal type of undifferentiated institutions, since states can obtain similar loan programs from institutions with varying standards. Figure 3 shows how states choose to adjust their national policies in the undifferentiated regime complex scenario (right panel). As before, states are arranged according to their ideal policy levels, from 0 to 1. States select among the original institution (IO 1), as well as an institution with deeper (IO 2) and shallower (IO 3) standards for compliance. The unified regime is reproduced (left panel) to demonstrate how cooperation shifts once new institutions are present. State behavior in this regime complex reflects regulatory arbitrage, as states forum shop to institutions with weaker compliance standards. The only states willing to comply with IO 1 and IO 2 are those with ideal policy levels that are already above the standards set by these institutions. Those with lower ideal policy levels can obtain a higher utility by forum shopping to the weakest institution. As a result, the ability of IO 1 and IO 2 to induce policy adjustment among states has been nullified by the presence of IO 3.

20 Unified Regime Regime Complex, Undifferentiated

1 1 Comply with no policy adjustment IO 2 A. Comply with no policy adjustment Comply with no policy adjustment

IO 1 IO 1 B. Comply with Comply with no policy adjustment policy adjustment

IO 3 C. Fail to comply with Comply with no policy adjustment policy adjustment Fail to comply with 0 0 no policy adjustment

Figure 3: Regime Complex with Undifferentiated Institutions: States arrayed on a continuum of ideal policy levels choose whether to comply with a standard set by a single international institution (left panel) or a set of undifferentiated institutions (right panel).

Only IO 3, the institution with the weakest compliance standard, can persuade states to adjust their policies to obtain the benefits of compliance. Depending on the compliance standard set by the weakest institution, there may be a remaining group of non-compliant states who are unwilling to bear the costs of policy adjustment. Compared to a unified regime, the undifferentiated regime complex changes both who adjusts and how much adjustment occurs. States that previously adjusted their national policies to comply with IO 1 will now forum shop to IO 3, obtaining the same benefits at lower cost. They no longer undertake any policy adjustment. In their stead is a set of new states who were previously unwilling to bear the policy adjustment costs of IO 1 but are willing to pay the lower costs of complying with IO 3. This suggests more broadly that in regime complexes with undifferentiated institutions, institutional proliferation will shift policy adjustment toward states with the “weakest” preferences in the policy space.17

17This distributional shift in policy adjustment does not result from coercion from states with the “highest” policy preferences. Instead, it stems from the new opportunity for cooperation provided to states with preferences for lower policy levels. These states now face a low-standard institution that offers them a compliance benefit without the need for large shifts in national policies. All states — including those that undertake new policy adjustment in the undifferentiated regime complex — are “better off” in terms of their net utility compared to the unified regime.

21 How does depth of policy adjustment in the regime complex compare to a unified regime? In general, the ability to forum shop results in less policy adjustment by member states (Proposition 1). This result is proven formally in the appendix, but the intuition is ap- parent from Figure 2. Policy change in the undifferentiated regime complex only occurs among states with ideal policies below the weakest institutional standard (IO 3). With some minimal assumptions about the distribution of ideal policies, the “best case” scenario for the undifferentiated regime complex is to deliver the same policy adjustment as the unified regime.18 This would occur if, for example, ideal policy levels were continuously distributed and IO 3 set a compliance standard at α + θ or greater. If any IO sets a lower standard, the set of states motivated to adjust their policies will be lower than in the unified regime.

Proposition 1: Depth of Policy Adjustment is weakly lower when moving from a unified regime to an undifferentiated regime complex.

This result means that the proliferation of undifferentiated multilateral institutions can- not increase policy adjustment among states; it can only decrease policy change or leave it unaffected. States’ ability to select among a new range of institutional options motivates a race to the bottom. While institutions may be able to mitigate this problem through coordination, the growing density of institutions creates strong incentives for states to evade rigorous standards via forum shopping.

5.2.2 Value-Differentiated Regime Complex

How does the pattern of policy adjustment shift as institutions offer distinct benefits to states? We now turn to a regime complex with value-differentiated institutions. In these regime complexes, the benefits of compliance are tied to the strictness of institutional stan- dards. To incorporate this feature into the model, I define the rewards associated with compliance to be a function of the institutional standard: α + θ(sj) for institution j. The payoff of compliance now features two distinct terms: a constant term (α) representing

18Specifically, we must assume that the distribution of states’ ideal policies are unimodal and reach their highest density at a policy level ≥ s1. This latter condition will be satisfied if the original institution was designed such that its compliance standard was at the mode of the ideal policy level distribution.

22 Unified Regime Regime Complex, Vertically Differentiated

1 1

IO 2 A. Comply with no Comply with policy adjustment policy adjustment

IO 1 IO 1 Comply with B. Comply with policy adjustment policy adjustment

IO 3 Comply with C. Fail to comply with policy adjustment no policy adjustment Fail to comply with no policy adjustment 0 0

Figure 4: Regime Complex with Value-Differentiated Institutions: States arrayed on a con- tinuum of ideal policy levels choose whether to comply with a standard set by a single international institution (left panel) or a set of institutions with varying benefits (right panel).

similar benefits across institutions, and a variable term (θ(sj)) that captures differentiation among institutions. θ(sj) is increasing in (sj) to reflect the value differentiation discussed above. Figure 4 visualizes state behavior in a value-differentiated regime complex (right panel). Unlike in the undifferentiated context, states do not automatically forum shop to the weakest institution. Because institutions with higher compliance standards (e.g., IO 2) offer a unique level of benefits to states, many states now choose to adjust their national policies to become compliant with this institution. Just as a market with differentiated products can sustain different price levels, the regime complex can sustain policy adjustment across multiple institutions with different standards. The willingness of states to forum shop “upwards” suggests the possibility that more states can be induced to adjust their policies. Unfortunately, comparing expected state behavior in the value-differentiated and undifferentiated regimes is not feasible without an additional assumptions about the distribution of states’ preferred policy levels. If we assume a well-behaved distribution (e.g., pi is distributed uniformly), depth of policy adjustment is

23 always higher in a value-differentiated regime complex (Proposition 2). See the appendix for further details.

Proposition 2: Depth of Policy Adjustment is strictly higher in a value-differentiated regime complex, compared to an undifferentiated regime complex.

Proposition 2 establishes that regime complexes are more effective at driving policy change when institutions are differentiated by value. This leaves unanswered the ques- tion of whether value-differentiated regime complexes can improve upon unified regimes. The transition from a single institution to multiple, differentiated institutions creates two cross-cutting effects. It allows states to forum shop, giving them the ability to secure compli- ance benefits at lower cost. But it simultaneously creates incentives for selection into more rigorous institutions which provide greater rewards. As Proposition 3 states, the layering of new institutions will increase depth of policy adjustment if the new institutions are sufficiently differentiated. Specifically, policy change increases when the difference in compliance payoff from the weakest to the strongest insti- tution is greater than a constant determined by α and θ(s1). Details are provided in the appendix.

Proposition 3: Depth of Policy Adjustment is greater in a value-differentiated regime

complex than in a unified regime, if θ(s3) − θ(s2) > α + θ(s1).

5.3 Discussion

The model provides three important insights into state behavior in the context of overlapping institutions. First, undifferentiated regime complexes tend to generate a race to the bottom, lowering (or leaving unaffected) the depth of policy adjustment achieved by multilateral institutions. In these regime complexes, only the lowest-standard institution can actually motivate states to change their policies. States may claim compliance with high-standard institutions, but only because the policy level they would have adopted in the absence of any regime is sufficiently high to meet institutional standards. Undifferentiated regime

24 complexes are therefore composed of a single, low-standard institution capable of driving policy adjustment and several higher-standard but effectively neutered institutions. Second, value-differentiated regime complexes always outperform their undifferentiated counterparts in motivating policy adjustment. When high-standard institutions can offer benefits that low-standard institutions cannot, some states will “race to the top.” In value- differentiated regime complexes, institutions with various standards can sustain policy ad- justment in states. Finally, the creation of overlapping institutions can increase depth of policy adjustment compared to a unified regime, if the new institutions are sufficiently differentiated. Because states tend to have different ideal policy preferences in any domain, a set of institutions with varied standards can increase policy adjustment as long as the institutions are not viewed as substitutes by states. The model suggests the emergence of regime complexes will generate heterogeneous effects on international cooperation, consistent with the debate in the existing literature. These heterogeneous effects emerge naturally from rational states responding to different strategic environments. Value differentiation among institutions is the key variable that shapes when regime complexity will yield more or less policy adjustment by states. A final question not directly addressed above regards the strategic adaptation of insti- tutions as the dynamics of the model play out. In the undifferentiated regime complex, we observed that many high-standard institutions were rendered incapable of motivating policy adjustment among member states. How do these institutions respond to their new environment? While it is reasonable to think of institutions as fixed in the short term, what happens in the long term as states begin to shift elsewhere? The framework presented here suggests four possible outcomes. First, high-standard institutions may continue to lose “market share” as states flock to lower-standard bodies. Eventually, the high-standard institutions will cease to exist or become “zombie” organiza- tions that fail to make progress towards their mandate (Gray, 2018). Second, institutions may lower their standards in an attempt to regain the engagement of a larger number of

25 states. This is the classic “regulatory race to the bottom” scenario where competitive pres- sures lead to the deterioration of standards. Third, institutions may try to differentiate themselves from their peers. Although most of the potential for value differentiation is set exogenously by the issue area, institutions may have some capacity for strategic differentia- tion. If multilateral institutions can incorporate signaling or gatekeeping as a key component of their activities, they may survive (and even thrive) in the presence of lower-standard in- stitutions. This would allow value differentiation to emerge endogenously from the strategic incentives faced by overlapping institutions. Finally, undifferentiated institutions may try to coordinate rules or standards to prevent opportunistic forum-shopping. Like a cartel of producers engaged in price-fixing, the coordination of standards would allow institutions to keep demanding rigorous policy adjustment from states. Co-financing schemes among development banks and patterns of “institutional deference” among regulatory institutions (Pratt, 2018) are examples of this behavior.

6 Policy Adjustment in Two Regime Complexes

To test the predictions of the model, I compare depth of policy adjustment in two regime complexes, development finance and election monitoring. These issue areas were selected be- cause they approximate the ideal-types of an undifferentiated and value-differentiated regime complex, respectively. The model suggests competing results for states’ policy adjustments across the issue areas. As states confront multiple development finance institutions, they should forum shop to the institution with the weakest compliance standards, reducing their need to change national policies. I therefore expect a null or negative effect of institutional overlap on depth of policy adjustment. The proliferation of election monitoring bodies, on the other hand, should be associated with an increase in policy adjustment by states. Each regime complex is linked to a specific policy domain where states are required to maintain certain standards to qualify for the benefits of institutional cooperation. Within the domain of development finance, I focus on the practice of development policy lending. Development policy loans (also known as structural adjustment loans) are issued by mul-

26 tilateral development banks to facilitate the adoption of policies that promote economic growth in recipient states. The funds provide financial support to member states that are undertaking costly regulatory reforms.19 The interaction between states and development banks operates in a manner consistent with the model: states must commit to a set of macroeconomic and regulatory policies to achieve the desired benefit (financial assistance) from the multilateral institution. States may approach a range of development banks for a development policy loan. These banks have varying standards for compliance, allowing states that have the appropriate standing in multiple institutions to forum shop (Heldt and Schmidtke, 2019). In the domain of election monitoring, states can similarly forum shop among monitoring institutions with varying levels of rigor. Election monitoring institutions operate by sending observer missions into countries to assess the quality of domestic elections. Because election observation missions require the consent of the host government, states can opportunistically choose to invite institutions with low or high standards to observe and certify their national elections.

6.1 Structural Features of the Regime Complexes

Henning and Pratt (2020) argue that regime complexes are usefully classified according to two patterns of institutional interaction: relations of authority and differentiation. Before testing policy adjustment in the election monitoring and development finance regimes, I compare the two regime complexes on these dimensions. The development finance regime complex began with the IBRD (World Bank), which was established in 1944 as the focal institution for multilateral development assistance. In subsequent years, the regime complex became populated with a growing collection of regional and sub-regional development banks (Pratt, 2020). In addition to intergovernmental insti- tutions, private and non-governmental bodies supplement global development efforts with

19The World Bank, the largest multilateral development bank, defines development policy financing as a loan, credit, or guarantee of budget support to governments or a political subdivision for a program of policy and institutional actions to help achieve sustainable, shared growth and poverty reduction. http: //www.worldbank.org/en/projects-operations/products-and-services.

27 sector-specific initiatives.20 There is no formal hierarchy of authority in the development finance regime complex. Institutions are not legally bound by the decisions and standards of the World Bank, for example. But the regime displays some evidence of an informal hierarchy centered on the Bank. Compared to other development finance institutions, the Bank has an elevated status due to its longevity, near-global membership, and financial capacity. Other institutions in the regime complex are generally smaller in size and operational scope. Many are regional or sub-regional multilateral bodies that focus on development in particular geographic regions. Heldt and Schmidtke (2019) argue that the Bank’s informal influence shaped the evolution of the regime complex, encouraging other development banks to adopt similar core governance functions. Henning and Pratt (2020) classify the regime complex as “moderately hierar- chical.” This informal hierarchy does not preclude institutions from developing differences in compliance standards or decision-making procedures, which states leverage for strategic advantage (Lipscy, 2015). The election monitoring regime complex developed later, though its initial evolution has many similarities to the development finance regime. In the late 1980s and early 1990s, the United Nations appeared poised to serve as a focal organization for election monitoring. It supervised and observed a series of landmark elections in Timor-Leste, South Africa, Mozambique, El Salvador and Cambodia. The UN subsequently receded as a participant in election monitoring as preference divergence among member states reduced its scope for action. Dozens of other institutions began to serve as election observers. Many of these were regional IGOs like the Organization for Security and Co-operation in Europe (OSCE), which became the most active institution in the regime complex. Non-governmental actors like the Carter Center, International Republican Institute, and National Democratic Institute are also prominent participants. Election monitoring has no obvious equivalent to the World Bank, though two institutions arguably serve as focal points for different features of the regime. The UN no longer regularly

20For example, Microsoft founder Bill Gates donated seed money for the Global Fund to Fight AIDS, Tuberculosis, and Malaria, a major financing mechanism for health-related development efforts.

28 monitors elections, but maintains a robust role in delivering technical assistance, articulating norms and standards, and generally adding legitimacy to the regime. Operationally, the OSCE is the largest of the election monitoring bodies and helps bring a degree of coherence to the process of electoral observation. The different election monitoring institutions tend to share a set of core functions and design features.21 As in development finance, however, these institutions feature significant variation in compliance standards.22 Both regime complexes feature a reasonably high degree of geographic differentiation. The majority of institutions in both issue areas are regionally defined, though this does not preclude non-regional member participation. Both regime complexes feature less functional differentiation among constituent institutions. Most multilateral development banks are “full service” institutions that implement projects across a wide range of sectors. Similarly, election monitoring bodies typically observe and judge an election holistically rather than focus exclusively on subissues such as gender equality in ballot access. There are exceptions in each regime complex that prove the general rule. In sum, the two regime complexes are broadly similar on many of the theoretical dimen- sions raised by Henning and Pratt (2020). Unlike the development finance regime, however, election monitoring institutions are value-differentiated. The benefits of compliance stem from the signal that an election certification sends to the domestic public and international actors, and this signal will vary in strength depending on the particular monitoring in- stitution. I therefore expect election monitoring institutions to reflect characteristics of a value-differentiated regime complex. States that have access to multiple institutions should experience a greater increase in policy adjustment compared to states that have fewer insti- tutional options. The remainder of this section turns to a test of this proposition.23 There are two significant threats to inference when estimating the effect of regime com-

21For example, each institution conducts election monitoring via structured electoral observation missions, and each must be invited by governments to observe an election. 22Kelley (2012) describes the differences in practice among election monitoring institutions that generate variance in certification behavior. Election monitors disagree frequently and vary significantly in their willingness to highlight problems with an election. 23Because the two issue areas are very different, there is no feasible measurement for national policies that would apply to both regime complexes. As a result, I cannot directly test Proposition 2.

29 plexity on depth of policy adjustment. First, the outcome variable (depth of policy ad- justment) requires knowledge of an unknown counterfactual. It is defined as the change in national policies that arise due to the presence of a regime, compared to what states would have done in the absence of a regime. In both development finance and election monitoring, policy areas in which an international regime has governed state behavior for many decades, it is difficult to approximate what national policies would look like absent any multilateral institution. Fortunately, this problem can be sidestepped by examining how depth of policy adjustment changes as a system shifts from a unified regime to a regime complex. Using the definition of depth of policy adjustment provided in Section 3, the outcome of interest is the following:

N X ∆DPA = {E[Policy Leveli|Regime Complex] − E[Policy Leveli|No Regime] − i=1

(E[Policy Leveli|Unified Regime] − E[Policy Leveli|No Regime])}

N P which simplifies to {E[Policy Leveli|Regime Complex] − E[Policy Leveli|Unified Regime]. i=1 In other words, we do not need to make inferences regarding states’ behavior in the absence of a regime. Instead, we can focus on the difference in states’ policy levels when they face a large set of institutional options compared to fewer options. The second threat to inference is the endogeneity of overlapping institutions. States are strategic actors; they create overlapping institutions to serve political goals. Comparing policy levels among states that are subject to a single institution’s jurisdiction and those that are subject to multiple institutions could produce biased estimates if states consider the effect of institutional proliferation before constructing new governing bodies. I take two steps to mitigate this problem. First, I conduct a difference-in-differences analysis that leverages dynamic shifts in institutional overlap. Specifically, I compare changes in the policy levels of states that remain under the jurisdiction of a fixed number of institutions to those that experience growth in the number of institutions claiming authority to regulate their behavior. This strategy allows for the possibility that states with more institutional options have systematically different policy levels than states that have fewer options. The

30 difference-in-differences approach instead relies on a “parallel trend” assumption: in the absence of the treatment (here, the presence of more overlapping institutions), states would have equivalent changes in their policy levels as in a unified regime. Second, I examine only the subset of weaker states that would find it difficult to create new institutions on their own. These states are “price takers” in the market; the structure of the regime is plausibly exogenous to their political preferences because they have limited ability to shape it.

6.2 Data

For both analyses, the unit of analysis is the state-year. Outcome variables represent state policies in the issue area regulated by the election monitoring and development finance regimes, respectively. In the election monitoring regime complex, I use an annual measure of the quality of states’ domestic elections. In development finance, I use a yearly index of states’ macroeconomic and regulatory policies. In both cases, the primary independent variable is the number of institutions that a particular state can select from in a given year.

Election Monitoring The dependent variable for the election monitoring analysis is the extent to which states hold national elections in a free, fair, and open manner. Data on the quality of elections comes from the “executive recruitment” score in the Polity IV dataset. This variable combines annual measures from the Polity dataset on the regularity, competitiveness, and openness of national elections (Marshall, Gurr, and Jaggers, 2016). It ranges from 1 (16.2% of observa- tions) to 8 (31.6%), with scores increasing in the quality of a state’s elections. The independent variable is the number of election monitoring institutions from which a particular state can select. I use data from Kelley (2012) to identify the set of election monitoring institutions and their dates of operation.24 To translate this data to the state- year level, I count the number of institutions each state could potentially invite to monitor its elections in any given year. The number of “potential observers” ranges from 1 to 11. There is

24Following Kelley, I include both intergovernmental organizations and non-governmental organizations that monitor elections.

31 significant temporal and cross-sectional variation in this variable. Variation across countries occurs due to the different geographic scope of monitoring institutions. Some institutions only monitor the elections of member states (e.g., the OSCE); others are regional (Asian Network for Free Elections) or global (e.g., International Republican Institute) in scope. The entry of new institutions (e.g., the Commonwealth of Independent States in 2001) drives temporal variation. As a result, the number of election monitoring institutions available to Jordan in the year 1986 (1) is different from the number available to India in the same year (2), and is also different than the number available to Jordan in 1989 (4). The data cover the period 1980-2015.25 and include 5,439 state-year observations.

Development Finance The dependent variable for the development finance regime complex is the extent to which states adopt liberal macroeconomic policies. To operationalize this variable, I draw on the Worldwide Governance Indicators (WGI) Project composite measure of “Regulatory Quality” (Kaufmann, Kraay, and Mastruzzi, 2011). The WGI Regulatory Quality index assesses the ability of states’ economic and regulatory policies to promote private sector development. It assigns each state a score based on its trade posture, monetary policy, and regulatory environment. Regulatory Quality scores range from -2.65 to 2.26; higher scores indicate a more liberal macroeconomic policy stance. The WGI data is available for most states in the system but only for the years 1996, 1998, 2000, and 2002-2015. The independent variable is the number of multilateral development banks a state is a member of in a given year. States must be a member of a development bank in order to seek a development policy loan. Because such loans are only available to developing countries, I exclude states in the top 50% of global GDP per capita each year. Among the remaining states, there is significant variation in membership patterns across development finance institutions. I use the COW IGO dataset to code states’ memberships in multilateral development banks (Pevehouse, Nordstrom, and Warnke, 2004). In the sample, the number

25I begin in 1980 because it is the first year a multilateral institution (the Commonwealth Secretariat) sends an election observation mission, according to the Kelley (2012) data.

32 of potential development banks available to states ranges from 0 (0.5% of obserations) to 8 (0.07%). The variable increases over time as states join new development banks (e.g., Armenia’s set of available banks grows from 2 in 1996 to 4 in 2009, after joining the Asian Development Bank and the Eurasian Development Bank). The dataset includes 1,428 state- year observations.

6.3 Results

To estimate the effect of overlapping memberships on states’ national policies, I use a difference-in-differences design. The treatment variable represents the introduction of a new overlapping institution in the issue area. Control observations are those which did not experience an increase in the number of available institutions from which they can select. Importantly, this approach does not require treated and control observations to have similar levels of national policies. Instead, it assumes that without the introduction of a new insti- tution, treated and control states would have similar trends in their national policies over time. If this assumption is correct, any observed differences in these trends can be attributed to the onset of new overlapping institutions. To minimize systematic differences between treated and control units, I employ the matching approach proposed by Imai, Kim, and Wang (2018). For each treated observa- tion (i.e., each observation in which a state gains an additional institutional option in the issue area), I identify a matched set of control observations that are not treated but have an identical treatment history over the past three years. I refine this matched set by selecting only the control observations that have similar covariate values to the treated observation.26 Treated observations that have an empty matched set are removed from the dataset.27 This

26I calculate the Mahalanobis distance measure between the treated observation and all control observa- tions in the matched set, using information on states’ economic power (GDP) and income (GDP per capita). I keep only those control observations that have a Mahalanobis distance of less than three from the treated 1 observation. Control observations for treated unit i are assigned a weight of with Mi denoting the number Mi of matched observations. 27The selection of matched control observations and the elimination of treated observations with no matched control set reduces the sample significantly in both the election monitoring and development finance analyses. There are 1,901 remaining state-year observations in the election monitoring sample and 796 in the development finance sample.

33 process is performed separately for the two issue areas, yielding a set of treated and control variables that have very similar pre-treatment trajectories. Figure 5 displays the trend in national election quality among treated and control states in the election monitoring regime complex. The blue points show the average “executive recruitment” score of the states that gained at least one new overlapping institution in a given year. The red points show the same quantity for states that do not gain a new potential election monitoring institution. In the years prior to the introduction of the new institution, both groups feature an upward trend in election quality. Once the new institution is present, however, the treated group experiences a noticeable increase in election quality while the control group trend remains flat. This is evidence that the introduction of overlapping election monitoring institutions increases policy depth among states. Contrast this result with Figure 6, showing the same relationship for the development finance regime complex. In the years prior to the introduction of a new multilateral develop- ment bank, both treated and control observations are experiencing a flat trend in regulatory quality. Once the new bank is introduced, the trend for both groups is largely unaffected. If anything, the control group begins a slight upward trend in regulatory quality, suggesting the availability of an additional institution for treated units may have slightly depressed their regulatory quality scores in subsequent years. This is consistent with a negative or null effect of new development banks on states’ macroeconomic policies. Table 1 presents estimates of the difference-in-differences analysis for the election moni- toring and development finance samples.28 All standard errors are clustered at the country level. Column 1 shows results for a baseline model in the election monitoring regime com- plex. The positive and statistically significant coefficient of NEW INSTITUTION indicates that states that experienced the introduction of overlapping election monitoring institutions ad- justed the quality of their elections in a positive direction. These results are substantively identical when GDP and GDP per capita are added as control variables (Column 2).

28The models use weighted least squares with unit and time fixed effects, as recommended by Imai, Kim, and Wang (2018). Weights are shaped by how often the observation appears in the matched set of a treated unit. See Imai, Kim, and Wang (2018, 16) for the specific weighting scheme.

34 6.0 ● control ● treatment

5.8 ● ● 5.6

● 5.4 ●

● 5.2

● ●

5.0 ● ● Executive Recruitment Score Executive ● ● ● ●

4.8 ● 4.6

−3 −2 −1 0 1 2 3

Years to New Institution Figure 5: Election Monitoring Regime Complex: Points represent means for every time period from t=-3 to t=3 years from the introduction of a new institution. Treated units, defined as states that gained a new election monitor, are shown in blue. Controls, defined as states experienced no growth in institutions, are red.

● control 0.1 ● treatment

● ● ● 0.0 ● ● ● ● −0.1 −0.2 −0.3 Regulatory Quality Index ●

−0.4 ● ● ● ● ● ● −0.5

−3 −2 −1 0 1 2 3

Years to New Institution Figure 6: Development Finance Regime Complex: Points represent means for every time period from t=-3 to t=3 years from the introduction of a new institution. Treated units, defined as states that gained a potential new development bank, are shown in blue. Controls, defined as states experienced no growth in institutions, are red.

35 TABLE 1: Effect of Institutional Overlap on Depth of Policy Adjustment

(1) (2) (3) (4) Election Election Development Development Monitoring Monitoring Finance Finance NEW INSTITUTION 0.244∗∗ 0.251∗∗ 0.039 0.042 (0.107) (0.105) (0.028) (0.026)

GDP 0.050 0.110 (0.467) (0.104)

GDP PER CAPITA −0.264 2.207∗∗∗ (0.513) (0.589)

Observations 1,901 1,901 796 796 Notes: Results of difference-in-difference models estimating the effect of overlapping insti- tutions on depth of policy adjustment. Coefficient estimates are displayed with standard errors in parentheses. ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.01.

In contrast, the creation of overlapping institutions has no effect on policy adjustment in the development finance regime complex (Columns 3-4). Not only is the coefficient of NEW INSTITUTION statistically insignificant in these models, it is substantively close to zero. The presence of overlapping development banks appears to have little bearing on states’ regulatory and macroeconomic policies. To compare the estimated substantive effect size of a new institution in the two regime complexes, I standardized the treatment and outcome variables and re-estimated models 2 and 4. This allows us to gauge the effect of a one-standard deviation increase in the treatment variable on states’ national policies in each issue area. The results underscore the large difference in the estimated magnitude of the effect across the election monitoring and development finance domains. A one standard deviation increase in institutional options in the election monitoring regime complex is associated with a 0.07 standard deviation increase in national election quality. The analogous effect in the development finance regime complex

36 is only 0.01, seven times smaller. These results are consistent with the contrasting effects predicted by the model.

7 Conclusion

This paper resolves an important puzzle that has emerged in the study of overlapping inter- national institutions: why does the proliferation of governing bodies seem to improve coop- eration in some issue areas, while harming it in others? I provide a theory of multilateral cooperation that explains these heterogeneous effects. The theory highlights a consequen- tial distinction between undifferentiated and value-differentiated regime complexes. In the former, states treat institutions like homogeneous goods, substituting one for another based solely on the degree of policy adjustment required to meet compliance standards. In the latter, institutions provide unique value to states. They are not easily substituted, so states will bear greater costs in order to achieve compliance with high-standard institutions. The concept of differentiation has long been used by economists to understand pricing and consumer behavior in markets. This paper demonstrates its value to students of international cooperation. Just as consumers acknowledge the heterogeneous value of differentiated goods, states recognize that international institutions in the same issue area offer distinct benefits. In the context of international cooperation, the value of an institution is often linked the depth of its rules. When deeper rules generate more benefits for member states, institutions have a high potential for value differentiation. This facilitates depth of policy adjustment because states are willing to assume greater costs (policy adjustment) to participate in institutions with greater value. I elucidate the role of value differentiation via a model of states in a “market” for multi- lateral cooperation. The model demonstrates how the shift from a unified regime to a regime complex—as in the shift from a monopolistic to oligopolistic industry—can have drastically different effects on state behavior. Undifferentiated regime complexes encourage a regulatory “race to the bottom” that limits the ability of institutions to shape states’ national policies. Value-differentiated regimes, however, allow an array of institutions with different standards

37 to have a meaningful impact on member states. Results from the model show that the prolif- eration of undifferentiated institutions is likely to decrease policy adjustment among states, while the creation of overlapping institutions that are sufficiently differentiated can increase the regime’s effect on state behavior. A paired analysis of the election monitoring and development finance regime complexes supports the intuition of the model. In development finance, the introduction of new, over- lapping multilateral development banks has no discernible effect on states’ adoption of liberal macroeconomic policies. However, the introduction of new election monitoring institutions significantly increases the quality of states’ national elections. These results are consistent with the lack of value differentiation among development banks and the significant differen- tiation among election monitors. By highlighting the role of differentiation in regime complexes, the paper has important implications for the design and operation of global governance institutions. Scholars and policymakers routinely call for greater harmonization and cooperation among institutions that regulate the same policy domain. The analysis presented here suggests such strategies could potentially make institutions less effective. Harmonization represents a return to a unified regime, where all states are governed by a single set of rules. If a regime complex features institutions that already provide highly differentiated benefits, harmonizing stan- dards would yield less policy adjustment by states. Instead, institutions could engender more policy adjustment by increasing the differentiation among regulatory bodies in the issue area. Finally, the paper begins to unpack the sources of value differentiation, which stem from the basic activities that institutions in an issue area perform. There is ample room for continued theorizing to identify circumstances that differentiate overlapping institutions. In addition to value differentiation, institutions can horizontally differentiate by appealing to specific constituencies or developing local expertise. They may also functionally differentiate by dividing labor among institutions in the same regime complex. The implications of these types of differentiation for depth of policy adjustment are less clear, since there is no inherent correlation between the value provided to member states and the depth of institutional rules.

38 Future work should examine the impact of these dimensions of differentiation on cooperative outcomes.

39 References

Abbott, Kenneth W. 2012. The Transnational Regime Complex for Climate Change. Envi- ronment and Planning C: Government and Policy 30 (4):571–590.

Abbott, Kenneth W., Philipp Genschel, Bernhard Zangl, and Duncan Snidal. 2015. Inter- national Organizations as Orchestrators. Cambridge, UK: Cambridge University Press.

Abbott, Kenneth W, Robert O Keohane, Andrew Moravcsik, Anne-Marie Slaughter, and Duncan Snidal. 2000. The Doncept of Legalization. International organization 54 (3):401– 419.

Alter, Karen J., and Sophie Meunier. 2009. The Politics of International Regime Complexity. Perspectives on Politics 7 (1):13–24.

Annen, Kurt, and Stephen Kosempel. 2009. Foreign Aid, Donor Fragmentation, and Eco- nomic Growth. The BE Journal of Macroeconomics 9 (1).

Bearce, David H., and Stacy Bondanella. 2007. Intergovernmental Organizations, Social- ization, and Member-State Interest Convergence. International Organization 61 (4):pp. 703–733.

Boehmer, Charles, Erik Gartzke, and Timothy Nordstrom. 2004. Do Intergovernmental Organizations Promote Peace? World Politics 57 (1):1–38.

Brazys, Samuel, Johan A Elkink, and Gina Kelly. 2017. Bad Neighbors? How co-located Chinese and World Bank development projects impact local corruption in Tanzania. The Review of International Organizations 12 (2):227–253.

Breitmeier, Helmut, Arild Underdal, and Oran R. Young. 2011. The Effectiveness of Interna- tional Environmental Regimes: Comparing and Contrasting Findings from Quantitative Research1. International Studies Review 13 (4):579–605.

Buchanan, Allen, and Robert O Keohane. 2006. The Legitimacy of Global Governance Institutions. Ethics & international affairs 20 (4):405–437.

40 Bueno de Mesquita, Bruce, and Alastair Smith. 2016. Competition and Collaboration in Aid-for-Policy Deals. International Studies Quarterly 60 (3):413–426.

Busch, Marc L. 2007. Overlapping Institutions, Forum Shopping, and Dispute Settlement in International Trade. International Organization 61 (4):735–761.

Bush, Sarah Sunn, and Lauren Prather. 2018. Who’s There? Election Observer Identity and the Local Credibility of Elections. International Organization 659–692.

Davis, Christina, and Tyler Pratt. 2020. The Forces of Attraction: How Security Inter- ests Shape Membership in Economic Institutions. Review of International Organizations https://doi.org/10.1007/s11558-020-09395-w.

Downs, George W., David M. Rocke, and Peter N. Barsoom. 1996. Is the Good News About Compliance Good News About Cooperation? International Organization 50 (03):379–406.

Drezner, Daniel W. 2009. The Power and Peril of International Regime Complexity. Per- spectives on Politics 7 (1):65–70.

Efrat, Asif, and Abraham L Newman. 2016. Deciding to Defer: The Importance of Fairness in Resolving Transnational Jurisdictional Conflicts. International Organization 70 (2):409– 441.

Gabszewicz, J Jaskold, and Jacques-Francois Thisse. 1979. Price Competition, Quality and Income Disparities. Journal of Economic Theory 20 (3):340–359.

Gehring, Kai, Katharina Michaelowa, Axel Dreher, and Franziska Sp¨orri.2017. Aid Frag- mentation and Effectiveness: What Do We Really Know? World Development 99:320–334.

Gehring, Thomas, and Benjamin Faude. 2014. A Theory of Emerging Order Within In- stitutional Complexes: How Competition Among Regulatory International Institutions Leads to Institutional Adaptation and Division of Labor. The Review of International Organizations 9 (4):471–498.

41 Goldstein, Judith, Douglas Rivers, and Michael Tomz. 2007. Institutions in International Relations: Understanding the Effects of the GATT and the WTO on World Trade. Inter- national Organization 61 (1):37–67.

Gowa, Joanne, and Soo Yeon Kim. 2005. An Exclusive Country Club: The Effects of GATT 1950-94. World Politics 57 (4):453–478.

Gray, Julia. 2018. Life, Death, or Zombie? The Vitality of International Organizations. International Studies Quarterly 62 (1):1–13.

Hafner-Burton, Emilie M., and Alexander H. Montgomery. 2006. Power Positions: Inter- national Organizations, Social Networks, and Conflict. Journal of Conflict Resolution 50 (1):3–27.

Heldt, Eug´eniaC, and Henning Schmidtke. 2019. Explaining coherence in international regime complexes: How the World Bank shapes the field of multilateral development finance. Review of International Political Economy 26 (6):1160–1186.

Helfer, Laurence R. 2004. Regime Shifting: The TRIPS Agreement and New Dynamics of International Intellectual Property Lawmaking. Yale Journal of International Law 29:1– 83.

Henning, C Randall. 2017. Tangled Governance: International Regime Complexity, the Troika, and the Euro Crisis. Oxford University Press.

Henning, C. Randall, and Tyler Pratt. 2020. Hierarchy and Differentiation in International Regime Complexes: A Theoretical Framework for Comparative Research. Working Paper. https://www.tylerbpratt.com/s/HenningPratt_PEIO_Jan17.pdf.

Hofmann, Stephanie C. 2009. Overlapping Institutions in the Realm of International Secu- rity: The Case of NATO and ESDP. Perspectives on politics 7 (1):45–52.

Hotelling, Harold. 1929. Stability in Competition. Economic Journal 39:41–57.

42 Imai, Kosuke, In Song Kim, and Erik Wang. 2018. Matching Methods for Causal Inference with Time-Series Cross-Section Data. http://imai.princeton.edu/research/files/ tscs.pdf.

Johnston, Alastair Iain. 2001. Treating International Institutions as Social Environments. International Studies Quarterly 45 (4):487–515.

Jupille, Joseph Henri, Walter Mattli, and Duncan Snidal. 2013. Institutional Choice and Global Commerce. Cambridge University Press.

Kaufmann, Daniel, Aart Kraay, and Massimo Mastruzzi. 2011. The worldwide governance in- dicators: methodology and analytical issues. Hague Journal on the Rule of Law 3 (2):220– 246.

Kelley, Judith. 2009. The More the Merrier? The Effects of Having Multiple International Election Monitoring Organizations. Perspectives on Politics 7 (1):59–64.

Kelley, Judith G. 2017. Scorecard Diplomacy: Grading States to Influence Their Reputation and Behavior. Cambridge University Press.

Kelley, Judith G, and Kiril Kolev. 2010. Election quality and international observation 1975-2004: Two new datasets. Available at SSRN 1694654 .

Kelley, Judith Green. 2012. Monitoring Democracy: When International Election Observa- tion Works, and Why it Often Fails. Princeton, NJ: Princeton University Press.

Keohane, Robert O. 1984. After Hegemony: Cooperation and Discord in the World Political Economy. Princeton, NJ: Princeton University Press.

Keohane, Robert O., and David G. Victor. 2011. The Regime Complex for Climate Change. Perspectives on Politics 9 (1):7–23.

Koremenos, Barbara, Charles Lipson, and Duncan Snidal. 2001. The Rational Design of International Institutions. International Organization 55 (4):761–799.

43 Lesage, Dries, and Thijs Van de Graaf. 2013. Thriving in Complexity? The OECD Sys- tem’s Role in Energy and Taxation. Global Governance: A Review of Multilateralism and International Organizations 19 (1):83–92.

Lipscy, Phillip Y. 2015. Explaining Institutional Change: Policy Areas, Outside Options, and the Bretton Woods Institutions. American Journal of Political Science 59 (2):341–356.

———. 2017. Renegotiating the World Order: Institutional Change in International Rela- tions. Cambridge University Press.

Marshall, Monty G., Ted Robert Gurr, and Keith Jaggers. 2016. Polity IV Project: Political Regime Characteristics and Transitions, 1800-2016. Dataset Users’ Manual. http://www. systemicpeace.org/inscr/p4manualv2016.pdf.

Martin, Lisa L. 1992. Interests, Power, and Multilateralism. International Organization 46 (4):765–792.

Morse, Julia, and Tyler Pratt. 2018. Shirking and Signaling: Avoiding Reputation Costs in Multilateral Institutions. Working Paper.

Morse, Julia C., and Robert O. Keohane. 2014. Contested Multilateralism. The Review of International Organizations 9 (4):385–412.

Orsini, Amandine, Jean-Fr´ed´ericMorin, and Oran Young. 2013. Regime Complexes: A Buzz, a Boom, or a Bust for Global Governance? Global Governance 19 (1):27–39.

Pevehouse, Jon C., Timothy Nordstrom, and Kevin Warnke. 2004. The COW-2 International Organizations Dataset Version 2.0. Conflict Management and Peace Science 21.

Pratt, Tyler. 2018. Deference and Hierarchy in International Regime Complexes. Interna- tional Organization 72 (3):561–590.

———. 2020. Angling for Influence: Institutional Proliferation in Development Banking. International Studies Quarterly sqaa085:https://doi.org/10.1093/isq/sqaa085.

44 Raustiala, Kal, and David G. Victor. 2004. The Regime Complex for Plant Genetic Re- sources. International Organization 58 (2):277–309.

Riles, Annelise. 2014. Managing Regulatory Arbitrage: A Conflict of Laws Approach. Cornell International Law Journal 47 (1):63–119.

Rose, Andrew. 2004. Do We Really Know That the WTO Increases Trade? American Economic Review 94 (1):98–114.

Russett, Bruce, and John Oneal. 2001. Triangulating Peace: Democracy, Interdependence, and International Organizations. New York: Norton.

Simmons, Beth. 2000. International Law and State Behavior: Commitment and Compliance in International Monetary Affairs. American Political Science Review 94 (4):819–835.

Steinwand, Martin C. 2015. Compete or Coordinate? Aid Fragmentation and Lead Donor- ship. International Organization 69 (2):443–472.

Struett, Michael J, Mark T Nance, and Diane Armstrong. 2013. Navigating the Maritime Piracy Regime Complex. Global Governance: A Review of Multilateralism and Interna- tional Organizations 19 (1):93–104.

Von Stein, Jana. 2005. Do Treaties Constrain or Screen? Selection Bias and Treaty Compli- ance. American Political Science Review 99 (4):611–622.

Young, Oran. 1999. The Effectiveness of International Environmental Regimes. Cambridge, MA: MIT Press.

45 Appendix

A group of i, ..., N states are endowed with an ideal policy level, pi, distributed on by the density function f(p). They are members of one or more international institutions which provide rewards if state policies are compliant with exogenously set institutional standards,

denoted by sj for institutions j, ..., J. The game proceeds in two steps. First, states choose a policy level. If they adjust their policy away from the ideal level, they incur costs that are equivalent to the distance between their ideal and realized level. Second, states receive the rewards associated with compliance.

If a state’s chosen policy level is above an institution’s compliance threshold (sj), it receives

a payoff of α + θ(sj). If a state’s chosen policy level is below all institutional compliance thresholds, it receives no payoff. Compliance thresholds are known by states before they choose a policy level. Depth of policy adjustment is calculated as the number of states that choose a policy higher greater their ideal policy level.

Proposition 1: unified regime vs. undifferentiated regime complex

In the unified regime scenario, N states choose a policy level when confronting a single

international institution with compliance threshold s1. State payoffs are:

• 0 if a state chooses not to comply with the institution (non-compliance)

• α + θ(s1) if a state complies and its ideal policy level is higher than the institutional

standard (pi ≥ s)(compliance with no adjustment)

• (α + θ)−(s − pi) if a state complies and its ideal policy level is lower than the

institutional standard (pi < s)(compliance with adjustment)

A states will only choose non-compliance when its ideal policy level pi is sufficiently low that the costs of adjustment (s1 − pi) are greater than the benefits of compliance (α + θ(s1)).

This occurs when pi < s − α − θ(s1). The number of non-compliant states is therefore

N(F (s1 − α − θ(s1))), and the quantity of compliant states is N(1 − F (s1 − α − θ(s1))).

46 The set of compliant states includes two types: 1) states that adjust their policies to become compliant, and 2) states that are compliant “by default” (i.e., their ideal policy level is above the single institution’s compliance threshold). We subtract the latter from the total quantity of compliance to calculate depth of policy adjustment: N(F (s1)−F (s1 −α−θ(s1))). In the undifferentiated regime complex, the same N states choose a policy level when confronting the original institution plus multiple new institutions with differing compliance thresholds. Because the new institutions are undifferentiated, they offer identical compliance rewards to the original institution (α + θ(s1)). First, consider the case where all “new” institutions have a higher compliance standard than the original institution. States can achieve equal payoffs from each institution, but policy adjustment is costly. No state is willing to bear the costs of policy adjustment in order to meet the higher standards of the new institutions. Since all states forum shop downward to the weakest institution, depth of policy adjustment is equal to the unified regime. Now consider the case where at least one new institution has a lower compliance standard than the original institution. As before, no state will adjust its policy level to comply with anything but the weakest institutional standard (slow). Policy adjustment will only occur among states with ideal policy levels that are 1) below the new, lowest compliance standard

(pi < slow, and 2) above a cutoff where the magnitude of policy adjustment required to meet the lowest standard is equal to the benefits of compliance (slow −(α+θ(s1)). This establishes a range of ideal policy levels, just below slow and of length α + θ(s1), in which states will be motivated to engage in policy adjustment. To compare total policy adjustment in this scenario and the unified regime, we add the additional assumptions that f(p) is unimodal and reaches its highest density at ≥ s1. In that case, policy adjustment in the undifferentiated regime complex: N(F (slow) − F (slow − α − θ(s1)), is weakly less than policy adjustment in the unified regime: N(F (s1) − F (s1 − α − θ(s1))).

47 Proposition 2: undifferentiated vs. value-differentiated regime com- plex

The setting for the value-differentiated regime complex is identical to the undifferentiated regime complex, with the exception that the rewards of compliance vary across institutions:

α + θ(sj). For a fair comparison between the undifferentiated and value-differentiated sce- narios, I assume that the sum of benefits provided by multilateral institutions is identical in each regime complex. Otherwise, the difference in performance would arise by construction: if one type of regime complex has the advantage of offering a higher quantity of benefits to states, it can trivially induce more policy adjustment in those states. In the undifferentiated regime complex, each institution offers an identical benefit of

α + θ(s1) to compliant states (total benefits across J institutions = J(α + θ(s1))). In the

value-differentiated regime complex, each institution provides a unique benefit of α + θ(sj), J P totaling Jα + θ(sj). Setting these quantities to be equal implies that the constant θ(s1) j=1 term in the undifferentiated regime complex is equivalent to the average of the θ(sj) terms in the value-differentiated regime complex. Depth of policy adjustment in the value-differentiated regime complex depends on the rate at which θ(sj) increases in j. Consider first the simple case where θ(sj) increases at greater than a 1:1 rate: θ(sj) − θ(sj−1) > sj − sj−1. Substantively, this means that the marginal gain from complying with institution j compared to institution j −1 is greater than

the costs of adjusting policy from sj−1 to sj. In this case, the highest-standard institution always generates more net benefits for states than other institutions. States either choose non-compliance or forum shop “upward” by moving policies into compliance with the top institution. Depth of policy adjustment in the regime complex is therefore equivalent to the policy adjustment induced by the highest-standard institution: N(F (sJ )−F (sJ −α−θ(sJ )) where J indicates the most rigorous body. We cannot make direct comparisons between policy adjustment across regime complexes without additional distributional assumptions regarding F (p). If F (p) is distributed uni- formly, it is apparent that the value-differentiated regime complex generates more policy ad-

48 justment. The value-differentiated regime then induces policy adjustment among N(α+θ(sJ ) states while the undifferentiated regime complex motivates N(α + θ(s1) states. Since θ(sj) is increasing in j and sJ represents the standard of the highest-standard institution, the value-differentiated regime complex produces greater policy adjustment.

Now consider the more complicated case where θ(sj) increases at a slower rate: θ(sj) −

θ(sj−1) ≤ sj − sj−1. In this case, each institution in the value-differentiated regime complex produces some level of policy change. The lowest-standard institution induces adjustment equal to N(F (slow) − F (slow − α − θ(slow)) as states with ideal policies below its compliance threshold choose between compliance or non-compliance. States with ideal policies above slow must choose between forum shopping down to the next weakest institution and forum shopping up to the next strongest. For example, states with ideal policies in between insti- tutions j and j + 1 choose to accept the rewards associated with institution j or seek the greater rewards and costs associated with moving their policy into compliance with institu- tion j+1. Comparing the payoffs of each identifies a cutoff ideal point at which it is profitable to adjust policies upwards: state i will do so when α + θ(sj+1) − (sj+1 − pi) ≥ α + θ(sj), or pi ≥ sj+1 − (θ(sj+1) − θ(sj)). Adopting the uniform distribution and summing across institutions yields aggregate policy adjustment of N(α + θ(sJ )), once again higher than the undifferentiated regime complex.

Proposition 3: unified regime vs. value-differentiated regime com- plex

The minimum possible depth of cooperation in the value-differentiated regime complex occurs when the weakest compliance standard (slow) is 0, such that it requires no policy adjustment in order for any state to comply. In that case, depth of policy adjustment is in the value- differentiated regime complex (N(α + θ(sJ ))) is reduced by the quantity of states that were previously motivated to comply with the weakest institution: N(α + θ(sJ )) − N(α + θ(slow).

That quantity will be higher than the unified regime when N(α + θ(sJ )) − N(α + θ(slow) >

N(α + θ(s1), or θ(sJ ) − θ(slow) > α + θ(s1).

49