Peacekeeping and Foreign Aid in Conflict-Affected States

ABSTRACT

The Intervention Nexus: Peacekeeping and Foreign Aid in Conflict-Affected States

by Jonathan Kurt Simmons

The continued deployment of uniformed peacekeeping operations (PKOs) and simultaneous commitment of foreign aid demonstrate the belief that these interventions are viable tools for generating stability in conflict-affected environments. However, there appears to be no concerted effort within the international community to design or employ of these interventions in a constructive manner. In this thesis, I argue that these independent interventions increase stability by targeting the two components of stability: the network of political, economic, and social interactions or behaviors that define a state, and a socially-defined oversight mechanism that attempts to restrain those behaviors within accepted norms. I also argue that variation in mission design affects the level of oversight a PKO generates and that higher levels of United Nations involvement will generate more oversight. Furthermore, increased levels of development- focused foreign aid applied under this higher level of oversight will create an interactive effect that results in higher stability. Rather than looking for success in those indicators that are specific to either intervention, I argue that investments made in the conflict-affected economy by foreign firms seeking profit and security of their assets (foreign direct investment (FDI) inflows) are a viable measure to

determine changes in stability. By considering all states that have hosted a uniformed peacekeeping mission 1970-2013, I find that United Nations PKOs and higher levels of development-focused foreign aid have a positive interactive effect on FDI inflows. However, we only observe these results when we account for the time necessary for aid commitments to be utilized in the field and information derived through PKO oversight to affect policy decisions aimed at conflict resolution and reconciliation. The results provide more evidence for the value of international peacekeeping and link the efficacy of peacekeeping to that of foreign aid. The results also demonstrate the impact that these interventions have on international investments and open new doors for further research.

Acknowledgments

It would be difficult to attempt to name every individual who has offered some degree of assistance or advice in the completion of this research project. That being said, I would like to acknowledge my thesis advisor, Professor Ric Stoll, who kept me focused on my task and grounded in the principles of social science research. I would also like to express my gratitude to Dr. Lee Schwartz, Geographer of the United States, as well as Dr. Debbie Fugate, for allowing me to serve for three years as an analyst covering international peacekeeping operations, aid-related issues, and their policy implications. I arguably gained more knowledge and expertise on these topics during my tenure at the US Department of State than I could have by reading any book or article. I must also thank my friend and cohort member, Cem Birol, who tirelessly served as a sounding board for my ideas. I will humbly admit that I could not have even begun this journey without the full support, patience, love, and understanding of my wife Kimberly and my daughters, Rachel and Lillian; they have sacrificed more for my academic and professional ambitions than I could begin to detail in this short section. Finally, I must thank my father

Ronnie Burns Simmons who always encouraged me to pursue my academic goals; it is to him this work is dedicated.

Contents

Acknowledgments ...... iv Contents ...... v List of Figures ...... ix List of Tables ...... x Introduction ...... 1 1.1. An alternative framing of stability and stability-building interventions ...... 1 1.2. Foreign investor judgements of stability ...... 3 1.3. Conflict-affected states vs. developing states ...... 4 1.4. A limited understanding of stabilization interventions ...... 5 1.5. Why peacekeeping matters ...... 8 1.6. UN involvement ...... 9 1.7. The way forward...... 10 Literature Review ...... 12 2.1. Studies on Peacekeeping ...... 12 2.1.1. Modern peacekeeping literature ...... 13 2.1.2. Peacekeeping intelligence ...... 18 2.2. Extant Literature on Foreign Aid ...... 22 2.2.1. The good and bad of foreign aid ...... 22 2.2.2. Foreign aid in conflict and post-conflict scenarios ...... 25 2.3. Foreign Direct Investment - a proxy for success ...... 27 2.3.1. The economic enabling environment and investment risk ...... 28 2.4. Summary ...... 29 A theory on increasing stability in conflict-affected states through intervention ...... 32 3.1. Introduction ...... 32 3.2. What is stability? ...... 34 3.2.1. Stability in the abstract ...... 34 3.2.2. A practical look at stability ...... 41 3.2.3. A refined definition of stability ...... 46

3.3. A theory on achieving greater stability in post-conflict states through intervention ...... 48 3.4. Why does the international community choose to intervene? ...... 55 3.5. Choosing from the intervention menu ...... 64 3.6. Targeting foreign aid to change behavior ...... 67 3.7. Scrutiny, state behavior, and peacekeeping options ...... 70 3.7.1. PKO variety in action: a look at the first Liberian Civil War ...... 71 3.7.2. Choosing levels of oversight ...... 74 3.7.3. Building variation in PKO scrutiny ...... 76 3.7.4. Why United Nations involvement means greater scrutiny ...... 76 3.7.4.1. Peacekeeping intelligence capability ...... 77 3.7.4.2. Access to peacekeeping intelligence and sanctioning power ...... 80 3.7.5. PKO categories ...... 82 3.7.5.1. UN-led operations ...... 82 3.7.5.2. UN-authorized operations ...... 84 3.7.5.3. UN-recognized operations ...... 85 3.7.5.4. Non-UN operations ...... 86 3.7.6. PKO composition options ...... 86 3.7.6.1. Troops/police/observers ...... 86 3.7.6.2. National origin and doctrinal foundations of peacekeepers ...... 88 3.7.6.3. Troop type ...... 93 3.8. A nexus of effects: the impact of PKO-driven oversight on targeted foreign aid in increasing stability ...... 94 3.9. Summary ...... 100 Research Design ...... 102 4.1. Introduction ...... 102 4.2. It’s the economy… ...... 107 4.2.1. Foreign Direct Investment as a measure of stability ...... 109 4.2.2. FDI as the dependent variable ...... 112 4.3. Independent variables ...... 117 4.3.1. Targeted Foreign Aid – targeting security vs. development ...... 117 4.3.2. Peacekeeping Operations – modeling oversight by UN involvement ...... 121 4.3.2.1. Levels of UN Involvement ...... 122 4.3.2.2. Refining oversight - additional PKO variables ...... 125 vii

4.3.2.3. Doctrinal foundations ...... 126 4.3.2.4. Force size and PKO composition ...... 129 4.3.2.5. Troop type ...... 132 4.3.3. The nexus of aid and PKO-driven oversight ...... 135 4.3.4. Control variables ...... 136 4.3.4.1. Conflict periods ...... 137 4.3.4.2. Country specific controls ...... 139 4.3.4.3. Regional effects ...... 140 4.4. Modeling the Intervention Nexus ...... 141 4.5. Summary ...... 143 Analysis and Results ...... 146 5.1. Data and modeling ...... 148 5.1.1. FDI inflow values ...... 148 5.1.2. Refining peacekeeping variables for analysis ...... 155 5.1.3. Refining aid commitment variables for analysis ...... 161 5.1.4. Baseline model ...... 166 5.2. Model refinement and hypothesis testing ...... 170 5.2.1. Variable refinement ...... 170 5.2.2. Testing the Completed Model ...... 175 5.2.3. Addressing unexpected results for conflict periods ...... 182 5.2.4. Testing PKO Doctrine ...... 185 5.3. Testing the interaction between UN led PKOs and development aid ...... 192 5.4. Summary ...... 201 Placing the research in context ...... 205 6.1. A review of the study ...... 205 6.2. Finding support for the theory and results: UNOCI ...... 211 6.2.1. Pre-intervention Cote d’Ivoire ...... 212 6.2.2. Conflict and intervention, the 2002-2003 Ivorian Civil War ...... 215 6.2.2.1. The transition to and evolution of UN peacekeeping and the need for more information ...... 217 6.2.2.2. UNOCI role in elections monitoring ...... 221 6.2.2.3. Post-election violence 2010-2011 and reconciliation ...... 223 6.2.2.4. The impact of limited development aid...... 225 6.2.2.5. Future policy recommendations and final comments ...... 230 viii

Appendix A ...... 248 Appendix B ...... 254 Appendix C ...... 282 Appendix D ...... 284 Appendix E ...... 285 Appendix F ...... 287

List of Figures

Figure 4-1: Liberian FDI inflows vs. GDP 2003-2017, ...... 111

Figure 4-2: FDI inflows 1970-2013, extreme FDI values omitted ...... 116

Figure 4-3: UN deployment map for the UN PKO in the Central African Republic (MINUCA), February 2018 (from reliefweb.int; accessed January 2019) ...... 134

Figure 5-1: Comparing histograms of FDI inflows vs. ln(FDI inflows) ...... 151

Figure 5-2: Histogram of FDI inflows without extreme values ...... 152

Figure 5-3: Scatterplot of FDI inflows by PKO-type ...... 153

Figure 5-4: Scatter plot of FDI inflows by development aid commitments ..... 154

Figure 5-5: Scatterplot of FDI Inflows by security aid commitments ...... 155

Figure 5-6: Predicted FDI inflows – mission types and aid commitment variables (Model 5) ...... 168

Figure 5-7: Residuals plot – mission types and aid commitment variables (Model 5) ...... 169

Figure 5-8: Coefficient plot for Troop, FPU, and Observers totals - Model 6a 181

Figure 5-9: Coefficient plot for Pre-conflict and Conflict year dummy variables - Model 6a ...... 183

Figure 6-1: Aid Commitments and Peacekeeper Deployments to Cote d'Ivoire 2002-2013 ...... 227

Figure 6-2: FDI Inflows to Cote d'Ivoire 2002-2017 (millions 2011 constant USD) ...... 229

List of Tables

Table 4-1: AidData Coalesced Purpose Codes and Aid Sectors used for analysis ...... 118

Table 4-2: PKO by Type/UN Involvement score, taken in part from Bellamy and Williams (2015) pg. 20 ...... 123

Table 4-3: Frequency of PKO types and UN involvement in the dataset ...... 125

Table 4-4: World Bank regions ...... 141

Table 5-1: Two sample t-test results – FDI Inflows and PKO presence dummy variable ...... 156

Table 5-2: Two sample t-test results – FDI Inflows and Mission Type dummy variables ...... 158

Table 5-3: Two sample t-test results – FDI Inflows and UN involvement dummy variables ...... 158

Table 5-4: OLS regression for PKO variables ...... 161

Table 5-5: Missing aid data by aid type variable ...... 163

Table 5-6: OLS regression, aid commitment variables and percentage of total aid variables ...... 165

Table 5-7: OLS regression with key independent variables only ...... 167

Table 5-8: Dummy variable representations within analysis sample ...... 177

Table 5-9: OLS regresstion results Full analytical model (6a) and UCDP/PRIO conflict variant (6b) ...... 178

Table 5-10: OLS regression results for doctrine effect testing, FDI inflows and FDI inflows per capita (FDI per Capita) ...... 188

Table 5-11: OLS regression results - Interaction model, UN-led dummy and development aid per capita ...... 194

Table 5-12: OLS regression results – Lagged variables and interaction with lagged variables: UN-led dummy (1 year lag), development aid per capita (1 year lag) and (3 year lag), FDI per Capita (1year lag) ...... 197

Chapter 1

Introduction

1.1. An alternative framing of stability and stability-building

interventions

The research presented in this thesis aims to increase our understanding of the international community’s capacity to increase stability in conflict-affected states. Although the concept of stability can be nebulous or highly context-specific, this study attempts to frame stability in a more systematic way. While stability remains a condition that is used to describe a state, the study treats stability as the measurable product of two components, a network of accepted interactions or behaviors and the socially-generated oversight mechanism that attempts to constrain those behaviors. Each component can be targeted by external interventions aimed at creating change, thus stability can be measurably affected.

Unlike other research on post-conflict interventions, where success is often measured in terms of peace duration, this investigation looks for the impact that interventions have on stability by considering their effects on conflict-affected economies. The research will attempt to show that we can assess intervention success or failure by demonstrating that, on average, both targeted foreign aid and the presence of peacekeeping forces have significant effects on the flow of foreign direct investment (FDI) into conflict-affected economies.

More importantly the research aims to demonstrate how these independent interventions (meaning they are not coordinated in their motivation, design, or implementation) can create a measurable interactive effect on stability that we can assess by how FDI inflows are affected. The ultimate goal of the project is to identify which intervention characteristics affect positive influence on FDI inflows, thereby creating a general model for future interventions that have a higher likelihood of increasing stability.

Going beyond the presence of armed or unarmed peacekeepers, the study emphasizes the influence that a mission’s mandate authority has in generating or providing oversight of the conflict-affected state. Force size, and composition also play a role in creating oversight; a key component of these mission characteristics to be discussed will be the doctrinal background of the peacekeepers themselves.

Foreign aid is recognized as a collection of fiscal efforts that attempt to affect long-term behavior changes in the conflict-affected state. Therefore, the research 3 focuses on how aid monies are targeted rather than looking solely at the total amount of aid a state receives.

1.2. Foreign investor judgements of stability

Investor judgements on the internal conditions of those conflict-affected states who receive foreign aid and host peacekeepers provide an alternative perspective on how effective international stabilization interventions can be.

Investment capital in the form of non-portfolio foreign direct investment (FDI) provides an independent measure, indicative of investor optimism, for long-term stability and affords an opportunity for systematic analysis of stabilization efforts as well as the state itself. Arguably, an analysis reliant on an independent assessment of stability and the subsequent decision to invest or withdraw monies into a conflict

-affected economy offers potentially more credible results than those using measures based on subjective input from the interventionists themselves.

The efforts made by a foreign firm to invest in any state suggests that the target economy is viable, and that local markets are capable of sustaining outside competition with labor, skill, and the potential for profit. While developing states with the desire for goods and services might welcome such investment, even at the expense of a domestic company, the notion that a foreign firm would be willing to invest can potentially tell us as much about the target state as it does about the firm.

Because no investor aims to lose money, investing firms look for qualities in a target state that go beyond supply chains, strong local markets, or even a viable work 4 force. Firms want assurances that their investments will be safe. This does not suggest investments must be risk-free, but it does demand that competent governance has established and enforces policies reflecting the rule of law. Through these conditions economic development (inclusive of FDI) should occur, which contributes to domestic stability.

1.3. Conflict-affected states vs. developing states

Conflict-affected environments offer significantly different challenges beyond those experienced by perhaps even the most under-developed state, yet the conditions of a conflict-affected state subject to stabilization efforts are likely similar. Conflict-affected governments are challenged with the hurdles of returning the domestic economy to its pre-conflict state, addressing infrastructure that has suffered due to conflict-focused budgets, and potentially the reunification of its populace. However, these governments are likely weak or weakened by conflict and therefore governance is arguably degraded, the populace is potentially burdened by the reduction of government support, and the economy has most likely suffered as policy focus has been placed on victory or survival rather than development and growth.

In light of these challenges a conflict-affected state will typically require outside assistance to achieve stability and regain its pre-conflict position in the global community. And, the success of this overall process, or stabilization effort, is vital to ensure that a relapse into conflict does not occur. While the notion of 5 stabilization, or post-conflict reconstruction, has entered the modern vernacular mostly due to the costly efforts by the United States and other Western states to rebuild Iraq and Afghanistan following brief high-intensity conflicts and subsequent protracted civil conflicts, the idea of bringing states back to the international arena following conflict is not new. Perhaps the most recognizable examples prior to Iraq and Afghanistan would be the post-World War II reconstruction of both Germany and Japan, the difference being that these latter cases are often heralded as success stories while the former are seen as examples of what never to do.

1.4. A limited understanding of stabilization interventions

In order to achieve the most favorable outcome, that includes the prevention of renewed fighting in a conflict-weakened state, the global community is challenged to develop or support interventions that will subsidize where government falls short, spur economic growth, and motivate backing from the population that will allow the post-conflict state to stand on its own two feet, conflict free, without external assistance. The introduction of peacekeeping forces and targeted foreign aid are two mechanisms often employed in these situations albeit without any noticeable consideration of how these interventions actually interact.

The research on peacekeeping and peace building has seen periods of high and low interest over the past few decades that appear to correlate with major shifts in geopolitical realities, such as the end of the Cold War, major events within the peacekeeping community, such as the failures to prevent atrocities against civilians 6 in Somalia and Rwanda, and paradigm shifts in peacekeeping policy, such as the mandate of civilian protection.1

For three years, while researching and writing this thesis, I worked as and alongside US Government analysts focused on policy issues related to peacekeeping and foreign aid topics. This allowed me to gather direct insight into senior policy making circles within the US Government and afforded opportunities to meet and interview peacekeeping experts from the United States military and the United

Nations Department of Peacekeeping Operations (UNDPKO).

While these experiences, or my 20-year military career that includes deployments in support of post-conflict stabilization operations as a US Army Civil

Affairs Officer do not make me the definitive expert on peacekeeping or foreign aid, I can attest to the limited scope through which these efforts are viewed. Barring a limited number of research programs, few scholars have successfully gained traction within policy making arenas on peacekeeping issues, resulting in a dominance of limited perspectives on the best approaches to an extremely complex problem set. A significant literature exists as a result of these programs, but this literature suffers from two major shortcomings.

1 In 2000, in response to a variety of conditions that were hampering the solidification of the peace process in post-conflict Sierra Leone including the failure of some groups to disarm and concerns over human rights violations, the Security Council expanded the mandate of the UN Mission in Sierra Leone (UNAMSIL) to include the “protection to civilians under imminent threat of physical violence, taking into account the responsibilities of the Government of Sierra Leone”. This was the first time such a caveat was included in a UN PKO mandate (UNDPI, 2005).

First, the majority of peacekeeping research has focused primarily on those missions executed by the United Nations (UN). However, the UN does not hold a monopoly on peacekeeping. Various other international and regional organizations, ad hoc partnerships, and even domestically generated missions have attempted to prevent conflict recurrence in both interstate and intrastate war. Out of 175 peacekeeping missions deployed between 1947 and 2013 where a signed peace deal was present, only 70 were classified as UN-led; 29 were authorized by the UN, 33 recognized by the UN, and 43 were not affiliated with UN efforts at all.

Additionally, no research has looked beyond the generic classifications of uniformed peacekeeping mission; troops are typically assumed to be interchangeable in their effect regardless of the type of troop they are. For example, peacekeeping forces could deploy large numbers of military police, however, these peacekeepers are potentially policing only the peacekeeping force itself and not performing any direct mission with regards to the populace. This would directly impact the number of armed troops available for performing those tasks such as patrolling or providing security that we might typically associate with peacekeeping missions. The same could be said for any support troops who would be counted as armed peacekeepers yet never engage the populace.

Second, few programs have attempted to explain how simultaneous peacekeeping interventions and interventions via post-conflict foreign aid deter (or promote) the stabilization process. This gap in our understanding is significant if we consider the fact that peacekeeping efforts, even those carried out by uniformed 8 military or police, can target the same underlying issues that aid programs do.

Ideally, we expect all efforts to add positively to the process, but this expectation is unfounded. Without understanding the effects of this inevitable interaction, it is difficult to justify either intervention.

A final critique of these programs is that they typically look for proof of success in a peacekeeping mission’s ability to prevent conflict recurrence rather than a mission’s ability to influence the prerequisite success of the stabilization effort; this suggests that a peacekeeping mission is the causation of long-term peace, even after the peacekeepers have gone home. If we only measure the success of a mission by its ability to prevent an arbitrarily determined number of yearly combat deaths during its deployment, we miss the potential that peacekeeping missions have as part of the peace building process.

1.5. Why peacekeeping matters

I suggest that the presence of a peacekeeping mission is a key factor in the success of stabilization efforts because it promotes foreign aid’s ability to affect governance, economic, and societal issues. Our understanding of this interactive impact on the stabilization process is insufficient to determine how best to offer assistance to the conflict-affected state. Measures of FDI inflows serve as the primary indicator of intervention success because they reflect the culmination of investor perceptions on the future of the conflict-affected state and thus the success of stabilization efforts. 9

I argue the ability of peacekeeping missions to affect the impact of foreign aid is achieved through the level of oversight or scrutiny imposed on the host state.

Because any policy decision is based on information, I argue that in interventionist policy, where the external actor is deciding on deployment of a physical force or the level or target of foreign aid, information available to those actors regarding ground conditions is key to decision making. The information made available to those decision makers will come from a variety of sources including those peacekeepers deployed and physically present inside the conflict-affected state. I will show how the level of oversight or scrutiny that these peacekeepers can provide varies significantly between mission types or characteristics.

The research considers all post-conflict cases where peace agreements have been signed and peacekeeping missions have been employed. Those independent variables used in the analysis to represent the peacekeeping portion of the model will reflect the level of scrutiny through mission construct and design. Most important will be the level of United Nations (UN) involvement in the mission itself.

1.6. UN involvement

The level of UN influence is significant for three reasons. First and foremost, the degree to which the UN influences a mission, particularly with regards to mission control or mandate, can significantly impact the mission’s ability to collect and analyze information (i.e. the generation of peacekeeping intelligence (PKI)). 10

Second, as international participation increases so does the size of the community that has knowledge of the host state’s behavior.

The UN represents the largest international body that supports peacekeeping operations and while a significant amount of tactical information may not be shared across the entire assembly, the likelihood of significant strategic information regarding the target state’s behavior and UN interests is much higher. This implies that more members of the international community will have insight on the target state’s behavior which increases the potential for punishment if that behavior is bad. This ability to punish is the third significance to UN involvement. Because the

UN is the largest international body, sanctions enforced by member states could come from significantly more member states than in cases where fewer states have access to that information.

1.7. The way forward.

While the first peacekeeping missions began with the founding of the UN in the 1940s, the availability of foreign aid data and FDI inflow data during these early years precludes the inclusion of 16 missions that began before 1970; as such coverage of these cases will not be possible for these years. Notably, many of those first missions deployed have extended well into the covered time period and remain active today which will allow for the inclusion of those cases during those years.

Observations considered for empirical testing are also limited to those in 2013 or 11 earlier because this is the current limit of foreign aid information disaggregated at the level that will be used for this analysis.

Chapter 2 will provide an overview of relevant academic literature for the three primary fields of study addressed in this thesis: peacekeeping, foreign aid, and foreign direct investment. Chapter 3 presents the theory behind this research project, or how foreign aid and peacekeeping, two independent interventions that promote stability or potentially deter it. Chapter 4 provides the research design, specifically focusing on the operationalization of key components of the theory into measurable variables and viable statistical models. Analysis of results are presented in Chapter 5 along with an assessment of those initial findings. Chapter 6 concludes the study by placing the findings in context of ongoing interventions. The chapter also offers a way forward for continued academic study as well as policy implications that can be drawn from the results.

Chapter 2

Literature Review

2.1. Studies on Peacekeeping

There have been two primary approaches to the study of peacekeeping operations since the first mission was deployed in 1948: studies on the motivations behind deployment, and studies on the efficacy of those missions. Constant in earlier research on peacekeeping are the observations that there are more conflicts in need of peacekeepers than there are peacekeepers available, but also that the presence of peacekeepers, as expected, typically reduces violence to some degree.

While a majority of qualitative work has looked at peacekeeping in terms of the idiosyncrasies of a particular mission or a series of missions, most early quantitative works focused predominantly on mission characteristics such as the operation mandate or the type of intervention (armed versus unarmed) and their ability to keep the peace. More recent quantitative works have expanded on these

13 basic findings in an attempt to understand how mission nuances impact efficacy of violence reduction as well as the motivations behind the decision to deploy forces.

The study of peacekeeping has not been a consistently popular topic among scholars. As Fortna and Howard (2008) have demonstrated, academic attention to peacekeeping appears to wax and wane with major geopolitical events, such as the end of the Cold War, or significant peacekeeping events, such as the adoption of the civilian protection mandate following the conflict in Sierra Leone. Although this has divided peacekeeping studies more or less into temporal periods (Cold War, post-

Cold War, post-mandated civilian protection), the two primary approaches of study have remained the same. The following review of more recent peacekeeping literature demonstrates this reality and addresses the challenges to a broader study of peacekeeping that have only recently been partially alleviated with the availability of more data on United Nations peacekeeping missions

2.1.1. Modern peacekeeping literature

Gauibulloev, et al. (2009) notably argue that the motivation behind peacekeeping deployment is dependent on whether or not the mission is UN-led.

They find that non-UN missions are motivated more by self-interest versus UN missions that are motivated by global public good. Choi (2013) also argues that domestic economic motivations and normative pressures drive states to push not only for intervention but participation in UN missions. Hultman (2013) provides additional support to the altruistic nature of UN missions by showing that 21st

Century UN missions are more likely to deploy when civilians are at risk. However, 14 more recent studies have found less altruistic motivation behind UN missions.

Benson and Kathman (2014) suggest that UN Security Council (UNSC) biases towards belligerents drive both the decision to intervene and the level of UN troops committed. Stojek and Tir (2015) bring the argument full circle suggesting that economic interests of the five permanent members of the UN Security Council motivate deployment decisions. None of these studies suggest that previous qualitative or quantitative works are flawed in the findings that peacekeeping forces, on average, result in a reduction of violence. They do however generate debate over the motivations behind those decisions. This debate over motivations has been made possible by the availability of data on UN peacekeeping.

Although UN peacekeeping has been in practice since 1948 only thirteen missions deployed prior to 1988; over fifty more have deployed in the past twenty- nine years. Only within the last several years has the UN made data on their missions more readily available, particularly the breakdown of troops, police, and unarmed observers. Pairing this data with UN data on Security Council voting and decisions has allowed for these newer insights into the motivations behind peacekeeping decisions. In addition, the availability of data on missions has opened the doors to larger research projects on the efficacy of missions beyond the more traditional approach of unarmed observers versus armed troops.

Many studies on efficacy since the end of the Cold War investigated the outcome of peacekeeping operations based on presence of troops alone or by the basic differentiation of armed troops versus unarmed observers as discussed above. 15

These works, acknowledged and typified in Fortna’s comprehensive research program (1993, 2004a, 2004b), most commonly consider the lack of renewed violence, or the duration of peace, as the only indicator of efficacy. The evolution of research on efficacy has demonstrated that mission design is important; meaning who participates, what mandate they operate under, and what force composition looks like. This research on efficacy has attempted to identify why one actor may be better suited than another to lead or participate in peacekeeping within a specific country or in response to a particular situation (Daniel et al., 2015; Durch &

Berkman, 2006; Mullenbach, 2005).

These studies validate earlier qualitative work by Fortna (1993) who argued the positives and negatives of regional peacekeeping and the need for cooperation with the UN, as well as the UN’s own assessment by the Department of Peacekeeping

Operations (DPKO) (1999) that acknowledged the need for cooperation with regional organizations to ensure sustained peace. This theme was pushed further by an independent review of operations commissioned by DPKO’s Peacekeeping Best

Practices Unit (Jones & Cherif, 2004) and appears to have taken hold with the release of the Ramos-Horta Report (2015).

The Ramos-Horta Report (the culmination of an 8-month study directed by then-UN Secretary General Ban Ki Moon to assess current UN peacekeeping operations and identify emerging concerns) notably points to four necessary shifts in peacekeeping: the recognition that political solutions should drive mission design and deployment, full spectrum operations must be used more flexibly on the 16 ground, the need for stronger UN-regional partnerships, and that the UN must be more field-focused while operations are more people-centered. Each of these changes are deemed necessary to ensure success at preventing conflict, protecting civilians, and mediating and sustaining peace processes.

This call for flexible forces and hybrid (UN-regional) missions follows more recent shifts in research that considers force characteristics and their impacts of mission outcome. For example, Beardsley (2011) demonstrates how the relative risk of conflict spreading across international borders is reduced by 89% when peacekeepers are deployed to the conflict-affected country compared to when they are not. And, that smaller peacekeeping forces are capable of performing the security operations needed to achieve that outcome, although larger peacekeeping forces may reduce the relative risk more. Surprisingly, Beardsley does little to differentiate the breakdown of the roles and responsibilities of the troops that comprise these missions considering those ratios would add greatly to his argument, and focuses primarily on overall personnel count. As with previous studies, this shortfall resulted from a lack of readily available data on UN missions.

The newly available data on the breakdown of UN forces now allows for more research on the efficacy of force composition on various aspects of a peacekeeping mission (Kathman, 2013). Hultman et al. (2013) were some of the first to capitalize on this information to demonstrate that the composition of peacekeeping missions can impact mandate-specific tasks such as protecting civilians. While the availability of data on UN missions has allowed for this sort of 17 composition-driven inquiry, few research programs have attempted to demonstrate the effects of force composition systematically across different classifications of peace operations.

The four classifications of peacekeeping operations that will be used in this study are taken from Bellamy and Williams (2015) and reflect the participation or influence of the United Nations in the PKO, they include: UN-led, UN-authorized, UN- recognized, and non-UN missions. UN-led missions are simply those approved, planned, led, and financed through the United Nations. At present, missions involving uniformed soldiers or police are being planned, directed, and managed through the Department of Peace Keeping Operations, while those missions without a uniformed presence would fall under the Department of Political and

Peacebuilding Affairs2. UN-authorized missions are those mandated by one of the five Principal Organs of the UN3 (usually the Security Council) but managed by a non-UN entity such as the African Union, OSCE, or NATO. UN-recognized operations are welcomed or requested by one of the five Principal Organs but not mandated by them. While non-UN missions have not been vetted or condoned by any UN entity

(Bellamy & Williams, 2015). PKO classification based on UN participation or influence offers more than an explanation of who provides and manages an

2 This study will consider only the former. 3 These include the General Assembly, the Security Council, the Economic and Social Council, the International Court of Justice, and the Secretariat. A sixth organ is the Trusteeship Council which has been inactive since 1994. 18 operation, it also offers insight into the efficacy of the mission’s information sharing or peacekeeping intelligence (PKI) capability.

2.1.2. Peacekeeping intelligence

Peacekeeping intelligence (PKI) is an area of peacekeeping study that has received limited attention despite the UN’s growing recognition over the past two decades that intelligence is necessary to be proactive rather than reactive in the utilization of UN assets (Abilova & Novosseloff, 2016). The use and application of intelligence in support of tactical combat operations is ubiquitous but it has not been traditionally employed in support of UN peacekeeping operations which are historically, by definition, almost exclusively considered as non-combat operations.

Considering that UNPKOs perform their mandated tasks at the invitation of a host- nation and other former belligerents, the collection and dissemination of what might be considered secretly obtained information may appear counter to the notion of peacekeeper impartiality; regardless of how that information was used.4

However, Smith (1994) argued soon after the end of the Cold War why the

UN needed to adopt the use of intelligence as PKOs transitioned to more robust, combat-like operations in increasingly uncertain conditions. Boyd (1999) later

4 Arguably, impartiality should be interpreted as impartiality between the signatories of the peace accord that drives a PKO mandate or between those signatories who are legitimately abiding by the tenants of an accord. Impartiality does not therefore extend to those parties who challenge the peace. It is in the context of securing the peace and securing the peacekeepers that PKI should be considered. 19 explained how military intelligence professionals had only recently recognized the applicability of tactical intelligence assets in U.S.-military led PKOs. Based on extant military doctrine of the time, these assets would have been sharply focused on threats from military adversaries. However, in the context of peacekeeping they would be more broadly focused on political, economic, and social factors that might affect the performance and safety of US personnel.

Fortna (2003) expanded the scope and applicability of this concept to PKOs in general by suggesting that national intelligence assets serve as a compliance verification method and foster cooperation by reducing uncertainty about former belligerents – lack of information on opponent behavior being a causal mechanism for the return to conflict. Hultman et al. (2015) also argue that PKOs reduce information problems and find that PKO size and composition matters in this regard. Ravndal (2009) believes the UN has come closer to accepting the need for

PKI. He suggests this is because the organization has reached a critical juncture on the debate of creating an internal PKI capacity.5 According to Ravndal, the continued push by key leaders within the UN to develop an internal PKI capacity, and the effect that those efforts have on Non-Aligned Movement (NAM) countries (a large block with significant political power who are becoming more involved in UN peacekeeping) are likely to generate change to UN policy on PKI. Ravndal suggests

5 The term critical juncture is borrowed from the study of historical institutionalism that describes as a point where decisions made by key members of an institution result in the selection of one pathway of development over another (Capoccia, 2016). 20

(at the time of his publication) this policy change might include the further development of PKI-oriented teams within UNDPKO such as mission-level Joint

Mission Analysis Centres (JMAC) or an Assessment Team (A-Team) located at

UNDPKO’s Office of Military Affairs. At present, these PKI teams continue to operate at mission and headquarters (tactical through strategic levels) and the UN had, as late as 2018, a dedicated Peacekeeping Intelligence Coordinator tasked with developing UN PKI doctrine.6

Yet, despite over two decades of post-Cold War peacekeeping and the recognition that the application of PKI can benefit stabilization interventions,

Lefebvre (2011) suggests that sharing intelligence between international partners remains challenging due to the nature of intelligence gathering (i.e. highlighting national sources and methods). Each of these concepts are echoed in the remainder of a limited body of work which share a stated goal in promoting the development of greater intelligence collection and analytic capacity within UNPKOs and the UN itself

(Abilova & Novosseloff, 2016; Chesterman, 2006; Dorn, 1999, 2007; Hennessey,

2007). These works do not attempt to extend the importance of PKI beyond the UN, as Ravndal (2009) notes, but they do suggest through case study analysis, how the use of PKI has proven beneficial in specific cases.

6 Based on visits conducted by the author to the UNDPKO Office of Military Affairs, discussions with unattributed UNDPKO officers, UN officials, and an interview with Colonel Ulisses Gomes, Chief of Policy and Doctrine Team, Acting Chief of Current Military Operations Service, UNDPKO, May, 2018. 21

For example, Dorn (2007, pp. 118-122) shows how strategic intelligence analysis by a now defunct UN team (the Information and Research Unit) successfully identified corruption and predicted humanitarian crises in Zaire during the mid

1990s. While the Zaire case makes an argument for the benefits of analytical capacity within the UN, it also showed how that capability was reliant on third party information obtained by the national intelligence apparatuses of those analysts assigned to the team. Dorn (2009) more recently shows how the UN mission in

Haiti (MINUSTAH) successfully employed its assigned forces for tactical intelligence gathering. The limits of research on PKI outside of the context of the United Nations shows we lack significant understanding of how this capability effects success of peacekeeping in a general sense and, moreover, how it effects other facets of stabilization intervention.

As indicated above, the biggest challenge in researching peacekeeping continues to be the lack of data for non-UN led missions. For example, a non-UN mission conducted by a unilateral actor is not detailed in publicly accessible databases because they are de facto military or political actions. Unlike the well- documented UN missions that define specific numbers of troops or observers that are mandated by a UN Security Council Resolution, those missions that are not UN- led likely have restrictions established by bilateral or multilateral agreement; thus, determining numbers and composition requires some degree of interpretation based on the units deployed. Further breakdowns of the number of troops, police, or unarmed observers become more challenging. 22

The lack of data is understandable considering the sending organizations or unilateral actors are less concerned about providing information on security details to the public. Any work on these missions, to date, has relied on secondary sources of information to construct novel datasets. This research program is no different and will use both existing datasets as well as a newly constructed dataset to study the efficacy of these categories of peacekeeping missions. However, peace operations are not solitary interventions, they are in fact a multifaceted approach to conflict resolution and/or conflict prevention. Unlike other research programs that consider these missions or their characteristics as independent variables, I will consider the interaction of these interventions with another significant intervention, targeted foreign aid.

2.2. Extant Literature on Foreign Aid

2.2.1. The good and bad of foreign aid

No peacekeeping operation, whether it is an “observe and report” mission, or one driven by the more modern mandate of civilian protection, is simply about the introduction of military personnel, police, or civilian political interlocutors; some degree of foreign aid geared at enhancing the gains of a military intervention will likely be provided. While a significant portion of aid is likely to come from private donors, governmental (GO) or non-governmental organizations (NGOs), states are the largest contributors of funds and these contributions are typically spread across a wide range of targeted program fields. 23

The expansive literature on foreign aid7 is clearly divided on the positive or negative impacts on the recipient state. Often cited are those works that suggest aid, especially when provided in large amounts, detracts from governance and the public sector’s economic institutions because it inherently generates corruption or pulls talented bureaucrats towards more lucrative employment (Alesina & Weder, 2002;

Djankov et al., 2008; Knack, 2001).

On the surface, these arguments make logical sense if the observer considers aid to be a stop-gap or the fulfillment of a provision the recipient state cannot or will not provide on its own. The recipient government, no longer needing to allocate its limited resources toward programs already placed at the bottom of a list of priorities, is able to focus on issues that promote its own self-interest rather than those that are welfare-enhancing.8

In fact, Alesina and Dollar (2000) find that aid donations contribute less towards economic development and suggest this is because aid is more likely to go to those states that have commonalities with the donor, rather than the political institutions or economic policies of the target state. For example, they find French aid is more likely to go towards former colonies, US aid towards Israel and Egypt,

7 I refer to any sort of external provision of aid at this point, not solely that provided by another state. This includes contributions from private donors such as the Bill and Melinda Gates Foundation efforts to combat HIV and polio or promote agricultural development in Africa. Alternately, aid contributions could come from global institutions with multiple member countries such as the World Development Bank’s International Bank for Reconstruction or Development which provides loans and other financial services to middle-income and select low-income countries. 8 This could include personal profit of political leaders or politicians, especially in states with no existing checks or balances addressing these actions. 24 and Japanese aid towards recipients who share similar voting patterns at the United

Nations. This perhaps explains the external perception of the recipient state’s capability to govern absent a patriarchal sponsor.

However, it could also be argued that financial oversight inherent within the modern aid system9 has become so dominant that those who would desire to cheat the system may simply be unable to profit, directly or indirectly, without drawing attention. In fact, Tavares (2003) finds that aid can actually decrease corruption in recipient states. Others go further to suggest that aid does more than subsidize, it can potentially promote change in the character of recipient governments. Finkel, et al (2008), and Kalyvitis and Vlachaki (2010) suggest that when aid targets concepts such as transparency, free elections, or political equality through the institutions that promote them, governments display more democratic tendencies.10 And,

Simmons (2014a) finds that aid targeting democratic institutions can promote democratic characteristics in a state’s political culture through a process of political socialization. In this case, aid’s impact is societal rather than institutional and arguably more far reaching.

9 The “aid system” is an extensive network of state-sponsored and/or privately-run organizations that respond to specific needs; network does not imply full coordination. 10 Based on democracy indices. 25

2.2.2. Foreign aid in conflict and post-conflict scenarios

Post-conflict scenarios can bring a significantly different dynamic to the question of foreign aid, and more relevant to this study, aid’s effects on the affected population, not simply the institutions that aid hopes to temporarily bolster or rebuild. Böhnke and Zürcher (2013) look specifically at aid’s impact on security in conflict-affected Afghanistan through the impact on attitudes of the population; they find no support for their hypothesis that aid can bolster internal support for interveners or the state. However, they do find evidence that aid creates the perception of state legitimacy among recipients. This would seem to be a “win” for an incumbent government; even if the populace does not like a policy, they adhere to it. Garriga and Phillips (2014) and Bandyopadhyay et al. (2014) argue that aid can also signal external actors by reducing the perception of future threats and promoting confidence in the government.

If aid can promote legitimacy, even without increased support, it seems that aid can be a tool to indirectly reinforce the state’s monopoly on power, meaning the role of the state in the enforcement of policy or law. Therefore, we might consider that in lieu of an internal ability to provide welfare, receipt and subsequent distribution of foreign aid is a viable substitute for demonstrating a state’s ability to govern – at least within the polity.

Marrying this notion of foreign aid to policy prescription within the context of a post-conflict environment, Collier and Hoeffler (2002) find that aid and economic policy do not directly affect conflict risk or recurrence, but they do affect 26 the economic growth rate and dependence on commodity exports, two factors that do have an impact on the chances of conflict onset. This demonstrates that foreign aid is an important contributor to a peace process although not always directly tied to the political process. If intervention through foreign aid is a boon to state legitimacy, state power, and a potential contributor to the peace process11, then the intervention of an external peace operation – arguably a detractor from the state’s monopoly on power – should have some recognizable effect on that process. It is here, at the nexus of interventions, that I argue finding the suitable type of intervening force (UN-led, non-UN, etc.) and the right mix of foreign aid is most important.

It should go without saying that the endurance of peace is the ideal condition in a conflict-affected state, which explains the heavy focus of empirical work on peace duration, conflict renewal, or conflict spread as discussed above. However, the absence of violent conflict does not assure the health of a conflict-affected state, especially if that peace is the result of the continued presence of peacekeepers or infusion of aid. On the contrary, we might expect that if continuous intervention is the sole driver of peace, that peace has no potential for endurance. We should therefore look for other indicators beyond the absence of violence, that follow

11 I do not believe this aspect of aid necessarily holds true for all observers – particularly foreign investors. 27 intervention and demonstrate a return to pre-conflict stability. I suggest that measures of foreign direct investment (FDI) inflows can be used in this way.

2.3. Foreign Direct Investment - a proxy for success

FDI can be a confusing topic and it is often due to the terminology used. FDI is divided into two primary categories, portfolio (i.e. stock holdings – often referred to as Foreign Portfolio Investment) and non-portfolio (physical holdings or full/partial ownership of a firm inside another state). Non-portfolio holdings can be further disaggregated into inflows and outflows. Inflows, or the investment of foreign monies into the economy of interest is what this study focuses on. Unless specifically noted I will adopt the practice of using the terms FDI or FDI inflows to refer only to non-portfolio inflows of FDI.

Considering Collier’s highly influential research program that ties economic recovery to conflict cessation and prevention (1995, 1999; Collier & Hoeffler, 2002,

2004; Collier et al., 2008), it is no surprise that the rare FDI literature associated with conflict searches for the positive impacts of FDI. Bussman (2010), for example, finds that states who invest in each other are less likely to fight each other. However, the literature seems to be in disagreement over the factors that actually promote or detract investors in a post-conflict scenario. 28

2.3.1. The economic enabling environment and investment risk

The World Bank’s position is that investors are wary of post-conflict states because those states lack stability in all four pillars of investment: general security and stability, finance and infrastructure, workers and labor markets, and a regulatory framework and taxation (Mills & Fan, 2006). Here, the state’s “enabling environment” needed to attract FDI must demonstrate stable and secure institutions, governance, political economy, capacity and social capital. Yet other research suggests that financial conditions may do less to drive investor interest.

For example, Hayakawa et al. (2013) find the negative effect of conflict (what they classify as an indicator of political risk) on FDI inflows but their findings also suggest that the financial risk associated with the target state is not a major concern.

Accepting risk may be within the realm of some investors. As Dixit (2011) argues, some investors are simply accustomed to greater risk due to the nature of the states they operate in. While Dixit’s argument may be geared toward the developing state at peace, his point suggests that investors become accustomed to the political conditions of the state and that while they may not always detract investment, political considerations have primacy over financial concerns.

Furthering this point, Blanton and Blanton (2007) argue that investors look for adherence to norms such as human rights, while Appel and Loyle (2012) demonstrate a return of legal accountability (via post-conflict judicial systems) signals a return to normalcy. 29

Conflict recurrence is also a concern, and while some firms can invest in products like the World Bank’s risk mitigation insurance (MIGA, 2013) investors without the tolerance for risk that Dixit alludes to are unlikely to base their investment decision on a worst case scenario. Thus, only if foreign entities believe risk has been mitigated to an acceptable level and other components of the enabling environment are comparable to a pre-conflict condition, should we expect to see positive growth in FDI. Despite the fact that conflict is addressed within the FDI literature, nowhere is there any significant mention of peacekeeping, especially how variations in peacekeeping impact FDI or how physical and fiscal interventions interact to spur investment in conflict-affected states.

2.4. Summary

The purpose of this chapter was to provide an overview of our understanding of peacekeeping operations, foreign aid, and FDI. First, we see that the study of peacekeeping is relatively broad in the sense that research has attempted to describe or predict success or failure, identify the motivations behind deployments, and explain the extension of effects beyond the conflict-affected country itself.

We see that earlier works were limited in scope due to the availability of data, a continuing challenge if we hope to understand the totality of peacekeeping, but that more recent efforts to improve data collection has allowed research to expand into nuances like mission design, force construction, or the employment of 30 specialized peacekeepers such as intelligence experts. However, these nuances demand a greater understanding of peacekeeping forces themselves, namely what drives their performance, and whether that is different compared to non- peacekeeping missions.

The extant literature on foreign aid also covers a wide array of topics that include efficacy but are also segregated into the “benefits of” or “detriments of” bin.

That said, we also see a distinction between aid in conflict-affected states versus developing states, despite the fact that these may represent the same cases of interest. Additionally, the study of how aid dollars are targeted within the context of the cases is a common approach, as are the motivations behind aid donations. What the literature lacks is a full understanding of aid’s efficacy under a mixture of these conditions: conflict/post-conflict scenarios, variety in aid targeting, aid provision with or without serious scrutiny over its usage.

Finally, we see how research on foreign direct investment, specifically the smaller body of literature on investment in conflict-affected states, logically ties the topic to both peacekeeping and foreign aid. But, more importantly, the literature demonstrates that FDI is likely a good measure to test for success in both peacekeeping and aid interventions. This is because each intervention attempts to impose external influence on the economic enabling environment that promotes or impedes FDI. This is how we might use a measure like FDI to gauge the success of stabilization efforts as a whole. 31

In the next chapter I will introduce the theory that foreign aid and peacekeeping generate an interactive effect on stability. This effect is dependent on the specifics of each intervention and measurable by considering FDI inflows into a conflict-affected state.

Chapter 3

A theory on increasing stability in conflict-affected states through intervention

3.1. Introduction

This chapter presents a theory on how the international community can increase stability in a conflict-affected state through intervention. While the condition of stability can be thought of in various contexts, the concept of stability I will use is in the context of post-conflict states12 that have engaged in a peace

12 Throughout this chapter I will use the terms “post-conflict” and “conflict-affected”; the latter describes a condition that is necessary but not sufficient for the former. The use of the term “conflict- affected” appears to me to have come in to more common usage within the peacekeeping community over the past several years, likely because many states where peacekeepers are employed are still experiencing violent conflict to some degree and therefore not fully in what a layperson or even a policy-maker might consider a “post-conflict” status. My use of the term “conflict-affected” is done in an attempt to remain consistent with the current practitioners’ vernacular and does not imply that I 32

33 process.13 The definition will have its roots in an abstract construct based on a state’s political network and the oversight mechanisms employed to keep that network in check. This broad concept will then be narrowed down to one that parallels the concepts of promoting stability, or stabilization through intervention, that are currently incorporated in United States Government (USG) strategic foreign policy documents.

After presenting the definition of stability that I will be using for this project,

I present my theory on how stability can be increased through intervention by targeting the post-conflict state’s political network and the oversight mechanisms that govern it. I will present two tools of intervention common to the international community: foreign aid and peacekeeping operations (PKO)14, and I will argue how variations in the targeting of foreign aid and PKO design might affect those components of stability and, in turn, promote increased stability both directly and through an interactive effect. Furthermore, I will offer why we should see a

will be considering all cases where states are involved in conflict. The focus of this research is stability in post-conflict states which I specify as those conflict-affected states where the primary combatants have agreed to some formal cessation of hostilities and the international community has subsequently intervened. 13 For the purposes of this project a peace process means that the state and some or all of its former adversaries have reached an agreement to stop fighting in order to resolve their differences without resorting to violence. While the majority of the cases I will employ the empirical portion of the project involve civil conflicts it is possible for a peace process to exist between two sovereign states. 14 I consider peacekeeping operations to be any physical intervention with a military/police component that is deployed in support of a peace process at the behest of the host state and any other signatories to an official peace building agreement. 34 measurable difference in stability across the four time periods associated with conflict and intervention.15

The remainder of the chapter will focus on the potential variations in foreign aid targeting and PKO design. I will start with the basis of my theory, namely the motivations for intervention and how the international community has built these accepted response mechanisms for dealing with conflict-affected states. I will discuss how the international community can create variation in these interventions through their construction, and how these variations matter, not only in relation to their immediate objectives but also in relationship to each other. I will conclude the chapter by discussing the interaction I believe is key to successful stabilization efforts. This nexus of effects will result in increased stability if interventions are properly designed.

3.2. What is stability?

3.2.1. Stability in the abstract

Defining stability in the context of a post-conflict state is difficult because the term can be used, even within the laypersons’ vernacular, to describe the state in a variety of contexts ranging from regime survival to discord among political parties,

15 The four time periods are: pre-conflict, conflict, post-conflict intervention, post-intervention. I will specify post-intervention later to mean the departure of peacekeeping forces, not the cessation of foreign aid. 35 civil war, or even international relations. That being said, to define stability in the context of post-conflict states we can start by taking the nature and variety of these contextual situations into account. From there we can see that, at its core, stability describes an environment of interactions between actors.

Ake (1975, p. 271) suggests that interaction, rather than random contact, between actors within a society drives them to behave in patterns that are defined by the environment, somewhat predictable, and political in nature16. As such,

“political behavior is ubiquitous” in an organized society and this political behavior, potentially particular to the society itself17, is attributable to roles that define each actor and are carried out in an expected but “generally vague” (i.e. predictable but not definite) manner (Ake, 1975, p. 273). Ake suggests that the aggregate of these political role expectations forms a network that defines the society’s political structure or its political network.18 This political network facilitates the flow of expected political exchanges between actors. Key to Ake’s construct is that the roles and behaviors that serve as the foundation for a political network are governed by laws, customs, or practice. Ake argued that stability could be measured at a given point in time based on the number of violations to expected behavior that fell within

16 Here “political” suggests relevance to the power associated with making societal decisions, not solely those actions one might attribute to those in government or specify as politics. 17 Ake argues that societies themselves vary, and changes to roles and expected behavior occur within societies over time. Therefore, stability is relevant to the society itself; this could be extended to interactions between two or more states in a global system. 18 I elect to use the term “political network” to distinguish my interpretation of Ake’s construct from the original. 36 the confines of those bounding principles. Expanding Ake’s description slightly, we can say that political stability can be thought of as the “regularity of the flow of political exchanges” (Ake, 1975, p. 273) that is bounded by some oversight mechanism(s) identified and accepted by the society. This variation allows us to conceptualize that stability has two foundational components. First, is the balanced political network of interactions that are accepted and somewhat predictable.

Second is an oversight mechanism or boundary that acts like any set of rules or limits by defining the range of behaviors that are acceptable, preventing the network from varying outside of these expected or accepted behaviors, and informing the society when the network is either balanced or exceeding these socially accepted behavioral bounds.19

Recalling that roles and behaviors should be socially accepted but not definite, more lenient oversight allows for greater variation in the interactions or perhaps a more liberal interpretation of what is accepted by the society. Stricter oversight will limit variation making it easier for roles or behavior to exceed what is accepted by the society. Arguably, if the role of oversight is to prompt the network to return to accepted behaviors once it has varied out of bounds, it should be acknowledged that while the limits of socially accepted behaviors can be breached at any time, the system is able to self-correct and return to a balanced condition on

19 I use the term “boundary” but I do not imply that there is a physical limitation to behavior. Instead, the oversight boundary should be interpreted as the limits of socially accepted behavior. 37 its own. This offers an explanation of how the oversight mechanism not only provides direct impact on stability by limiting variation in the political structure, it also provides feedback to the society should the political network become unbalanced and exceed set bounds.

Political instability can be seen as the condition where the flow of political exchange is irregular, behavior is not occurring as expected or accepted by the society as a whole (i.e. behavior has exceeded the bounds). This would imply there is an imbalance in the system defined by a fault in the political network. Or, it could also be a situation where a deficiency within the oversight mechanism has allowed for the political network to migrate towards a condition of imbalance. This suggests that oversight not only limits variation in the political network (its direct contribution to stability) but it can also prompt changes to the network that will preclude the political network from exceeding the boundary (an indirect contribution to stability by affecting the impact of the political network). Similarly, because the oversight boundary is established by the society, it is conceivable that variation in roles and behaviors could alter the boundary itself meaning the political network would affect how oversight contributes to stability.20

20 Because laws, customs, or practices can change over time I do not suggest that the limits of socially accepted behavior are fixed. However, I do assume that the oversight boundary is not likely to change easily, dramatically, or quickly considering it has been developed over the entire history of the society. 38

If either contributing part creates or allows enough instability into the system, we should expect that it will, at some point, reach the threshold of what the society can actually endure. We might consider violent civil conflict as a situation that results when instability has surpassed the state’s capacity to endure unaccepted political behaviors and, as a result, the state itself breaks down in part or in total. For example, an irregularity in a state’s political network (e.g. government corruption) that precludes government leaders from behaving as the society would expect them to otherwise could motivate a spectrum of acceptable political acts or behaviors21 that represent the correcting function that oversight brings. If these accepted responses are unable to resolve what has been deemed irregular behavior and bring the network back into balance, a breakdown of the society itself (e.g. a rebellion) could be the final result.22 In this case, the role of a post-conflict stabilization intervention could be to rebuild the political network by defining or redefining acceptable roles and behaviors for all actors within the political network (e.g. honest government officials)23, redefining the limits of oversight (i.e. what is or is not accepted), or some combination of the two.

Furthermore, successful post-conflict stabilization would be indicated by a

21 These could include public debate, calls for reform, protests, or civil disobedience. 22 This does not imply that violent civil conflict only results from behavior linked to a government. The origin of violent conflict can be tied to the behavior of any number actors in the political network. 23 This example does not imply that all post-conflict stabilization is focused solely on the changes in the political behavior of the government. 39 measurable increase in stability that demonstrates those changes made will promote continued strengthening of the system post-intervention.24

It is important to point out that this conceptualization of stability does not preclude the possibility that an externally focused interaction could create a similar failure of the system. For example, a state that initiates conflict with another state would necessarily generate more irregular behavior within its own political network (i.e. societal decisions would be focused, in part, on an external conflict rather than those issues expected within the society). Instability would, in the context of this conceptualization, increase. While instability may not reach a level that threatens a breakdown of the society, the effect on the larger external system

(i.e. the instability imposed on the victim state) might prompt an external intervention aimed at restoring stability to the internal system (i.e. defeating the aggressor and forcing behavior back to accepted norms) that would also increase stability in the larger international system (i.e. assisting the victim state in its return to stability).

Applying an abstract construct is helpful in understanding that stability can be viewed as a condition dependent on a balanced system of interactions between actors in the society that are constrained by a mechanism that defines which

24 Post-conflict stabilization can be accomplished by the state itself. Although this study will only consider cases where external actors (i.e. the international community) intervene, this does not suggest the only way to resolve conflict, even violent civil conflict, is with external involvement. 40 interactions are accepted. However, applying this abstract construct generates several questions.

First, do these political behaviors extend across all aspects of the society – politics, economics, and social issues?25 Second, does the return of actors in a post- conflict state to accepted roles and behaviors, or even a redefined oversight boundary, imply that the state is now free from all violent conflict or even conflict- averse simply because it is more stable? To clarify, if rebellion is caused by the behavior of a highly corrupt government, does the absence of rebellion under a modestly corrupt government suggest stability is at a sufficient level to prevent future violent conflict? While the society may accept modest corruption and not rebel because other interactions or behaviors counter its effects, modest corruption could lead to conflict along different lines of grievance at a later time if it is not managed by oversight. At best it could be argued that the post-conflict state is now less susceptible to developing behaviors that might decrease stability and lead to violent conflict because of oversight. Third, supposing these changes in roles and behavior were the result of external influences (i.e. an intervention); who would judge which roles and behaviors should be accepted or what needs to be modified?

Is corrupt behavior acceptable if there is no consequence that demands or draws a

25 Economic behavior could include the government imposing higher taxes on select industries or labor unions entering into negotiations with management over wages and working hours. Social behaviors could include special interest groups raising awareness to their topic of choice in an effort to change public opinion or civic groups providing assistance to others in an attempt to subsidize state-sponsored support mechanisms. 41 response from an external actor? Furthermore, what conditions describe a satisfactory level of stability in a post-conflict state such that an intervention is halted?

These questions, particularly the lack of explanation on external responses to a state’s stability, are what makes an abstract construct less useful if we want to determine how stability can be increased through a real-world intervention. What we need is a practical conceptualization of stability that acknowledges the role societal interactions play but does so in a manner that precludes its reduction to simply one of socially accepted, predictable behavior; identifying measurable components and effects are essential. In order to accomplish this, I elect to constrain the abstract conceptualization of stability and the roles of the political network and oversight presented above by considering the practical conceptualization of stability currently employed by the United States Government in its response to conditions of instability in conflict-affected areas.26

3.2.2. A practical look at stability

Although the United States does not hold a monopoly on post-conflict stabilization efforts, it is a founding member of the United Nations (UN) and a permanent member of the UN Security Council (a body tasked with resolving conflict among the organization’s member states), and the world’s top provider of

26 The US Government does not conduct stabilization operations inside the United States. 42 foreign aid.27 Also, the US military has and continues to actively participate in a wide range of interventions ranging from unilateral operations to those that are UN- led.28 It should be noted however that the US Government continues to refine its conceptualization of stability and the act of stabilization in an apparent effort to improve on a process it has been engaged in for over seventy years. This suggests that experience has demonstrated how the USG approach to stabilization, and perhaps that of the international community itself, has been flawed to some degree.

The USG’s 2018 Stabilization Assistance Review (SAR) report acknowledged that the three primary US proponents of stabilization interventions, the US

Departments of Defense (DOD), and State (DOS), and the US Agency for

International Development (USAID) believed a “new and more disciplined approach to conducting stabilization in conflict-affected areas” was necessary (SAR, 2018, p.

4). This realization, resulting from an interagency strategic review of the problem set, suggests the US approach has thus far been less about how the US Government, as a whole, should approach this task and more about how each proponent would address its portion (security, diplomacy, or development) of a complex foreign policy question. A stove-piped approach like this is problematic if each proponent is working towards a common goal but doing so with a different conceptualization of what that final product should look like and what measures should be taken to

27 The US provided over $14 billion in Country Programmable Aid (CPA) or aid targeted at the country or regional level during 2016 alone. See: OECD (2018). 28 See Smith (2014). 43 achieve it. Until the SAR, this was not simply practice, the process had been codified in earlier strategic documents such as USAID’s Strategy on Democracy,

Human Rights, and Governance (DRG) (USAID, 2013), and the US DOD’s Joint

Publication 3-0 - Stability (DOD, 2016) where each organization not only defined their role in stabilization efforts but did so with varied definitions or approaches to stability.

According to the DOD document, stability can be defined as a:

“characterization of effects created by activities of the United States Government (USG) outside the US using one or more of the instruments of national power to minimize, if not eliminate, economic and political instability and other drivers of violent conflict across one or more of the five USG stability sectors (i.e., security, justice and reconciliation, humanitarian assistance and social well-being, governance and participation, and economic stabilization and infrastructure).”(DOD, 2016, p. ix) 29 30

A surface-level reading of this earlier DOD definition suggests that generating stability in post-conflict states can be accomplished by USG efforts alone, exclusive of participation from the state and other actors. While, the underlying executive guidance provided (DOD, 2009) dictated that the US military would be prepared to

29 According to Joint Publication 3-0, the five stability sectors represent those key focus areas for civil-military efforts. Civil-military efforts are defined in Joint Publication 3-57, Civil-Military Operations, as those military actions that “establish, maintain, influence, or exploit relationships between military forces and indigenous populations and institutions (IPI), by directly supporting the attainment of objectives relating to the reestablishment or maintenance of stability within a region or host nation (HN).” (DOD, 2013, p. ix) 30 Notably, the DOD definition states an intent to eliminate drivers of violent conflict but seems to support the recognition that only minimizing these drivers is an acceptable result. This suggests that no state is expected to be conflict-free but instead that there is a threshold of conflict that states can endure (allowing external actors to withdraw) and a threshold of conflict that the international community (in this case the US) will allow. 44 support a variety of actors (USG agencies, foreign governments, security forces, or international governmental organizations) in the conduct of stabilization activities, the language suggests that DOD support is independent and, at best, additive to other efforts, rather than integrated. Employing a different approach, USAID’s 2013 strategy focused on the concept that greater citizen participation or inclusion in governance and instilling more accountability from institutions and leaders promoted stability while mitigating threats against it. While these two approaches were not exactly divergent, they did suggest a disconnect at the strategic level within USG that arguably led to the 2018 SAR.

A key aspect of the SAR was a new USG definition for stabilization:

“an inherently political behavior that requires aligning U.S. Government efforts… toward supporting locally legitimate authorities and systems to peaceably manage conflict and prevent violence…stabilization may include efforts to establish civil security, provide access to dispute resolution, and deliver targeted basic services, and establish a foundation for the return of displaced people and longer-term development” (SAR, 2018, pp. 1,4). 31

In this new definition, stability is no longer construed as the product of what could be disparate actions, each with specified short-term goals.32 Instead, stability is the product of the conflict-affected state that is achieved with the help of the US

31 The report lists three lines effort: diplomacy, foreign assistance, and defense (i.e. military forces). This project does not look specifically at diplomacy but recognizes that diplomacy does play a role in the application of aid and the employment of military forces within a sovereign country. 32 Compared specifically with the DOD definition presented above. 45

Government. US Government effort are now presented as a coordinated33, whole-of- government approach to a whole-of-society condition. Alignment of effort demands communication between the proponents and a constructive approach, where the actions of one proponent are planned, resourced, and executed with the others’ actions in mind. By acknowledging “locally legitimate authorities and systems” this conceptualization of stabilization allows for processes (i.e. laws, markets, social practices), not just government officials, economic experts, or social leaders, to have a role in stability. Additionally, the stated role of the USG in stabilization efforts is to support the efforts of authorities and systems to manage conflict and prevent violence; this implies both the promotion of an oversight capacity, and an expectation that a level of stability higher than pre-conflict and conflict periods will endure beyond US intervention. As such, the new USG definition acknowledges that the way to increase stability and ensure it continues to grow after stabilization efforts end is to somehow affect what was identified above as the political network and the oversight mechanism of the post-conflict state.

Notably, the SAR report qualifies its findings in the notion that stability is context-dependent34, implying that the US recognizes some states will be more stable than others according to its own assessment. So, while the US expects to see measurable increases in stability resulting from their efforts, there is no expectation

33 This is not to say that previous efforts were done without communication between the three groups. Instead it suggests that efforts can now be seen as cooperative, rather than disparate efforts that provide a necessary response to the others. 34 See (SAR, 2018, p. 4). 46 that all results will be equal; as long as US-defined drivers of violent conflict are reduced or mitigated according to US measures, US objectives have been met and, by their definition, stability has increased. Arguably, this is problematic if the US misjudges the threshold of instability a state can endure before conflict returns and cease or modify an intervention too early. Finally, these strategic national policy documents clarify that US involvement in a post-conflict stabilization is first and foremost done out of concerns for US national security interests – not necessarily those of the conflict-affected state.35 What this tells us is that we should be wary of judging the success of stabilization efforts, or how much stability has increased, based on measurements provided by an intervening agent – this is an issue I will discuss further in the chapter.

3.2.3. A refined definition of stability

I now present a definition of stability that is directly relevant to this project: the condition in post-conflict states where political, social, and economic behaviors across the wide spectrum of a society are accepted within both the state and the larger international community such that the need for external intervention is deemed unnecessary.

35 It should be recognized that while minimizing violent conflict is presented as a primary goal of the United States in these documents; this may not be the primary goal of other states or entities that choose to intervene. 47

This definition stays true to the notion that stability is reliant on socially accepted interactions (i.e. those occurring within the boundary established by oversight) between various actors within the state that define its political network.

It also allows for stability and the inputs to stability to vary in accordance with what the state can tolerate before its ability to function independently is surpassed.

However, this variance must be within the accepted levels of stability that the broader international community expects the state to exist under.36 In the case of post-conflict states, this places the determination of increased stability under the auspices of both the conflict-affected state and the international community. This then allows post-conflict state stability to be judged by an external observer, not necessarily the intervening actor, based on measures that are specific to the state itself. Although this definition could be applied at a higher level (i.e. in relation to the accepted interactions between multiple states within the larger international community) this project and my theory are solely focused on achieving greater stability in post-conflict states.37

36 By this I suggest that the international community will only intervene when stability is so degraded that other states are being affected. This could be because of a spillover of conflict or refugees to an immediate neighbor, or the disruption of regional trade agreements, but it could also result from the pressures applied to governments by constituents who believe an intervention is merited. While this does not solely occur in conflict-affected states, this project only considers post-conflict scenarios as previously defined. 37 This does not mean I will not consider stability in post-conflict states that engaged in interstate conflict. It only suggests that I will not examine the stability shared between states involved in conflict with each other at this time. 48

3.3. A theory on achieving greater stability in post-conflict states through intervention

Using a definition of stability that highlights the role of a state’s political network and the oversight mechanisms that impose internal and external constraints on the system, we can now theorize how interventions aimed at increasing stability in a post-conflict state might be constructed and subsequently perform. Performance can be measured relative to all four of the periods associated with conflict and intervention (i.e. pre-conflict, conflict, post-conflict intervention, post-intervention38).

I posit stability is affected when interventions target a post-conflict state’s political network and supplement the state’s internal oversight mechanism. Each intervention has an independent effect on stability, meaning that if the international community elected to employ only one intervention, we should still see an increase in stability, but that increase will not be as great as when both interventions occur.

In cases where only one intervention occurs, we should expect increased stability when the following conditions are met.

Stability is more likely to increase when an international intervention promotes political, social, and economic behavior that meets accepted standards held by the international community. By this I suggest that the intervention should

38 Later I will clarify that this implies the removal of the external oversight mechanism. 49 be aimed at changing interactions across society to meet these standards. Stability is more likely to increase if the intervention aims to achieve this rather than returning to a condition like that prior to conflict (when conflict could not be avoided) or immediately subsequent to the end of hostilities (when stability is high enough simply to promote a ceasefire).

Alternately, stability is more likely to increase when an international intervention is employed to provide supplementary oversight capacity to the state’s internal oversight mechanism. This external oversight informs on current behavior and sets conditions for the internal mechanism to constrain future behavior.

Greater oversight should result in higher stability because the intervention places additional conditions on the conflict-affected state that must be satisfied in order for the intervention to end.

In situations when only one intervention is made, stability observed during the intervention period should be higher than that observed during the conflict period (when both components of stability likely have shortcomings due to the conflict itself) and during the pre-conflict period (when conditions were such that the components could not force the system back into balance). However, in those situations where the interventions described above occur simultaneously, an interactive effect is also generated that has an observable effect on stability.

In this case, an intervention aimed at changing behavior will result in higher stability if it is made under the conditions of increased oversight provided by the oversight intervention. That interaction should result in higher stability compared 50 to that achieved by either single intervention. Also, the interaction between the two interventions will create a higher level of stability than was observed during the conflict period, as well as during the pre-conflict period when the conditions of either component of stability were insufficient to prevent a breakdown of the system. As more effort is placed on changing interactions and increasing oversight, as discussed above, stability should increase.

In all of the scenarios discussed above, once stability is assessed high enough to end the oversight intervention, thereby relying fully on the state’s oversight mechanism39, we should expect stability to remain at levels above the pre-conflict and conflict periods but fall below that of the intervention period. This is because the added oversight provided by the intervention will no longer provide immediate feedback on behavior. As such, a lower level of stability is expected because behaviors will likely emerge that are tolerable in accordance with the state’s internal oversight mechanism but not ideal from the perspective of the international community. This simply suggests that an outside observer will likely see certain changes in behavior after the intervention ends as a reduction in stability.

With this argument in mind the question now becomes one of how these interventions might actually occur in a practical sense. As discussed above, the

United States presents a three-branch approach to a two-part problem set by

39 I classify this period the “post-intervention” period although the alternate intervention may be ongoing. This will become clearer when I associate the oversight intervention with peacekeeping operations and the behavior changing intervention with targeted foreign aid. 51 pooling the combined resources of its military, diplomatic corps, and international development agency. And, in its definition of stabilization, the USG offers its approach, namely targeting select aspects of the society or promoting certain actions through an application of US resources. I offer that any post-conflict stabilization intervention (US or otherwise) will, by definition, be limited to intervening along those two lines of effort relevant to the political network and oversight mechanism. To further simplify things, if we assume that diplomacy is an inherent requirement for any intervention40, we can group the remaining elements of national power available for stabilization efforts into physical and fiscal interventions.

Arguably, money and people will, by necessity, be applied to almost any aspect of a stabilization effort, but I suggest that each category of intervention has a practical implementation that is common throughout the international community.

In the context of a post-conflict stabilization effort, a fiscal intervention is most practically represented by the application of targeted foreign aid, while peacekeeping operations clearly typify a physical intervention used for stabilization efforts.

40 It should be noted that the US Department of State has authority over significant expenditures of foreign aid funding. I only imply that diplomacy, which can be conducted by any emissary, is necessary for either physical or fiscal interventions to take place. 52

By definition, foreign aid is a fiscal input41 or intervention provided by one country (or organization) to another country for the express purpose of affecting some aspect of that state’s behavior. Donors target select sectors of the target state through the infusion of monetary or in-kind donations in order to achieve their desired effect. The effect may be achieved directly (e.g. providing immediate humanitarian assistance to save lives) or indirectly (e.g. building social awareness on a topic of interest to the donor by funding civic groups). Regardless of intent, in the context of a post-conflict state we can assume the ultimate desired effect is increasing stability such that open-ended aid contributions are not required.

Peacekeeping operations are a physical intervention composed of military, law enforcement, and civilian experts. Like foreign aid, we can assume that no peacekeeping mission is designed to be indefinite in duration. Peacekeepers are deployed as emissaries of the international community, and active participants in assuring peace agreements are met. PKOs perform in accordance with a mandate that has been mutually accepted by the target state(s)42, non-state actors party to the conflict, and the sending agent. Missions can involve a wide variety of mandated tasks ranging from observing the physical compliance of treaties, demining operations, disarming combatants, supporting humanitarian relief operations, physically protecting civilian populations, or monitoring human rights issues.

41 While foreign aid can include “in-kind” donations those inputs still reflect a fiscal inject. Although aid funding may be manifested in physical outcomes or events (e.g. food relief, elections), I argue that these are predominantly the result of those fiscal injects. 42 A peacekeeping operation can be deployed to address interstate or civil conflict. 53

Considering the tasks PKOs perform we see how they can serve as a direct contributor to stability by imposing the international community’s definition of what is accepted behavior, but also an indirect contributor by informing the international community on changes within the state’s political network through direct observation.

Recalling the abstract conceptualization of stability being composed of two parts (the balanced political network bounded by an oversight mechanism), and recognizing, from the practical example of the United States, that stabilization interventions are whole-of-society problem sets requiring collaborative solutions.

We can see that foreign aid and PKOs not only represent practical means to affect stability but that they can be designed in a way that is constructive in order to address their independent objectives as well as an overarching result of increased stability.

My theory accounts for how these two independent but parallel interventions, designed to affect different components of stability in conflict- affected states, can create an observable effect on stability but, more importantly, that their design creates an interactive effect that should positively contribute to stability if done correctly. Two key assumptions I make are that the interventions are not mutually exclusive, nor are they necessarily zero sum – donor states can contribute to peacekeeping and foreign aid because each intervention draws from different resource pools. Additionally, it is important to remember that each intervention has its own independent goal or objective even though an overarching 54 desire for increased stability in the target state might drive the donor’s strategic decision-making.43 This suggests, as discussed earlier, that we can observe the effect of each independent intervention on stability. However, due to the independent and specific nature of each intervention we cannot look for that effect using a measure specific to each individual intervention.

Peacekeepers may look only at the completion of mandated tasks as demonstration that the operation is moving the conflict-affected state towards a level of stability desired by the sending agent;44 this also assumes that the mandated tasks accurately reflect the needs of the state to reach that condition. Similarly, aid donors may only look at the short-term accomplishments that aid is targeting (e.g. free and fair elections, newly constructed schools, refugee resettlement) to make a similar determination. In both cases, the donor serves as the primary judge of their accomplishments. Granted, each intervention will have its critics in turn, but the same problem arises; the interventions will most likely be judged in accordance with their stated short-term objectives rather than if they have contributed to a measurable increase in stability. This study offers a new approach to understanding the effects of these interventions on post-conflict states by considering their

43 Here I remind the reader that peacekeeping missions have specific tasks defined or mandated by the authority that employs them while aid funding is most likely tied to a specific program or project. 44 I use the term “sending agent” to represent the state, alliance, or international organization that deploys the PKO. 55 independent contributions to stability and how their interaction generates an observable effect on stability.

The remainder of the chapter will cover how and why the international community uses financial aid and PKOs as intervention methods in post-conflict states and offer more explanation of how each intervention can be employed.

Because we know a great deal about the independent role that foreign aid has in regard to stability and how variations in contributions matter I will briefly layout how foreign aid targeting matters in the context of this project. I will then spend significant effort to justify how and why variations in PKO design matters in the context of this research. This is necessary because, as stated previously, PKOs are predominantly designed to perform mandated tasks that revolve around security issues or other military-specific issues; this project is suggesting an alternate benefit that could impact how future operations are constructed.

3.4. Why does the international community choose to intervene?

The dramatic increase in the deployment of PKOs to conflict-affected states immediately following the Cold War, coupled with a diversity of targeted aid programs and donors focused on those same countries, demonstrates the international community’s collective perception that external interventions can 56 successfully increase the level of stability in almost any state.45 However, the creation of the United Nations and its Security Council, whose primary actions are geared at promoting and ensuring peace between or within the organization’s member states, affirms these physical and fiscal interventions were accepted components of international norms long before the 1990’s. The predominant difference between many earlier interventions, those of the post-Cold War era, and what is now recognized among the international community as the post-civilian protection mandate and subsequently the post-9-11 eras, is a marked decline in the number of post-interstate conflicts, compared to civil conflicts, that have resulted in the deployment of a peacekeeping operation. 46

This shift in both the nature of conflicts targeted by post-conflict stabilization interventions and that of peace-seeking belligerents brought about new norms such as the inherent expectation to protect civilians from any harm posed by the conflict resolution process, and the emergence of non-state, third-party spoilers as significant challengers to peace agreements. These third-party spoilers are more commonly recognized as armed groups or private militias but also include what are identified in the post-9-11 era as terrorist organizations. The motivations of any

45 I am not asserting that this is the only reason PKOs or greater focus on international aid have increased. I simply suggest that the increase in both demonstrates the perception that interventions, in general, can build stability and that these are two forms of intervention that have become or continue to be used more since the end of the Cold War. 46 Between 1946 and 1990, 20 of 49 (41%) peacekeeping missions were deployed in response to some form of interstate conflict, between 1991 and 2013 (the upper limit of the dataset used for this project) 10 of 129 (8%) were deployed after interstate disputes (Bellamy & Williams, 2015). 57 third-party spoiler can range across a spectrum of religious or political ideology but can also include more basic criminal inclinations resultant from the lack of local government control either brought on by the conflict or exacerbated by it.47 Despite what is arguably a paradigm shift in the conditions that define post-conflict stabilization, there has been little deviation from the approach used by the international community in conflict-affected states since the 1940s. The international community’s common knowledge of the post-World War II occupations of Germany and Japan could explain why this perception exists.48

For the decade following the end of World War II both Germany and Japan were forced to deal with degradation of their pre-war industrial infrastructure.

Their viable or educated workforce was depleted, and the monetary losses resulting from waging and losing what approached a decade-long, expeditionary war effort left them unable to return to pre-war self-sustainability without intervention. In each case the Allies suspended established bureaucracies and replaced them with military governorships whose mandates were aimed at rebuilding the defeated

47 Armed groups in the Democratic Republic of the Congo (DRC) fight for control over areas with limited government presence. The United Nations Organization Stabilization Mission in the DRC (MONSUCO) is heavily focused on countering the threat these armed groups manifest in an attempt to maintain a peace, fraught with resurgent violence, established after a series of rebellions that ended with “free and fair elections” in 2006. https://monusco.unmissions.org/en/background, accessed October 1, 2018. 48 Neither occupation of post-World War II Germany or Japan represent conditions identical to the vast majority of post-conflict cases considered in this study. They were more about state-building, not stabilization or peacekeeping efforts per se. However, the transition from military occupation and governance to general oversight and subsequent transition to local governance over a period of multiple years, coupled with the infusion of targeted foreign aid, offers a parallel conceptualization of more modern post-conflict interventions characterized as stabilization efforts. 58 states in a manner that would preclude their ability to wage future wars. Each state was subject to a reconstruction effort that included military occupation and the influx of targeted aid spending. Key to each plan was the goal of a return to stability that would result in self-administration and self-reliance as newly constructed democracies that were, by design, conflict-averse; as Lake(2016, pp. 81-85) points out, this was aided by the fact that those post-war democratic governments of both

Germany and Japan were heavily influenced by the Allies who oversaw their construction. These efforts were costly in monetary and military terms49 (as well as a prolonged loss of autonomy for Germany and Japan) but in hindsight these costs have averaged out to highly positive outcomes.50

Although they are not representative of the majority of more modern post- conflict stabilization interventions, post-war reconstruction in Germany and Japan have come to serve as hallmarks for successful state-building operations (Lake,

2016, p. 3; SSI, 2008) such that the Marshall Plan, the US reconstruction plan for post-war Germany, has become a model for comparison in several modern post- conflict scenarios (Mills, 2014, pp. 384-387). While this viewpoint has the advantage of time (allowing us to potentially overlook some of the challenges encountered during execution) the political reformation, social restructuring, and

49 Total US assistance, in 2005 constant dollars, to Germany and Japan, 1946-1952 was $29.3 billion and $15.2 billion respectively (Serafino et al., 2006); as of 2018, US military forces remain based under bi-lateral agreements in both Germany and Japan. 50 In 2018 Germany and Japan’s economies ranked 3rd and 5th respectively in the Global Competitiveness Index 4.0, (Schwab, 2018). 59 economic growth we continue to observe over 70 years later serve as an example of how post-conflict interventions can lead to positive results.51 However, despite our collective experience in this field we continue to observe what might be termed

“failed interventions” in post-conflict states, meaning that some states failed to maintain stability independent from external intervention and hover on (or cross over) the edge of violent conflict that threatens the state’s structure for what is an indefinite period. Two questions arise when we consider these failures. First, was the World War II generation simply fortunate or can we actually design interventions that really work if we are not able to redesign governments, rewrite constitutions, or make the key decisions on how a conflict-affected state will operate after the international community departs? Second, can we know if interventions are working in the short-term when patience for resolution wanes quickly and the desired outcomes are long-term in nature?

A contemporary case such as Liberia illustrates the challenge of determining success in real time. Liberia has seen significant challenges in establishing any sort of marked stability despite a series of interventions following its 1989-1997 and

1999-2003 civil wars. Liberia’s population remains predominantly trapped in abject poverty while corruption and political violence are reportedly commonplace

(BBC, 2018). Because of these protracted issues, as early as 2016, many Liberians

51 These results may solely reflect the desired end state of the occupying countries and those who took control after local governance was restored. 60 began voicing concerns over a potential return to conflict following the scheduled departure of the United Nations Mission in Liberia (UNMIL) (Pilling, 2016). These concerns were notably echoed by then President of the Economic Community of

West African States (ECOWAS), Marcel de Souza, who publicly alluded to concerns over Liberia’s perceived inability to secure the October 2017 elections absent UN or

ECOWAS intervention (ECOWAS, 2017). The overall concern for the safety and legitimacy of the 2017 elections, as well as the safety of Liberian citizens, resulted in a final extension of UNMIL’s mandate through those elections and the post-election period to ensure a safe transition for the winning party (UNPS, 2016). Notably, a key factor in the final mandate renewal of UNMIL was the perception by the United

States52 that Liberian institutions remained fragile and subject to corruption and impunity despite international efforts (UNPS, 2016). The detractors to stability which average Liberians, Mr. Souza, and Security Council members were concerned about existed despite a 15-year physical intervention and the international community’s subsidization of Liberia’s annual budget through foreign aid.

According to a 2016 report by AidData, during the 2009-2010 fiscal year

Liberia received $449 million in foreign assistance while its official budget was only

$374 million (Parks & Kabada, 2010). The report suggests a major concern with

Liberia’s receipt of foreign aid was that the majority of aid funding was received

52 The United States is the traditional “penholder” for Liberia policy within the Security Council The term penholder refers to the Security Council member who drafts and coordinates policy documents across the various committees and subcommittees of the Council. 61

“off-budget” meaning donors directly funded agencies (NGOs or contractors), who executed projects on their behalf, rather than routing funds through state agencies charged with fiscal oversight or project management. Parks and Kabada suggest that this sort of government circumvention does little to promote the development of viable and sustained institutions needed for long-term stability, yet it remains an accepted practice when donors are concerned about the safety of funds in the hands of an unstable conflict-affected government.

Despite the bleak outlook for long-term levels of increased stability that the

UNMIL case suggests, the study of peacekeeping interventions has confirmed the presence of PKOs, on average, reduces the likelihood of renewed conflict (Fortna,

2004a, 2004b; Fortna & Howard, 2008). It is therefore understandable why the international community accepts the physical presence of peacekeeping operations as a viable means to assist with post-conflict stabilization efforts and why states are willing to call for the deployment of these organizations or deploy their own.

However, as the Liberia-UNMIL case demonstrates, the implication on long-term levels of increased stability following the departure of PKOs is unclear.

A similar debate arises when we consider the provision of foreign aid. If we recognize that the notion of foreign aid intervention is to temporarily subsidize a state’s ability to function across certain sectors of society (in the abstract conceptualization we said this was accomplished by promoting accepted roles or behaviors) it is possible to suggest that any state receiving aid will remain dependent on aid unless the state becomes self-sufficient. This development of self- 62 sufficiency and a return to stability arguably represents the goals of donors that should extend into all targeted sectors ranging from humanitarian issues to governance and security. As with a physical intervention like peacekeeping, the question becomes whether or not stability is high enough to endure if and when aid is shifted across sectors, reduced across all or certain sectors, or completely eliminated.53

The reality these lingering questions imply about the utility of peacekeeping and foreign aid is disheartening because it implies that in some circumstances an enduring presence of peacekeepers and indefinite injections of aid may be necessary in order to ensure long-term stability. And, while this might be a reality for select cases, the ability of the international community to provide indefinite support across the entirety of conflict-affected states is likely limited by individual donor political will, resource capacity, or even the tolerance of respective electorates or contributors.

Subsequent sections will build on the extant literature that demonstrates development-targeted aid leads to greater post-conflict stability (Collier, 1995;

Collier & Hoeffler, 2004; Savun & Tirone, 2011), while a security-focused approach to aid targeting may be detrimental. While the literature typically looks at development or security in a very specific sense (i.e. targeting sectors such as

53 I will discuss later how certain aspects or variations in PKO design and foreign aid allocation can result in higher levels of stability. 63 education or economic policy vs. defense spending), development aid, in terms of this project, would be those contributions that aim to redefine roles or change behaviors within the society in order to prevent a future collapse of the system as a whole.54 Foreign aid donors may only consider increased stability as an overarching or added benefit of their efforts but, as discussed above, affecting the political network in this way should increase stability.

Oversight’s contribution to stability, and the idea that PKOs can serve as a physically present supplement to existing oversight mechanisms has been presented above. Like foreign aid, the manner in which PKOs are designed affects their contributions to stability but more importantly, PKO design plays an important role in overall post-conflict stabilization efforts. I will offer various options available for peacekeeping operation design with special emphasis on the role that the United

Nations has in a mission’s authority to operate in the host country. I argue that the

UN’s level of involvement in a specific peacekeeping mission is a significant factor in determining the degree of international oversight that a mission applies to the targeted post-conflict state. Other factors related to the composition of the force will also play a significant role and are addressed below. I suggest that the level of oversight derived by the aggregation of these characteristics has a varied effect on

54 Here the study will depart slightly from the traditional conceptualization of development aid by treating governance issues (i.e. rule of law, election issues, etc.) as an independent aid category. This approach allows for a more nuanced analysis of aid in post-conflict scenarios by addressing the impact that the larger body of development aid has on the state’s political network. 64 the successful implementation of targeted foreign aid. If aid promotes development and is applied under increased oversight, we should see a positive effect on stability.

3.5. Choosing from the intervention menu

Under most circumstances PKOs and directed foreign aid contributions are independent interventions. According to a senior aid programming officer with the

United States Agency for International Development (USAID), decisions to allocate aid at the strategic policy level may be influenced by the presence of a peacekeeping operation but there is no direct link between a PKO (specifically how missions are constructed or employed) and the donor (i.e. state donor) community.55 This is difficult to accept considering the donor could contribute both peacekeepers and development funds, unless we consider each type of intervention to be encompassed in its own independent bureaucratic process operating under a broad foreign policy umbrella. Here PKOs and foreign aid contributions represent pieces of the larger post-conflict stabilization effort addressed previously.56 While these processes operate simultaneously, they remain independent; decisions to change the characteristics of either intervention are driven by factors directly attributable to their specific situation.

55 Interview with USAID officer, 2017. 56 I do not demand that a formal stabilization plan has been conceived. Instead, I use the phrase “stabilization effort” to suggest that the international community has a collective effort that may or may not be coordinated that will contribute towards increased stability in the post-conflict state. 65

Although PKOs and directed aid have independent objectives (i.e. fulfilling a

PKO mandate or a sector-specific aid project) that generate independent impacts on stability, those impacts on stability should change if aid targeting and PKO characteristics vary. Recalling how oversight affects the political network, the simultaneous execution of each intervention suggests an interactive effect on the level of stability achieved is inevitable but also subject to the variations in either aid programming or PKO design. This means a stabilization effort, where foreign aid is targeted to address stability enhancing aspects of society (i.e. development focused aid) during the deployment of a PKO designed to promote the greatest amount of oversight, should generate a higher level of stability than an effort that employs only one intervention or one where aid is poorly targeted and PKO oversight is lower.

This research project examines stability conditions across all four periods of conflict, meaning it is possible that foreign aid will be applied in those periods where PKO oversight is absent (pre-conflict, conflict, post-intervention). However, no case under investigation represents one where no PKO was deployed. This is because understanding the interactive effect on stability created when targeted foreign aid is applied under varied PKO oversight conditions is absent in our current understanding of post-conflict interventions. In order to suggest that a successful post-conflict intervention is attributable to this interactive effect we should briefly consider why oversight, in general, is a condition necessary for any foreign aid to achieve its intended goals. 66

To facilitate a successful stabilization effort, governments57 must be held accountable for resource allocation and encouraged to shift those resources away from those conditions that led to conflict. Neither of these propositions are novel concepts. The role of oversight in keeping political actors accountable to those who place or keep them in power is well-covered in extant literature on democratic institutions (Strom, 2000; Strom & Mueller, 1999); and Collier (1995) argued via the peace dividend how post-conflict states who focus on improving society through development rather than reinvesting in their security apparatus (which I suggest equates to maintaining a post-conflict status quo) experience the economic boost needed to ensure enduring stability. However, our understanding of these topics with regard to how the international community might impact this process via their choices in intervention is limited. The international community has a large menu of intervention options to choose from when it designs a post-conflict stabilization effort. The following sections offer possible options and why those selections matter.

57 It is feasible that non-government actors can not only control territory and resources following a conflict but do so under the terms of a cease fire agreement or peace accord. Examples include the Moro Islamic Liberation Front (MILF) in the southern Philippines, who were given control over specific areas as part of the peace process with the Philippine Government, and pro-Russian separatists who forcibly maintain de facto administrative control of eastern Ukraine despite those regions still falling under the sovereignty control of the Ukrainian state. 67

3.6. Targeting foreign aid to change behavior

Earlier I argued that foreign aid should be targeted to affect select sectors of the post-conflict society if we expect to see increased stability over that witnessed during conflict conditions. If the international community is seeking greater stability it would arguably desire to focus not only on ensuring roles and behaviors are accepted but also moving those behaviors away from those that led to or immediately resulted from conflict. I suggest that this notion is demonstrated when foreign aid efforts support development goals rather than security goals alone.

As mentioned above, the notion that development-focused aid generates higher levels of stability than security-focused aid is established in extant literature

(Collier, 1995; Collier & Hoeffler, 2004; Savun & Tirone, 2011). We could understand if an aid recipient’s first order of business would be to ensure their own defense to secure gains achieved during conflict. This could prompt them to devote significant national resources (and aid) to the security sector to lock in conditions that are favorable to them. And, knowing that aid donors make decisions based predominantly in their own interests (as demonstrated by the US example) they might also desire to channel aid into security spending for similar reasons

(assuming the security of the target state is a security concern for the donor).

However, focusing solely on security would lead to the reinforcement of behaviors that contribute to a level of stability just above that during conflict. Even if oversight is increased, that oversight is only emphasizing conditions that, at best, should only lead to minimal increases in stability. 68

Development, on the other hand, suggests changing behaviors in order to improve on conditions at the end of conflict rather than maintaining them. We know from Collier’s study of the peace dividend (1995), that a reduction of spending on defense and the redistribution of resources into non-security issues (i.e. rule of law, elections, etc.), economics, and social programs is likely to boost the economy and overall recovery. We can see how stability should increase from this approach and how greater oversight would promote this increased stability by informing on the progress being made.

We expect this boost to stability even though aid programs and goals can vary widely. For example, the ultimate goal for programs centered on rule of law, might be aimed at improving how the state applies and enforces law across all aspects of society. Governance aid focuses on improving bureaucratic efficiency, promoting communication between the state and the populace, or ensuring minorities have a voice in policy making. Aid for social programming may be totally devoid of government involvement but can promote civic action groups or education in an effort to bring about greater participation in society, affect employment opportunities, or improve markets. Although the goals vary, these programs are associated with improving institutions that promote cooperation between the state and the populace and within the populace itself.

Although these examples are typical goals for any development aid program; targeting certain sectors in a post-conflict state should generate different effects than we might observe from the same sort of targeting in the case of a developing 69 country. This is because developing states will likely have well defined challenges to state institutions such as corruption, poor economic policies, etc. The post-conflict state is not as likely to offer a clear picture of those limitations; institutional shortcomings may have only been brought about recently due to the conflict itself

(Mills & Fan, 2006). Additionally, aid will likely be needed to address the physical and non-political damage of conflict such as degraded or destroyed infrastructure, social distress, or disenfranchisement of the defeated. This only serves to suggest that development may take on a broader concept in a post-conflict state than a developing state, so how aid is targeted will necessarily be different between these two situations.

Assuming that resources (national and foreign aid) will be directed to both security and development, the difficulty then becomes suggesting where aid should be prioritized. And, from the example of Liberia, where donors reportedly curtailed the government’s direct control of aid funding, a concern is that aid provision actually inhibits the development of institutions needed for long-term stability.

Returning to the basic premise behind foreign aid, we would expect that those sectors needing the most aid would be targeted. For example, humanitarian relief is likely to be high on the list of aid targets. While this type of aid is likely necessary, and provision could allude to government competence, it is arguably less important to long-term success of the intervention where investment in changing institutions

(i.e. development-focused aid) is key. 70

Notably, Collier’s economic peace dividend is a delayed benefit because of the time it takes to rebuild infrastructure, industry, and the workforce. However, the post-conflict state should move toward recovery more rapidly than a developing state when more aid is directed into non-security sectors. This occurs because the peacekeeping mission deployed to the state serves as the supplemental oversight mechanism necessary to inform on and restrict behavior that might prove detrimental to increasing stability. As the following sections will demonstrate, the international community has a significant capacity to model PKOs in a manner to gain the greatest amount of oversight available.

3.7. Scrutiny, state behavior, and peacekeeping options

In order for PKOs to provide an oversight function they must operate with some degree of autonomy and authority separate from the authority of the target state. While peacekeepers require some degree of acceptance by the target state58, they operate under the credibility bestowed by their sending agent and defined by their mission mandate. A PKO can therefore be considered a physical extension of the sending agent itself. And, by conceptualizing the PKO as an extension of its sending agent, the roles of the PKO would include informing the sending agent about the operational environment it is exposed to as much as it is about the day-to-

58 The reference to the “state” includes those former belligerents who have signed a peace accord with the current regime or other adversaries. Regardless of the final post-conflict regime’s construct, signatories to a peace accord have accepted the state as the ultimate authority. 71 day efforts at keeping peace. Fortna (2003) suggests that reducing uncertainty over a former opponent’s behavior is a key factor in preventing a return to conflict. A logical extension of Fortna’s argument is that PKOs, acting on behalf of the sending agent, can reduce uncertainty over a wide variety of state behaviors and comment on the immediate impact of those behaviors. Here the PKO acts as an oversight or scrutinizing mechanism by providing the sending agent with direct insight or judgements regarding the operational environment.

As discussed above, accountability matters between the state and the constituency. However, to assert that peacekeeper oversight has a direct influence on the post-conflict environment (an environment primarily driven by the state), a necessary assumption is that states consider the external response that increased scrutiny over its level of accountability might bring (e.g. some form of sanctions) as a motivator or detractor for cooperation and adherence to established norms within the international community. The first Liberian civil war (1989-1997) demonstrates how PKOs may have drastically different mandates to achieve short term objectives but fail to create an environment that promotes long-term stability.

3.7.1. PKO variety in action: a look at the first Liberian Civil War

In 1990, under the auspices of a mutual security agreement, the Economic

Organization of West African States (ECOWAS) deployed an armed intervention, 72

ECOMOG59, to address the outbreak of conflict between the Samuel Doe regime

(who himself ruled Liberia following a 1980 coup) and rebel forces under Charles

Taylor. The mission’s initial objective was to forcefully halt rebel advances and stabilize the country in support of Doe. The intervention was only partially successful. Taylor’s forces were prevented from taking total control of the country, but Doe was captured and killed by a splinter rebel group in late 1990, prompting

ECOWAS to establish an interim government headquartered in neighboring Gambia.

Liberia remained in conflict until 1993 when ECOWAS negotiated the

Cotonou Agreement between the interim government, Taylor’s National Patriotic

Front in Liberia (NPFL), and remnants of Doe’s regime under Major General Alhaji

Kromah (UNSG, 1993). The cease-fire prompted the UN Security Council to deploy its own observer mission (UNOMIL) composed primarily of 303 military observers60 to oversee ceasefire compliance, support UN humanitarian operations, and report on humanitarian conditions or violations of humanitarian law (Jennings, 2015;

UNSC, 1993). Beyond coordination, particularly with military engineering issues and disarmament efforts, the two missions had little direct crossover such that

ECOMOG could not provide security for UNOMIL observers.

59 ECOWAS Monitoring Group in Liberia (ECOMOG). 60 This was the first UNPKO to deploy in conjunction with another peacekeeping force. Originally mandated with a maximum deployment of 398 observers, UNOMIL would draw down due to violence and lack of observer security to a minimum of 92 observers (UNDPI, 1997, 1998). 73

By 1997, despite periods of continued factional fighting and what qualified as a conflict-induced humanitarian crisis, ECOMOG and UNOMIL successfully oversaw the election process that put Taylor in the presidency, effectively ending their mission and prompting withdrawal. While the election process was internationally recognized, conditions within Liberia remained tenuous through 2000 when the anti-Taylor Liberians United for Reconciliation and Democracy (LURD) began what would become the second Liberian civil war.

UNOMIL and ECOMOG represented two categories of peacekeeping mission61, UN-led and UN-authorized respectively. Each mission performed portions of what a single mission might be tasked with on its own; ECOMOG fulfilling troop-intensive patrolling and engagement at the tactical level while the smaller UNOMIL observer force focused on higher level monitoring of major events such as disarmament or investigating criminal allegations. With neither mission subordinate to the other each had its own mandate-specific information requirements to report, and its own sending agent to report to. And, while neither mission failed its respective mandate, the UN Security Council would soon impose sanctions on the Taylor regime for supporting rebels in Sierra Leone, implying that once scrutiny (within Liberia) had been reduced, Taylor’s behavior reversed. Faced with increasing conflict and an ECOWAS agreement to provide more peacekeepers

61 ECOMOG was technically not a peacekeeping force until the 1993 ceasefire. 74 as a precursor to a larger UN-led effort, Taylor, who had been indicted for war crimes due to his support of rebels in Sierra Leone, fled the country.

3.7.2. Choosing levels of oversight

Conflict-affected states may elect or at least heavily sway the decision to invite one category of peacekeeping mission over another to encourage or prevent higher degrees of oversight or scrutiny. The Liberia case, as well as those cases in which smaller regional interventions are advocated over larger international missions, may be a direct example of state leaders hoping to influence the degree of oversight they will be subject to. Initially, Doe’s acceptance of ECOMOG was more about regime survival than peacekeeping (the fragile peace was forged and then enforced by the intervening mission – only after Doe’s death). But Liberia’s prior agreement’s with ECOWAS regarding external intervention suggested Doe believed his neighbors would provide more favorable terms than the UN. Subsequently,

Taylor’s decision to flee Liberia with the knowledge an intervention was burgeoning and that it would transition to an UN-led effort suggests that Taylor, having direct experience under both types of PKO, recognized his outlook was bleak.

Peace-seeking states or belligerents do not always seek lower levels of accountability and may actually desire higher scrutiny to ensure their former adversaries comply with terms of a peace accord. A more recent example of former belligerents seeking higher accountability comes from the 2016 peace deal between the Columbian government and the FARC that includes the invitation of a UN-led monitoring mission (UNN, 2016). Arguably this caveat in the peace plan was 75 included because Bogota and the FARC recognize the impartiality of UN-led operations, and they are willing to endure higher scrutiny if it guarantees the other side will be similarly monitored.

As noted in the discussion on targeted aid, the oversight imposed by a PKO becomes highly important as aid is injected into the post-conflict state. The targeting and reception of aid within varied levels of uncertainty, where uncertainty is determined by the ability of the PKO to scrutinize the environment, impacts reconstruction efforts overall. Anecdotal evidence62 suggests that PKOs63 are rarely concerned with the management or execution of foreign aid (a responsibility passed from the donor state to partnered non-governmental organizations (NGOs)) or the fiduciary dealings of the post-conflict government. Instead, peacekeepers are typically focused on the proper execution of their mandate. However, even if the mandate driving an operation has little to do with monitoring the application of aid or a state’s fiscal responsibilities, with greater attention on the state’s behavior by a wider audience (e.g. the PKO’s contributing states) we would expect its use of public resources to fall in line with donor expectations. As suggested by the UNOMIL case, each variety of PKO characterizes its own level of oversight. This variation in scrutiny or oversight is the peacekeeping “contribution” to the concept of stabilization I have presented.

62 Based on interviews with prior U.S. PKO participants and intelligence analysts. 63 Specifically, the military component if in like some UN-led missions they are composite in nature. 76

3.7.3. Building variation in PKO scrutiny

Two primary factors drive the level of scrutiny that a PKO imposes on the post-conflict state: composition of the force itself and the level of UN participation or involvement in the mission.

Force composition (particularly strength and breakdown of peacekeeper type) has been recognized as promoting post-conflict peace duration (Hultman et al., 2015) and key in preventing the spread of conflict (Beardsley, 2011; Beardsley &

Gleditsch, 2015). The mechanisms behind these effects have been identified as the

PKO’s ability to reduce information gaps or the ability to enforce mandates.

Although numbers and breakdown are logically important, so too are the finer points of the composition such as the trained expertise of the peacekeepers – a factor that goes further than simply the designation of “troop” “police” or

“observer”. More important however is that the degree of UN involvement offers insight into more than just who authorizes a PKO, it also provides insight into how the mission contributes to international scrutiny.

3.7.4. Why United Nations involvement means greater scrutiny

Three factors determine how the degree of UN involvement contributes to the variable level of effective oversight or scrutiny provided by peacekeeping operations in a post-conflict environment. First is the ability of the PKO (and its sending agent) to collect and process information about the operational environment – this capability can be referred to as generating peacekeeping 77 intelligence (PKI). Second is the breadth of access to that intelligence, or the number of external actors who share the intelligence. Third is the enforcement capacity of the intervening actors, or their ability to hold former belligerents accountable for their behavior.

3.7.4.1. Peacekeeping intelligence capability

According to Milgrom et al. (1990) knowledge about an actor’s past actions promotes their honest behavior because it allows their counterparts to decide if a trust-built relationship can be maintained. As such, effective decision-making requires access to information that has been vetted for accuracy and relevance. This truism is most challenging in situations such as PKOs where a decision-maker64 may have limited access to data taken from the operational environment and lacks sufficient resources to translate the information that has been collated in appropriate categories into usable intelligence through critical analysis and the production of thought-provoking intelligence-driven products. Considering this challenge through the lens of an international organization like the UN, a conglomerate of multiple self-interested states each possessing varied levels of

64 A decision-maker here would be any authority that may rely on information obtained from a source they do not fully control in order to make their final decision. In terms of a PKO it could be an authority that represents the sending agent (e.g. United Nations, African Union, Troop Contributing Country) and makes decisions about PKO design or employment. It could also include an authority making decisions about aid targeting based on this information.

78 intelligence capability, demonstrates why the ability to generate peacekeeping intelligence is vital to the level of scrutiny missions can provide.

While senior UN leaders have come to recognize the importance of intelligence support to PKOs - particularly since the end of the Cold War, the organization has traditionally shied away from employing overt intelligence efforts

(Dorn, 1999, 2007). Instead UNPKOs, the UN Department of Peacekeeping

Operations (UNDPKO), and ultimately the Security Council, have relied on the intelligence apparatuses (particularly the analytic capacity) of the troop contributing countries or those member states with the willingness to share

(Hennessey, 2007). Recognizing that reliance on external intelligence processes can lead to poor decisions,65 and that intelligence products are, by nature, judgements or predictions based on information available and the analytic expertise of the provider, policy makers must decide which reports they have confidence in if they plan to include them in their decision-making process. This decision over reporting will be based on their opinion of the provider of the intelligence (meaning their belief that the provider has access to reliable information which serves as the foundation of a finished intelligence report), and that any assessment is made

65 Although it was not intended as a stabilization effort, an example would include the United States’ politicized pre-2003 invasion assessment on Iraqi weapons of mass destruction. Before the US-led invasion, this intelligence was presented publicly to the Security Council. Although the effort failed, Great Britain and Spain were convinced enough to support a UN resolution that would prompt UN- authorized action against Iraq; Great Britain, Spain, Australia, and Poland among others eventually contributed to the US-led invasion or post-invasion stabilization efforts (ACA, 2003; Goodman, 2003). 79 without attempting to sway their decision (i.e. being politicized). Additionally, the policy maker must consider whether or not the argument being made in an analytic report is sound based on the information that has been used, the sources of that information, and the methods of analysis used by the provider.

This lack of capacity within the UN might suggest that UNPKOs have a disadvantage compared to other missions, even those led by regional organizations that may also lack sophisticated intelligence networks (e.g. African Union) or unilateral efforts where the interventionist relies on their own capabilities (e.g.

Russia). Without an internal intelligence capacity, the UN (and more specifically

UNDPKO) cannot choose which sources are employed, which sorts of information are collected, how that information is processed, and finally analyzed to create finished intelligence products that might answers specific questions they need answered to facilitate the operation. However, if UN policy makers have access to finished intelligence products that provide qualified and reliable insight on the operational environment, their lack of access to granular data may be less important.66 Accepting that policy makers are capable of differentiating the quality of intelligence they receive, even without control over the sources of collection or methods of analysis, and that intelligence providers are disinclined to purposely

66 Access to finished intelligence could include exposure by official or unofficial means (i.e. speeches, prepared comments, testimony, or bi-lateral communication) from fellow member-state representatives who have access to those products. 80 provide faulty intelligence to an organization they support, the next question becomes how far that intelligence is shared.

3.7.4.2. Access to peacekeeping intelligence and sanctioning power

According to Smith (1994) the dissemination of intelligence is as much an important part of the intelligence process as collection and development of products themselves. This argument follows the logic that effective organizations operate under the premise that decision-makers have access to key information pertinent to the group. This logic holds true for peacekeeping operations as well, which is why the breadth of access to insights on a post-conflict state is the second significant contributor to variation in PKO scrutiny.

Although the vast majority of PKOs represent the collaborative effort of multiple states, all national-level decision-makers, even in those cases where a unilateral intervention occurs, must answer in one manner or another to their electorates over the use of national resources. These resources can include troops, police, equipment deployed to a PKO, or, just as importantly, monetary commitments to peacekeeping efforts.67 As such, each national-level decision- maker who either represents a member state of an intervening organization or whose state is intervening unilaterally needs access, to some degree, of insight on the post-conflict state to ensure their resources are being employed effectively and

67 This means that all members of an organization that sends peacekeepers will have some interest in the information available regarding the targeted state. 81 to make future decisions in support of the operation – this includes potential punishments if the post-conflict state fails to comply with their agreements.

If belligerents are not held to any sort of standard by those who agree to support peacekeeping efforts, there is no incentive to cooperate or as Milgrom et al

(1990) would posit, behave honestly to avoid punishment. This suggests that the real power behind an intervention is the ability of the sending agent to impose some manner of meaningful sanctions if the post-conflict state fails to comply with agreed-upon terms. This penalty could range from changes to the composition of the peacekeeping force to perhaps a more damaging response such as public accusations against the post-conflict regime, or even the enforcement of economic or military sanctions.

With access to this information, any state could decide to join in collective sanctions with a larger collaborative group or impose sanctions on their own. The extent to which sanctions could be imposed would increase the weight that the PKO, and the scrutiny it brings, has on the post-conflict environment. Furthermore, because the number of actors with sanctioning power, as well as knowledge of the post-conflict environment, will expand with the size of the collaborative group itself, the level of oversight or scrutiny that the PKO generates also increases. Using

Liberia as an example, the Security Council’s sanctions against Charles Taylor subsequent to the withdrawal of UNOMIL demonstrated that behavior-monitoring and punishment can occur beyond the deployment of a PKO, although the time it takes to gather and confirm information may be longer. 82

3.7.5. PKO categories

Bellamy and Williams (2015) offer a clearly-defined PKO classification system based on the level of UN involvement. As the world’s largest international organization, the UN offers the largest population of states that could contribute to peacekeeping efforts but also the largest population of states with some degree of sanctioning power that can be directed at a state with bad behavior. The following sections will discuss why and how UN involvement in peacekeeping can be used to characterize the levels of scrutiny that PKOs provide but also suggest the potential sanctioning power those PKO’s represent.

3.7.5.1. UN-led operations

UN-led operations are those PKOs mandated by the UN Security Council, funded by the entirety of member states, and conducted by the military forces of select member states that, during mission execution, fall under the command and control of the UN through the Department of Peacekeeping Operations (UNDPKO) and the Department of Field Support (Bellamy & Williams, 2015). UNPKOs are typically deployed when the primary belligerents in a conflict have agreed that they desire a cessation of hostilities and require an impartial third-party intervention to assure ceasefire compliance by both sides (UNDPKO, 2003).

Because these operations are costly, the UN has committed PKOs to less than half of states that require post-conflict assistance. While some suggest this has more to do with the interests of those states who make the final decision on deployments 83

(i.e. those on the Security Council) (Stojek & Tir, 2015), all member states are required to shoulder a portion of the financial or personnel contributing burden.

Regardless of the respective costs per member state, this implies the international community as a whole sees the intervention as necessary and is monitoring the behavior of the former belligerents to certify compliance.

Because UNPKOs must be welcomed by the belligerents, the state has publicly agreed to adhere to norms that characterize the organization. Failure to behave accordingly becomes a negative mark against the post-conflict state and risks discontinued support or sanction by the member-states.

Within the past decade the UN has gradually developed capability to monitor and assess behavior at both the tactical and operational levels (Joint Mission

Analysis Centres (JMAC)) and strategic level (UN Operations and Crisis Center

(UNOCC), and the Assessment Team within the Office of Military Affairs). The organization has also begun to employ its own information collection methods, including new technologies such as unmanned aerial vehicles (UAVs) (Abilova &

Novosseloff, 2016). Most recently the UN has worked with various troop contributing countries to develop its own intelligence doctrine68.

Although the efficacy of these resources are still heavily dependent on the quality of personnel provided by member states, implying that the UN will continue

68 Based on author’s conversation with an unattributed UN official, Washington DC, 2018 . 84 to rely to some degree on external national intelligence capabilities for finished intelligence, UN-led missions offer the highest level of scrutiny of any physical intervention because more actors with greater sanctioning power have access to key information about behavior of the post-conflict state.

3.7.5.2. UN-authorized operations

Peacekeeping operations that are mandated by one of the UN’s Principal

Organs69 but are supervised by another non-UN organization (e.g. European Union,

African Union), coalition (e.g. NATO), or lead-state are classified as UN-authorized

(Bellamy & Williams, 2015). Although the expertise in PKI may be greater than in a

UN-led mission, the levels of scrutiny on the targeted state in these cases will be less than a UN-led mission because neither funding nor force contribution is covered by the organization as a whole. In these cases, the UN has decided that the situation warrants a peacekeeping intervention and they acknowledge that the executor of the mission is acting in accord with the organization’s position. There is no set rule of impartiality,70 and the peacekeeping force does not answer to the UN but instead to the coalition or sending state. Despite some degree of international attention, because the targeted state is more answerable to the coalition or unilateral actor

69 The principal organs are: General Assembly, Security Council, Trusteeship Council, Economic and Social Council, International Court of Justice, the UN Secretariat 70 UNPKOs are only conducted under the premise that signatories of a peace accord will be treated equally, meaning neither side will receive preferential treatment with respect to the mission’s execution of its mandate – or less scrutiny. The absence of that premise could mean that one signatory (e.g. the current government) is not judged as critically as other signatories. 85 than the UN, this subsequently translates to a lesser demand for accountability from the state.

3.7.5.3. UN-recognized operations

These operations are not mandated by any UN body but their objectives are supported or welcomed by the organization, meaning they are mandated by another authority to prevent armed conflict by promoting a peace process (Bellamy &

Williams, 2015). Like UN-authorized operations, UN-recognized missions are resourced and managed by non-UN actors, which could mean greater or less PKI capacity, but assures a smaller group of states with collective sanctioning power.

Importantly, the only criteria for a mission to receive this classification in the

Bellamy and Williams dataset is that it has been mentioned specifically for its efforts by a UN body in some formal capacity, typically official documents or statements.71

Despite providing enough information to gain what equates to an endorsement from the UN, there is no evidence of an expectation for these missions to provide any type of direct information reporting to the UN. Without any direct participation of the

UN itself (except via some of its member states), the UN-recognized mission imposes the least amount of international scrutiny (among UN-related missions) on the targeted state.

71 According to personal correspondence with Paul D. Williams (2018), November 20, 2018. 86

3.7.5.4. Non-UN operations

The non-UN mission brings the least amount of international scrutiny on the post-conflict state. Unlike UN-affiliated operations, the non-UN mission receives its mandate from the targeted state (and potentially the other belligerent) and may not be an action called for or even condoned by the UN. For example, the International

Monitoring Team (IMT) observing the ceasefire in Mindanao (Republic of the

Philippines) with military and civilian observers from Europe, Africa, and Southeast

Asia, receives its mandate from the Philippine government and the Moro Islamic

Liberation Front (MILF) who have signed various ceasefire and peace agreements over the past 16 years (Felongco, 2014; GRP/MILF, 2009, 2011; OPAPP, 2015).

Notably the IMT has been ineffective in preventing bouts of fighting between the two belligerents and has become more of a facilitator of peace talks when the sides are willing to engage each other. Although monitoring the behavior of former belligerents warrants some degree of PKI employment, the primary consumer of that information would likely be internal to the conflict. Therefore, non-UN missions offer the least amount of scrutiny because they are the least likely to represent a large coalition of international actors with sanctioning power.

3.7.6. PKO composition options

3.7.6.1. Troops/police/observers

Within each type of peacekeeping mission, the sending agent must decide how the mandate will be executed. There are three general categories of 87 peacekeepers that are deployed to carry out a mandate: armed troops, civilian police, and unarmed observers. Each category of peacekeeper provides certain capabilities and can therefore be combined to achieve the mission objective.

Troops are typically associated with the face-to-face interface between the peacekeeping force and the population. Their numbers are typically higher than police or observers because of the security aspect of their collective mission. A greater number of troops overall (I will discuss the types of troops employed separately), would suggest larger footprints or more oversight on the general conditions within the post-conflict state. This means that troops have the ability to observe and report on the implementation of aid projects or to facilitate projects by providing security.

Civilian police fall into two sub-categories: individual police and formed police units (FPU). Both would be expected to focus primarily on rule of law matters, either enforcing law in the absence of a local force (FPU) or training a local force to perform those duties themselves (individual). As with troops, higher numbers of civilian police would imply a higher degree of oversight, through either potential role.

Observers can be military or civilian but, in both instances, they are unarmed or armed only for self-defense. Observers’ primary role is to ensure that the former belligerents are adhering to the terms of the negotiated peace agreement but can also be mandated to monitor issues the sending agent deems necessary for their 88 involvement in the resolution process (e.g. humanitarian conditions, or human rights issues) thereby promoting accountability from all sides of the conflict.

3.7.6.2. National origin and doctrinal foundations of peacekeepers

There is a high likelihood that the UN Security Council takes peacekeeper country of origin into consideration when conducting mission planning. Particularly for larger contingent requirements, this is likely due to concerns over the ability to provide adequate numbers of equipped peacekeepers who meet UNDPKO training requirements more so than the compatibility between the sending and receiving states. However, the requisite pre-deployment training is not designed to create a peacekeeper in its own right. Training is highly targeted to specific issues focused on operating within the parameters of a United Nations mission; peacekeepers are expected to come with a baseline professionalism provided by the contributing country. 72 For this reason, the troop contributing country (TCC) profile of a peacekeeping force can be valuable in determining how the mission will perform with respect to PKI collection, analysis, and reporting, regardless of mission specifics. One way of accomplishing this in a succinct manner is to consider how those TCCs train, educate, and utilize their militaries. In the absence of observing how a military has performed, or performs in real time, we can consider the military

72 Based on interviews and conversations by the author with United States Military Observer Group, former UNPKO participants, and deploying US peacekeepers, October 2017. 89 doctrine a state has either developed or adopted from another state’s military.73

Similar to the doctrine of any organization, military doctrine establishes the foundation of a military’s way of achieving objectives desired by the state. This foundation is not only the guiding philosophy of a military, meaning how it defines its role among other elements of national power, but doctrine will necessarily define the tactics, techniques, and principles a military employs to fulfill that role.

According to Posen (1984) military doctrine is a key component to a state’s national security policy that defines how military assets will be selected and employed in order to achieve national-level political objectives. Additionally, Posen suggests that doctrine reflects, among many things, the “judgements of professional military officers” but more importantly, military doctrine can define a state’s approach to international politics via offensive, defensive, or deterrent posturing. In the case of the US military, doctrine is developed by multiple proponents within the

Department of Defense and published in various publications that range from the strategic level, where concepts are defined and put into broad context (e.g. Joint

Publication 3.07, Stability), to service and occupational specialty74 focused documents where military personnel are expressly told how to conduct specific

73 Although PKO contributors also send civilian police units, those units would likely not undergo similar training as military forces due to their law enforcement purpose. While each police contributing state may have varied approaches to law enforcement, this research project will consider civilian police to share a common approach to law enforcement. This is because, regardless of where they are deployed and unlike military peacekeepers whose primary roles fall within combat operations, police peacekeepers are performing duties in line with their profession. 74 A soldier’s occupational specialty would be the specific skill set they are trained to perform. This could include infantry (combat operations), logistics, engineering (construction or counter-mine), civil affairs, or intelligence. 90 tasks and how to train their personnel accordingly (e.g. Army Field Manual 3-57,

Civil Affairs Operations, Army Techniques Publication 3-57.30).

Not all militaries publish doctrine in this manner or make those documents available to the general public. Likewise, some militaries may only adopt the doctrine of another military they choose to emulate based on cooperative training.

That being said, a doctrinal approach to a specific type of military operation may be reflected in the manner that a military habitually performs.

This suggests the core competencies peacekeepers bring to a PKO, regardless of any near-term UNDPKO training, are defined by the doctrinal approach they were trained under, which in turn would be derived from the national strategy of their home country and would arguably vary from state to state. Most doctrine (official or reflective of an accepted military partner) employed by militaries around the world have some heritage in NATO, Warsaw Pact, or other non-affiliated doctrine.75

These distinctions are relevant as they drive how peacekeepers approach their mission and what influences their military decision-making practices.

NATO militaries traditionally place a high emphasis on their competence and execution of Civil-Military Operations which United States Department of Defense

Joint Publication 3-57, Civil-Military Operations, defines as “the integration of civil

75 It is probable that doctrine will change over time, however, I assume the core factors that drive doctrine development (the nation’s approach to employing military resources) will remain constant barring a significant shift in that approach. Former Warsaw Pact states that transitioned to NATO would be an example of this shift. 91 and military actions for support to civil administration, populace and resources control, foreign humanitarian assistance, nation assistance, and civil information management” (DOD, 2013, p. x). Civil-Military operations do serve a military objective, to reduce civilian interference with military operations, but the methods employed (particularly emphasis on support to administration and resources control) promote a post-conflict state’s development of material and human resources allowing that state to achieve its own goals. Key to this development is the concept of government accountability which, as has been argued, is a PKO’s contribution to the peacekeeping-aid nexus.

Unlike the US and NATO doctrinal approach to peacekeeping, Russia (and previously the Soviet Union) has no established doctrine specifically addressing peacekeeping operations or civil-military operations in the same context as the US military. In its most notable peacekeeping efforts shortly after the collapse of the

Soviet Union, Russia deployed what it termed peacekeepers to former Soviet states to restore stability. However, without a specific doctrine the Russian military approached the task as any other military operation, meaning a reliance on Soviet- era combat operations similar to what had been employed during their occupation of Afghanistan (Mackinlay & Cross, 2002). While the basic objectives of these missions (i.e. restoration of peace) falls in line with any other UN or NATO-led missions, the focus on creating viable, accountable institutions to secure the peace was unlikely a mission objective. Additionally, Mackinlay and Cross (2002) suggest definitions of accountability (for the forces themselves) vary between the Russian 92 model, based on the “authoritarian practices of the outgoing Soviet Regime” and models based on high expectations of accountability (i.e. US, NATO or EU models).

Arguably, if a Russian or any other peacekeeping force operates with this interpretation of accountability, the oversight on accountability it provides would be weakened. And while Eisenstadt and Pollack (2001) suggest that Soviet doctrinal influence was most likely minor on some client states (specifically Syria, Egypt, and

Iraq) despite the Soviets being well invested in those militaries’ training and equipping,76 those states drawn to Soviet/Russian military cooperation could likely have a similar disregard or interpretation of accountability. This suggests that

NATO-influenced militaries, whose professional and doctrinal development share a similar approach to post-conflict scenarios with NATO states, will expect and impose greater accountability from the target state and their security forces as peacekeeping occurs.

For those states whose militaries display no clear doctrinal alignment (i.e. via membership or partnership), their participation in peacekeeping signals some appreciation for the accountability provision role that PKOs bring. As such, non- aligned militaries are expected to impose greater accountability than

Soviet/Russian influenced militaries but less than US/NATO influenced militaries.

76 Instead Eisenstadt and Pollack argue that those states morphed Soviet practice according to specific cultural characteristics. 93

3.7.6.3. Troop type

A final characteristic that would impact scrutiny and likely change a PKOs ability to affect the post-conflict environment is the troop type reflected by occupational specialty. Beardsley (2011) finds that variation in mission type, which is operationalized by considering force size, is equally effective at reducing the spread of conflict but we should look further at this distinction because analysis based on troop numbers could be misleading if significant numbers of the troops in question are never employed outside of a PKO compound. Referring back to the notion that larger forces equal larger footprints and therefore greater scrutiny, the actual number of troops directly exposed to the post conflict environment may be a more relevant measure.

However, this cannot be simply a question of numbers or ratios. Admittedly, observer-only missions will have a high ratio of operational peacekeepers to support personnel, but their ability to cover large amounts of territory will likely be limited by the size of the force. Larger missions may have the potential to observe conditions over a greater area, but those missions numbering in the thousands are likely to have significant numbers of contingent troops committed to support rather than operational tasks. Therefore, it is not only a matter of the size of the force but also the number of the operational troops that would matter for increased scrutiny.

Greater numbers of troops actually conducting mandate-related tasks (i.e. operational troops) will likely provide more scrutiny and have a greater 94 contribution to stability because there will be greater visibility on local conditions and reporting of those conditions will prompt higher levels of accountability.

3.8. A nexus of effects: the impact of PKO-driven oversight on

targeted foreign aid in increasing stability

At this point I have presented a conceptualization of stability that is dependent on the political network of a state and an oversight mechanism that defines the acceptable roles and behaviors which compose that network. I then suggested that the international community can not only intervene on both components but presented various ways the international community might design interventions to change institutions (i.e. changing roles and behaviors with development-focused foreign aid) and promote greater accountability (i.e. imposing increased scrutiny or oversight with the deployment of peacekeeping operations).

Although each intervention may have an independent objective, they will still positively affect stability if designed accordingly. This section recounts why the design of each intervention is important but also why, when the interventions occur simultaneously, a more positive effect on stability can be observed.

First, the manner in which donors target foreign aid matters. Our understanding of the effects of foreign aid tells us that when aid is directed at security-related issues (i.e. military spending, unit training, etc.) those sectors that promote development (i.e. governance, social issues, economics, etc.) suffer. I suggested this is because a security-focused approach is, by design, intended to 95 prevent significant change to the political network observed at the end of conflict.

Development-focused aid should promote those changes in the political network that will move the society away from conflict conditions (closer to what the international community desires) and allow that movement to continue in order to promote greater stability.

However, we also know that our understanding of foreign aid suggests that aid empowers governments (or those who hold power within the state). Collier and

Hoeffler (2007) argue that foreign aid promotes the redistribution of assets towards a recipient regime’s preferences – not necessarily those in the best interest of their state. This suggests that state authority, or the authority of the party in control of a conflict-affected area, dominates the impact that aid has because foreign aid is simply another resource they control, either directly or indirectly. We can look to the conflict in eastern Ukraine for a contemporary example.

In late 2015 the de facto separatist governments in the Luhansk and Donetsk oblasts (provinces) of eastern Ukraine decided to block aid deliveries from international donors despite a signed ceasefire agreement and the presence of a UN- authorized observer mission led by the Organization for Security and Cooperation in

Europe (OSCE) (O’Brien, 2015). This action proved that the separatists could direct and enforce policy within their area of control. Also, donors were required to communicate and negotiate with the separatists, which granted them some degree of credibility. A large international outcry (not an outcry from the Ukrainian government) was needed in order for the separatists to finally change their position. 96

The Ukraine case demonstrates how those with power are further empowered by their authority to permit or facilitate the flow of aid distribution.

This effect has little to do with whether or not these power brokers actually control how funds are utilized because their consent is needed in order for aid to be distributed in the areas they control. If that empowerment is not supervised and there is no accountability of resource expenditure the potential to redirect assets for personal gain is high.77

In terms of intervention, herein lies the value of a peacekeeping force; by imposing supervision or oversight the international community imposes the accountability needed for aid to be effective. However, peacekeeping missions are not created equal. They are, in fact, complex operations built from a menu of options offering variation in the sending agent, origin and scope of mandate, and the resources available to conduct the mission. Yet, the most important contribution of

PKOs is the amount of oversight, (i.e. the level of scrutiny) that these missions impose on the target state. This characteristic is the most important because scrutiny serves as a forcing function for those who control resources to behave within certain norms, particularly the degree of accountability they demonstrate with regard to the use of resources.

77 Here I am talking primarily about the diversion of state assets for personal gain. This could be possible if aid contributions freed state resources that would otherwise be used in the targeted sector. 97

Now I reassert my argument that there is an interactive effect at play in stabilization efforts. In addition to providing independent effects on stability, the internal oversight mechanism affects the political network contribution to stability by providing a constant feedback on the interactions or behavior between political actors.78 Translating the abstract conceptualization to practical means, the interactive effect generated when development-focused foreign aid is applied under increased accountability, generated by high PKO-imposed scrutiny, will result in increased stability.

Although decisions on foreign aid targeting are made by the international community, those in power within the state control the allocation of all resources at work in the state and can negate the impact of aid. PKO-imposed oversight can affect aid’s contribution to stability because the PKO enforces accountability through its reporting function. By informing the international community on how the state utilizes its aggregated resources to support or negate aid objectives PKO- imposed oversight is affecting how donors target subsequent aid contributions thereby changing what aid targets and its effect on stability.

Accountability is a common theme that has emerged throughout this chapter.

The notion of a mechanism promoting accountability in aid provision is not novel, in fact the need for accountability is defined in the US Agency for International

78 Recall that the state’s oversight boundary is not likely to change easily, dramatically, or quickly considering it has been developed over the entire history of the society. 98

Development’s (USAID) Strategy on Democracy, Human Rights, and Governance

(DRG) (USAID, 2013), a publication previously identified as a supporting document for current US Government strategic policy on interventions in conflict-affected states.

The USAID approach advocated in the DRG Strategy, one reliant on greater civilian participation in governance, is an indirect way to promote accountability and requires some initial degree of cooperation from the targeted state. If accountability is lacking at the outset, the ability of aid programs to generate an intended outcome seems unlikely if there is no mechanism to ensure resources are used appropriately.

Cooperation from the conflict-affected state should come more easily and quickly if a mechanism that forces accountability is in place. PKOs provide a physical motivation for regimes to be more accountable to donors and, most importantly, their people. As the level of international scrutiny inherent in a PKO design increases, accountability should also increase. As discussed above, this level of scrutiny can increase in several ways.

First is by the level of UN influence in the mission. UN-led missions, representing the highest level of UN influence, will contribute most to scrutiny due to their wide distribution of information about the target state’s behavior and capacity to punish that behavior. As UN influence declines (UN-authorized to UN- recognized) to the point where there is no UN influence (non-UN missions) the

PKO’s scrutiny will be reduced. Additionally, within these categories of PKOs we can 99 consider the size and breakdown of force composition (i.e. troops, police, and observers), troop specializations, and the doctrinal background of the deployed force as other ways that scrutiny can be increased, and accountability enforced.

As accountability increases, based on PKO scrutiny, the effectiveness of aid should increase. This means that the objective of an aid program will be more readily achieved because the state’s use of resources is being monitored and diversion of resources is less likely.

If there is a problem with accountability it is that we should see this effect regardless of how aid is targeted. If states are monitored in their use of security- related aid, we should expect that they would use the aid in that manner. However, we know from our understanding of foreign aid that focusing on security issues alone is not a stability-enhancing practice, a whole-of-society approach to aid is what drives development and creates stability. This is because targeting aid into sectors such as rule of law, economics, or institutions that generate trust and confidence between the state and the populace, motivates markets, or guarantees property rights are improved. These sorts of aid programs are exactly what USAID’s

2013 strategy points to, it just does so with the perception that an acceptable level of accountability is in place for these programs to take hold.

This combined effect is the nexus of peacekeeping and foreign aid interventions. In order for stability to grow and endure, the right combination of peacekeeping and aid design must be selected. This will provide the right amount of accountability with the right focus of aid contributions. If aid is targeted into the 100 appropriate sectors under accountability motivated by a particular PKO design, we should expect to see increased stability in the post-conflict state in line with the four stages of conflict I offered earlier in the chapter. A stabilization plan incorporating a

PKO design that promotes the highest degree of accountability, combined with aid programming directed at development, will generate the greatest stability in a post- conflict society.

3.9. Summary

This chapter has defined stability using components of Ake’s (1975) formulation, and current US Government doctrine on stabilizing conflict-affected areas. Stability implies balance and predictability; even though behavior is not dictated; exchanges occur across political, economic, and social domains within bounds defined by the society and, at a higher level of interaction, the international community. Instability implies an imbalance of behaviors, potentially across a wide spectrum of society, that may result in a need for external intervention if the society cannot restore the balance or if instability reaches a point of concern for the international community (e.g. violent conflict that impacts other members of the international community).

I presented a theory on how two independent and measurable interventions, peacekeeping missions and foreign aid, can affect the behavior of internal state actors, prompting them to accept or redefine roles and behaviors within the state, thereby promoting increased stability. Applying the proper stabilization plan 101 design should prompt the state’s ability to maintain or grow stability after the intervention, albeit at a lower level. Each intervention targets a specific factor in the stabilization process. Peacekeeping operations ensure varied degrees of oversight and spur the state to certain levels of accountability. Aid can address a wide range of sectors but needs proper targeting and oversight to preclude malfeasance allowing the foundations of a stability-enhancing structure to be built. Working in concert, the variation in scrutiny on the post-conflict state brought on via the oversight inherent in a specific type of peacekeeping mission should prompt the government to be more or less accountable in its use of development aid (or public resources in general), which should lead to a more stabilized and durable post- conflict environment all interventions will be striving for.

Given a theoretical argument that accounts for the components of stability and how they can be targeted through intervention, and defines the role that variations in peacekeeping, aid, and their interactions have stability on post-conflict states, the next step is to build a model that allows us to test for increased stability in a post-conflict stabilization plan.

102

Chapter 4

Research Design

4.1. Introduction

The theoretical argument presented in Chapter 3 posits stability has two primary components. The first component consists of behaviors, associated with the existence of a state, that form a network of political interactions. This network of interactions extends beyond behaviors associated with governance alone and includes behaviors associated with social or economic issues. Despite some variance, which falls within the limits of what the society deems acceptable, interactions within the network are somewhat predictable.

Additionally, the behaviors that drive respective interactions are conceptually bounded by laws, customs, or practices. These laws, customs, or practices, serving as an oversight mechanism, provide the second component of stability by attempting to restrain behavior deemed unacceptable by the society. 103

If we accept that stability is composed of these two primary components, the political network of interactions and an oversight mechanism that serves to keep those interactions or behaviors in check, we can expect any external effort aimed at increasing stability in a post-conflict state to target one or both of those components. Foreign aid and peacekeeping operations have been identified as means by which the international community has demonstrated efforts to affect behavior and generate oversight in post-conflict states respectively. Foreign aid is specifically designed and targeted to address identified or perceived shortcomings in the conflict-affected state, while peacekeeping operations offer a physically present oversight mechanism that brings international scrutiny and prompts a level of accountability. We should be able to account for the impact these interventions have on stability by looking at an indicator not tied to the interventions themselves

(i.e. an aid-related project or mandated PKO task). The economy of a conflict- affected state was offered as the sector where such an indicator could be found.

To test the theory, the analysis will look for the positive effect that peacekeeping and foreign aid have on the net inflows of foreign direct investment

(FDI). Unlike some economic indicators that rely on the aggregation of multiple inputs across multiple sectors (e.g. gross domestic product (GDP) which considers the value of all goods and services produced minus the costs of all goods and services imported), FDI inflow represents a more narrowed concept. FDI inflows are the sum of equity capital, reinvestment of earnings, and other capital that reflects a foreign resident (or firm) controlling or influencing the management of an enterprise in another economy (Simmons, 2018). Key to the selection of FDI inflows 104 as the dependent variable is the fact that decisions made by investors to commit significant resources in a foreign state reflect an external, unbiased assessment of factors beyond the host nation’s economy including political, social, and legal issues.

Together these represent what the theory pointed to as primary factors in the stability of the state.

A dataset composed of 66 conflict-affected states was constructed with the unit of analysis being country-year from 1970 to 2013. Each case was selected because at some time during the period covered the country hosted one or more uniformed peacekeeping operations as part of a signed peace accord. The existence of an accord implies that two or more of the former belligerents (including the recognized government) have agreed to the intervention.

In some cases a state hosted multiple peacekeeping operations within a given year but, using criteria established by Bellamy and Williams (2015) in their review of peacekeeping operations, the pairings of conflict-affected states and peacekeeping operations were further limited to uniformed missions (i.e. missions involving military personnel and/or civilian police). Therefore, states that only hosted civilian peace efforts (e.g. United Nations Good Offices Missions) are not included, and those missions are not included in the dataset even if they occurred simultaneously with a uniformed peacekeeping operation. 105

A total of 180 uniformed peacekeeping operations are included in the dataset.79 However, because the study aims to test the impact of peacekeeping operations on the conflict-affected state they deployed to, a single mission that deployed across multiple countries is considered a separate deployment in each country (see Appendix A). And, while the Bellamy and Williams list of PKOs includes those missions deployed from 1947-2013, this analysis excludes observations before 1970.

This restriction in years covered results from a lack of available data of both the dependent variable (Foreign Direct Investment inflows) 80 and PKO personnel data needed to code several independent variables discussed further in this chapter.

While this eliminates 23 years of observations and 19 missions (or observations including those missions) from the dataset, three missions beginning in this time period did continue into the years covered by the dataset. And, while data on peacekeeping operations, particularly UN-led missions, have become more available to the public, more recent cases (2014-2018) are currently limited by consistently available data on the second source of independent variables used in the analysis, foreign aid commitments.81

79 The United Nations Mission for the Referendum in Western Sahara (MINURSO) is not included in the analysis because the status of Western Sahara as a sovereign state is not established nor is the data relevant to this study available for the region. 80 UN data on FDI inward inflows are available beginning in 1970, other FDI measures such as FDI stock are only available from 1980 onward. 81 Based on personal communications with representatives from the AidData project, beginning in 2017, an updated dataset through 2016 is being compiled but has yet to be released. 106

The decision to include observations for each conflict-affected state for the duration of the period of analysis, rather than looking only at those years where

PKOs were deployed, results from the argument made in the theory that we should be able to demonstrate the measurable effects that peacekeeping and foreign aid have on stability across four time periods defined as: pre-conflict, conflict, intervention, and post-intervention.82

While each of the two types of intervention is independent from the other and focused on separate components of stability, their parallel execution generates an interactive effect. The application of targeted foreign aid under increased scrutiny should generate a measurable increase in stability that varies according to the construct of each intervention (accounting for these design options are addressed in more detail below). The interactive effect posited in the theory should generate greater stability than if either intervention occurs alone. And, once one intervention is halted (specifically the peacekeeping effort), stability will remain higher than the pre-conflict and conflict periods, but not as high as when both interventions were in place. Therefore, by looking at each country across all four periods of conflict, each experiencing variation in the duration of these periods, we should be able to determine if the theory is correct in its assertions.

82 It should be noted that the period labeled “intervention” is distinguished by the presence of both foreign aid spending and the deployment of one or more PKOs however, aid can flow to a conflict- affected state during any of the four periods. 107

The remainder of this chapter will provide further detail on the reasons why choices were made regarding the selection of the dependent and independent variable used for the analysis, and how those variables were constructed from a variety of available data sources. A series of testable hypotheses are presented, each address assertions made in the theory. Finally, three models are provided along with an explanation of how they will be employed to test the hypotheses and find support for the theory.

4.2. It’s the economy…

Considering the interactive effect of aid and peacekeeping on the economy of a post-conflict state is in line with the work of Mills and Fan (2006) who espoused the recuperative benefits of creating a viable investment climate. According to Mills and Fan, post-conflict states are typically challenged with a degraded investment climate. The investment climate is composed of various policy-driven conditions that generally fall into four “policy pillars” which include: security and stability,83 finance and infrastructure, workers and labor markets, and regulatory framework and taxation (Mills & Fan, 2006, p. 6). This investment climate is highly specific to a country because it emerges from policy decisions that are particular to the state itself.

83 Mills and Fan do not employ a definition of stability identical to the one used for this project. As such, their use of the term ‘stability’ in relation to the four policy pillars should not be considered a direct reflection of the theory or argument presented in this thesis. 108

However, a policy is simply an idea or concept. The implementation of a particular policy requires proper conditions that enable a government to prescribe the policy and enforce it. These conditions, which Mills and Fan refer to as the

“enabling environment” are the product of factors unique to each state: their institutions, quality of governance, the degree of trust between the citizens and the state, and the political economic conditions. The condition of the enabling environment is what this project considers as the economic condition of a conflict- affected state.

This framework is ideally suited to the study of stability in conflict-affected states for two significant reasons. First, foreign aid is directed into select sectors of society which will address specific components of the enabling/economic environment. Those targets can be policy-related, such as the construction of infrastructure, training officials about contracting, or engaging key leaders on property rights. However, aid can also target intangibles such as institutions, governance frameworks, or trust issues that affect the state’s authority to enforce sound policies. Second, while peacekeeping might be viewed as a type of aid that focuses solely on policies associated with security, their presence does more. As discussed in Chapter 3, PKOs bring a degree of scrutiny that affects the broader enabling environment by promoting accountability of public resource allocation.

Taking these examples of how aid and peacekeeping might target various aspects of a targeted post-conflict state, it is possible to see how variations in both interventions can impact the enabling/economic environment. Finding the best 109 measure of that impact will allow us to confirm if the overall intervention effort is or is not promoting increased stability.

4.2.1. Foreign Direct Investment as a measure of stability

The World Bank lists over 100 financial indicators under the category of

Economy and Growth (IBRD-IDA, 2019a). Perhaps the most commonly recognized indicator of economic health is Gross Domestic Product (GDP). According to the

Organization for Economic Cooperation and Development (OECD), GDP is the measure of the value of final goods and services produced by a country during a period minus the value of imports (OECD, 2019). GDP is considered to be one of the primary indicators of a country’s economic health (Kramer, 2018) and may be the obvious choice as a measure of the economic environment in post-conflict states.

However, according to some critics, GDP is not an effective indicator when considering those transactions that are not reported to the government (Gertner,

2010). For example, if we return to the case of post-conflict Liberia from Chapter 3, where “off-budget” foreign aid surpassed the national budget by tens of millions of dollars in one year alone (Parks & Kabada, 2010), the reliance on GDP as a valid measure of the health of post-conflict economies becomes less convincing.

The theory presented in Chapter 3 does not demand an externally driven measure, meaning one could potentially look to other indicators that speak to certain aspects of the conflict-affected state’s economy, governance, or social construct. However, due to the nature of stabilization efforts, specifically the significant investment of public (or sometimes private) resources into a state that 110 continues to experience higher levels of instability within its wide-ranging political network, having success declared (or “stability achieved”) by a contributor, whose efforts target perhaps only a single aspect of the larger instability issue, could be questionable. It is not difficult to conceptualize an aid donor claiming success after the completion of a single development project or, as witnessed in the Liberia case, when two peacekeeping missions (ECOMOG and UNOMIL)84 claimed success once

ECOWAS and the UN judged their respective mandates to be complete (Jennings,

2015). As such, using a measure that is based on an external evaluation of the economic environment offers a more objective determination of stability.

Despite the myriad of concerns within post-conflict Liberia, barring the 2008 global financial crisis and the Ebola outbreak period that lasted from mid-2014 until early 2016, Liberia experienced positive inflows of foreign direct investment (FDI) following the end of the Second Liberian Civil War (see Figure 4-1).

84 Economic Community of West African States (ECOWAS) Military Observer Group (ECOMOG) and United Nations Mission in Liberia (UNOMIL). 111

Figure 4-1: Liberian FDI inflows vs. GDP 2003-201785,86

Notably, Liberia’s economy appears extremely strong with continued increases in reported GDP during this time period, despite the 2009 global financial crisis. However, as discussed above, Liberia received heavy injections of off-budget aid during this time period. Because GDP reflects the value of goods a state

85 GDP and FDI inflow data as of 14NOV18 from: World Development Indicators, databank.worldbank.org, IBRD-IDA (2018a, 2018c) 86 Liberia timeline from: Liberia profile-Timeline, BBC (2018) 112 produces, minus the cost of goods the state imported, any state that does not account for all of the goods it receives (e.g. aid received as goods in kind) would possibly have an inflated GDP. This should detract from the picture of economic health (i.e. growing economic health despite a national health crisis resultant from the 2014 Ebola outbreak) that this statistic seems to purport. FDI inflows however suggest that outside investors saw the potential for future profits was higher than risks associated with operating in a conflict-affected country until this unforeseen challenge to stability threatened various factors within Liberia (i.e. the government’s ability to cope, workforce welfare, etc.).

Considering the Ebola crisis is still in recent memory and that Liberia has continued to face a variety of challenges with corruption (as discussed in Chapter 3), it is not surprising that FDI has yet to rebound to pre-outbreak inflows. Apparently, in the opinion of foreign investors looking at Liberia as an investment possibility, stability is not where it should be to motivate significant investments in the future – a story that is not represented in GDP figures. It would seem that foreign investors can therefore serve as ideal external evaluators of the economic environment, and the measure of their investments in the post-conflict state offers true insight into their evaluations. As such, foreign direct investment (FDI) inflows will serve as the primary dependent variable used in this project.

4.2.2. FDI as the dependent variable

Like GDP, FDI has numerous indicators or categories based on its measure.

The primary FDI measure used here is non-portfolio FDI inflows. According to 113

World Bank data specialists (Simmons, 2018), unlike foreign portfolio investments that concern transactions in equity securities and debt securities (sold by enterprises that need to raise capital for short term use), non-portfolio FDI represents the sum of equity capital, reinvestment of earnings, and other capital that reflects a foreign resident (or firm) controlling or influencing the management of an enterprise in another economy. The World Bank considers the relationship to exist when a foreign investor has ownership of 10% or more of ordinary shares of voting stock in the local enterprise.

But why should we consider non-portfolio FDI as such a valuable indicator?

First, non-portfolio FDI demands a greater degree of risk for the investor because it represents significant ownership in real property. Foreign investors, without a firsthand understanding of the investment environment, take significant risk to invest in real property. Unlike securities investments that can be redeemed in accordance with the terms of the investment (potentially at a gain or a loss), ownership implies profit is tied to the physical aspects of the corporation (i.e. physical property, inventory, workforce) that are subject to the economic enabling environment of the host country. In a conflict-affected state this risk can be even greater. Those investors have decided that the potential for profit out-weighs the risk that the physical property they hold could be lost to further conflict, seizure by the state, or market decline. This suggests that even if conditions degenerate in the short term or through a series of high and low points in stability (which might be evident in a temporary recurrence of conflict), the long-term stability within the state is growing. 114

A reasonable argument against the use of any FDI value as a measure of stability could be that investors simply look for signals that might give them an edge over the competition. We know that UN peacekeeping operations and foreign aid are two methods of intervention that offer signals to investors in some situations

(Garriga & Phillips, 2014; Simmons, 2014b). However, even with the availability of investment insurance vehicles (MIGA, 2013) the reliance on signals as an investment motivator seems more reasonably tied to fluid investments associated with portfolio investments where firms have the ability to easily restructure their holdings (i.e. sell off their foreign holdings). In fact, we should expect that firms would utilize significant resources to ensure conditions are right for strategic investments.87

There are various ways to account for non-portfolio FDI inflows (e.g. per capita, growth, etc.). However, according to the United States Federal Reserve Bank of Dallas (2016), considering a measurement that accounts for the value of FDI inflows (a basic measurement of levels rather than growth rate) at a specific time, we can easily determine the effect of both interventions and make a comparison between FDI inflows across the four periods of conflict we are interested in.

Therefore, the analysis will employ a straight FDI inflow measurement as the dependent variable.

87 Corporations such IHS Markit Ltd., and periodicals like the Financial Times provide strategic analysis services to firms looking to invest in foreign markets. These services include products such as financial assessments, threat assessments, and information on other greenfield investments. 115

Yearly by-country FDI inflow data was taken from the World Bank’s World

Development Indicator dataset (IBRD-IDA, 2018b) that is derived from the

International Monetary Fund Balance of Payments database and supplemented by data from the UN Conference on Trade, as well as national sources. Figures taken from the World Bank’s dataset are presented in current US dollars (USD). However, in order to conduct a comparative analysis between conflict-countries and across time, all monetary values must be converted to a constant USD value. 2011 was selected as the base year for constant USD conversion because of its use in the

AidData Core Research Release Level 1 version 3.1 dataset that was used to obtain foreign aid commitments for the analysis (AidData, 2017; Tierney et al., 2011).88

The histogram below (Figure 4-2) shows the distribution of FDI inflows across the entire sample. It must be noted that extreme FDI inflow values have been removed from the graphic to offer a better visualization of the data.89 A normal distribution curve is overlaid to provide an additional depiction of the entirety of the data.

88 Monetary values are converted to 2011 constant USD by dividing current year figures by the yearly US consumer price index (CPI) figures (IBRD-IDA, 2019d) scaled to the US 2011 CPI. CPI figures were scaled by dividing the yearly US CPI figures (1970-2013) by the 2011 US CPI value. 89 There are 330 observations in the dataset where net FDI inflows exceed $1billion, these represent 15% of all observations. The highest reported value is $78.4 billion (Hungary, 2008). There are 21 observations in the dataset where negative net FDI inflows (i.e. withdrawal from the economy) exceed $500million, these represent 1% of all observations. The largest loss reported is $21.6 billion (Hungary, 2010). 116

Figure 4-2: FDI inflows 1970-2013, extreme FDI values omitted

As discussed in the introduction to this chapter, cases used in the analysis will include those conflict-affected states that hosted a uniformed peacekeeping mission from 1970 to 2013 resultant from a signed peace accord between two or more of the former belligerents. Extending the study back to 1947 when the first peacekeeping missions that meet these criteria were employed is not possible because data on FDI is not available before 1970.90

90 UN data on FDI inward inflows are available beginning in 1970, other FDI measures such as FDI stock are only available from 1980 onward. 117

4.3. Independent variables

4.3.1. Targeted Foreign Aid – targeting security vs. development

Foreign aid data from the AidData project (Tierney et al., 2011) is used as the raw data source for foreign aid commitments for the project. Annual country-level data on foreign aid commitments covering the entire period of study are included.91

AidData’s breakdown of commitments into “purpose codes” allows for targeted aid to be more easily quantified, which facilitates modeling specific aid packages with specific peacekeeping mission types. However, it should be noted that some aggregation of AidData’s information was necessary to place a reasonable limit on the number of sectors studied.92 The dataset includes 29 different aid sectors derived from AidData’s coalesced purpose codes (see Table 4-1).

91 It should be noted that commitments are reported, not actual contributions. Additionally, donors include public (i.e. state) as well as private sources. 92 For example, there are four sub-series included in the Education 11000 code series, each sub- series is further disaggregated with up to seven activity codes/sectors designated. 118

Table 4-1: AidData Coalesced Purpose Codes and Aid Sectors used for analysis AidData Coalesced Purpose Code Grouped Aid Sector used in Analysis 11000 Education, combination of purposes 12000 Health 13000 Population Policies/Programs and Reproductive Health 14000 Water Supply and Sanitation Government and Civil Society, combination of activities 15000 (including Conflict Prevention and Resolution, Peace and Security) 16000 Other Social Infrastructure and Services 21000 Economic Infrastructure and Services 22000 Communications 23000 Energy Generation and Supply 24000 Banking and Financial Services Business and Other Services, Privatization, Business 25000 Education and Training 31000 Agriculture, Forestry, Fisheries 32000 Industry, Mining, Construction 33000 Trade Policy Regulations and Tourism 41000 Environment 42000 Women Urban and Rural Development, Multisector 43000 Education/Training, Scientific Institutions and Research 51000 General Budget Support 52000 Development Aid/Food Security 53000 Other Commodity Assistance 60000 Action Relating to Debt 70000 Humanitarian Aid 72000 Emergency Response 73000 Reconstruction Relief 74000 Disaster Prevention Preparedness 91000 Administrative Costs of Donors Support to Non-Governmental Organizations and 92000 Government Organizations 93000 Refugees in Donor Countries Unallocated or Unspecified, including Development 94000 Awareness

119

Following the argument presented in Chapter 3, a higher focus of spending on security issues over other development issues is likely detrimental to economic development. From the list of 29 sectors created by aggregating data according to

AidData’s coalesced purpose codes, the “Government and Civil Society” category is the only category that includes aid directly targeted towards security-specific issues.93 Disaggregating “Government and Civil Society” commitments into three sub-categories (Governance, Security, and Peace) allows for the analysis to account for foreign aid targeted specifically towards security issues.94 The “Reconstruction

Relief” category is tied to post-conflict reconstruction and is treated as a separate aid category because it does not fall in the realm of traditional development programming. Keeping this category separate also allows for its combination with the “Government and Civil Society” category to identify aid commitments particular to post-conflict cases.

The remaining 27 sectors represent those foreign aid commitments that target what could be considered more traditional development programs (i.e.

Education, Health, Actions Related to Debt, Banking and Financial Services, etc.).

However, the 27 sectors include seven categories that are not included in the analysis portion of this study: Humanitarian Aid, Emergency Response, Disaster

93 Commitments originating from the United States Department of Defense are included in this category. This suggests some commitments are directly tied to security/defense issues. 94 By aggregating the main categories “Government and Civil Society” along with “Reconstruction Relief” the analysis also considers those aid commitments that would be applicable in a post-conflict reconstruction scenario. 120

Prevention Preparedness, Administrative Costs of Donors, Support to NGO/GO,

Refugees in Donor Countries, and Unallocated or Unspecified contributions. While each category may represent a significant monetary amount, these categories represent funds to be directed at short term (e.g. humanitarian aid, disaster preparedness) rather than long term stabilization, the administrative costs of intervention to the donor, monies spent on donor-nation infrastructure to accommodate target-state refugees, or unknown uses. Accordingly, these categories are not included in the analysis.

The aggregation of the remaining 20 sectors of aid commitments will serve the international community’s fiscal intervention focused on traditional development issues. These aid-related variables allow for two hypotheses to be tested during the analysis.

Hypothesis 1: Increased commitments to development-focused aid categories have a positive effect on inflows of FDI.

Here development-focused aid categories include governance, peace, reconstruction, and traditional development aid. Traditional development aid will be referred to as “development aid” from here forward.

Hypothesis 2: Increased commitments to security-focused aid have a negative effect on inflows of FDI.

121

4.3.2. Peacekeeping Operations – modeling oversight by UN involvement

As discussed in the introduction, I will analyze data from 180 uniformed peacekeeping operations deployed to 66 conflict-affected states from 1970-2013.95

The unit of analysis will be country-year (of the conflict-affected state). The missions were selected from a larger dataset compiled and categorized by Bellamy and Williams (2015) that includes missions dating back to 1947. According to

Bellamy and Williams, the distinguishing factor of these operations, compared to the deployment of armed forces to other conflict or post-conflict scenarios, is the presence of uniformed (i.e. military and/or police) personnel and a recognized peace process between two or more of the former belligerents. As mentioned above, limitations on FDI data, as well as reliable PKO data, result in any missions occurring in years prior to 1970 to be dropped from the analysis.96

Going beyond the descriptive nature of Bellamy and Williams’ classification system, the theory argues that each type of peacekeeping mission imposes a level of scrutiny or oversight that is attributable to variations in the mission design.

Additionally, a peacekeeping operation’s ability to collect greater amounts of relevant information about the conflict-affected state (i.e. peacekeeping intelligence

95 This includes some PKOs that are deployed to multiple states. For example, the United Nations Truce Supervision Organization (UNTSO) is simultaneously deployed in Egypt, Israel, Lebanon, and Syria. Each deployment is treated as a separate mission. Within UNTSO, UN observers can be relocated to different UNTSO countries during their tour, as required. Absent specific details on the location of select troops, force characteristics (e.g. troop strength) are averaged across all missions for the year. 96 UNTSO has been deployed since 1948. 122 focused on the state’s use of resources, to include aid-related resources) and subsequently distribute that information to a larger audience with some form of sanctioning power, are the primary components of a mission’s level of imposed oversight. This led to the argument that the level of UN involvement within peacekeeping operations can be used as the primary indicator of a PKOs oversight capacity.

This argument holds true, despite the absence of an internal peacekeeping intelligence infrastructure resident within the UN or more specifically, UN

Department of Peacekeeping Operations (UNDPKO), because policy makers are experts who can differentiate the quality of information they receive, relevant to the issues their decisions are aimed to affect. Furthermore, not only can any UN member state join in sanctioning a fellow member state that the organization does, it can also elect to sanction independently. This makes the UN the world’s largest sanctioning body both collectively and at the member- state level.

4.3.2.1. Levels of UN Involvement

There are different levels of UN involvement and higher levels of UN involvement suggest that more states which could potentially participate in a post- conflict intervention would have access to peacekeeping intelligence. If the PKO were UN-led (e.g. UNTSO) the information flow would be the most direct from the field and more member states would have access to it. 123

UN-authorized missions (e.g. the NATO-led Kosovo Force, KFOR) would have less UN involvement because another organization or state leads and/or finances the mission, despite a mandate provided by the UN itself. In this case the lead organization or state will more likely filter the information flow to the wider UN audience regardless of any reporting requirements a UN mandate might impose.

UN-recognized missions (e.g. the ECOWAS-led missions in Liberia, Guinea-

Bissau, or Sierra Leone), being those only acknowledged and perhaps remotely monitored by one of the UN’s principal bodies might only report that information its sending agent deems necessary to maintain the UN’s endorsement. Finally, non-UN missions (e.g. the Moldova Joint Control Commission Peacekeeping Force) have no obligation or likely any motivation to share information outside of a small circle of contributing states.

Table 4-2: PKO by Type/UN Involvement score, taken in part from Bellamy and Williams (2015) pg. 20

Types of Peacekeeping Operations, 1970-2013 Type of Peacekeeping Number of Operations UN involvement ranking Operation UN-led 77 (43%) 4 UN-authorized 28 (15%) 3 UN-recognized 38 (21%) 2 Non-UN 38 (21%) 1

Table 4-2 provides a summary of the number of PKOs included in this study, by type, as well as rankings for UN involvement by PKO, the UN involvement ranking is based on the reasoning presented in the theory and in the text above 124 where higher UN involvement generates higher oversight. I create dummy variables for each mission type allowing for an analysis of the individual effect of each mission type. Based on my theory I develop the following hypothesis:

Hypothesis 3: Higher levels of UN involvement in peacekeeping operations have increasing positive effects on inflows of FDI.

Although this approach allows me to interpret the effect of mission type this approach complicates my ability to interpret whether or not the level of UN involvement matters for those situations when there are multiple missions deployed.97 To address this concern the UN involvement ranking is used to create an ordinal variable that provides the highest level of UN involvement deployed within a conflict-affected country in a given year. For example, coding UN involvement “3” for a specific country-year indicates that the highest level of UN involvement in any PKO deployed in that year to that conflict-affected country would be equal to the level of involvement that a UN-authorized mission is theorized to bring. Table 4-3 provides a by-observation breakdown of PKO types represented in the dataset as well as the number of UN involvement observations.

97 This occurs within 37 conflict-affected states or 327 country-year observations within the dataset. 125

Table 4-3: Frequency of PKO types and UN involvement in the dataset

Type of Total Observations UN Involvement Total Observations Peacekeeping in the dataset in the dataset Operation UN-led 571 4 571 UN-authorized 95 3 41 UN-recognized 172 2 97 Non-UN 169 1 107 No PKO deployed 2044 No PKO deployed 2044

This coding only recognizes the highest level of UN involvement during the country-year observed. However, the UN involvement variable allows me to test a key part of the theory (greater oversight creates more stability) using a single variable, and this will prove important when I introduce an interaction variable later in the analysis.

4.3.2.2. Refining oversight - additional PKO variables

The theory presented in Chapter 3 argues that PKOs of the same type can provide different levels of scrutiny or oversight based on their mission characteristics. In order to account for these characteristics, the analysis considers two additional factors that, subsequent to the decision of what type of mission should be deployed and its level of UN involvement, influence the amount of oversight a PKO can generate: the doctrinal background of the military forces deployed, the size of the force itself. 126

4.3.2.3. Doctrinal foundations

I argue that the manner in which a PKO performs begins at the individual peacekeeper level and is largely defined by the baseline level of professional military training that peacekeeper receives from their home country. Despite subsequent pre-requisite training that may be imposed by a PKO sending agent (e.g.

UN-mandated training required for participants in UN-led PKOs), the baseline military training dominates the character in which peacekeepers conduct themselves. Furthermore, this baseline training is defined by a military doctrine that is either created or adopted by a peacekeeper’s home country.

The emphasis that the doctrines of NATO militaries place on successful Civil-

Military Operations (where promoting host nation accountability is an essential mission task) during their conduct of combat and post-conflict missions suggests that peacekeepers trained under NATO doctrine (and the PKOs they serve in) will impose greater accountability (DOD, 2013, p. x). Identifying the presence of NATO peacekeepers is easily accomplished in an analysis of yearly observations by identifying PKO contributing countries and coding the contributions of NATO member states according to their membership status in a given year.

Based on extant literature regarding Soviet or Russian military doctrine

(Mackinlay & Cross, 2002), I argue that a Russian peacekeeping force, or one where

Russian military doctrine might have influenced a peacekeeper via their home- country training, is less likely concerned with building or enforcing accountability within the conflict-affected state it deployed to. This implies those states who share 127 a Russian influenced military doctrine (i.e. former Warsaw Pact states) will demand less accountability than their NATO peers thereby offering less oversight as a group, a result that could negatively impact the PKOs ability to affect stability. Similar to the approach employed for NATO peacekeepers, those contributors with former military ties to Russia are coded accordingly.

It must be noted that there are cases where, following the collapse of the

Soviet Union, former Warsaw Pact states have migrated to NATO membership (e.g.

Albania, Bulgaria, Romania, Hungary, Czech Republic). Assuming a necessary expectation that NATO members follow basic tenants common to all member state militaries, those former Warsaw Pact states who have migrated are treated as if their military doctrine now meets some NATO standard that assures operational compatibility (i.e. an expectation of host-nation accountability). These potential mission characteristics generate the following hypotheses:

Hypothesis 4: NATO presence during a peacekeeping intervention has a positive effect on inflows of FDI.

Hypothesis 5: Warsaw Pact presence during a peacekeeping intervention has a negative impact on inflows of FDI.

While the theory depicts a distinct doctrinal difference between NATO and former Warsaw Pact PKO contributing states or militaries based on extant literature, this leaves a significant number of non-aligned states who contribute to

PKOs, including China and large force contributors such as India and Pakistan. The 128 theory suggests that absent knowledge of a doctrinal approach to accountability seen in NATO states but not in former Warsaw Pact states, a non-aligned state’s participation in a PKO signals an appreciation for the accountability role that PKOs bring, this could be parsed more by looking at other similarities between non- aligned states and NATO or former Warsaw Pact states.

There are various ways to further categorize those contributing states such that similar doctrinal considerations toward building accountable systems in PKO- targeted states might be identified, but these are not investigated in this analysis.98

However, Chinese PKO participation is accounted for due to their increasing participation in peacekeeping operations and their permanent membership on the

UN Security Council.

Because there is no specific literature that discusses how Chinese military doctrine is concerned with internal accountability in the states it intervenes in it is difficult to make a clear prediction beyond what the theory suggests – that stability attributed to a non-aligned contributor should fall between NATO, where accountability is professed, and former Warsaw Pact states, who extant literature suggests would be indifferent to the concept. Accordingly, the following hypothesis is generated:

98 It is possible to look at former colonial relationships (e.g. former British or French holdings) to find similar doctrinal roots. Similarly, a client or partner relationship (e.g. US or Russian trained militaries in Africa, Asia, or the Americas) could also indicate similar doctrinal tendencies. 129

Hypothesis 6: Chinese peacekeeper presence during a peacekeeping intervention has a lesser positive effect on FDI inflows than NATO presence, but greater positive effect on FDI inflows than Warsaw Pact presence.

Unlike UN involvement discussed above, where categories reflect the level of access to information by larger numbers of sanctioning actors, the doctrinal aspect of peacekeeping presented in the theory is rooted at the individual level. Therefore, the analysis will consider the total number of NATO, former Warsaw Pact, or

Chinese peacekeepers that are deployed to a conflict-affected state in a specific year.

This approach accounts for the fact that in many cases, including most modern UN- led missions, participation from states outside of these three classifications represent the bulk of peacekeepers deployed. If doctrinal background matters, the effect on stability should be limited to the degree that these influences are present within the larger PKO contingent.

4.3.2.4. Force size and PKO composition

Beyond the type of uniformed peace operation employed (UN-led, UN- authorized, UN-recognized, non-UN) and doctrinal nature of the deployed forces

(NATO, former Warsaw Pact, or China) and consistent with the theory’s suggestion that a larger PKO size will likely result in greater collection of information, the analysis will account for the size of all deployed forces in a given year segregated by

Troop, Civilian Police, Formed Police Units, and Observers.

Previous studies (Benson & Kathman, 2014; Hultman, 2013; Hultman et al.,

2013; Kathman, 2013) have considered the numbers of troops deployed to UN-led 130 missions, and Simmons (2014b) demonstrates that an increase in the numbers of

UN troops deployed has a positive effect on FDI inflows. Observers are, by definition, information collectors and reporters. The theory argues more observers means more information and greater stability. While Simmons (2014b) found no significant effect on FDI inflows as the number of civilian police increased in UN-led

PKO, this study accounts for a wider range of PKOs and an analysis that considers mission strength and breakdown across all PKO categories, without accounting for civilian police contributions (to include Formed Police Units), will likely suffer from omitted variable bias. Despite earlier findings, the theory suggests that the presence of civilian police should positively contribute to the collection and dissemination of information based on the interactive role they play within a mission’s parameter.

The basic information gathering roles associated with each type of peacekeeper suggests the following:

Hypothesis 7: Increases in peacekeeping force strength have positive effects on inflows of FDI.

This hypothesis can be tested by considering a total count of peacekeepers deployed in a country-year, but this offers little information on the impact of peacekeeper type. The theory does not suggest that one type of peacekeeper is better at generating oversight than the other, instead the theory posits that each type of peacekeeper has the ability to collect information due to the nature of their duties and greater numbers should increase information collection. Taking this into account, I will also test by considering the total contributions by peacekeeper type. 131

This approach will offer greater insight into the effects of force composition that the theory suggests has an effect on PKO oversight.

While the breakdowns of troop, observer, and civilian policing figures are well known for UN missions post-1992, not all peace operations offer details to such a level. To build a reliable and valid dataset it was necessary to use a wide variety of primary, secondary, and even tertiary sources that represent are recognized as reputable collections of historic PKO data (See Appendix B).99

For all UNPKOs deployed after 1991 I utilized those statistics published monthly by the Department of Peacekeeping Operations (DPKO) to construct a monthly by-contributing country dataset that I converted to yearly observations for each mission. This was accomplished by taking the maximum contribution per contributor in each category: troop, police, formed police unit, and observers.100 For the remaining UN missions and all non-UN-led missions, I built comparable yearly datasets using the sources described above. These yearly peacekeeper contribution datasets were converted to by-country-year datasets for all cases in the sample and finally merged into a single dataset for analysis.

The resultant dataset provides a comprehensive account of PKO participation across all missions in this study, but while contributing states may be identified,

99 These include online archival resources available from the UN, the African Union, NATO, newspaper reports, and hard copy periodicals such as The Military Balance published annually by International Institute for Strategic Studies. 100 The UN data from 1991 is not disaggregated by peacekeeper type. The figures from these files are included in yearly force totals but I did not include them in the disaggregated totals for those years. 132 gaps remain in the details for some missions on specific deployment numbers. This includes key UN-led missions such as the UN Observer Mission in India and Pakistan

(UNMOGIP) before 1992, and UNTSO.101

4.3.2.5. Troop type

Although data issues prevent its inclusion in the analysis at this time, the final PKO characteristic that I have argued is relevant to increased scrutiny or oversight is that of troop type. Based on my theory, classifying troop type entails the separation of operational troops, who would be the direct collectors of information, from those support troops whose primary role in the operations does not likely involve interaction with the local environment.

The mission profiles of these two troop types are drastically different and their deployment would likely be tied to the expected employment during the peacekeeping mission. For example Beardsley (2011), Beardsley and Gleditsch

(2015), and (Kathman, 2013) point to the ability of peacekeepers to seal borders and prevent the movement of armed actors, but there is no real discussion on how many members of the operations examined were actually involved in this sort of activity. Similarly, Hultman, et al. (2013) use the aggregate number of troops as a

101 An effort was made to find missing UN-led data by visiting the UN archives in at UN Headquarters in New York, NY in May 2018. However, a variety of issues with both UNDPKO record keeping (namely the lack of mission specific data for historic missions) and UN archive organization made a complete review of potential data sources for this level of detail on these specific mission years unfeasible for inclusion in this study. 133 key independent variable in their study and argue that more troops equates to fewer civilian casualties. At a minimum understanding what part of a force might actually leave the compound to conduct peacekeeping is necessary if a full understanding of the relevance of PKO size is expected.

Much like available data on troop strength, data on troop type is similarly problematic across the entirety of the sample. While periodicals such as The

Military Balance provide specific information on the type of unit (infantry battalion, signal company, Military Police platoon) and strength numbers for each unit type, there is a high degree of variance in how the periodical reports this information from year to year and if missions are reported at all.102 This holds particularly true across the span of the dataset as the data collection and reporting rules of the periodical’s editors have changed over time.

A second approach to identifying troop type is particular to some UN-led missions where troop type designations are not available in UN reporting or other common sources. This method involves identifying units by type according to graphical depictions on UN troop deployment maps. As seen in Figure 4-3 the UN uses graphical symbols103 to depict the geographic location, command affiliation, unit type, and relevant size, of its peacekeeping forces. These maps are used

102 In some instances, only the location of a deployment was provided rather than a named mission. In these cases, data from Military Balance was cross referenced with other sources, such as Mays (2011) to associate deployments with known peacekeeping operations. 103 The UN provides a separately published document detailing the meaning of each graphical symbol. 134 primarily for planning and briefing purposes at the UN headquarters level but are now released publicly and available online or in the UN library’s map holdings.104

Coupled with extant numerical data, these maps allow for a detailed analysis on UN- led missions and may be used for future research.105

Figure 4-3: UN deployment map for the UN PKO in the Central African Republic (MINUCA), February 2018 (from reliefweb.int; accessed January 2019)

104 Based on interviews with representatives from UNDPKO and the UN’s geospatial analysis staff, May 2018. 105 This method was developed and employed by the author during his tenure at the US Department of State’s Office of the Geographer and Global Issues (2015-2018) to compile mission specific data on UN PKOs. 135

4.3.3. The nexus of aid and PKO-driven oversight

To this point a series of testable hypotheses have been offered that reflect the theory presented in Chapter 3. However, key to the theory presented in that chapter and summarized above is the notion that stability has two primary components. First, the behaviors or interactions inherent in the state’s political network and second, the oversight mechanism that alerts when behaviors go beyond what is accepted by the society and therefore performs a limiting function on behavior.

In post-conflict states where the international community has deemed it necessary to intervene in order to restore stability within both the conflict-affected state and the broader international community, the two tools identified to address perceived faults in the political network and the oversight mechanism are targeted foreign aid and the deployment of peacekeeping operations respectively. As described above, it is possible to determine the independent effect of each intervention on stability. The hypotheses proposed demonstrate that by considering various characteristics of the interventions we can build a model to show how each variation in aid or peacekeeping might do so.

I argue that the effect of aid funding and the presence of peacekeepers on stability can best be determined by considering the judgement of foreign investors on the economic enabling environment within the conflict-affected state. Evident in the discussion and hypotheses presented above, this chapter offers foreign direct investment inflows as a feasible measure of the state’s economic enabling 136 environment. A proxy of overall stability, the enabling environment is a concept defined by societal conditions, including a regularity of behavior, that appeals to foreign investors who are profit-driven but also concerned over the security of their long-term investments.

Beyond the independent effects discussed above, aid and peacekeeping have an interactive effect. Aid’s ability to positively affect stability is reliant on the supply of information regarding the target state’s use of national resources. PKOs perform this function of external oversight or scrutiny at varied levels depending on mission design. I also argue that higher levels of UN involvement serve as the primary driver of oversight capacity, while the remaining characteristics (force size, doctrinal background, and troop type) refine oversight capacity within each PKO category.

Together, this suggests that independent effects on stability will be less than what is observed when both aid and peacekeeping are considered at the same time.

An interaction is included in the analysis model to account for this relationship, this nexus of effects represents the primary hypothesis the analysis aims to test.

Hypothesis 8: The interaction of development-focused aid and higher levels of UN involvement has positive effects on FDI inflows.

4.3.4. Control variables

In addition to the independent variables presented above, the analysis will include several controls. These variables are either necessary to complete the story 137 of aid and peacekeeping’s effects in conflict-affected states presented in the theory or to account for the significant disparity between those cases included in the analysis.

4.3.4.1. Conflict periods

As discussed in Chapter 3, each case included in the analysis represents a state that has gone through four stages of conflict: pre-conflict, conflict, intervention, and post-intervention.106 I argue that stability across these four time periods varies with the effects of targeted foreign aid and the presence or absence of peacekeepers.

By definition, stability will be lowest during the conflict period, but the theory asserts stability will be it will be highest during periods of intervention due to the interactive effect discussed above. Stability during a PKO’s presence is increased over the pre-conflict period, regardless if aid is flowing during both periods, because oversight will be the highest of any period. Following the physical intervention, stability is expected to decline but remain higher than the pre-conflict period due to the remnant effect of increased oversight.

In addition to the theoretical reasons for including the conflict periods in the analysis, it is necessary to consider and control for the possibility that investors are simply looking for obvious signals indicating that general conditions have changed if

106 Because foreign aid can flow across all conflict periods this study uses the concept of an intervention period to indicate the presence of a PKO; post-intervention indicates the period after the mission has departed. 138 we acknowledge the dependent variable (FDI inflows) reflects the decisions of profit-driven investors. While extant literature on investment in post-conflict states offers a wide variety of indicators that investors might use to differentiate risk to investment (thereby delineating one conflict period from another),107 the analysis segregates pre-conflict from conflict based on a 25 battle-related death statistic.108

However, rather than considering the conflict to begin once 25 deaths are reached, the analysis uses the start year for the original dispute, as reported by Pettersson and Eck (2018) and Gleditsch et al. (2002). This allows for the fact that a state may be involved in a conflict where the number of battle-related deaths may fall below

25 per year. Finally, the analysis assumes the remnant effect of PKO oversight on stability (segregating post-intervention from a subsequent pre-conflict period) extends to three years after the departure of a PKO.109 A by-country breakdown of the total number of conflict period years is provided in Appendix C.

What may not be clear from the information provided in Appendix C is why there are cases where these periods appear to overlap. For example, Lebanon has

107 These include adherence to human rights norms (Blanton & Blanton, 2007), the establishment of post-conflict justice systems (Appel & Loyle, 2012) or even changes in aid contributions (Bandyopadhyay et al., 2014; Garriga & Phillips, 2014). 108 The UCDP/PRIO Armed Conflict Dataset v. 18.1, Pettersson and Eck (2018) and Gleditsch et al. (2002) provides the start year of the conflict and the year when 25 battle deaths are reached. The analysis utilizes the former. 109 There is no recognized time span to define a post-intervention period; a three-year period was selected in an effort to account for the assumption that aid commitments made under higher levels of oversight will demand similar, albeit lower, levels of accountability until the associated projects are complete. Assuming a two-year budgeting cycle on aid programming (as used by the US Agency for International Development), three years would likely account for project identification, approval, and execution. 139

44 years coded as intervention years as well as 44 years coded as conflict years.

Within the UCDP/PRIO Armed Conflict Dataset v. 18.1 there are three periods where battle deaths in Lebanon reached 25 (1975-76, 1982-86, and 1989-90). Each of these periods is attributed to a conflict that began in Lebanon in 1958. I code 1970-

1990 as conflict years to cover the start of the 1958 conflict period and the end of the most recent period marked by 25 battle deaths 1970-2013. However, because of the continued deployment of UNTSO in Lebanon, resulting from the conflict over the 1948 partition of Palestine, I also code 1970-2013 for Lebanon as conflict years and intervention years as well. 110

4.3.4.2. Country specific controls

I will control for population and GDP per capita to account for the wide variance in state-level characteristics among the cases included in the dataset.

Yearly population totals for each case in the study were taken from World Bank’s

Open Data website (IBRD-IDA, 2019c). Yearly GDP figures in current US Dollars also come from the World Bank (IBRD-IDA, 2019b) and those yearly figures are converted to constant 2011 USD GDP per capita for each case in the sample using the respective population data. Although these variables are somewhat related, they provide different stories related to FDI inflows when compared to aid or peacekeeping interventions.

110 Because the analysis dataset has been collapsed into country-year observations the overlapping conflict years are not double counted. 140

GDP per capita reflects the economic well-being of the average citizen based on the growth of the national economy. Since this is a statistic compiled and reported by the state it could arguably be used to incentivize investment in cases where firms look for opportunities in emerging markets111 Similarly, GDP per capita could influence how development aid is targeted; higher GDP per capita might prompt lesser focus on economic development if markets and policies are viewed as sufficient to sustain a higher level of stability. As a result, aid donors may focus more on other social issues or even place greater concentration on security concerns. As discussed previously, greater focus on security issues is argued to be detrimental to economic welfare in post-conflict states.

4.3.4.3. Regional effects

The main dataset includes 2860 country-year observations, of which 1180

(38.46%) represent post-conflict cases in Sub-Saharan Africa and an additional 440

(15.38%) in the Middle East and North Africa. While these two regions are not identical, the fact that over 51% of all observations originate from the African continent and its nearest neighboring region suggests the possibility that results may be affected by region. To account for this a variable is introduced into the analysis that groups observations according to their World Bank regional classification (seeTable 4-4) (IBRD-IDA, 2019e).

111 Emerging markets are defined by rapid economic growth, low per capita income, high market volatility, immature capital markets, higher-than-average return for investors (Amadeo, 2019). 141

Table 4-4: World Bank regions

World Bank Frequency Percentage Cumulative % Region East Asia & Pacific 220 7.69 7.69 Europe & Central 528 18.46 26.15 Asia Latin America & 396 13.85 40.00 Caribbean Middle East & North 440 15.38 55.38 Africa South Asia 176 6.15 61.54 Sub-Saharan Africa 1100 38.46 100.00

4.4. Modeling the Intervention Nexus

The analysis will employ standard OLS regression due to the continuous nature of FDI inflows. Two basic models will be tested to determine if the theoretical effects of targeted aid and the presence of peacekeepers are supported.

Model 1 will account for all variables discussed above minus the interaction and the variable accounting for intervention years.112 The intervention year dummy variable is removed because it represents the presence of a PKO in the observed country-year. Because the dummy variables for mission type offer the same information (PKO presence) there is a strong correlation with the dummy variable for UN led missions (the dominant mission type represented in the dataset). In cases when no UN led mission is present and the other types are, those dummy

112 A preliminary analysis found this variable had high collinearity, scoring a VIF over 9.0. This is likely due to the fact that the variable accounting for UN involvement represents a related concept (i.e. PKO presence) and there are instances where intervention occurs in the same year as conflict is ongoing. 142 variables also provide the same information to the model as an intervention year dummy variable. This preliminary analysis is used to determine if the predicted independent effects of aid and peacekeeping can be observed when we account for all aspects of the theory. The interaction variable is introduced in Model 2. In this model, the mission type dummies are removed and replaced by the ordinal variable indicating UN involvement. Like Model 1, the intervention year dummy variable is removed because any UN involvement not equal to zero indicates PKO presence.

Based on the theory, the interaction will be generated using the variable specifying

UN involvement and the variable specifying development aid commitments.

Because the variable is categorical and represents a grouping by UN involvement the model allows us to see the interactive effect as that involvement increases across the sample.

Model 1: 113

�� = � + ��. �� + �� +

�� + �� + �� + �� + �� +

�� + �� + �� + �� + �� + ��. �� + � �� + � �� + � �� + �

113 These models are representative of the statistical models used in the analysis employing Stata15. The “i.” designation indicates where the variable will be coded as a categorical or factor variable. This means Stata15 will calculate the regression incorporating the single categorical variable but report the effects of each category represented in that variable. This allows us to see the different effects attributed to each level of UN involvement. 143

Model 2:

�� = � + ��. �� + �� +

�(�. �� ∗ �� ) + ⋯ + �

To determine whether or not investors base their decision to invest on the previous year’s investment a third model is introduced to determine if FDI inflows are positively related to inflows from the previous year.

Model 3:

�� = � + �� + ��. �� + �� + �(�. �� ∗ �� ) + ⋯ + �

Introducing a lagged dependent variable should account for any effects that the remaining independent variables would have on current-year FDI inflows if each variable were lagged individually. Additionally, if the non-lagged variables offer similar results generated by Models 1 or 2, it would suggest that stability can be established in a short time period if the correct interventions are introduced, regardless of the previous year’s level of stability.

4.5. Summary

This chapter provided a summary of the theory presented in Chapter 3 and further explained the logic of using economic conditions to represent a post-conflict state’s enabling environment. Additionally, a justification was offered for the use of 144 non-portfolio FDI inflows as the key dependent variable in the study. Multiple hypotheses were presented that are derived from assertions made in the theory regarding the effect that targeted aid and the presence of peacekeeping operations on stability.

These hypotheses account for the independent and interactive effects that aid, and peacekeeping interventions have on stability; this includes the manner in which aid is targeted, the level of UN involvement during an intervention year, as well as additional mission characteristics that are posited in the theory to account for variations in effect among like-PKO types.

Control variables that account for national level variations and regional variations across the sample are introduced to address the possibility that the dependent variable selected is responding to non-intervention effects. Additionally, controls categorizing the conflict period specific to each yearly observation are included to address the theory’s assertion that the effects of intervention can be identified across these time periods, and to account for the fact that investors may use unspecified signals to identify the best or worst times to invest.

Finally, three empirical model types that will be used in the study provide the basic roadmap the study will employ during analysis. The first model looks to establish a baseline and determine the validity of assertions made in the theory about the independent effects of aid and peacekeeping. The second model applies an interaction to test the theory’s assertion that aid is most effective at promoting stability when it is applied under the increased oversight imposed by a PKO. The 145 final model tests for the effect that the previous year’s stability has on current year stability in order to determine if interventions make a positive impact in the current year but also to understand the effect they have on future years. 146

Chapter 5

Analysis and Results

In Chapter 4 I presented three general models to test the theory that two independent but simultaneously occurring interventions, directed foreign aid and the deployment of peacekeeping forces, impact stability in conflict-affected countries. More importantly, I argued that the most positive impact on stability results when higher levels of development aid are injected under higher levels of international scrutiny, a condition brought about in this context through increased

United Nations involvement in peacekeeping efforts. This argument is based on the premise, initially characterized by Ake (1975) that stability is defined by a network of somewhat predictable interactions or behaviors that occur within a society (its political network) and the oversight provided by the laws, systems, or customs that attempts to limit the network from exceeding what the society deems acceptable. 147

I further argued that we can look to economic conditions within a state to determine its level of stability. Recalling Mills and Fan (2006), who espouse that a state’s economic enabling environment114 is the driver of its investment climate, I suggested that international interventionists aimed at increasing stability are actually focused on affecting change within this environment. Foreign aid aims to change or improve selected behaviors, while the physical presence of peacekeepers provides inherent oversight – particularly in regard to the accountability of state resources.

Recognizing the relationships between the enabling environment, the investment climate, and two notable mechanisms of international intervention, we can determine the efficacy of interventions by looking at the results of decisions made based on an independent external evaluation115 of the investment climate and the enabling environment that defines it. I suggested that non-portfolio foreign direct investment (FDI) inflows, where private investors control or significantly influence the management of an enterprise (i.e. ownership) physically located within the conflict-affected state,116 serve as a measure of stability. This is because

114 This is defined by institutions, quality of governance, trust between government and the populace, and political-economic conditions. 115 Recall that each intervention will have its own advocates or detractors judging their impact on stability through intervention-specific measures (i.e. the completion of an aid-funded program or the fulfilment of a mandate-driven task). 116 The World Bank defines non-portfolio FDI as the sum of equity capital, reinvestment of earnings, and other capital invested across international borders affording a significant degree of ownership in a foreign firm; “ownership of ten percent or more of the ordinary shares of voting stock is the criterion for a foreign direct investment relationship” (Simmons, 2018). 148

decisions to inject financial assets into (or remove from) a foreign economy represent judgements made (resulting from that external evaluation) on the current and long-term stability of the conflict-affected state. Positive FDI inflows would indicate increased confidence in the investment climate and its supporting enabling environment (i.e. increased stability), while negative FDI inflows suggest the opposite.

5.1. Data and modeling

5.1.1. FDI inflow values

To begin the analysis, it was necessary to decide on which measure of the dependent and independent variables would be used. As discussed in Chapter 4,

FDI inflows are available in a variety of measurements. In an effort to keep the analysis as straight forward as possible, I elected to begin with current year US dollar measures of FDI inflows obtained from the World Bank (2018b). However, two issues with this selection were immediately recognized.

First, the use of current US dollars (USD), where values reflect the US inflation rate of each year in the dataset, would make any time series analysis, or a comparison of results between different time periods when those rates differed, problematic. This is an issue subsequently identified in data for other monetary- based variables used in the analysis as well (specifically foreign aid commitments and gross domestic product figures). 149

It was decided that converting all currency figures to a constant USD measure would be needed.117 2011 was selected as the base year for constant USD conversion because monetary values in constant 2011 USD were an existing variable in the AidData Core Research Release Level 1 version 3.1 dataset that was used to obtain foreign aid commitments for the analysis (AidData, 2017; Tierney et al., 2011).

The second issue immediately identified was the scale of FDI inflow values.

Both positive and negative FDI inflows are marked by a few extreme values. These extreme values result in a mean FDI inflows value of $833 million (constant 2011

USD) for the dataset; their exclusion drops the mean to $575 million (constant 2011

USD).118 Notably, the highest positive FDI inflow value, $78.4 billion, and the highest negative FDI inflow (i.e. outflow), -$21.6 billion, occurred in Hungary 2008 and 2010 respectively.119,120 FDI inflows were first converted to millions of constant

117 Monetary values are converted to 2011 constant USD by dividing current year figures by the yearly US consumer price index (CPI) figures scaled to 2011 CPI figures. CPI figures were scaled by dividing the yearly US CPI figures (1970-2013) by the 2011 US CPI value. 118 FDI inflows values exceeding $10 billion or below -$10 billion were removed for the calculation. 119 According to a report on Hungary by the Organisation for Economic Co-operation and Development (OECD), Hungary experienced one of the most severe economic recessions among OECD countries following the 2008 global financial crisis. The report specifies that collapsed trade was compounded by a collapse of foreign investor confidence based on faulted economic policy decisions (OECD, 2010). 120 Separate analyses using the interaction models discussed later in this chapter were completed due to the possible impact of the 2008 financial crisis. Two approaches to account for the crisis were utilized; the first creating a dummy variable for the year of the crisis (2008), and the second using a dummy variable to split the sample into pre/post crisis observations. The results reflected a significant effect (negative) only when the single year dummy was lagged for one year, none of the other coefficients were significantly impacted in any test. This suggests that the year following the crisis did experience an effect on FDI inflows due the crisis, but this effect did not change the impact of any intervention. 150

2011 USD (2011M$) simply to make values more comprehendible. Also, FDI inflow values were scaled121 to allow for a natural logarithmic transformation. Both options were used for initial testing purposes but due to general consistencies in the results across key independent variables there was no clear benefit to choosing one measure over the other.

Figure 5-1 depicts the distribution of FDI inflows for both values. It is clear that the vast majority of FDI values fall within a small range, regardless of what scale or transformation is being used, and that the extreme values continue to skew the data accordingly. It was decided to use FDI inflows (2011M$) rather than the natural log transformed values to more easily interpret the results.

121 All figures were summed with the positive value of the lowest FDI inflow value to create all positive values allowing for the logarithmic transformation. 151

Figure 5-1: Comparing histograms of FDI inflows vs. ln(FDI inflows)

Due to the remaining skewness in the distribution resulting from these extreme values, an alternate remedy was to identify those individual country-year observations that contained the extreme values and account for them in the analysis. There are eight states that saw FDI inflows greater than $10 billion in a given country-year, all observations with this characteristic occur after 2006 and include India: (eight observations), Peru (one observation), Israel (four observations), Hungary (five observations), Egypt (two observations), Cyprus (two observations), South Africa (1 observation) and Bulgaria (two observations).

Alternatively, Cyprus and Hungary were the only two states to have negative FDI inflows in excess of -$10 billion (one observation each) for the same period. A dummy variable was created for each country-year where being coded “1” indicates 152

FDI inflow values exceed $10 billion or -$10billion.122 These dummy variables were included in all models in the analysis in an effort to mitigate the effect these extreme values might have on the results. Figure 5-2 provides a representation of the distribution of FDI inflows if those few cases are removed. Notably, the distribution remains skewed slightly towards positive values.

Figure 5-2: Histogram of FDI inflows without extreme values

A preliminary analysis of the net inflows of FDI in the presence of aid and peacekeeping was performed. The scatter plots provided in Figure 5-3, Figure 5-4, and Figure 5-5 suggest that, in a majority of cases, FDI inflows are higher when UN-

122 Recall that FDI inflows measures used in the analysis are in millions of constant 2011 USD. 153

led PKOs are present and when more aid dollars are spent on development compared to security issues respectively. Notably, the sum and variance in FDI inflows during both UN- authorized and UN-recognized mission deployments is visibly smaller compared to no mission deployment or the presence of Non-UN missions – and in some cases FDI inflows are negative. A correlation analysis using the full dataset shows FDI inflows have a negative correlation with UN-authorized mission (-0.0291) and UN-recognized missions (-0.0208).

Figure 5-3: Scatterplot of FDI inflows by PKO-type

FDI Inﬂows by PKO Type 80000

60000

40000

20000

0 FDI net inﬂows in millions constant 2011constant millions in FDI net inﬂows USD

-20000

No Mission Non-UN UN-Recognized UN-Authorized UN-led PKO Type

Regarding foreign aid commitments, Figure 5-4 and Figure 5-5 illustrate how much greater development-focused aid commitments are compared to security- 154

focused aid, but that these higher development aid commitments do not correlate with high FDI inflows for a majority of time. Instead, security aid correlates with high FDI inflows even if those commitments are low for a majority of time.

Figure 5-4: Scatter plot of FDI inflows by development aid commitments123

FDI Inﬂows by Development Aid 80000

60000

40000

20000

0 FDI net inﬂows in millions constant 2011constant millions in FDI net inﬂows USD

-20000

0 5000 10000 15000 20000 Development Aid Commitments in 2011 millions constant USD

123 Development Aid data reflects only traditional development aid. Governance, Peace, and Reconstruction aid are not included. 155

Figure 5-5: Scatterplot of FDI Inflows by security aid commitments

FDI Inﬂows by Security Aid 80000

60000

40000

20000

0 FDI net inﬂows in millions constant 2011constant millions in FDI net inﬂows USD

-20000

0 200 400 600 800 Security Aid in 2011 millions constant USD

5.1.2. Refining peacekeeping variables for analysis

I created a created a dummy variable indicating PKO presence in the observed country-year and two sets of mission-type dummy variables prior to analysis, the first indicating solely mission type (UN-led, UN-authorized, UN- recognized, and Non-UN), the second indicating the highest level of UN involvement in the conflict-affected country in a given country-year based on an ordinal score 1-

4, with 4 representing highest UN participation. I then ran two sample t-tests on 156

each variable to test the hypothesis that PKO presence has an effect on FDI and to test if these variables captured those effects. 124,125

Table 5-1: Two sample t-test results – FDI Inflows and PKO presence dummy variable

PKO present Dummy PKO present* Variable

1=mission present 0 1 Observations 1504 733 Mean 634.9659 1239.748 Standard Error 83.89313 152.5799 Standard Deviation 3253.496 4130.943 t value -3.4733 degrees of freedom 1188.58 2-sided p value 0.0005 *Levene's Test indicates unequal variance, Satterwaite's degrees of freedom reported. The t-test of FDI inflows by PKO presence126 yielded t(1188.58)=-3.47, p<0.001127 demonstrating, as expected, that the variance in FDI inflows when PKOs are present is not random. However, when looking at the specific groupings of mission types deployed, as well as the highest level of UN-involvement during a given country-year, the results were not as expected. First, it was necessary to

124 I did not expressly present the hypothesis in Chapter 4 that PKO presence, in general, affects FDI but this is a premise of the thesis. 125 Prior to running t-tests I tested for homogeneity of variance between the two groups (i.e Mission type present or not present) using Levene’s test. A table of the results can be found in Appendix D. 126 Due to results from Levene’s test that the two groups have unequal variance, the t test was run under this assumption. 127 The two-sample t-test, performed using Stata15, yielded at p<0.001 that the difference between the mean (absent PKO) and the mean (PKO present) would not equal zero. This suggests that within a given sample of the data, changes in FDI inflows under PKO presence are not likely due to chance. 157

account for possibility that the two groups represented in each of the dummy variables (i.e. when the dummy =1 or 0) did not share equal variance. Levene’s Test for homogeneity of variance was conducted for each variable (see Appendix D) before the two-sample t-tests were run. Of the mission type variables, only the UN- led and UN-authorized variables were identified as lacking equal variance; this was accounted for during t-testing.

Notably, the t-tests for UN-recognized, and Non-UN missions yielded t values that were insignificant (see Table 5-2). This indicates that the presence of these mission types alone has no evident effect on FDI inflows. This process was repeated for the UN Involvement variables (see Table 5-3). Only the highest level of

UN involvement (UN Involvement 4)128 was significant with t(615.775)=-4.121.

These results indicate that only the highest possible level of UN involvement has an effect on FDI inflows.

128 Recall that the highest ordinal score for UN involvement (4) results from the presence of a UN-led mission in a given country-year. As a result, the UN-led dummy variable and the UN Involvement 4 dummy variable are perfectly correlated. 158

Table 5-2: Two sample t-test results – FDI Inflows and Mission Type dummy variables

Mission Type UN-led* UN Authorized* UN Recognized Non-UN Dummy Variable 1=mission type 0 1 0 1 0 1 0 1 present Observations 1736 501 2,152 85 2,073 164 2,084 153 Mean 619.748 1572.54 853.79 310.32 854.077 568.43 818.39 1034 Standard Error 73.3015 219.277 78.532 35.964 81.2646 87.189 80.313 157.2 Standard Deviation 3054.13 4908.09 3643.1 331.57 3700 1116.6 3666.3 1944.5 t value -4.121 6.2919 0.9849 -0.7197 degrees of freedom 615.775 1480.42 2235 2235 2-sided p value 0.0000 0.0000 0.3248 0.4718 *Levene's Test indicates unequal variance, Satterwaite's degrees of freedom reported.

Table 5-3: Two sample t-test results – FDI Inflows and UN involvement dummy variables

UN Involvement UN Involvement 4* UN Involvement 3 UN Involvement 2 UN Involvement 1 Dummy Variable 1=PKO(s) present 0 1 0 1 0 1 0 1 with associated score Observations 1,726 501 2,169 41 2,144 93 2,139 91 Mean 619.748 1572.54 842.04 356.36 843.29 599 847.66 516.05 Standard Error 73.3015 219.277 76.98 67.614 78.638 138.3 78.905 101.86 Standard Deviation 3054.13 4908.09 3607.4 432.94 3641.2 138.3 3649.3 1008.4 t value -4.121 0.8618 0.6449 0.8978 degrees of freedom 615.775 2235 2235 2235 2-sided p value 0.0000 0.3889 0.519 0.3694 *Levene's Test indicates unequal variance, Satterwaite's degrees of freedom reported. 159

As a follow-up to the t tests, I ran OLS regressions for each set of mission- type variables. Although the t-test results suggested that FDI Inflows weren’t affected by the presence of UN-recognized or Non-UN missions, or when UN involvement was not at the highest level, the t-tests (particularly for mission type variables) do not reflect the reality that multiple mission-types can be present at the same time in a conflict-affected country. I judged that each set of variables would be included in the initial regression analyses to account for this.

These initial regression analyses included only the PKO variables (and dummy variable controls for the extreme FDI inflow values) to determine if the PKO variables had a significant effect on FDI inflows, see Table 5-4. More importantly, I wanted to determine which set of variables should be used for the full analytic model.

The preliminary analysis supports the theory that high levels of UN involvement in deployed PKOs have positive effect on FDI inflows.129 However, the results appear to show that this only matters when the UN leads a mission or if a UN led mission is deployed alone or beside any other PKO. If another organization or contributor leads a PKO, despite having some level of UN involvement, these initial results indicate a negative effect on FDI inflows. The positive and significant effect of Non-UN missions was surprising. However, there are 60 observations where

129 All regression models include extreme FDI dummy variables, but they have been removed for reporting purposes. 160

Non-UN missions are deployed alongside UN led missions; this equates to 36% of all

Non-UN missions. It is possible that this positive and significant effect reflects my assertion above that simultaneously deployed missions have a combined effect on

FDI inflows.

With three of the four mission-type variables returning a statistically significant results in the PKO variable-only regressions compared to only one of the

UN involvement variables, I judged that using the specific mission-type dummies would be the most effective way to capture the effect of UN involvement on FDI inflows while also accounting for each mission-type’s presence or absence in a country-year observation. 161

Table 5-4: OLS regression for PKO variables

Model 1 Model 2 VARIABLES FDI Inflows FDI Inflows

UN-led dummy 389.1*** (70.05) UN-authorized dummy -383.6* (149.0) UN-recognized dummy -110.5 (109.1) Non-UN dummy 280.7* (112.6) UN Involvement 4 371.1*** (69.73) UN Involvement 3 -133.7 (211.0) UN Involvement 2 109.0 (142.5) UN Involvement 1 25.99 (139.0) Constant 493.2*** 490.1*** (33.43) (34.49)

Observations 2,237 2,237 Adjusted R-squared 0.862 0.861 Standard errors in parentheses *** p<0.001, ** p<0.01, * p<0.05

5.1.3. Refining aid commitment variables for analysis

Foreign aid commitments represent the second key independent variable for the analysis. As discussed in Chapter 4, all aid commitments were aggregated according to the coalesced purpose codes defined by AidData, and further 162

aggregated into five primary aid groups130 in an effort to address the hypotheses specific to aid type.

Although the AidData dataset (AidData, 2017; Tierney et al., 2011) used to create the analysis dataset contains observations for over 1 million recipient- specific aid related projects, data gaps are generated when those contributions are compiled into recipient country-year observations and further disaggregated by usage code. This results in a significant number of observations with missing data for one or more of the aid commitment variables. Knowing that some donors do not provide the specifics of aid donations at a highly disaggregated level it was deemed inappropriate to code observations without a corresponding project in the AidData datasets as zero.131,132 Therefore any observations that had no reported values were coded as missing data.

Table 5-5 provides a pattern summary of missing aid values by aid category.

Each column in the table reflects a category of aid. Each row in the table provides the percentage of all observations in the dataset where the missing data pattern depicted in that row occurs.

130 Development (i.e. Traditional Development), Security (specific to military/security sector issues), Governance, Peace, and Reconstruction. 131 AidData’s associated literature highlights that some donors only report aggregate contributions. 132 Chinese data, taken from a second AidData dataset (Dreher et al., 2017), is the only supplemental aid related data included in the analysis. However, personal correspondence with the AidData team (Russell, 2019) confirmed that coding rules permitted the combination of these two datasets. 163

Table 5-5: Missing aid data by aid type variable

Patterns of missing data in aid catagories within the dataset Percentage of total Development Governance Reconstruction observations Peace Aid Security Aid Aid Aid Aid were pattern occurs 21 1 0 0 0 0 20 1 1 0 0 0 18 1 1 1 1 1 17 0 0 0 0 0 6 1 1 1 0 0 5 1 1 0 1 1 3 1 1 1 0 1 3 1 1 1 1 0 3 1 1 0 1 0 2 1 1 0 0 1 2 1 0 1 0 0 <1 1 0 0 0 1 <1 1 0 1 1 0 <1 0 1 0 0 0 <1 1 0 0 1 0 <1 0 0 0 1 0 <1 0 0 1 0 0 <1 1 0 0 1 1 <1 1 0 1 1 1 100% 1 indicates dataset includes aid commitment data for select aid variable, 0 indicates missing data. Highlighted row reflects the percentage of observations included in the analysis

164

For example, Row 1 indicates that 21% of all observations contain data only for development aid, data for all other categories of aid is coded as missing. Rows are ordered in descending order of percentage represented within the dataset.133

From Table 5-5 we can see in Row 3 (highlighted) that only 18% (514) of the observations in the dataset have no missing data in any of the five aid category variables. However, 65% of observations in the dataset have missing data in one or more of the five aid categories while the remaining 17% have no aid data at all.

As a result of these missing data and the decision not to code missing commitment data as zero, the number of observations included in the analysis drops from a possible 2237 (based on available FDI and PKO data) to 510 observations when all aid categories are included. Although this highly restricts the analysis to only those country-years when all types of aid relevant to the study are being contributed, the subset better reflects conditions expected in a post-conflict situation (or ongoing conflict situation) where PKOs may or may not be deployed but the conflict-affected states are receiving all variety of relevant aid types. I performed OLS regressions using the by-sector aggregated commitment values in

133 The ordering of rows with equal percentages is generated by Stata 15. It can be assumed that the ordering of these rows reflects descending order, but Stata does not report below whole numbers. 165

Table 5-6: OLS regression, aid commitment variables and percentage of total aid variables134

Model 3 Model 4 VARIABLES FDI Inflows FDI Inflows

Development Aid 0.221*** (0.0461) Security Aid -2.653 (1.393) Governance Aid 0.262 (0.379) Peace Aid -1.557 (2.533) Reconstruction Aid -0.0278 (0.392) % Development Aid 1,774 (2,079) % Security Aid 621.8 (2,552) % Governance Aid 729.8 (2,249) % Peace Aid omitted

% Reconstruction Aid 310.0 (2,368) Constant 672.3*** -642.0 (83.02) (2,066)

Observations 510 510 Adjusted R-squared 0.767 0.754 Standard errors in parentheses *** p<0.001, ** p<0.01, * p<0.05

134 The dummy variable for percentage of total aid applied to Peace efforts (% Peace Aid) serves as the reference variable for Model 4. 166

millions of constant 2011 USD as well as the percentages of total aid commitments each group represented, see Table 5-6.135

Notably, Development Aid (in millions constant 2011USD) was the only variable in either model to return a positive and statistically significant result. I had expected Governance, Peace, and Reconstruction Aid categories (each an aspect of non-security focused aid) to have a similar effect on FDI inflows. This would have been inline not only with my theory but also the expectation suggested by aid literature. However, the fact that the Development Aid variable accounts for a large portion of aid subcategories and the majority of commitments, the result is not totally unexpected. Despite this preliminary result, the analysis will include all commitment amount variables (not percentages) to ensure that the cumulative effect of each aid type is reflected in the results.

5.1.4. Baseline model

Based on the initial OLS regression results (Models 1-4) (see Table 5-4 and

Table 5-6) I elected to include all mission-type dummy variables (UN-led, etc.) in the next series of tests. Likewise, I elected to include all purpose-specific total aid

135 As discussed in Chapter 4, commitments to select categories such as humanitarian relief and disaster response were not included in the development category, nor were they included in total aid commitments used to calculate percentages. 167

commitment variables. Model 5 generated similar and generally expected results based on earlier testing (see Table 5-7). While the negative and significant coefficients associated with UN authorized and UN recognized mission appear to counter my theory, the model does not account for all mission parameters discussed in Chapters 3 and 4.

Table 5-7: OLS regression with key independent variables only

Model 5 VARIABLES FDI Inflows

UN-led dummy 356.1* (142.8) UN-authorized dummy -688.8*** (115.7) UN-recognized dummy -496.6*** (119.0) Non-UN dummy 198.6 (169.9) Development Aid 0.188* (0.0914) Security Aid -2.244 (1.237) Governance Aid 0.439 (0.528) Peace Aid -0.636 (2.171) Reconstruction Aid -0.0554 (0.415) Constant 710.8*** (110.3)

Observations 510 Adjusted R-squared 0.774

Robust standard errors in parentheses *** p<0.001, ** p<0.01, * p<0.05

168

That said, it is apparent from the predicted values and residuals plots in

Figure 5-6 and Figure 5-7 respectively that Model 5 appears to under-predict FDI inflows. What is more notable is the linear trend of residual values away from 0 as the predicted values increase. This suggests heteroskedasticity in the regression, or variance in the model error attributed to some unspecified variable.136,137

Figure 5-6: Predicted FDI inflows – mission types and aid commitment variables (Model 5)

Predicted FDI Inﬂows Primary Independent Variables 10000

5000

0 FDI 2011M$Inﬂows

-5000

FDI inflows 2011M$ 95% CI Fitted values -10000 -2000 0 2000 4000 6000 8000 Predicted FDI Inflows Extreme FDI inflows not represented

136 I also followed this process using ln(FDI inflows) to confirm extreme FDI values were not generating any unanticipated effect on the model. The resultant plots were similar. 137 A post-estimation analysis using White’s test for homoskedasticity was performed using Stata 15 and verified the heteroskedastic condition. 169

Figure 5-7: Residuals plot – mission types and aid commitment variables (Model 5)

Residuals Plot Primary Indepedent Variables

20000

10000 Residuals

-10000 -2000 0 2000 4000 6000 8000 Linear prediction Extreme values not plotted

As previously highlighted, my theory rests on the premise that foreign aid and peacekeeping affect stability by targeting behaviors and imposing oversight respectively. In practice, the interventions aim to affect the post-conflict state’s economic enabling environment which is the composition of country-specific factors representing multiple aspects of the society. Due to this complexity, the heteroskedastic condition of the regression is not unexpected; the independent variables selected for the analysis cannot account for all potential variations in each country within the sample.

The modeling misspecification is arguably the result of an assumption made during initial modeling and testing that each observation is independent from the 170

other. Rather than all conflict-affected states in the analysis sharing some similarity that would allow them to be considered a single group (thus imposing a single, constant source of variance on the model that would be observed in the residuals), the initial results suggest there is some significant un-modeled country effect or time effect that needs to be mitigated in order to obtain reliable results.138

Moving forward I elected to also employ robust standard errors, a technique that aims to address the heteroskedasticity issue. However, as King and Roberts

(2015) point out, while the employment of robust standard errors in OLS regression has become a standard practice when model misspecification is known to exist, the procedure does not correct the model itself. This not only required a reconsideration of the variables that would be included in the final models but also how those variables would be quantified.

5.2. Model refinement and hypothesis testing

5.2.1. Variable refinement

In Chapter 3 I argued that PKO mission design, second only to UN involvement, was the most obvious way to change the level of oversight that a PKO brings into a post-conflict environment. In Chapter 4 I offered two ways that

138 Region-specific OLS regression analyses were conducted using the full model in an effort to identify a higher-level group effect. No pairing of regions shared similarities in coefficients, suggesting the variation is generated at a lower level or due to time. 171

mission design can be altered which will be tested in this analysis: force composition and PKO doctrinal background.139

Recalling that force composition is defined by the number of troops, military observers, and individual civilian police or civilian formed police units (FPUs) it is important to specify which quantities were used. As discussed in Chapter 4, all force composition data for UN-led PKOs beginning in 1991 were taken directly from consolidated monthly spreadsheets uploaded to the UN Department of

Peacekeeping Operations website.140

While the reporting format varied slightly between 1991 and 2013 the consolidated monthly reports provide the number of troops, civilian police141, and observers, by Troop Contributing Country (TCC) or Police Contributing Country

(PCC) for each UN-led mission that was active in that month. It is important to recognize that these reported numbers reflect the total number of personnel present and under the control of the mission at the time of the count. This means that numbers do not reflect the total number of personnel assigned to the mission

139 A third option (comparing operational to support troops within the force) was offered and a methodology was presented in Chapter 4, however, current data limitations prohibit the inclusion of this design option in the current analysis. 140 See: https://peacekeeping.un.org/en/data. 141 It should be noted that formed police units (FPUs) or civilian peacekeeping police units that operate in the absence or in support of a local police force, are not represented as complete units throughout the UN data. FPUs are only listed in the dataset for this analysis if they were designated by the UN to be FPUs, regardless if numbers are consistent with earlier reports. 172

but only those present for duty on the day of the count (e.g. not on a temporary leave of absence or enroute to the mission).142,143

These monthly totals were compiled into a larger dataset of UN-led missions post-1991 from which the highest number of personnel per TCC/PCC, per mission- year were drawn. Barring the error imposed by the UN’s methodology for reporting only those peacekeepers physically present on the day of the report, this process for determining yearly by-TCC/PCC contributions for each mission arguably injects an additional degree of error into mission composition numbers. However, in all other cases, outside of the post-1991 UN-led missions, mission composition numbers used for the analysis dataset were predominantly derived from the number of personnel each TCC/PCC reported as being sent by the contributor, not necessarily from an official report such as those UN reports mentioned above.144,145 Assuming TCCs and

PCCs would report their largest verifiable contribution totals, the decision was made to use the largest reported number of contributions per TCC/PCC, per mission, per year. These yearly values were combined with the post-1991 UN data to construct

142 According to discussions with various staff officers within UNDPKO, May 2017. 143 This reporting practice is also observable in reports from the Secretary General to the UN Security Council. 144 Sources, such as The Military Balance (1970-2013), (Mays, 2011), and (Boulden, 2003), whose figures on mission composition were used to construct the analysis dataset, cite a variety of primary and secondary sources to derive contribution numbers by TCC/PCC. 145 In select, pre-1991 cases reports filed by the UN Secretary General and submitted to the security council were used to determine troop commitments. All data sources are provided by mission in accompanying code book. 173

the mission totals for the troop, police, FPU, and observer variables, as well as a variable for the total force strength.146

Because the data were constructed by yearly TCC/PCC contributions, it was possible to create variables identifying the doctrinal make-up of the missions.147

These include dummy variables for the presence of NATO, Warsaw Pact (to include former Warsaw Pact), and Chinese peacekeepers, as well as total contributors according to each doctrine grouping.

A correlation analysis of the composition and doctrine variables identified a high correlation (0.89) between variables for the total number of troops (Total

Troops) and the total number of NATO personnel (Total NATO)148. Similarly, the

NATO dummy variable had a high correlation (0.77) with both the UN-led dummy variable and the dummy variable for the highest level of UN involvement (UN

Involvement 4).149 This made the inclusion of either NATO variable problematic. A post-estimation Variance Inflation Factor (VIF) analysis using a test model with

146 In those instances when the specific number of personnel per TCC/PCC was not known the average across all contributors was used for each TCC/PCC. Additionally, if a mission is dispersed across multiple countries but only a single total for each peacekeeper was known, the average was used for each mission subset. 147 Missions were coded as having “NATO”, “Warsaw Pact”, or “Chinese” peacekeepers based on the observation year; specifically, which contributors had troops or military observers in the PKO that year and the contributor’s affiliation (NATO or Warsaw Pact only). Totals for each category were also constructed based on contributor totals for a given year. 148 Doctrine variables include both troops and observer numbers. 149 Recall that the highest ordinal score for UN involvement (4) results from the presence of a UN-led mission in a given country-year. As a result, the UN-led dummy variable and the UN Involvement 4 dummy variable are perfectly correlated. 174

either NATO variable demonstrated that their inclusion yielded a test result above

5.0.150

Coupled with the correlation test results, the removal of the NATO-specific independent variable from the model was deemed necessary to avoid collinearity issues.151 The high correlation between the total number of troops and the total number of NATO personnel suggests that within the analysis dataset, the effect that could be attributed to NATO presence in a PKO will be captured by the troop total variable. To maintain consistency, variables representing the total number of

Warsaw Pact and Chinese peacekeepers deployed to each mission per country-year were used to account for doctrinal influence.152 This course of action also allows for those hypotheses concerning both mission composition and doctrinal differences within mission design to be tested by exchanging the total troop variable with the total NATO personnel variable.

As discussed in Chapter 4, dummy variables identifying the conflict period will also be included in the model (Pre-conflict, Conflict year, Post-Intervention).

The only issue identified was the high correlation (0.78) between the dummy

150 A VIF score above 5.0 suggests collinearity among the independent variables. Combining VIF test results with correlation testing results allows for independent variables, whose inclusion might lead to poor regression results due to collinearity, to be removed or re-specified. 151 I will later exchange the Total Troops variable with the Total NATO variable in order to test my hypotheses that are doctrine-specific. 152 The correlation between the total number of Chinese personnel and the total number of observers was moderately high compared to all other variables (0.6) but a VIF analysis resulted in scores for neither variable going above 2.1. 175

variable identifying intervention years (Intervention year) and the mission type variable (UN-led or UN Involvement 4). This makes sense because these variables represent the majority of PKO observations in the dataset. A subsequent VIF analysis on a test model OLS regression also yielded a score of 8.71 on the intervention year variable. To avoid collinearity issues the intervention year variable is not included in the analysis; inferences on the effect of that variable on

FDI inflows are drawn from the mission type variables.

5.2.2. Testing the Completed Model

With no correlation concerns identified with any of the remaining control variables described in Chapter 4153 a second round of regressions were run. Model

6a (Table 5-9) represents the full analytical model. FDI inflows in millions of constant 2011 USD serves as the dependent variable, PKO-type dummy variables and all aid commitments in millions of constant 2011 USD serve as the key independent variables. The remaining independent variables include: variables providing mission composition totals154, totals for Chinese peacekeepers and

Warsaw pact peacekeepers, and conflict periods. All controls (e.g. Population, GDP per capita, World Bank regions) were also included. 155,156 As discussed above,

153 The control variables are: population, GDP per capita, World Bank region. 154 Total Troops, Total Police, Total FPU, and Total Observers. 155 Dummies for extreme FDI inflows were included in all models but are not reported. 156 Other World Bank Region variables include Sub-Saharan Africa, Europe and Central Asia, Latin America and Caribbean, and Middle East and North Africa. East Asia Pacific represented my reference category and was systematically dropped from all models in the analysis except Model 9b. 176

robust standard errors were employed in an effort to address the heteroskedasticity issue.

Similar to the loss of observations observed when aid commitment variables were added to the model, the inclusion of the remaining variables and controls generated a loss of 17 additional observations leaving a total of 493 observations in the sample. Table 5-8 provides a breakdown of select dummy variables in the subset used for analysis. Compared to the full dataset, the smaller sample includes a higher representation of PKO presence as well as each of the mission type and conflict period variables; the exception is a lower representation of pre-conflict years. One result of this disparity is that we may see a larger effect from these variables.

177

Table 5-8: Dummy variable representations within analysis sample

Independent 1/Yes 0/No % of dummy % of dummy Variable = 1 in sample =1 in full dataset

PKO present 235 258 47 29 (Intervention Year) UN-led dummy 152 341 31 20 UN-authorized 62 431 13 3 dummy UN-recognized 75 418 15 6 dummy Non-UN dummy 41 452 8 6 Pre-conflict Year** 68 425 14 38 Conflict Year** 312 181 63 50 Post-intervention 47 446 10 6 Year

**conflict year defined by one in which a dispute, that at some point before resolution, results in 25 battle-related deaths.

The results for aid variables provided in Table 5-9 partially support

Hypothesis 1 and Hypothesis 2. With the exception of Peace Aid, the effects of increased commitments of development-focused aid has, as proposed in Hypothesis

1, stayed positive however the resulting coefficients (including Development Aid which was positive and highly significant in initial tests) are insignificant. As proposed in Hypothesis 2, the relationship between FDI inflows and security- focused aid is negative.

178

Table 5-9: OLS regresstion results Full analytical model (6a) and UCDP/PRIO conflict variant (6b) Model 6a Model 6b VARIABLES FDI Inflows FDI Inflows

UN-led dummy -265.8 -233.2 (154.0) (174.1) UN-authorized dummy -404.0** -415.9** (130.9) (143.2) UN-recognized dummy -255.2* -296.0* (124.5) (135.1) Non-UN dummy 114.1 43.72 (156.9) (177.9) Development Aid 0.107 0.102 (0.0712) (0.0715) Security Aid -3.340** -3.720** (1.122) (1.192) Governance Aid 0.523 0.481 (0.466) (0.465) Peace Aid -0.225 0.269 (2.482) (2.598) Reconstruction Aid 0.247 0.212 (0.265) (0.269) Total Troops 0.00867 0.0101 (0.00498) (0.00521) Total Police -0.215** -0.247*** (0.0747) (0.0744) Total FPU 0.190 0.186 (0.116) (0.113) Total Observers 0.0173 0.0249 (0.297) (0.299) Total Warsaw Pact 0.328** 0.391** (0.124) (0.120) Total Chinese 1.875*** 1.933*** (0.471) (0.483) Population 6.78e-06*** 6.67e-06*** (1.60e-06) (1.60e-06) GDP per Capita 0.347*** 0.332*** (0.0464) (0.0429) Pre-conflict dummy -423.1 (271.1) Conflict year dummy 191.8 (141.4)

179

Table 5-9 (continued): OLS regression results Full analytical model (6a) and UCDP/PRIO conflict variant (6b)

Model 6a Model 6b Continued FDI Inflows FDI Inflows

UCDP/PRIO pre-conflict dummy -196.4 (249.4) UCDP/PRIO conflict year dummy 324.5* (160.5) Post Intervention dummy -654.6** -615.5** (200.9) (227.7) South Asia dummy -472.0* -584.9* (216.0) (237.6) Sub-Saharan Africa dummy 159.1 75.60 (173.2) (170.9) Europe/Central Asia dummy -420.9* -444.5** (163.2) (158.8) Latin Am./Caribbean dummy 243.9 207.9 (273.3) (267.1) Middle East/N. Africa dummy -342.5 -243.1 (278.5) (285.3) Constant 30.93 107.1 (146.7) (149.6)

Observations 493 493 Adjusted R-squared 0.855 0.855 Robust standard errors in parentheses *** p<0.001, ** p<0.01, * p<0.05

When considering the full model there is less support for Hypothesis 3 that, on average, higher UN involvement will have increasing positive effects on FDI inflows. In fact, UN leadership (despite insignificance of the coefficient) or higher involvement in peacekeeping (evident in the statistically significant results for UN authorized and UN recognized missions) appears to negatively affect FDI inflows within the sample. Instead, mission design becomes more important.

Because any increase in PKO strength was theorized to increase information gathering and therefore have a positive effect on stability, Hypothesis 7 suggested that an overall force increase would have a positive effect on FDI inflows. However, 180

preliminary testing with this single variable yielded an insignificant result. The variables for totals by peacekeeper type were included in all subsequent models to determine if the individual effects theorized (that increases in any peacekeeper category would yield a positive effect on FDI inflows) had any support.

The results for increased troops, FPUs, and observers are all insignificant.

However, a plot of the coefficients associated with these variables (see Figure 5-8) shows that increasing troops or FPUs is more likely to generate a positive effect on

FDI inflows than a negative effect, 157 offering some support to my theory albeit - minimal at best. However, increasing observers is just as likely to have a positive effect as it is to have a negative effect.

157 Based on the 95% confidence intervals for each coefficient. 181

Figure 5-8: Coefficient plot for Troop, FPU, and Observers totals - Model 6a

Coefﬁcient Plot Troop, FPU, and Observer Totals - Model 6

TotalTroop

TotalFPU

TotalObs

-.5 0 .5 Coefﬁcient estimates with 95% Conﬁdence Intervals

Counter to my theory, the effect of increased police is negative and significant and could explain why the force total variable offered nothing in preliminary testing.

While my theory posits a positive relationship between increased PKO police and

FDI inflows, due to the information gathering capacity police bring to the missions, an increased police presence demonstrates practically that local law enforcement is insufficient. Recalling the role that rule of law plays in the enabling environment and stability overall, the signaling effect that an increased police presence has for investors could outweigh the effect generated by the oversight that more police bring. 182

The modeled effects of conflict periods on FDI inflows in this sample were less supportive of the theory. Recalling the premise that the mission-type variables would account for the intervention year effect, the negative and significant coefficients for UN-authorized and UN-recognized PKOs (with UN-led and Non-UN mission variables returning insignificant results) suggests investors leave the market during intervention years. This is not totally unexpected based on the baseline regression analysis (Model 5) (see Table 5-7) but is counter to the initial argument that peacekeeper presence alone increases stability. Also, the large negative and significant effect of the post-intervention period is in line with portions of the theory, specifically that FDI inflows will be reduced when PKOs depart, but inflows should not be lower than what we would see during conflict periods.

5.2.3. Addressing unexpected results for conflict periods

I offered no hypotheses to address conflict periods, but I argued in Chapter 3 that stability will change across these conflict periods and implied that change could be measured. Although the results are insignificant, a plot of the coefficients for pre- conflict and conflict years shows the likelihood of conflict years having a positive effect on FDI inflows is high, while it is more likely that pre-conflict years have a negative effect158 (see Figure 5-9).

158 Based on the 95% confidence intervals for each coefficient. 183

Figure 5-9: Coefficient plot for Pre-conflict and Conflict year dummy variables - Model 6a

Coefficient Plot Pre-conflict and Conflict Years - Model 6

Pre-Conﬂict

Conﬂict

-1000 -500 0 500 Coefﬁcient Estimates with 95% Conﬁdence Intervals

Arguably, a higher likelihood of a positive effect on FDI inflows during conflict years seen in Figure 5-8 is counterintuitive and could possibly result from how I elected to distinguish between pre-conflict and conflict years. Although the conflict period variables were derived from the UCDP/PRIO Armed Conflict Dataset, version 18.1 (Gleditsch et al., 2002; Pettersson & Eck, 2018), the variables created for this analysis do not distinguish between a pre-conflict period and a conflict period based on reaching a 25 battle-related deaths reported threshold. Instead I elected to define the beginning of a conflict period based on the start date of a dispute (provided in the UCDP/PRIO dataset) that, at some point in its duration, resulted in 25 battle-related deaths reported. This choice converts what can be 184

characterized as flare-ups in a dispute that result in an arbitrary number of reported battle deaths to a single conflict.

I made this decision to ensure that all conflicts (as defined in the UCDP/PRIO dataset according to battle deaths) were included in my analysis dataset, but also to account for the fact that the UCDP/PRIO-defined conflicts likely spanned more years, when fewer battle deaths were reported or simply when battle-related injuries did not result in a reported death. Arguably, a threshold of this sort can be useful for analysis, but I elect not to use it to segregate conflicts by intensity because it negates the reality that battle-related deaths can go unreported, underreported, or that access to immediate medical care (or even first aid) deflates the perceived intensity of a conflict.

This method of distinction reduces the number of pre-conflict period years across the sample (from 115 to 68) and increases the number of conflict period years (from 186 to 312). More importantly, some conflict-affected states (e.g. India,

Pakistan, Israel, Lebanon) who host PKOs for the entirety of the analysis timespan are also in a conflict period during all observed country-years.

To determine if this method of coding conflict periods created an unanticipated impact on the results a second run, Model 6b (see Table 5-9), was performed using the UCDP/PRIO 25 battle-related death threshold as the demarcation limit. Not only did the initial results hold, but the effect of the conflict period (defined by 25 battle-related deaths) was still positive and also significant. 185

5.2.4. Testing PKO Doctrine

In Chapter 3 I argued that the institutional training peacekeepers receive due to the military doctrinal background of their home country will impact their propensity for collecting and sharing information about the operational environment; this includes development issues, security issues, and host-nation governance. Locally gathered and processed information is passed to higher levels of a PKO’s sending organization or mandate authority (i.e. the UN, African Union,

NATO, etc.) as part of regular military reporting procedures. This information, in some form, should be available to those member states participating in the operation or who have some stake in the mission’s success.159 Simply put, this dissemination of locally gathered and analyzed data about on-the-ground conditions to a larger international audience, who are stakeholders in the host-nation’s stability, increases scrutiny or oversight.

I further argued that because military allies share some similarities in their conduct of military operations (to promote interoperability), the explicit focus on host-nation accountability discussed in US military/peacekeeping doctrine would likely be a shared expectation from US military allies (i.e. NATO countries).160

Therefore, the presence of more NATO peacekeepers should positively affect FDI

159 According to interviews and observations made by the author at UN Department of Peacekeeping Operations, May 2018. 160 While host nation accountability is discussed in NATO peace support operations doctrine the focus is not as significant as that observed in US military doctrine (NATO, 2001). 186

inflows (Hypothesis 4). Recognizing that Russian peacekeeping doctrine is highly focused on enforcing peace rather than enforcing the adherence to international norms, I posited not only that NATO troops would increase stability but that Russian

(i.e. Warsaw Pact) doctrine affiliated peacekeepers would have a negative effect

(Hypothesis 5). And, that while there is no specific literature on Chinese peacekeeping doctrine or insight into Chinese military expectations with regard to host nation accountability, the increase in Chinese peacekeeping participation over the past two decades suggests their interest in promoting long-term stability. This would, in turn, promote a positive effect on stability in those states they deploy peacekeepers to but not as high as their NATO counterparts (Hypothesis 6). This supposition is based on the perception of Chinese non-interference in local governance.

Model 7a tests Hypotheses 4, 5, and 6 that focused on the notion the doctrinal background of peacekeepers matters (see Table 5-10). As discussed previously, the high correlation (0.89) between the variables for the total number of troops deployed and the total number of NATO personnel deployed generated collinearity concerns, so I was unable to include both variables in the same model.

For these doctrine-specific tests I elected to replace the total troop variable with the total NATO personnel variable. As expected, increased NATO presence has a positive, although insignificant effect, on FDI inflows (Hypothesis 4). However, the more positive and significant effect of the Warsaw Pact peacekeepers counters

Hypothesis 5 which predicted a negative relationship. And, while Hypothesis 6 187

predicted that Chinese peacekeepers would have a greater positive effect on FDI compared to Warsaw Pact peacekeepers, it was not expected for that effect to supersede the NATO peacekeeper effect. These results suggest that while the doctrinal background of participants is important, it may have less to do with increasing scrutiny as theorized. However, before fully accepting that result a second series of tests was run to see if making any changes to the variables would alter the results in a significant way.

188

Table 5-10: OLS regression results for doctrine effect testing, FDI inflows and FDI inflows per capita (FDI per Capita) Model 7a Model 7b Model 7c Model 7e VARIABLES FDI Inflows FDI Inflows FDI Inflows FDI per Capita

UN-led dummy -256.9 -256.9 -222.1 72.87* (152.7) (244.1) (213.5) (33.96) UN-authorized dummy -387.0** -387.0* -487.4* -17.16 (130.4) (155.2) (191.8) (18.75) UN-recognized dummy -248.2* -248.2 -273.0 -8.716 (124.9) (166.7) (159.0) (13.38) Non-UN dummy 111.0 111.0 131.3 -25.71 (156.9) (184.8) (232.9) (20.71) Development Aid 0.106 0.106 0.0987 (0.0711) (0.0919) (0.0910) Security Aid -3.287** -3.287* -3.350* (1.122) (1.588) (1.641) Governance Aid 0.524 0.524 0.574 (0.466) (0.425) (0.420) Peace Aid -0.181 -0.181 -0.883 (2.479) (2.601) (2.692) Reconstruction Aid 0.243 0.243 0.104 (0.265) (0.356) (0.373) Total Police -0.204** -0.204* -0.146 -0.0794** (0.0749) (0.0967) (0.0974) (0.0258) Total FPU 0.203 0.203 0.250 0.0472 (0.116) (0.212) (0.174) (0.0355) Total Observers 0.0891 0.0891 0.0898 -0.159*** (0.308) (0.258) (0.237) (0.0410) Total NATO 0.00888 0.00888 0.00663 0.000924 (0.00540) (0.00825) (0.00745) (0.000733) Total Warsaw Pact 0.330** 0.330* 0.154 0.0245 (0.125) (0.164) (0.130) (0.0145) Total Chinese 1.984*** 1.984*** 1.832*** 0.513*** (0.467) (0.519) (0.470) (0.109) Population 6.77e-06*** 6.77e-06*** 6.37e-06*** -3.78e-08 (1.60e-06) (1.73e-06) (1.69e-06) (3.75e-08) GDP per Capita 0.347*** 0.347*** 0.328*** 0.0475*** (0.0463) (0.0777) (0.0780) (0.00557) Pre-conflict dummy -419.6 -419.6 -255.8 55.90 (270.7) (466.1) (322.6) (32.06) Conflict year dummy 194.8 194.8 275.1 33.09 (141.2) (137.0) (139.9) (24.13) Post Intervention dummy -653.8** -653.8* -621.5* -18.50 (200.8) (309.7) (278.0) (17.34)

189

Table 5-10 (continued): OLS regression results for doctrine effect testing, FDI inflows and FDI inflows per capita (FDI per Capita) Model 7a Model 7b Model 7c Model 7e FDI Inflows FDI Inflows FDI Inflows FDI per Capita

South Asia dummy -465.7* -465.7 -56.17 (214.5) (270.0) (29.48) Sub-Saharan Africa dummy 163.1 163.1 231.6 -3.173 (173.5) (207.8) (246.6) (24.03) Europe/Central Asia dummy -416.6* -416.6* 29.62 (163.0) (206.1) (35.96) Latin Am./Caribbean dummy 248.8 248.8 -26.75 (274.1) (612.1) (33.54) Middle East/N. Africa dummy -335.5 -335.5 -178.1 -7.435 (278.3) (398.5) (529.7) (65.90) SecurityAid/capita -0.500 (0.974) DevelopmentAid/capita 0.254* (0.113) PeaceAid/capita 0.698 (1.167) GovernanceAid/capita -0.135 (0.277) ReconstructionAid/capita 0.703 (0.503) Constant 25.00 25.00 -92.39 -57.53 (146.3) (150.3) (188.1) (34.52)

Observations 493 493 493 493 Adjusted R-squared 0.855 0.855 0.852 0.657

Robust standard errors in parentheses *** p<0.001, ** p<0.01, * p<0.05

Four variants of Model 7a (see Table 5-10) were tested in an effort to find support for the initial results. First (Model 7b) I attempted to further control for the presumed country-effect discussed by clustering standard errors on the conflict- affected state. Next (Model 7c), I only controlled for those World Bank regions within the sample where China had the most participation (Middle East/North

Africa and Sub-Saharan Africa while still clustering errors on the host-nation. Third

(Model 7d) I ran only the dummy variables for doctrinal background while 190

clustering on the host-nation.161 The doctrinal effects originally observed in Model

7 still hold across all variants. The results from Models 7a-7d also suggest that, as anticipated, controlling for population size matters across all of these models.

As discussed in Chapter 4, population considerations have a logical place in the decision-making process of investors. I tested a final variant (Model 7e) that employed FDI per capita as the dependent variable as well as per capita values for all aid commitments.162 While a straight measure of FDI inflow totals provides an easily comprehensible measure, it is not the best choice when comparing FDI across states with different populations. Investors may look to states with larger populations when deciding to invest in controlling shares of a local firm or when starting a new enterprise from the ground up.163 Therefore, heavily populated states may draw more or larger investments (considering the total amount invested) but compared to a state with a smaller population, that total investment amount may be at the same level with respect to the size of the economy.

161 While this generates an elevated VIF score (5.2) due to the correlation between the NATO dummy variable and the UN-led dummy variable (0.748) I only use this combination of variables as part of this effort to confirm the original results. I do not include model 7d in the table of results because no doctrine results were significant. 162 Per capita values are calculated by dividing the annual inflows of FDI or aid commitments (by aid purpose) in constant 2011 USD by the yearly population totals for each country-year observation. No dummy variables were needed to account extreme FDI per Capita values in Model 7e. 163 As discussed in Chapter 4, population is a characteristic that investors likely take into account. This is due to the increase in the local consumer base as well as access to skilled and unskilled labor that larger populations imply. 191

As seen in the results for Model 7e, the resulting coefficients for PKO doctrine are consistent with all other doctrine tests. However, once the population effect is absorbed by these newly defined variables (apparent by the loss of significance and sign change in the population variable) a change in sign and significance to the UN- led coefficient suggests a positive trend is associated with higher UN involvement and PKO presence in general.

Recalling, the high correlation between the UN-led variable to the intervention year dummy variable, results from Model 7e suggest that intervention years have a more positive effect than pre-conflict years, and that inflows fall during conflict. These findings are in line with the expectations presented in Chapter 3.

Post-intervention years continue to follow the negative trend suggesting investors might withdraw assets following intervention, but there is no specific case evidence supporting the argument that a withdrawal of a PKO alone would cause investors to pull their assets out of a post-intervention economy. While the coefficient is not significant, the negative trend of FDI inflows per capita does, however, provide some support the argument presented in Chapter 3 that stability decreases following the end of an intervention.

192

5.3. Testing the interaction between UN led PKOs and development aid

In Chapter 3 I argued that increased levels of development focused aid during the presence of peacekeepers who generate higher levels of oversight (i.e. have a higher level of UN involvement) should promote stability. This was presented under Hypothesis 8 that states simply how the interaction effect generated between development aid and high UN involvement will have a positive effect on FDI inflows.

Analysis has demonstrated that, independently, both foreign aid and peacekeeping interventions have a significant effect on FDI. Although, within the smaller sample defined by independent variables selected for the analysis, those relationships do not fully support the theory. When considering direct inflows of

FDI we do not see the expected positive relationship between higher levels of UN involvement, and while we observe a positive trend with increases across most development categories there are no consistently significant results. It is only when we look at the comparative measure of FDI per capita as the dependent variable and consider per capita Development Aid (i.e. only what I classified as traditional aid) commitments rather than direct commitment amounts, that we see results that fit what was anticipated according to the theory. The results from this version of the full model (Model 7e) also appear to hold for several other independent variables 193

across all model variants (i.e. GDP per capita, Total Chinese peacekeepers, Total

Police deployed). 194

Table 5-11: OLS regression results - Interaction model, UN-led dummy and development aid per capita

Model 8 VARIABLES FDI per Capita

UN-led dummy 63.30* (25.12) DevelopmentAid/capita 0.229 (0.147) UNled*Dev/Cap 0.0953 (0.309) UN-authorized dummy -18.71 (18.80) UN-recognized dummy -7.254 (12.89) Non-UN dummy -24.66 (20.47) SecurityAid/capita -0.526 (0.944) PeaceAid/capita 0.563 (1.189) GovernanceAid/capita -0.108 (0.291) ReconstructionAid/capita 0.651 (0.430) Total Troops 0.000896 (0.000666) Total Police -0.0798** (0.0251) Total FPU 0.0450 (0.0369) Total Observers -0.163*** (0.0380) Total Warsaw Pact 0.0216 (0.0188) Total Chinese 0.495*** (0.0968) Population -3.21e-08 (3.27e-08) GDP per Capita 0.0475*** (0.00548)

195

Table 5-11 (continued): OLS regression results - Interaction model, UN-led dummy and development aid per capita Model 8 continued FDI per Capita

Pre-conflict dummy 57.77 (30.86) Conflict year dummy 34.30 (23.81) Post-Intervention dummy -17.24 (17.26) South Asia dummy -54.50 (27.99) Sub-Saharan Africa dummy -2.792 (24.03) Europe/Central Asia dummy 30.72 (36.16) Latin Am./Caribbean dummy -25.97 (33.74) Middle East/N. Africa dummy -6.453 (67.05) Constant -57.57 (34.22)

Observations 493 Adjusted R-squared 0.657 Robust standard errors in parentheses *** p<0.001, ** p<0.01, * p<0.05

To test Hypothesis 8, I continue to use the per capita measures introduced in

Model 7e but focus on the interaction between the UN-led variable and

Development Aid per capita (see Table 5-11). Recalling how these were both positive and significant, Model 8 reveals that the relationship still trends positive as expected, but the effect it is not significant in this sample. However, consistent 196

results across other independent variables including total Chinese peacekeepers and GDP per capita, combined with the consistent (albeit insignificant) effects resulting from conflict period suggest that the positive relationship seen in the interaction variable has some support.

Thus far the models have not accounted for the time needed for aid commitments to be disbursed and projects completed or for the oversight effect brought on by UN involvement to change the economic enabling environment.

Recalling that aid projects can take multiple years to execute once funds are committed, it would not be surprising if the effect those projects aim to generate takes longer to become evident. And, while the pace at which a stream of information from peacekeepers might result in a policy change was not identified during this project, we can assume that the time period we would be interested in regarding peacekeeping would be closer to the current year than that of aid commitments. This simply means introducing lagged variables into the model that account for the time differences needed for the independent interventions to take effect, and then interacting those respective variables accordingly.

I used the general model form presented in Chapter 4, but I continued to use the per capita measure for FDI inflows, aid commitments, and GDP that were used in

Model 8. I still controlled for a country-level effect by clustering errors by each state in the sample. I ran four versions of this model (see Table 5-12).

197

Model 9a Model 9b Model 9c Model 9g VARIABLES FDI per Capita FDI per Capita FDI per Capita FDI per Capita

1Lag FDI per Capita 0.808*** (0.0582) 1LagUNled*3LagDev/Cap 0.584* 0.0493 (0.283) (0.182) 1Lag UN-led dummy 84.59* 99.32** 43.67 15.12 (34.05) (35.39) (33.30) (16.19) 1Lag DevelopmentAid/capita 0.269 (0.135) 1Lag UN-authorized dummy -28.09 -27.91 -27.02 -11.62 (20.70) (20.79) (19.79) (7.755) 1Lag UN-recognized dummy -15.73 -22.31 -17.51 -19.67 (15.51) (17.76) (14.84) (11.34) 1Lag Non-UN dummy -27.36 -11.47 -6.694 -0.397 (20.72) (19.20) (22.22) (10.84) 1Lag SecurityAid/capita -0.759 (1.080) 1Lag PeaceAid/capita 0.253 (0.432) 1Lag GovernanceAid/capita -0.210 (0.248) 1Lag ReconstructionAid/capita 0.975 (1.012) 3Lag DevelopmentAid/capita 0.179 0.0484 -0.0111 (0.143) (0.120) (0.0739) 3Lag SecurityAid/capita -1.538* -1.530* -0.835*** (0.741) (0.624) (0.197) 3Lag PeaceAid/capita -0.250 -0.683 -0.440* (0.416) (0.450) (0.215) 3Lag GovernanceAid/capita 0.249 0.379 0.314 (0.434) (0.453) (0.223) 3Lag ReconstructionAid/capita 1.045 0.811 0.118 (0.788) (0.738) (0.244)

198

Table 5-12 (continued): OLS regression results – Lagged variables and interaction with lagged variables: UN-led dummy (1 year lag), development aid per capita (1 year lag) and (3 year lag), FDI per Capita (1year lag) Model 9a Model 9b Model 9c Model 9g Continued FDI per Capita FDI per Capita FDI per Capita FDI per Capita

1Lag Total Troops 0.00104 0.000937 0.000810 0.000126 (0.000719) (0.000654) (0.000576) (0.000123) 1Lag Total Police -0.0778** -0.0846*** -0.0820*** -0.0181*** (0.0241) (0.0188) (0.0205) (0.00515) 1Lag Total FPU 0.0459 0.0387 0.0293 0.00344 (0.0426) (0.0301) (0.0218) (0.00947) 1Lag Total Observers -0.181*** -0.211*** -0.146** -0.0296 (0.0490) (0.0531) (0.0504) (0.0184) 1Lag Total Warsaw Pact 0.0199 0.0376* 0.0257 0.0194 (0.0189) (0.0182) (0.0235) (0.0119) 1Lag Total Chinese 0.487*** 0.568*** 0.504*** 0.115** (0.102) (0.119) (0.129) (0.0350) 1Lag Population -4.53e-08 -5.32e-08 -2.64e-08 -1.07e-08 (4.07e-08) (3.86e-08) (3.39e-08) (1.29e-08) 1Lag GDP per Capita 0.0440*** 0.0406*** 0.0406*** 0.00498 (0.00536) (0.00444) (0.00445) (0.00309) 1Lag Pre-conflict dummy 31.04 13.90 17.44 -21.77 (31.26) (27.32) (27.83) (16.80) 1Lag Conflict year dummy 12.66 0.963 2.854 -21.58 (22.64) (20.91) (19.68) (12.69) 1Lag Post-Intervention dummy -18.19 -13.31 -10.82 -9.765 (23.51) (27.32) (26.64) (14.97) South Asia dummy -63.90* -62.74 -51.40 -13.46 (30.09) (80.65) (27.94) (9.173) Sub-Saharan Africa dummy -16.14 -7.346 -5.857 -1.396 (20.08) (75.82) (23.82) (9.699) Europe/Central Asia dummy 35.87 25.96 30.10 -1.661 (33.29) (78.78) (30.11) (14.58) Latin Am./Caribbean dummy -36.56 -23.23 -19.91 3.709 (27.88) (80.46) (34.00) (12.20) Middle East/N. Africa dummy 1.635 1.298 -0.211 (63.56) (70.01) (17.38) East Asia Pacific dummy 6.950 (74.38) Constant -25.12 -14.80 -7.750 28.31 (30.55) (70.25) (27.90) (18.21)

Observations 458 389 389 387 Adjusted R-squared 0.619 0.613 0.623 0.823 Robust standard errors in parentheses *** p<0.001, ** p<0.01, * p<0.05

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Model 9a reflects a one-year lag for all time-dependent independent variables and serves as a baseline for the remaining model variants. Model 9b introduces a three-year lag on the aid variables, one year on all remaining variables but no interaction. Model 9c introduces the interaction variable where I account for the level of UN involvement (specifically UN-led missions) in peacekeeping during the previous year, but the aid commitments from three years earlier. In operational terms the model attempts to reflect the reality that aid commitments made three years ago are likely still at work last year while peacekeeping provided oversight; the effect on stability is evident in FDI inflows per capita for the current year.

The results from Model 9c reflect a positive and significant relationship between the interaction variable and FDI inflows per capita. Coupled with the insignificant results for Development Aid from prior tests, the interaction results suggest that traditional development aid may or may not have a positive effect on its own, but on average, when development aid is at work under increased international scrutiny, the result is an increase in FDI inflows per capita. More importantly, these results support the notion that changes to the enabling environment require time as does the collection and reporting of information from the field.

When 2-year or 4-year lags are applied to aid variables (see Models 9d and

9e in Appendix E) the effect of the interaction variable is positive but only 200

significant in the 4-year lag model. This offers more support to the argument that the aid effect is delayed, and this outcome could be the result of aid organization budgeting cycles, where aid is committed and reported in one year, while funds may not be dispersed until a subsequent year.

Because Hypothesis 8 targets increasing levels of UN involvement and not solely UN led missions, a variant of Model 9c was run were all mission type dummy variables (lagged 1 year) were interacted with the Development Aid per capita variable (lagged 3 years). The positive and significant effect of the UN-led interaction with Development Aid held. However, the remaining interactions did not support the theory regarding increases in UN participation. In fact, the UN authorized interaction was negative and significant, and the coefficients of these interaction variables did not reflect an increasingly positive effect as theorized (see

Model 9f, in Appendix F).

A final test, Model 9g (Table 5-12) considers the possibility that FDI inflows are driven by the previous year’s FDI inflows. This equates to the idea that investors may base the decision to invest on how attractive the conflict-affected economy was in the previous year.

When looking at the results from Model 9g this argument has some support.

The one-year lagged FDI per capita variable is positive and highly significant while the interaction loses its significance and magnitude. However, by acknowledging that the lagged dependent variable represents the accumulated effects of all 201

previous years on FDI inflows per capita in the current year, we should expect that its inclusion accounts for any interaction effect from previous years.

It should be noted that the presence of Chinese peacekeepers (lagged one year) remains positive and significant, while increased police deployments remain negative and significant, even when the lagged dependent variable is included.

Similarly, the effect of increased security aid (lagged three years) remains negative and significant. These results provide continued support to earlier models and the theory that targeted aid allocations and PKO design have an important role in increasing or decreasing stability.

5.4. Summary

This chapter has provided an overview of the analysis conducted to test the effects of foreign aid and peacekeeping interventions on stability in conflict-affected states. The results are mixed.

Based on the results provided above we can see that effects generated by foreign aid and peacekeeping interventions are evident in FDI inflows. However, once the models are expanded to account for those elements of peacekeeping theorized as relevant to increased stability and also for basic controls, these initial effects lose their clarity or simply return unanticipated results. It is only by accounting for population totals in both the dependent and independent variables, thereby turning these measures into comparable per capita values rather than 202

direct monetary measures, that the results appear in-line with the theory and what was observed in initial data analysis.

While there is support for the theory that peacekeeping mission characteristics such as the doctrinal background of peacekeepers matter, the results are unexpected and inconsistent with the theory. In particular, increased numbers of Chinese peacekeepers have a consistently positive and significant effect on FDI inflows, greater than NATO peacekeepers, across all models. If doctrine is relevant as theorized, that is certain doctrines promote the expectation of higher accountability from the host nation and therefore generate more oversight, we should not see this result, or we should potentially see the NATO effect in some other variable. At best, we can look to the high correlation between UN-led missions

(on FDI inflows per capita) and the presence of NATO personnel within those missions and infer from the positive and significant effect that NATO doctrine does generate higher oversight.

The most important test conducted during the analysis, namely testing the interactive effect of peacekeeping and aid, generated results that fall directly in line with the theory. However, the significance of this result only holds under specific time constraints imposed on the model. While these time constraints are rooted soundly in the logic that time is needed for committed funds to be disbursed due to budget cycles and for information to be collected and reported, there is insufficient data to confirm if these assumptions are valid. 203

Additionally, when all mission types are included in interactions, we see a negative and significant effect for the UN-authorized mission interaction. It is possible that this results from which organization in particular serves as mandate authority (i.e. European Union vs. African Union), meaning those organizations predominantly represented in the sample collected and/or shared less information, and FDI inflows suffered as a result.

Insufficient data is also a notable challenge to the results obtained in the analysis. Despite starting with over 2000 country-year observations, limitations to data deemed necessary to best model the conditions relevant to the study resulted in a significantly reduced sample size, only 493 observations. Arguably this means that certain types of cases which could influence the results are under-reported due to missing values – specifically missing aid data. However, knowing that all commitments are not reported or reported at the level needed for this study; those missing values could not be assumed to represent zero commitments. And, while select aid commitments were omitted from the study (specifically those short-term aid contributions such as humanitarian aid or disaster relief deemed irrelevant to long-term stability) omitting known long-term aid commitments such as those targeting peace or reconstruction efforts would have injected additional bias into the analysis even if their removal increased the number of observations.

Finally, model misspecification is clearly an issue that was recognized early on in the analysis. While attempts were made to adjust the models and to account for these concerns by employing robust standard errors and then clustering errors 204

on the conflict-affected country, the models are still not accounting for some unidentified factor. This arguably reduces the validity of any results to some degree.

The final assessment is that the analysis has generated a series of findings that do provide support to the theory presented in Chapter 3, but they do so under limited circumstances. If data collection for UN peacekeeping or peacekeeping in general continues at its current pace and level of detail, and openness with foreign aid commitments continues to improve among all donors, the foundation created in this analysis affords ample opportunity for continued work along this line of inquiry.

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Chapter 6

Placing the research in context

6.1. A review of the study

The research detailed in this thesis was initially motivated by a simple question: can stability be imposed on a sovereign, conflict-affected state? In essence this is what post-conflict interventions aim to do. The international community identifies perceived shortfalls in some aspect or aspects of the conflict-affected state, believed to be the cause of instability, and attempt to affect a desired change within the state by introducing an external treatment.

I argue through my theory presented in Chapter 3 that by targeting the two components of stability, initially characterized by Ake (1975) as the political network of interactions or behaviors that define the state and the oversight mechanism developed by the state to prevent those behaviors from exceeding 206

socially accepted boundaries, stability can be increased. Furthermore, I argued that we can observe this process of increasing stability by considering the two most prominent forms of international intervention in conflict-affected states, targeted foreign aid and the deployment of peacekeeping operations (PKO).

Targeted foreign aid attempts to change those aspects of the conflict-affected state that the donor believes are below an externally developed standard and have therefore resulted in decreased stability.164 Peacekeepers, beyond the limited physical security they bring with their deployment, serve as providers of external oversight who provide real-time information on the internal conditions of the host nation. In both cases, the character of the intervention, namely how aid is targeted and what sort of peacekeeping mission is deployed, affects the level of stability achieved.

I posited that, in line with extant literature on foreign aid, increasing foreign aid towards development-related issues rather than security issues or those issues typically associated with post-conflict environments would generate greater stability. Additionally, I offered that because the United Nations (UN) is the largest international organization, with the greatest ability to sanction states who do not conform to international norms, peacekeeping operations with higher levels of UN

164 Recall from Chapter 3 that the international community is not expected to intervene in an internal conflict that reduces stability unless the dispute has led to a wider reduction of stability outside of the conflict-affected state. 207

involvement would generate higher levels of stability. Furthermore, I suggested that additional PKO characteristics, such as the mission composition (i.e. the total number of troops, police, or observers) and the doctrinal background of the peacekeepers (i.e. those with NATO influence, Russian or Warsaw Pact influence, or if Chinese peacekeepers participated) affected the level of oversight created and subsequently the level of stability achieved. However, the most crucial aspect of my theory is that these independent, but simultaneously occurring interventions generate a measurable interactive effect. Thus, increased development aid

(targeting what I identified as traditional aid issues) applied during the deployment of a PKO with higher UN involvement generates higher stability.

I tested my theory by considering the impact that these two independent interventions have on the target state’s economic enabling environment. As described by Mills and Fan (2006), the enabling environment is comprised of the same interactions or behaviors we use to define the state’s political network. The enabling environment generates an investment climate that drives foreign firms or individuals to invest (or divest) in a conflict-affected economy. This decision, motivated by a desire for profit while safeguarding private financial resources, is based on the foreign investor’s independent assessment of the target state’s economic outlook.

However, investing in the future implies that the investor has some confidence in the safety of their assets when they elect to take this risk. If investors are looking for long-term participation in a foreign economy, through some degree 208

of ownership in a locally-based enterprise, they are likely to base the decision to invest on current conditions rather than expected conditions alone. With this expectation I elected to utilize foreign direct investment (FDI) inflows as the dependent variable and proxy for stability in my analysis.

As detailed in Chapter 5, the results of my analysis were mixed. While I verified that, on average, each intervention has a significant effect on FDI inflows, and that there is a positive and significant interactive effect, those effects occur in what I characterize as a limited set of conditions. Two factors that I did not anticipate having a significant impact on FDI inflows were the population of the target state and the time needed for effects to be observed.

Population plays a significant role in how we measure both the intervention inputs and the outcomes if we want to see the interactive effect. I suggested this is likely due to the larger markets, greater labor resources, and increased numbers of educated workers that a larger population brings, However, to understand the relative effect of interventions across countries with significant differences in population it is also necessary to consider how much aid is injected per capita, the economic health of the state (depicted through GDP per capita) and how much FDI inflow is generated per capita. As development aid per capita increases under the oversight provided by UN led PKOs, a larger positive effect on FDI inflows per capita is generated. 209

However, this result is only observed when we consider the time it takes for aid commitments to become operationalized and for information to flow from the field and reach those policy makers who will further affect change.165 In fact, the results suggest that the level of stability we see in conflict-affected countries today results from aid committed three years ago and that effect is reliant on whether or not UN peacekeepers were present last year.166

While this outcome met expectations, others did not. I argued in Chapter 3 that a doctrinal focus on expecting and promoting accountability from the host nation would prompt greater information collection and sharing on a broader range of issues; I suggested NATO countries would rank highest in this category. However,

I found that increased numbers of Chinese peacekeepers had the greatest impact, both positive and highly significant. While I theorized their effect would be positive and higher than that of Russian or Warsaw Pact influenced peacekeepers, I did not believe their effect would surpass that of NATO troops – whose peacekeeping doctrine identifies the importance of host nation accountability. Additionally, I found the effect of increased numbers of individual police as well as observers to have a negative and significant effect. My theory is centered on the notion that PKOs

165 In this context a policy maker can be anyone involved in the stabilization effort, the key is that they are basing their policy decisions on the information that the PKO generates. 166 Subsequent findings that considered the interactive effect of every mission type found, counter to the theory, that UN authorized missions, the second highest level of UN participation generated a negative and significant effect on FDI inflows. However, the presence of UN authorized missions deployed alone (i.e. with no other mission type present) represents only 12% of all PKO deployments. 210

provide oversight by collecting information and sharing that information with a wider audience. Both individual police (typically employed as advisors to local police forces) and observers, despite their lower numbers compared to troops, are in the ideal positions to collect information on the local environment and their mission dictates that information be shared. Why these unexpected results occurred is not entirely clear and offers opportunity for continued investigation.

As discussed in Chapter 5 the models used for the analysis employed robust standard errors clustered on each conflict-affected country to account for heteroscedasticity. I offered that this is likely caused by an unidentified country- level effect which could also be generating the unexpected results. However, those results held when I included the lagged dependent variable in the final model. The inclusion of the lagged dependent variable, representing the cumulative impact of all factors on FDI inflows up to the current year, should absorb the effect of all intervention-related variables. It did not do this for the effect of Chinese peacekeepers or increased police suggesting these variables are related to FDI inflows through some other mechanism.

Recognizing that my models are imperfect, and that this is possibly the cause of the unexpected results, my findings still offer some support to my theory. The question becomes whether or not we can find instances of this occurring under natural conditions. One case that can serve as an illustrative example of my theory in action is the United Nations peacekeeping operation in Cote d’Ivoire (UNOCI). 211

6.2. Finding support for the theory and results: UNOCI

The United Nations Peacekeeping Operation in Cote d’Ivoire (UNOCI) completed its final mandate in June of 2017 after 13 years of operation. We can consider UNOCI a success on the merits of its departure alone, meaning the international community no longer perceived the need of a physical intervention in the country to help promote stability, the mission had successfully completed its tasks towards this effort. However, by placing Cote d’Ivoire and UNOCI in the context of the theory and findings presented in this thesis, we can see how the country’s return to normalcy was facilitated by the increasing levels of oversight that UN involvement created. Additionally, we can see how that oversight prompted the international community to modify its approach to affecting change in the destabilizing behavior of the belligerents.

A report to the UN Secretary General (UNSC, 2018) attributed UNOCI’s success to the series of mandates that directed the course of the mission as well as coordinated international effort that occurred throughout UNOCI’s deployment.

However, the report fails to highlight what exactly about the mandates helped

UNOCI attain its mandated goals. I argue that the mandates allowed for UNOCI to gradually increase its information gathering and sharing capacity. It was the gradual evolution in the mission, from an interposition force tasked with separating belligerents, to an information gathering organization that provided situational awareness for UN, African Union (AU) and Economic Community of West African 212

States (ECOWAS) members, that made UNOCI an integral player in the conflict’s eventual resolution and the country’s reconciliation.

6.2.1. Pre-intervention Cote d’Ivoire

Unlike many countries in Western Africa, Cote d’Ivoire was considered to be stable for the majority of its history as a sovereign state with a strong economic foundation. However, Cote d’Ivoire’s perceived strength was bolstered by an economy driven by ethnic and economic inequality and a dominant political leader.

Prior to gaining independence from France in 1960, Cote d’Ivoire was recognized as a primary international exporter of cocoa and coffee. The cultivation of these cash crops had profited French colonials since the mid-1800’s but also created a necessity for a large labor force and a cadre of business savvy “middle class” farmers capable of running the large plantations that produced them. As a result, the French imported labor from neighboring countries (namely Mali and

Burkina Faso) and laid the groundwork for the development of an Ivorian education system that would ultimately benefit a limited section of the population.167 By the

1950’s the agricultural middle class had evolved into a true bourgeoisie that held enough influence and political will to transition Cote d’Ivoire from a colony, to a

167 The use of migrant workers for the labor-intensive agricultural industry is a practice that continued after Cote d’Ivoire became and independent nation. 213

French republic, and finally an independent country in 1960 under President Felix

Houphouet-Boigny.

Houphouet-Boigny would lead Cote d’Ivoire from 1960 until his death in

1993, his first test at the ballot box not coming until the legalization of opposition parties in 1990 and a victory over Laurent Gbagbo. The death of Houphouet-Boigny brought Henri Bedie, a member of Houphouet-Boigny’s political party168 and leader of the National Assembly, into the presidency at a time when the Ivorian economy was impacted by the first devaluation of the African Financial Community (CFA) franc in 50 years; GDP growth in 1994 was limited to 0.8% compared to a regional average of 2.8% (Ali-Dinar, 2019). Bedie’s reelection in 1995 drew scrutiny due the boycott of opposition parties whose would-be candidates were disqualified under newly-established laws requiring candidates to be born to demonstrably-Ivorian parents.

The notion of ivoirité was once used to describe the cultural mix of native

Ivorians and those who had immigrated over the past century. However, under the

Bedie regime the term became weaponized to win support among those Ivorians concerned with the political impact that changing demographics of the country might bring as elections became more competitive. Under Bedie and the Ivorian

168 Houphouet-Boigny led the Democratic Party of Cote d’Ivoire-African Democratic Rally (PDCI- RDA), an Ivorian nationalist party that originated as the African Agricultural Union of Cote d’Ivoire before independence. Both parties were pro-farmer/pro-business. (FNA, 2019) 214

bourgeoisie who supported him, immigrants or those who could not demonstrate pure Ivorian descent were deemed to be non-Ivorian (meaning they could not participate in elections), regardless of their birthplace. In essence, this policy split

Cote d’Ivoire into a wealthier predominantly Christian south and an impoverished predominantly Muslim north.

Bedie’s presidency was cut short in 1999 when elements of the Ivorian military staged a coup and overthrew the government over issues of pay – not elections policy. According to two Americans169,170 who worked in different capacities in Cote d’Ivoire during the early 2000s, the pay issues originated when coup instigators returned from the UN peacekeeping operation in the Central

African Republic (MINURCA) and demanded the higher wages they had become accustomed to – something the Bedie government was unwilling to do.

The coup’s leader General Robert Guei shortly took control of Cote d’Ivoire, claiming victory in the 2000 elections, until October of that year when he was forced out of office by a popular uprising leaving his election opponent Laurence Gbagbo (a democratic socialist candidate from the Ivorian People’s Front (IPF)) in power.

169 Interview with Mr. Ryan McCannell (2017, pp. 11-12), Senior Advisor U.S. Agency for International Development, U.S. Army War College. Mr. McCannell worked in Cote d`Ivoire in 2000 for the National Democratic Institute, a non-partisan, non-profit NGO that promotes democratic institutions and practices. 170 Interview with Mr. James Stewart (2017), retired Foreign Service Officer, U.S. Department of State. Mr. Stewart served at the United States Embassy in Cote d`Ivoire from 1999-2004, first as an Economic Advisor and then as the Embassy’s Political-Economic Counselor. 215

However, Gbagbo’s government was almost immediately challenged by violent clashes with supporters of Alassane Ouattara, a Muslim whose candidacy in the

2000 election had been disputed by ivoirité policies. Despite continued ivoirité rhetoric from the Gbagbo regime, Ouattara’s Rassemblement des Republicains (RDR) party was eventually given a role in the government in an effort to promote reconciliation.

6.2.2. Conflict and intervention, the 2002-2003 Ivorian Civil War

It was in this politically tense and ethnically divided period in Cote d’Ivoire that a September 2002 mutiny within the Ivorian military over demobilization efforts would lead to a failed coup attempt and civil war. International attention became quickly focused on Cote d’Ivoire, particularly France and the United States.

By December 2002 the French military had begun increasing its presence within

Cote d’Ivoire.171 Initial French troops operated in an advisory role to government forces at the invitation of the Gbagbo regime but this evolved into the creation of a buffer force of approximately 4000 troops (Opération Licorne) physically separating government troops from rebel forces (Mays, 2011, p. 192).172

171 A small French force existed in the capital of Abidjan resulting from a previous bi-lateral agreement between the two countries. 172 Three separate rebel groups mobilized during this period: the Patriotic Movement in Cote d`Ivoire (MPCI), the Ivorian Popular Movement of the Great West (MPIGO), and the Movement for Justice and Peace (MJP) (Holt et al., 2009). 216

In addition to France and the United States, Cote d’Ivoire’s regional neighbors responded to French/ECOWAS-brokered cease fire agreements between the belligerents by deploying an ECOWAS peacekeeping mission to Cote d’Ivoire

(ECOMICI) (Mays, 2011, pp. 96-97; Novosseloff, 2015; UNSC, 2018). ECOMICI was composed of approximately 1500 troops from Benin, Ghana, Niger, Senegal, and

Togo with an additional 70 civilian police from Niger and Togo (Mays, 2011, p. 97).

While the ECOWAS force was expected to replace French forces, the two groups instead partnered to enforce the Linas-Marcoussis Agreement (LMA)173 signed in January 2003 as fighting continued across more parts of the country.174

Official US visits to meet with ECOMICI personnel verified that the force was competent (particularly the larger Ghanaian and Senegalese contingents) and, along with their Opération Licorne partners, were serving as an effective buffer between the belligerents despite suffering attacks from both parties (Stewart, 2017).

Despite international efforts to enforce the LMA and prevent new flare-ups, the Gbagbo regime continued to demonize the northern rebels and pushed the

Ivorian military to attack north of the French/ECOMICI-established buffer zone. The

173 The LMA was the third brokered cease fire agreement to that point in the crisis. Accra 1 (signed in September 2002) and Lome (signed in December 2002) acknowledged ECOWAS and French participation in monitoring the ceasefire as well the establishment of the demilitarized Zone of Confidence (ZOC) that expanded on earlier French efforts to physically separate the forces (Novosseloff, 2015, p. 710). 174 At the signing of the LMA, rebel forces had consolidated into the Forces Nouvelles de CI(FN) under Guillaume Soro (Holt et al., 2009). 217

continued efforts by both sides to violate the peace accord and challenge the

ECOWAS and French peacekeepers led to a call, promoted heavily by the United

States, for a more robust United Nations peacekeeping effort.175

6.2.2.1. The transition to and evolution of UN peacekeeping and the need

for more information

Initial UN peace efforts in Cote d’Ivoire consisted of a small political mission

(MINUCI)176 established on May 13, 2003 under United Nations Security Council

Resolution (UNSCR) 1479(2003) . MINUCI consisted of 75 advisors and observers who were to support existing ECOWAS and French efforts. That mission was replaced the following year by the larger UN Operation in Cote d’Ivoire (UNOCI) that absorbed the ECOWAS peacekeepers and brought in additional international support. Under UNOCI’s initial mandate, UNSCR 1528(2004)(UNSC, 2004a),

Opération Licorne became an authorized peacekeeping force, partnered with UNOCI and included in future mandates.

175 The US Ambassador assessed that Ghagbo’s rhetoric and willingness to challenge peacekeeping efforts was due to the lack of international support for ECOWAS and French efforts. A total of 27 diplomatic cables (an exceptionally high number for a single issue) were sent from the US Embassy in Abidjan to Washington and US representatives at the United Nations to encourage US support for a UN-led PKO (Stewart, 2017). 176 MINUCI is the French and official UN acronym for the United Nations Mission in Cote d’Ivoire. 218

UNOCI would grow to a mission composed of troops, police, formed police units, and observers from 68 contributing countries177, the largest contingents coming from Bangladesh and Pakistan.178 The mission also included participants

(predominantly observers) from NATO countries, Russia/former Warsaw Pact countries, and China.

Sporadic violence continued into early 2004 between the Gbagbo government and the Forces Nouvelles (FN)179 despite UNOCI’s deployment. The continued violence demonstrated early on that neither side of the conflict was ready to concede to the full obligations of the LMA. The UN Security Council recognized that without sincere support from Ivorian government or the FN the mission would be limited, even in its interposition role. Because neither side was sincere in its efforts to curb violence, a first step was to limit the flow of weapons into the country.

Under UNSCR 1572(2004) the council took initial steps to reduce the number of imported arms that were being used by government forces, pro- government forces, and rebels alike to continue to fight, and in doing so, commit

177 This represents the number of different countries that contributed over the course of the mission, not during a single year. All UN troop information was derived from reports located at: https://peacekeeping.un.org/en/troop-and-police-contributors. . 178 Like all modern UNPKOs, in addition to a military component, UNOCI deployed a significant civilian component. These UN personnel are often employed monitor and report on human rights issues, participate in civil affairs operations aimed at communicating between the mission and the local populace, and child protection issues (Holt et al., 2009). 179 At the signing of the LMA, rebel forces had consolidated into the Forces Nouvelles de Cote d’Ivoire (FN) under Guillaume Soro (Holt et al., 2009). 219

significant human rights violations. However, the Security Council quickly recognized that limited support of these efforts by either side had generated an information-poor environment that prevented the sanctions committee established in the resolution from effectively carrying out this task.

To address this issue the security council passed resolution 1584(2005) on

February 1, 2005 directing the mission to develop mechanisms for monitoring (a task inherited from the earlier mandate), information collection, and analysis of information regarding arms shipments.

Resolution 1584(2005) was significant because it represented the start of the

UNOCI’s transition away from being a buffer and monitoring force to one that would take a more active role in collecting, analyzing, and sharing information about specific aspects of the local environment. While not necessarily uncommon for a UN mission, the resolution also directed the creation of a Group of Experts within

UNOCI whose sole purpose was to collect, analyze and report on these issues.

However, the resolution also called for the experts to consider information gathered by UNOCI and Opération Licorne (i.e. peacekeeping intelligence) to complete their mandated tasks.

Two additional peace agreements, this time brokered by South Africa and the

African Union, were signed in 2005. Pretoria I, signed in April, recognized the role 220

of the UN in future elections verification,180 while Pretoria II focused on the legitimacy of UN sanctions, embargoes on weapons sales to Cote d’Ivoire and the

Ivorian diamond industry (a source of income through conflict diamonds)

(Novosseloff, 2015, p. 710).181 Despite the advances towards future elections, violence between rebel forces and the Ivorian government continued as the belligerents could not agree on election candidacy issues.

The continued impact of the situation in Cote d’Ivoire on regional stability, particularly the thousands of refugees fleeing Cote d’Ivoire for neighboring states, prompted the Peace and Security Council of the African Union (AU) to act. In

October 2005 the council passed a resolution calling for the establishment of a ministerial-level International Working Group (IWG) in October of 2005 to speed up the reconciliation process. The AU initiative was sanctioned in UNSCR

1633(2005)(UNSC, 2005c).

Notably, paragraph 24 of UNSCR 1633(2005) tacitly approved the sharing of information to the IWG (and the AU Mediation Group that performed day-to-day interaction with the belligerents) by the UN sanctions committee; the same committee that was now receiving PKI gathered from UNOCI and Opération Licorne

180 A specially appointed UN High Representative for elections (autonomous from the UNOCI structure) was installed to monitor and resolve elections related issues, see UNSCR 1603(2005) and later UNSCR 1721(2006). 181 Recall the arms embargo was imposed by the Security Council under UNSCR 1572(2004) following attacks by Government troops on UNOCI. The UNOCI mandate to monitor the production and trafficing of diamonds was added under UNSCR 1643(2005). 221

forces. Within a period of less than a year, information collected by the missions was being shared across two international organizations.

6.2.2.2. UNOCI role in elections monitoring

Progress over the next fifteen months led to the January 2007 Ouagadougou

Political Agreement (OPA) signed by Gbagbo and rebel leader Guillaume Soro. The

OPA brought more FN members into government, including Soro who was named

Prime Minister. It was the signing of the OPA that completed UNOCI’s evolution from being predominantly a separating force to a more integral part of CI’s shift from conflict to post-conflict period.

Between 2005 and 2007 UNOCI’s mandate was significantly expanded to include an active participation in the electoral process. Following the OPA, responsibilities of election certification and the creation of an elections cell under resolutions 1765(2007) 182 that would monitor any election-related dispute were shifted to UNOCI. These expanded mandate tasks not only increased the role of

UNOCI in the Ivorian political process, it further demanded an expansion of the mission’s information collection capacity. This included the expectation that UNOCI would share this information with the AU’s IWG and Mediation Group as well.

182 The mandate of the elections cell was reaffirmed under UNSCR 1865(2009). 222

Throughout this period UNOCI remained highly involved in supporting the efforts of both the African Union and ECOWAS through the provision of security and the sharing of information. However, UNOCI’s role and capacity as a peacekeeping operation was substantially different than its initial mandate called for by the time of the 2010 elections. While the core tasks associated with enforcing the peace agreements signed by Gbagbo’s government and the FN did not change, the tools

UNOCI used to achieve this did.

The signing of the OPA led in 2008 to the dismantling of the Zone of

Confidence that had split the country in two since 2003, while a perception of increased stability (due to increased freedom of movement throughout the country, initial progress on the disarmament and demobilization (DDR) of rebel forces, and economic growth183) led the UN Secretary General to recommend a reduction in

UNOCI’s military component by a single infantry battalion (UNSG, 2009).184 This recommendation was supported in Security Council Resolution 1865(2009). Going into the 2010 elections conditions looked to be improving.

183 From 2004 to 2009 the 5-year growth rate of FDI inflows was 23%, despite the absence of a steady inflow of development aid. (IBRD-IDA, 2018b) 184 According to the Sectary General’s report this reduction was possible due to the relocation of troops within the mission and the availability of quick response support from Operation Licorne if necessary . 223

6.2.2.3. Post-election violence 2010-2011 and reconciliation

Despite significant international effort, the December 2010 elections were contentious. UNOCI and the Ivorian Independent Electoral Commission declared

Alassane Ouattara the overall winner however, the Ivorian Constitutional Council refused to ratify the decision claiming instead that President Gbagbo had won the majority of votes. Despite ECOWAS and AU backing of Ouattara’s victory, Gbagbo’s subsequent refusal to concede the election resulted in a relapse of extreme violence between supporters of both candidates (UNSC, 2018, pp. 11-12).

In response the Security Council passed resolution 1975(2011) in March

2011 to reiterate UNOCI’s authority to protect civilians and bolster UNOCI security, including an increase in authorized troop strength and the temporary intermission transfer of troops from the UN Mission in Liberia (UNMIL). At this point, UNOCI action’s drew attention as they exercised their Chapter VII authorities in response to threats and attacks initiated by Gbagbo supporters with force. In early 2011

Gbagbo was captured by Ouattara’s forces and he was subsequently sent to the

Hague to stand trial for war crimes.185

185 UNSCR 1975(2011) noted that attacks perpetrated against civilians at this time could be tantamount to crimes against humanity and that violators would be held accountable. It is unclear why, despite repeated reports from UNOCI throughout the conflict about human rights violations, that the UN, AU, or ECOWAS had not called for actions, beyond individually targeted sanctions, to stop abuses earlier. 224

As highlighted in the Security Council report on UNOCI (UNSC, 2018), following Ouattara’s assumption of office UNOCI’s focus shifted towards the reconciliation process, this required increased information collection and reporting capacity from the mission. In 2014 UNOCI’s increased focus on human rights issues included the deployment of a special advisor on women’s protection issues; the intent was to expand UNOCI’s capacity to gather, analyze and report information on sexual violence to the Ivorian government. This effort was enhanced by a UNOCI- supported initiative creating an interagency group (UNOCI, Ivorian military, and

National Human Rights Commission) tasked with addressing human rights violations by the military. This group met monthly to review allegations made against the military. UNOCI also employed a variety of communications efforts with the Ivorian people, including use of the mission’s dedicated radio station to ensure transparency during the reconstruction and reconciliation process.

These continuously expanding efforts by UNOCI to collect and share information with the Ivorians and the international community represents the power that UN involvement brought to the conflict-affected country. Arguably

UNOCI’s initial success was hampered by the lack of support it initially received from the Gbagbo regime as well as the FN. While this may have impeded the mission’s ability to enforce the peace agreements early on, the lack of support drove the development and use of the various information networks, including French intelligence networks, described above. Each information component contributed to the situational awareness of the international community that, in turn, led to 225

modifications in how the international organizations involved (UN, AU, and

ECOWAS) worked to resolve the conflict.

Notably, this increased information capacity was not always part of UNOCI’s uniformed component. While regular reporting from military (including Opération

Licorne) and police units arguably contributed to the overall information collection and analysis capacity of the mission, it was the additionally mandated teams or committees, typically comprised of civilian subject matter experts, whose efforts expanded UNOCI’s ability to inform a wider audience. In fact, it was not until the mission had transformed from a buffer force to an organization with a broader mandate (and broader information capacity) that it demanded the respect of both the Gbagbo government and the FN such that progress towards stability became more apparent. However, the continued failure of reporting on human rights violations to prompt noticeable change in the behavior of either belligerent until well after the post-election violence in 2010-2011 shows that oversight alone cannot prompt change.

6.2.2.4. The impact of limited development aid.

Although the international community invested significant resources into

UNOCI, Opération Licorne, and the various commissions or bodies that were in place over the course of the conflict, foreign aid flows to Cote d’Ivoire were not consistent.

Figure 1 depicts foreign aid commitments and peacekeeper deployment totals 226

through 2013;186 it is apparent that foreign aid commitments to Cote d’Ivoire were dramatically impacted beginning with the 2002 mutiny. And, because the conflict was not full resolved until mid-2011, as late as 2011 foreign aid to Cote d’Ivoire was limited (at least from the United States) to humanitarian initiatives such as fighting the AIDS epidemic and addressing internally displaced persons or refugees.187

Considering the embargoes and sanctions regime in place at this time, the decision by donors to limit the injection of aid dollars into Cote d’Ivoire was likely influenced by a concern over misappropriation of resources that may have resulted due to large injections of aid across the various development sectors.

Based on the findings in Chapter 5 we would expect that the reduction in development aid commitments under a UN PKO would have resulted in lower FDI inflows. And by looking at the difference in FDI inflows before and after the 2010

186 Data limitations for aid commitments prohibit the inclusion of aid figures past 2013. 187 From: Testimony by Deputy Assistant Secretary William Fitzgerald, Bureau of African Affairs, U.S. Department of State Senate Foreign Relations Committee Subcommittee on African Affairs, May 19, 2011. (Fitzgerald, 2011) 227

Figure 6-1: Aid Commitments and Peacekeeper Deployments to Cote d'Ivoire 2002-2013 Conflict Aid Aid Conflict

Post sum the represents of aid commitments targeted towards Security, Peace Governanace, and Reconstruction. Peacekeeper totals include UN, French, and ECOWAS forces if deployed that year. Development Aid Development Commitments Aid Conflict Post Commitments Deployed Peacekeepers Total Peacekeepers Deployed Peacekeepers Total 16000 14000 12000 10000 8000 6000 4000 2000 0 2013 2013 -

2012

Apr2011 Apr2011 - Dec 2010 Dec 2011

crisis election Post 2010 2009 2008

Year

signed Jan 2007 Jan signed OPA 2007 2006 2005 Aid Commitments and Peacekeeper Deployments to Cote d'Ivoire 2002 d'Ivoire Cote to Deployments and Peacekeeper Aid Commitments 2004

2003

Sept 2002 2002 Sept Military coup fails coup Military 2002 0

6000 5000 4000 3000 2000 1000 Aid Commitments in millions constant 2011 USD 2011 constant millions in Commitments Aid

228

elections (see Figure 2) it appears that FDI inflows during periods of reduced development aid are lower than inflows during periods of increased development aid. What is not clear is why FDI inflows fell between 2008 and 2010 (before the election crisis).

It is possible that this is the result of the 2008 global financial crisis, however, a review of U.S. Department of State Investment Climate Statements for Cote d’Ivoire from 2009-2010 (DOS, 2009, 2010) suggests that only the continued internal political and economic challenges might deter investment (add in citations from investment statements). It is possible that during a time of global financial stress, foreign investors were less willing to risk additional investment dollars in

Cote d’Ivoire when issues that had spurred the original conflict (i.e. social tensions and contested elections) were yet to be resolved.

Figure 2 depicts a rebound of FDI inflows following the resolution of the

2010-2011 post-election crisis; this response is similar to what is observed after the initial deployment of peacekeepers in 2003. A lack of both cumulative and disaggregated aid data beyond 2013 prohibits an analysis of aid commitments commensurate to that done for the thesis, however, based on delayed effect of aid observed in the results reported in Chapter 5 we would expect that the increased development aid committed from 2011-2013 would reflect in FDI inflows from

2014-2016. And, despite UNOCI’s steady decrease in force strength, 2011-2016 arguably represents UNOCI’s period of greatest information collection and sharing if 229

we consider their efforts to expand communications with the Ivorian population throughout the reconciliation period.

Figure 6-2: FDI Inflows to Cote d'Ivoire 2002-2017 (millions 2011 constant USD)188

It was in 2014 that the U.S. State Department changed its characterization of

Cote d’Ivoire’s investment climate from being open to foreign investment but recovering from violence, damaged infrastructure, neglect, and degradation to being

“fertile” for FDI, a characterization that remained in place through 2018 (DOS, 2012,

2013, 2014, 2015, 2016, 2017, 2018). In fact, overall FDI inflow growth between

188 FDI inflow data from analysis dataset, raw data from the World Bank, (IBRD-IDA, 2018b) 230

2011 and 2017 was 105%, demonstrating that investors have judged Cote d’Ivoire’s outlook for long-term stability as positive.

6.2.2.5. Future policy recommendations and final comments

Although UNOCI’s deployment was plagued by continued violence and even complaints about the mission itself,189 its transformation over the deployment aided

Cote d’Ivoire’s return to a self-sustaining level of stability. What “lessons learned” should the international community take away if we want to replicate UNOCI’s success? I argue there are two lessons, supported by my research, that can be applied to any situation.

First is the realization that information is useful but only effective if those who collect it and analyze it pass the information to those who can affect change with it. As highlighted above, UNOCI was able to develop a network of networks that collected, analyzed, and reported information on day-to-day conditions as well as key information requirements for specific topics of interest. However, this was only accomplished when mandates directed the capacity be created and resourced.

Once information was in-hand it had to be shared across organizations – key was the follow-up by those organizations through the imposition of sanctions or even more ways of imposing oversight on the former belligerents.

189 UNOCI was one of several UNPKOs where allegations of sexual abuse and exploitation against the local populace by peacekeepers were reported (UNSC, 2018) 231

Future mission planning, by any peacekeeping organization, should consider the rapid creation of information networks at the local and national levels as a vital component to its operation, and make the collection and sharing of information deemed vital to achieving mandated tasks a prerequisite for deployment. I argue it was the directive to share information with those who could affect change through alternate actions (i.e. sanctioning power) that eventually made UNOCI successful.

But future missions, regardless of the sending organization, could employ the same strategy.

My research also demonstrated that development aid will not generate an immediate effect, even when a PKO with significant oversight capacity like UNOCI is present. This is likely due to the time needed for committed funds to be applied to projects and for those projects to promote the donor’s desired change. We saw in the case of Cote d’Ivoire how the vast majority of aid donations were curtailed during UNOCI’s first years of deployment. Although FDI inflows continued to rise during this period, the inflows were not commensurate to inflows following the

2010 crisis when UNOCI was at its information sharing peak and development aid resumed. This leads to a second implication of my research: oversight tasks should support development initiatives.

Simply put, if a PKO is tasked to collect information about a development sector and resourced with experts to discern potential abuse of those resources, it may incentivize donors to discount the risk of misappropriated aid funds by the target state. My research suggests high oversight and targeted development aid 232

have a positive interactive effect on stability. If those information networks are established early on in the deployment such that aid flows can return, my research suggests stability will increase earlier in the stabilization effort.

My research offers one more piece of knowledge to several important puzzles. I confirmed that peacekeeping and aid have an important role in stabilizing conflict-affected states, but I demonstrated how and offered a reasonable theory as to why these interventions work together even though they are not planned as supporting efforts.

By looking at FDI inflows as a proxy for stability I demonstrated that the international community can define success in terms that are not necessarily common to intervention, and that it can rely on the judgement of those not directly involved with an intervention to make that assessment. This extends our understanding of the link between the economy in post-conflict states and what motivates investors to take financial risk in these countries. It also opens or widens doors of research about peacekeeping, foreign aid, and foreign investment.

Finally, the theory I presented is general and can apply to any post-conflict stabilization effort; the analysis offers quantifiable evidence that the theory has merit. Based on my findings I presented the practitioners and policy makers of peacekeeping and foreign aid with options for future interventions that are not based on personal experience or anecdotal evidence even though we can see evidence of the findings in actual cases. Moving forward it is clear that more 233

research is needed to address instances of conflict and instability that are likely to repeat themselves in the future. 234

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Appendix A

PKOs deployed 1970-2013

Conflict- UN UN UN Non affected Mission START THRU led authorized recognized UN State Afghanistan UNGOMAPAfghanistan x 1988 1990 ISAF x 2001 2013 Albania MPF-Operation Alba x 1997 1997 ECMMAlbania x 1991 2000 AFOR x 1999 1999 Angola UNAVEM x 1988 1991 UNAVEMII x 1991 1995 MONUA x 1997 1999 UNAVEMIII x 1995 1997 Bosnia- IFOR x 1995 1996 Herzegovina UNMIH x 1995 1996 SFOR x 1996 2004 UNMIBH x 1995 2002 Rapid Reaction Force x 1995 1995 (UK, France) EUFOR Operation x 2004 2013 Althea UNPROFOR x 1992 1995 Bulgaria ECMMBulgaria x 1991 2000 Observer Commission Burkina Faso from ANAD Burkina x 1986 1986 Faso Burundi SAPSD x 2001 2009 OMIB x 1993 1996 AMIB x 2003 2004 ONUB x 2004 2006 Cambodia UNAMIC x 1991 1992 UNTAC x 1992 1993 Central MISAB x 1997 1998 African Rep. MINURCA x 1998 2000 MINURCAT_CAR x 2007 2010 249

Operation Sangaris x 2013 2013 (France) MICOPAX x 2008 2013 CEN-SAD x 2001 2002 FOMUC (ECCAS) x 2002 2008 MISCA x 2013 2013 Chad EUFOR-Chad x 2008 2009 Nigerian Peacekeeping x 1979 1979 Force MINURCAT_Chad x 2007 2010 OAU Peacekeeping x 1980 1980 Force 1 OAU Peacekeeping x 1981 1982 Force 2 UNASOG Chad x 1994 1994 Comoros OMIC 2 x 2001 2002 OMIC x 1997 1998 MIOC x 2004 2004 Operation Democracy x 2008 2008 in the Comoros (AU) AMISEC x 2006 2006 OMIC 3 x 2002 2002 MAES x 2007 2008 Congo, Dem. MONUC x 1999 2010 Rep. Operation Artemis / x 2003 2003 IEMF OAU Observer Mission x 1999 2000 EUFOR-RD x 2006 2006 MONUSCO x 2010 2013 EUSEC-CONGO x 2005 2013 Inter-African Force x 1978 1979 Zaire Costa Rica ONUCACostaRica x 1989 1990 Operation Licorne Cote D'Ivoire x 2002 2013 (France) ECOMICI x 2003 2004 MINUCI x 2003 2004 UNOCI x 2004 2013 Croatia UNCRO x 1992 1995 UNTAES x 1996 1998 250

ECMMCroatia x 1991 2000 UNPF x 1996 1996 UNMOP x 1996 2002 Cyprus UNFICYP x 1970* 2013 Egypt UNEF II x 1973 1979 UNTSOEgypt x 1970* 2013 MFO x 1982 2018 El Salvador ONUSAL x 1991 1995 OAS Military Observers x 1976 1981 II El Salvador ONUCAElSalvador x 1989 1990 OAS Military Observers x 1970 1972 El Salvador Ecuador MOMEPEcuador x 1995 1999 Eritrea UNMEEEritrea x 2000 2008 OLMEE, x 2000 2008 AULMEEEritrea Ethiopia UNMEEEthiopia x 2000 2008 OLMEE, x 2000 2008 AULMEEEthiopia South Ossetia Joint Georgia x 1992 2008 Peacekeeping Force CPKF/CPFOR x 1994 2013 (Abkhazia) UNOMIG x 1993 2009 Russia-Abkhazia Peacekeeping x 1993 1994 Operation Grenada CPF aka ECPF x 1983 1985 Guatemala ONUCAGuatemala x 1989 1990 MINUGUA x 1997 1997 Guinea- ECOMIB x 2012 2013 Bissau EU SSR x 2008 2010 MISSANG-GB Angola x 2011 2012 ECOMOG_Guinea x 1999 1999 Bissau Haiti UNSMIH x 1996 1997 Operation Uphold x 1994 1995 Democracy (US-led) MINUSTAH x 2004 2013 UNTMIH x 1997 1997 MIPONUH x 1997 2000 251

MIFH x 2004 2004 Honduras ONUCAHonduras x 1989 1990 OAS Military Observers x 1976 1981 II Honduras OAS Military Observers x 1970 1972 Honduras Hungary ECMMHungary x 1991 2000 India UNMOGIPIndia x 1970* 2013 Iran UNIIMOGIran x 1988 1991 Iraq UNIKOMIraq x 1991 2003 UNIIMOGIraq x 1988 1991 Israel UNTSOIsrael x 1970* 2013 UNDOFIsrael x 1974 2013 Arab Ceasefire Jordan x 1970 1971 Observer Mission Kosovo UNMIK x 1999 2013 KFOR x 1999 2013 Kuwait UNIKOMKuwait x 1991 2003 Lebanon MNF II x 1982 1984 MNF I x 1982 1982 UNIFIL x 1978 2013 UNTSOLebanon x 1970* 2013 Liberia ECOMIL x 2003 2003 ECOMOG_Liberia x 1990 1999 UNOMIL x 1993 1997 UNMIL x 2003 2013 Libya UNASOG Libya x 1994 1994 Macedonia, Operation Concordia x 2003 2003 FYR (EU) UNPREDEP x 1995 1999 Essential Harvest, Amber Fox, Allied x 2001 2003 Harmony (NATO) Mali MINUSMA x 2013 2013 Operation Serval x 2013 2013 (France) Observer Commission x 1986 1986 from ANAD Mali EUTM Mali x 2013 2013 AFISMA x 2012 2013 252

Moldova Joint Force / Joint Control Moldova x 1992 2013 Commission Peacekeeping Force JVC - Joint Verification Mozambique x 1990 1992 Mission ONUMOZ x 1992 1994 Namibia UNTAG x 1989 1990 Nicaragua ONUCANicaragua x 1989 1990 International Observer Nigeria x 1970 1970 Team in Nigeria OTN Pakistan UNGOMAPPakistan x 1988 1990 UNMOGIPPakistan x 1970* 2013 TMG (Truce Papua New Monitoring Group) x 1997 1998 Guinea (Bougainville) Peace Monitoring Group (PMG) x 1998 2003 (Bougainville) SPRPKF x 1994 1994 Peru MOMEPPeru x 1995 1999 Philippines IMT Mindanao x 2004 2013 Rwanda UNAMIR x 1993 1994 OAU NMOG II x 1993 1993 UNOMUR x 1993 1993 OAU MOT x 1991 1991 OAU NMOG I x 1991 1993 Sierra Leone UNAMSIL x 1999 1999 UNOMSIL x 1998 1999 Operations Basilica, x 2000 2005 Silkman (UK) Operation Palliser (UK) x 2000 2000 ECOMOG_Sierra Leone x 1990 1999 Slovenia ECMMSlovenia x 1991 2000 Solomon RAMSI x 2003 2013 Islands Somalia UNITAF x 1992 1993 UNOSOM x 1992 1995 UNOSOM II x 1992 1995 AMISOM x 2007 2013 EUTM Somalia x 2010 2013 253

Commonwealth Peacekeeping South Africa x 1994 1994 Assistance Group (CPAG) South Sudan UNISFASouthSudan x 2011 2013 UNMISS x 2011 2013 IPKF_India Peace Sri Lanka x 1987 1990 Keeping Force Sudan JCM and IMU x 2005 2007 UNAMID x 2008 2013 EU Support to AMIS II x 2005 2007 UNMIS x 2005 2011 UNISFASudan x 2011 2013 AMIS x 2004 2007 Syria UNTSOSyria x 1970* 2013 UNSMIS x 2012 2013 UNDOFSyria x 1974 2013 Tajikistan CPKF x 1993 2000 UNMOT x 1994 2000 Somali Observer Force Tanzania x 1972 1972 Tanzania Timor-Leste UNMIT x 2006 2013 JTF/ISF x 2006 2013 UNMISET x 2002 2005 UNTAET x 1999 2002 INTERFET x 1999 2000 Somali Observer Force Uganda x 1972 1972 Uganda Monitoring Observer x 1985 1986 Group EUTM x 2010 2013 Somalia(Uganda) Yemen JMC x 1994 1994 Arab League Observers x 1972 1972 Commonwealth Monitoring Force Zimbabwe x 1979 1980 (CMF) (Rhodesia/Zimbabwe) 254

Appendix B

Data sources and references for Troop/Police/FPU/Observer Contributions (Missions organized by start date)

Note: Peacekeeper contributions data originated from a variety of sources. Data for all UN-led missions deployed 1991-2013 were compiled from United Nations Department of Peacekeeping Operations (DPKO) monthly reports and are detailed below. Contribution data for other UN-led mission or non-UN led missions were derived from multiple sources. If possible, primary sources were used (i.e. publications, reports, websites hosted by the primary source) however in many cases secondary or even tertiary sources were used for data, or to clarify information from another source. These sources included The Military Balance (1971-2013), a yearly publication by the Institute for Strategic Studies (ISS), that offers varied degrees of detail on mission participation across the entire dataset. Full citations for those sources that provide data for multiple missions are included in Multiple Mission References; full citations for mission specific sources are subsequently detailed by that mission.

UN-led Missions 1991-2013

Mission Contribution Data References (cited by yearly groupings of UNPKO compiled monthly reports) United Nations Truce Supervision DPKO 1991-2013 Organization (UNTSO)* United Nations Military Observer DPKO 1991-2013 Group in India and Pakistan (UNMOGIP)* United Nations Force in Cyprus DPKO 1991-2013 (UNFICYP)* United Nations Disengagement DPKO 1991-2013 Observer Force (UNDOF)* United Nations Interim Force in DPKO 1991-2013 Lebanon (UNIFIL)* United Nations Observer Mission DPKO 1991-1995 in El Salvador (ONUSAL) United Nations Advance Mission in DPKO 1991-1992 Cambodia (UNAMIC)

255

United Nations Angola Verification DPKO 1991-1995 Mission (UNAVEM) II United Nations Iraq–Kuwait DPKO 1991-2003 Observation Mission UNIKOM United Nations Operations in DPKO 1992-1994 Mozambique (ONUMOZ) United Nations Confidence DPKO 1992-1995 Restoration Operation in Croatia (UNCRO) United Nations Operation in DPKO 1992-1995 Somalia (UNOSOM) I, II United Nations Protection Force DPKO 1992-1995 (UNPROFOR) United Nations Transitional DPKO 1992-1993 Authority in Cambodia (UNTAC) United Nations Assistance Mission DPKO 1993-1994 for Rwanda (UNAMIR) United Nations Observer Mission DPKO 1993-2009 in Georgia (UNOMIG) United Nations Observer Mission DPKO 1993-1997 in Liberia (UNOMIL) The United Nations Observer DPKO 1993 Mission Uganda–Rwanda (UNOMUR) United Nations Aouzou Strip DPKO 1994 Observer Group (UNASOG) United Nations Mission of DPKO 1994-2000 Observers in Tajikistan (UNMOT) United Nations Angola Verification DPKO 1995-1997 Mission (UNAVEM) III United Nations Mission in Bosnia DPKO 1995-2002 and Herzegovina (UNMIBH) United Nations Mission in Haiti DPKO 1995-1996 (UNMIH) United Nations Preventive DPKO 1995-1999 Deployment Force (UNPREDEP) United Nations Mission of DPKO 1996-2002 Observers in Prevlaka (UNMOP) United Nations Protection Force DPKO 1996 (UNPF) - Croatia United Nations Support Mission in DPKO 1996-1997 Haiti (UNSMIH) United Nations Transitional DPKO 1996-1998 Administration for Eastern Slavonia, Baranja and Western Syrmium (UNTAES) United Nations Verification DPKO 1997 Mission in Guatemala (MINUGUA) The United Nations Civilian Police DPKO 1997-2000 Mission in Haiti (MIPONUH) United Nations Observer Mission DPKO 1997-1999 in Angola (MONUA) United Nations Transition Mission DPKO 1997-1997 in Haiti (UNTMIH)

256

United Nations Mission in the DPKO 1998-2000 Central African Republic (MINURCA) United Nations Observer Mission DPKO 1998-1999 in Sierra Leone (UNOMSIL) United Nations Mission in the DPKO 1999-2010 Democratic Republic of the Congo (MONUC) United Nations Mission in Sierra DPKO 1999 Leone (UNAMSIL) United Nations Interim DPKO 1999-2013 Administration Mission in Kosovo (UNMIK) United Nations Transitional DPKO 1999-2002 Administration in East Timor (UNTAET) United Nations Mission in Ethiopia DPKO 2000-2008 and Eritrea (UNMEE) The United Nations Mission of DPKO 2002-2005 Support in East Timor (UNMISET) United Nations Mission in Côte DPKO 2003-2004 d'Ivoire (MINUCI) United Nations Mission in Liberia DPKO 2003-2013 (UNMIL) The United Nations Stabilization DPKO 2004-2013 Mission in Haiti (MINUSTAH) United Nations Operation in DPKO 2004-2006 Burundi (ONUB) United Nations Operation in Côte DPKO 2004-2013 d'Ivoire (UNOCI) United Nations Mission in the DPKO 2005-2011 Sudan (UNMIS) United Nations Integrated Mission DPKO 2006-2013 in East Timor (UNMIT) United Nations Mission in the DPKO 2007-2010 Central African Republic and Chad ( MINURCAT) African Union-United Nations DPKO 2008-2013 Hybrid Operation in Darfur (UNAMID) United Nations Organization DPKO 2010-2013 Stabilization Mission in the Democratic Republic of the Congo (MONUSCO) United Nations Interim Security DPKO 2011-2013 Force for Abyei (UNISFA) United Nations Mission in South DPKO 2011-2013 Sudan (UNMISS) United Nations Multidimensional DPKO 2013 Integrated Stabilization Mission in Mali (MINUSMA) * Mission deployed before digitized UDPKO records.

257

Non-UN led Missions and Pre-1991 UN-led Missions Mission Contribution Data References

Arab Ceasefire Observer Mission (Pace, 1970)

United Nations Emergency Force (UNSG, 1973a) (UNEF) II (UNSG, 1974b) (UNSG, 1975c) The Military Balance (ISS) 1974-1979

United Nations Force in Cyprus (UNSG, 1970) (UNFICYP) (UNSG, 1971) (UNSG, 1972) (UNSG, 1973b) (UNSG, 1975b) (UNSG, 1977) (UNSG, 1978) (UNSG, 1979) (UNSG, 1980) (UNSG, 1981) (UNSG, 1970) (UNSG, 1984) (UNSG, 1987) (UNSG, 1988a) (UNSG, 1990a)

United Nations Disengagement (UNSG, 1974a) Observer Force (UNDOF) (UNSG, 1975a)

Organization of American States (NYTimes, 1971) (OAS) Peacekeeping Operation in Honduras/El Salvador (OAS, 2009) (Diuguid, 1976)

Nigerian PKO in Chad (Nwolise, 1986) (Mays, 2011, p. 40) (Chigozie & Ituma, 2015)

Organization of African Unity (OAS, 1993) (OAU) Peacekeeping Force I (Allain, 1998) (Mays, 2002, p. 48)

Organization of African Unity (Tchioffo, 2013) (OAU) Peacekeeping Force II

258

Caribbean Peacekeeping Force (Ferguson, 1999) (CPKF) in Grenada (Worme, 1985)

Multinational Force and The Military Balance (ISS) 1982-2013 Observers (MFO) – Sinai/Egypt (MFO, 2015)

Multinational Force I & II (Cimbala & Forster, 2010) (Lebanon)

Observer Commission from (Boulden, 2003, p. 52) ANAD (Treaty on Non- Aggression, Assistance, and Mutual Defense)

Indian Peacekeeping Force The Military Balance (ISS) 1988, 1989 (IPKF) in Sri Lanka

United Nations Good Offices The Military Balance (ISS) 1988-1992 Mission in Afghanistan and Pakistan (UNGOMAP)

United Nations Transition The Military Balance (ISS) 1988-1989 Assistance Group (UNTAG) - Namibia

United Nations Angola The Military Balance (ISS) 1989-1992 Verification Mission (UNAVEM) (UNSG, 1988b) (UNSG, 1989) (UNSG, 1990b) (UNSG, 1991a) (UNSG, 1991b) (UNSG, 1993c) (UNSG, 1993a) (UNSG, 1993b)

United Nations Observer Group (UNSG, 1990d) in Central America (ONUCA) (UNSG, 1991c) (UNSG, 1992) (UNDPKO, 2003b)

United Nations Iran–Iraq (UNSG, 1990c) Military Observer Group (UNIIMOG)

Collective Peacekeeping Force (Sokolov, 1997) (CPKF) - Tajikistan

259

South Pacific Regional (UNPAN, 2005) Peacekeeping Force (SPRPKF)- Papua New Guinea

(Mays, 2011, p. 244)

TMG (Truce Monitoring Group) The Military Balance (ISS) 1998, 1999 (Bougainville) (UNPAN, 2005)

Bougainville Peace Monitoring The Military Balance (ISS) 1999-2002 Group

South Ossetia Joint Peacekeeping (ICG, 2004) Force (OSCE, 2018) Military Balance 92-02

Russia-Abkhazia Peacekeeping The Military Balance (ISS) 93, 94 Operation

Collective Peacekeeping Force (CPKF/CPFOR) - Abkhazia

(UNSC, 1993) (UNSG, 1994b) (UNSG, 1994a) (UNSC, 1995) The Military Balance (ISS) 1994-2013 (Thruelsen, 2006) (Marks, 1995)

Military Observer Mission (Mays, 2011, pp. 167-168) Ecuador-Peru (MOMEP) The Military Balance (ISS) 1995-1999

OAU Observer Mission in the (Mays, 2011, pp. 205-206) Comoros (OMIC) I, II, III (DefenseWeb, 2009)

Commonwealth Peacekeeping (CMP, 2008) Assistance Group (CPAG) – South Africa

260

Moldova Joint Force / Joint The Military Balance (ISS) 1992-2013 Control Commission Peacekeeping Force (Mays, 2011, pp. 152-153) (Waters, 2003) (Mackinlay & Cross, 2002) (Socor, 2012)

The Economic Community of (ROP, 2019a) West African States Monitoring Group (ECOMOG) – Sierra Leone The Military Balance (ISS) 1997-2000

The Economic Community of The Military Balance (ISS) 1991-1998 West African States Monitoring Group (ECOMOG) - Liberia (HRW, 1993)

Joint Verification Commission (Lundin, 2004) (JVC) in Mozambique (Armon et al., 1998) The Military Balance (ISS) 1990-1992

European Community Monitor (Landry, 1999) Mission (ECMM) – Balkans (Defensie.nl, 2019b)

OAU Military Observer Team (Boulden, 2003, p. 39) (MOT)

OAU Neutral Military Observer (Boulden, 2003, p. 39) Group (NMOG) I, II - Rwanda (Mays, 2011, pp. 178-179)

Unified Task Force (UNITAF)- The Military Balance (ISS) 1992, 1993 Somalia

Operation Uphold Democracy (Black, 1994) (US-led) - Haiti

(DOD, 1995) (DOS, 2000) The Military Balance (ISS) 1994, 1995

Rapid Reaction Force (UK, (Bauman et al., 2004) France) – Bosnia-Herzegovina

261

The Military Balance (ISS) 1995

Implementation Force (IFOR) – The Military Balance (ISS) 1995 Bosnia-Herzegovina

Stabilization Force in Bosnia- (SFOR, 1999) Herzegovina (SFOR)

The Military Balance (ISS) 1996-2004

Multinational Protection Force (Mays, 2011, pp. 176-177) (MPF)/Operation Alba - Albania The Military Balance (ISS) 1997

Mission Interafricaine de (Mays, 2011, p. 136) Surveillance des Accords de Bangui (MISAB) – Central African Republic The Military Balance (ISS) 1997, 1998 (UNSC, 1997) (UNSC, 1998)

Albania Force (AFOR) (GlobalSecurity.org, 2013) The Military Balance (ISS) 1999

Kosovo Force (KFOR) The Military Balance (ISS) 1999-2013

International Force East Timor (Nautilus, 2019) (INTERFET)

(INTERFET, 1999) (USMC, 2000) (Jago, 2010)

OAU Observer Mission in (Mullenbach, 2019a) Burundi (OMIB) (HRW, 1995) (IRIN, 1999b) (OAU, 1995) (Mays, 2011, p. 205)

OAU Observer Mission – (UNSC, 1999) Democratic Republic of Congo (DRC)

(ICG, 1999) (IRIN, 1999a) (HRW, 1999) (Boulden, 2003, p. 42)

262

OAU Liaison Mission in Ethiopia- (Mays, 2011) Eritrea (OLMEE)/African Union Liaison Mission in Ethiopia- Eritrea (AULMEE)

The Military Balance (ISS) 2006-2008

African Union Military Observer (AUPSC, 2004c) Mission in Comoros (MIOC)

Operation Palliser (UK) - Sierra The Military Balance (ISS) 2000 Leone

Operations Basilica/Silkman (Williams, 2010) (UK) -Sierra Leone

The Military Balance (ISS) 2000

International Security Force (NATO, 2018) (ISAF) The Military Balance (ISS)2002-2013

AU Special Task Force Burundi The Military Balance (ISS) 2007-2009

South African Protection Service (ACCORD, 2007) Detachment (SAPSD) - Burundi

(UNSC, 2001) The Military Balance (ISS) 2002

The Community of Sahel-Saharan (Mays, 2011, pp. 84-85) States (CEN-SAD) – Central African Republic

(Mullenbach, 2019b)

Operation Essential Harvest – (NATO, 2002b) Former Yugoslav Republic of Macedonia (NATO, 2002a)

Operation Amber Fox/Allied (NATO, 2002c) Harvest– Former Yugoslav Republic of Macedonia (NATO, 2003) (Bowman, 2003) (MOD-Italy, 2016) The Military Balance (ISS) 2001, 2002

263

Force Multinationale en (Mays, 2011, p. 94) Centrafrique (FOMUC) (ROP, 2019c) (AUPSC, 2004b) The Military Balance (ISS) 2004, 2005, 2006, 2008

ECOWAS Mission in Côte d'Ivoire (Mays, 2011, pp. 96-97) (ECOMICI)

The Military Balance (ISS) 2003

Operation Licorne (France) (MOD, 2014) The Military Balance (ISS) 2002-2015

Joint Military Commission (Mullenbach, 2019c) (JCM)/International Monitoring Unit (IMU) - Sudan

African Mission in Burundi (UNSG, 2003) (AMIB) (Nowrojee, 2004) (UNSG, 2004b) (Svensson, 2008) (Mays, 2011, p. 41) The Military Balance (ISS) 2003, 2004

Operation Artemis/Interim Multinational Emergency Force (UNSC, 2003a) (IMEF) – Democratic Republic of Congo (DRC) (UNSC, 2003b) (CEC, 2007) The Military Balance (ISS) 2003

ECOWAS Mission in Liberia (Mays, 2011, p. 97) (ECOMIL)

Operation Concordia (EUFOR) – (Defensie.nl, 2019a) Former Yugoslav Republic of Macedonia

(Lynch & Missiroli, 2009) The Military Balance (ISS) 2003

Regional Assistance Mission to The Military Balance (ISS) 2003 - 2013 Solomon Islands (RAMSI)

Multinational Interim Force Haiti (UNSG, 2004a) (MIFH) (Fishel, 2007)

264

International Monitoring Team The Military Balance 2004-2013 (IMT) – Mindanao (GRP/MILF, 2009) (GRP/MILF, 2011) (OPAPP, 2018)

African Union Mission in Sudan (Mays, 2011, pp. 45-46) (AMIS I, II) (AUPSC, 2004a) (AUPSC, 2005)

EUFOR Operation Althea – The Military Balance (ISS) 2005- 2013 Bosnia-Herzegovina

European Union Security Sector The Military Balance (ISS) 2008-20101 Reform Mission in the Democratic Republic of the Congo (EUSEC RD CONGO)

(ROP, 2019b) (EU, 2015) (EU, 2016) (Mays, 2011, p. 107) (EU, 2005b)

EU Support to AMIS 2 (EU, 2008c)

(EU, 2005a)

African Union Mission for (Mays, 2011, p. 43) Support to the Elections in the Comoros (AMISEC)

(AUPSC, 2007a) (ION, 2006)

EUFOR-RD Congo (Mays, 2011, p. 111)

The Military Balance (ISS) 2006

Joint Task Force/International (UNSG, 2006) Stabilization Force (ISF) - Timor Leste (East Timor)

The Military Balance (ISS) 2006-2013

African Union Mission to Somalia The Military Balance (ISS) 2007-2013 (AMISOM)

(AMISOM, 2019b)

1 References for The Military Balance reflect the publication years covered.

265

(AMISOM, 2019a)

Economic Community of Central The Military Balance (ISS) 2010-2013 African State mission in Central African Republic (MICOPAX)

(ROP, 2019d)

African Union Electoral and (Mays, 2011, p. 42) Security Assistance Mission in Comoros (MAES)

(AUPSC, 2007b)

EUFOR Chad – Chad and Central The Military Balance (ISS) 2008, 2009 African Republic

Operation Democracy in the (Mays, 2011, p. 42) Comoros (African Union)

EU Security Sector Reform (EU, 2010b) Mission(EU SSR) – Guinea Bissau (EU, 2010a) (EU, 2008a) (EU, 2008b)

EU Training Mission (EUTM) (EUTM-Somalia, 2019) Somalia

Angolan Technical Military and The Military Balance (ISS) 2011, 2012 Security Mission in Guinea Bissau (MISSANG-GB) (ANGOP, 2012)

ECOWAS Mission in Guinea- (UNSG, 2012a) Bissau (ECOMIB)

The Military Balance (ISS) 2013 (AEUP, 2018) (CIC, 2013)

African-led International (UNSG, 2012b) Support Mission to Mali (AFISMA) (UNSG, 2013) (UNSC, 2013) (ECOWAS, 2013)

(Maru, 2013)

266

Operation Sangaris (France) The Military Balance (ISS) 2013

African-led International The Military Balance (ISS) 2013 Support Mission to the Central African Republic (MISCA/AFISM- CAR)

Operation Serval (France) - Chad (Law, 2016)

The Military Balance (ISS) 2013

EU Training Mission (EUTM) The Military Balance (ISS) 2013 Mali

267

Appendix B References

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Department of Peacekeeping Operations, UNDPKO. (1992). Summary of contributions to peacekeeping operations. Monthly spreadsheets. Jan-May 92; Aug-Dec 92. https://peacekeeping.un.org/en/troop-and-police- contributors.

Department of Peacekeeping Operations, UNDPKO. (1993). Summary of contributions to peacekeeping operations. Monthly spreadsheets. January-December 1993. https://peacekeeping.un.org/en/troop-and-police- contributors.

Department of Peacekeeping Operations, UNDPKO. (1994). Summary of contributions to peacekeeping operations. Monthly spreadsheets. January-December 1994. https://peacekeeping.un.org/en/troop-and-police- contributors.

Department of Peacekeeping Operations, UNDPKO. (1995). Summary of contributions to peacekeeping operations. Monthly spreadsheets. January-December 1995. https://peacekeeping.un.org/en/troop-and-police- contributors.

Department of Peacekeeping Operations, UNDPKO. (1996). Summary of contributions to peacekeeping operations. Monthly spreadsheets. January-December 1996. https://peacekeeping.un.org/en/troop-and-police- contributors.

Department of Peacekeeping Operations, UNDPKO. (1997). Summary of contributions to peacekeeping operations. Monthly spreadsheets. January-December 1997. https://peacekeeping.un.org/en/troop-and-police- contributors.

Department of Peacekeeping Operations, UNDPKO. (1998). Summary of contributions to peacekeeping operations. Monthly spreadsheets. January-November 1998. https://peacekeeping.un.org/en/troop-and-police- contributors.

Department of Peacekeeping Operations, UNDPKO. (1999). Summary of contributions to peacekeeping operations. Monthly spreadsheets. Jan-Oct 1999, December 1999. https://peacekeeping.un.org/en/troop-and-police- contributors.

Department of Peacekeeping Operations, UNDPKO. (2000). Summary of contributions to peacekeeping operations. Monthly spreadsheets. January-December 2000. https://peacekeeping.un.org/en/troop-and-police- contributors.

Department of Peacekeeping Operations, UNDPKO. (2001). Country contributions detailed by mission. Monthly spreadsheets. January-December 2001. https://peacekeeping.un.org/en/troop-and-police-contributors.

Department of Peacekeeping Operations, UNDPKO. (2002). Country contributions detailed by mission. Monthly spreadsheets. January-December 2002. https://peacekeeping.un.org/en/troop-and-police-contributors. 268

Department of Peacekeeping Operations, UNDPKO. (2003a). Country contributions detailed by mission. Monthly spreadsheets. January-December 2003. https://peacekeeping.un.org/en/troop-and-police-contributors.

Department of Peacekeeping Operations, UNDPKO. (2004). Country contributions detailed by mission. Monthly spreadsheets. January-December 2004. https://peacekeeping.un.org/en/troop-and-police-contributors.

Department of Peacekeeping Operations, UNDPKO. (2005). Country contributions detailed by mission. Monthly spreadsheets. January-December 2005. https://peacekeeping.un.org/en/troop-and-police-contributors.

Department of Peacekeeping Operations, UNDPKO. (2006). Country contributions detailed by mission. Monthly spreadsheets. January-December 2006. https://peacekeeping.un.org/en/troop-and-police-contributors.

Department of Peacekeeping Operations, UNDPKO. (2007). Country contributions detailed by mission. Monthly spreadsheets. January-December 2007. https://peacekeeping.un.org/en/troop-and-police-contributors.

Department of Peacekeeping Operations, UNDPKO. (2008). Missions detailed by country. Monthly spreadsheets. January-December 2008. https://peacekeeping.un.org/en/troop-and-police-contributors.

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Department of Peacekeeping Operations, UNDPKO. (2010). Missions detailed by country. Monthly spreadsheets. January-December 2010. https://peacekeeping.un.org/en/troop-and-police-contributors.

Department of Peacekeeping Operations, UNDPKO. (2011). Missions detailed by country. Monthly spreadsheets. January-December 2011. https://peacekeeping.un.org/en/troop-and-police-contributors.

Department of Peacekeeping Operations, UNDPKO. (2012). Missions detailed by country. Monthly spreadsheets. January-December 2012. https://peacekeeping.un.org/en/troop-and-police-contributors.

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ISS. (1973) The Military Balance 1973-1974. The Institute for Strategic Studies. London

ISS. (1974) The Military Balance 1974-1975. The Institute for Strategic Studies. London

ISS. (1975) The Military Balance 1975-1976. The Institute for Strategic Studies. London

ISS. (1976) The Military Balance 1976-1977. The Institute for Strategic Studies. London

ISS. (1977) The Military Balance 1977-1978. The Institute for Strategic Studies. London

ISS. (1978) The Military Balance 1978-1979. The Institute for Strategic Studies. London

ISS. (1979) The Military Balance 1979-1980. The Institute for Strategic Studies. Air Force Magazine, December 1979 issue pp 61-138

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ISS. (1980) The Military Balance 1980-1981. The Institute for Strategic Studies. London

ISS. (1981) The Military Balance 1981-1982. The Institute for Strategic Studies. London

ISS. (1982) The Military Balance 1982-1983. The Institute for Strategic Studies. London

ISS. (1983) The Military Balance 1983-1984. The Institute for Strategic Studies. London

ISS. (1984) The Military Balance 1984-1985. The Institute for Strategic Studies. London

ISS. (1985) The Military Balance 1985-1986. The Institute for Strategic Studies. London

ISS. (1986) The Military Balance 1986-1987. The Institute for Strategic Studies. London

ISS. (1987) The Military Balance 1987-1988. The Institute for Strategic Studies. London

ISS. (1989) The Military Balance 1989-1990. The Institute for Strategic Studies. London

ISS. (1990) The Military Balance 1990-1991. The Institute for Strategic Studies. London

ISS. (1991) The Military Balance 1991-1992. The Institute for Strategic Studies. London

ISS. (1992) The Military Balance 1992-1993. The Institute for Strategic Studies. London

ISS. (1993) The Military Balance 1993-1994. The Institute for Strategic Studies. London

ISS. (1994) The Military Balance 1994-1995. The Institute for Strategic Studies. London

ISS. (1995) The Military Balance 1995-1996. The Institute for Strategic Studies. London

ISS. (1996) The Military Balance 1996-1997. The Institute for Strategic Studies. London

ISS. (1997) The Military Balance 1997-1998. The Institute for Strategic Studies. London

ISS. (1998) The Military Balance 1998-1999. The Institute for Strategic Studies. London

ISS. (1999) The Military Balance 1999-2000. The Institute for Strategic Studies. London

ISS. (2000) The Military Balance 2000-2001. The Institute for Strategic Studies. London

ISS. (2001) The Military Balance 2001-2002. The Institute for Strategic Studies. London

ISS. (2002) The Military Balance 2002-2003. The Institute for Strategic Studies. London

ISS. (2003) The Military Balance 2003-2004. The Institute for Strategic Studies. London

ISS. (2004) The Military Balance 2004-2005. The Institute for Strategic Studies. London

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ISS. (2007) The Military Balance 2007. The Institute for Strategic Studies. London

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Appendix C

Conflict Periods

Total Total Total Total Post- Conflict-affected Pre- Conflict- Intervention Intervention Country Conflict Years Years Years Years Afghanistan 5 39 15 3 Albania 32 0 9 3 Angola 0 44 12 3 Bosnia- Herzegovina 22 4 22 0 Bulgaria 32 0 9 3 Burkina Faso 38 2 1 3 Burundi 21 23 13 6 Cambodia 0 42 2 3 Central African Rep. 27 8 17 0 Chad 0 41 9 9 Comoros 25 2 9 11 Congo, Dem. Rep. 0 44 17 3 Costa Rica 38 0 3 3 Cote D'Ivoire 32 10 12 0 Croatia 29 4 12 3 Cyprus 0 44 44 0 Egypt 0 37 44 0 El Salvador 15 20 14 9 Ecuador 36 1 5 3 Eritrea 23 21 9 3 Ethiopia 0 44 9 3 Georgia 21 18 22 0 Grenada 38 1 3 3 Guatemala 0 44 5 6 Guinea-Bissau 26 6 7 3 Haiti 19 16 17 3 Honduras 24 0 11 9 Hungary 32 0 9 3 283

India 0 44 44 0 Iran 2 42 3 3 Iraq 0 44 15 3 Israel 0 44 44 0 Jordan 0 44 2 3 Kosovo 29 0 15 0 Kuwait 27 2 13 3 Lebanon 0 44 44 0 Liberia 10 24 20 3 Libya 33 4 1 3 Macedonia, FYR 32 1 8 6 Mali 15 25 2 3 Moldova 22 1 22 0 Mozambique 0 42 5 3 Namibia 39 0 2 3 Nicaragua 22 17 3 3 Nigeria 9 32 1 3 Pakistan 0 44 44 0 Papua New Guinea 27 8 7 6 Peru 0 41 5 3 Philippines 0 44 10 0 Rwanda 20 24 4 3 Sierra Leone 25 11 10 3 Slovenia 31 0 10 3 Solomon Islands 33 0 11 0 Somalia 7 36 11 3 South Africa 18 19 1 3 South Sudan 41 3 3 0 Sri Lanka 11 27 4 3 Sudan 0 44 10 0 Syria 0 44 44 0 Tajikistan 22 20 8 3 Tanzania 35 1 2 3 Timor-Leste 5 25 15 0 Uganda 1 43 8 6 Yemen 0 44 2 6 Zimbabwe 30 10 2 3 284

Appendix D

Results-Levene's Test for Homogeneity for mission type variables and UN involvement variables

Levene's Test for Homogeniety of Variance Variable Tested Levene's Statistic p-value PKO present 23.4032 0.0000 UN-led 50.4600 0.0000 UN-authorized 7.2683 0.0070 UN-recognized 3.7773 0.0521 Non-UN 0.0001 0.9911 UN involvement 4 50.4600 0.0000 UN involvement 3 2.8306 0.0926 UN Involvement 2 1.3080 0.2529 UN Involvement 1 2.4173 0.1201 p value > 0.05 indicates homogeniety of variance 285

Appendix E

OLS regression results, interaction model, UN led dummy (1 year lag) with development aid per capita (2 year lag) and (4 year lag) Model 9d Model 9e VARIABLES FDI per Capita FDI per Capita

1LagUNled*2LagDev/Cap 0.587 (0.313) 1LagUNled*4LagDev/Cap 0.537* (0.222) 1Lag UN-led dummy 38.00 47.78 (22.45) (29.37) 1Lag UN-authorized dummy -26.04 -29.57 (19.67) (21.01) 1L UN-recognized dummy -4.860 -5.332 (15.14) (16.19) 1Lag Non-UN dummy -9.486 -9.342 (18.80) (20.26) 2Lag DevelopmentAid/capita 0.138 (0.145) 2Lag SecurityAid/capita -1.424 (0.889) 2Lag PeaceAid/capita 0.138 (0.505) 2Lag GovernanceAid/capita 0.0342 (0.251) 2Lag ReconstructionAid/capita 0.881 (0.897) 4Lag DevelopmentAid/capita 0.00749 (0.130) 4Lag SecurityAid/capita -0.917 (0.600) 4Lag PeaceAid/capita -1.100* (0.434) 4Lag GovernanceAid/capita 0.374 (0.330) 4Lag ReconstructionAid/capita 0.869 (0.588) 1Lag Total Troops 0.000914 0.000821 (0.000595) (0.000657) 1LagTotal Police -0.0812** -0.0739*** (0.0256) (0.0153) 1Lag Total FPU 0.0385 0.0351 (0.0339) (0.0217) 1Lag Total Observers -0.147*** -0.198*** (0.0398) (0.0485) 1Lag Total Warsaw Pact -0.00132 0.0283 (0.0266) (0.0216) 1Lag Total Chinese 0.491*** 0.549*** (0.122) (0.0950)

286

Appendix E (continued): OLS regression results, interaction model, two year (L2) and four year (L4) lags on development aid per capita

Model 9d Model 9e continued FDI per Capita FDI per Capita

1Lag Population -1.82e-08 -2.72e-08 (3.14e-08) (3.31e-08) 1Lag GDP per Capita 0.0392*** 0.0378*** (0.00471) (0.00464) 1Lag Pre-conflict dummy 43.83 11.90 (29.42) (29.52) 1Lag Conflict year dummy 18.18 2.144 (22.80) (16.84) 1Lag Post-Intervention dummy -4.204 8.766 (21.10) (30.60) South Asia dummy -41.88 -49.85 (27.35) (29.95) Sub-Saharan Africa dummy -5.400 -10.12 (23.20) (30.33) Europe/Central Asia dummy 60.85 46.89 (31.49) (30.68) Latin Am./Caribbean dummy -22.63 -25.93 (32.14) (36.13) Middle East/N. Africa dummy 7.423 -2.605 (63.57) (76.02) Constant -32.19 -4.556 (32.75) (32.01)

Observations 424 355 Adjusted R-squared 0.635 0.609 Robust standard errors in parentheses *** p<0.001, ** p<0.01, * p<0.05

287

Appendix F OLS regression results, interaction model, all mission types (1 year lag) with development aid per capita (3 year lag) Model 9f VARIABLES FDI per Capita

1Lag UN-led dummy 24.01 (33.91) 1Lag UN-authorized dummy 29.27 (15.97) 1Lag UN-recognized dummy 6.227 (20.37) 1Lag Non-UN dummy -34.36 (22.92) 3Lag DevelopmentAid/capita 0.0467 (0.140) 1LagUNled*3LagDev/Cap 0.702* (0.265) 1LagUNauthorized*3LagDev/Cap -0.567*** (0.145) 1LagUnrecognized*3LagDev/Cap -0.268 (0.184) 1LagNonUN*3LagDev/Cap 0.235 (0.327) 3Lag SecurityAid/capita -1.311 (0.668) 3Lag PeaceAid/capita -0.613 (0.438) 3Lag GovernanceAid/capita 0.241 (0.432) 3Lag ReconstructionAid/capita 0.806 (0.755) 1Lag Total Troops 0.00103 (0.000550) 1Lag Total Police -0.0740*** (0.0210) 1Lag Total FPU 0.0223 (0.0190) 1Lag Total Observers -0.152** (0.0501) 1Lag Total Warsaw Pact 0.0310 (0.0276) 1Lag Total Chinese 0.497*** (0.135) 1Lag Population -5.61e-09 (3.16e-08) 1Lag GDP per Capita 0.0405*** (0.00452)

288

Appendix F (continued): OLS regression results, interaction model, all mission types (1 year lag) with development aid per capita (3 year lag)

Model 9f Continued FDI per Capita

1Lag Pre-conflict dummy 11.37 (28.05) 1Lag Conflict year dummy -1.420 (19.50) 1Lag Post-Intervention dummy -13.21 (27.21) South Asia dummy -57.07* (24.08) Sub-Saharan Africa dummy -11.08 (21.97) Europe/Central Asia dummy 39.36 (30.80) Latin Am./Caribbean dummy -20.97 (32.71) Middle East/N.Africa dummy -0.756 (69.46) Constant 0.154 (26.93)

Observations 389 Adjusted R-squared 0.627 Robust standard errors in parentheses *** p<0.001, ** p<0.01, * p<0.05