Governments of National Unity: Analyzing
the Conditions Influencing Dissolution
Prepared for the
U.S. Government Office of South Asia Analysis
By
Dylan Blake
Olivia Butler
Ryan Dunk
Michelle Duren
Katie Jenkins
Joel Lashmore
Allison Sambo
Workshop in International Public Affairs
Spring 2015
©2015 Board of Regents of the University of Wisconsin System
All rights reserved.
For an online copy, see
www.lafollette.wisc.edu/research-public-service/workshops-in-public-affairs
[email protected]
The Robert M. La Follette School of Public Affairs is a teaching and research department
of the University of Wisconsin–Madison. The school takes no stand on policy issues;
opinions expressed in these pages reflect the views of the authors.
The University of Wisconsin–Madison is an equal opportunity and affirmative-action educator and employer.
We promote excellence through diversity in all programs.
Table of Contents
List of Tables ................................................................................................................................. iv List of Figures ................................................................................................................................ iv Foreword ......................................................................................................................................... v Acknowledgments.......................................................................................................................... vi Executive Summary ...................................................................................................................... vii Introduction ..................................................................................................................................... 1 Literature Review............................................................................................................................ 2 Contextual Factors ...................................................................................................................... 2 Government Output .................................................................................................................... 4 Survival Model and Methods .......................................................................................................... 8 GNU Selection and Dating ............................................................................................................. 8 Data Description ......................................................................................................................... 8 Dependent Variable: Dissolution ................................................................................................ 9 Independent Variables .............................................................................................................. 10 Statistical Model ....................................................................................................................... 11 Survival Model Results ................................................................................................................. 12 Model 1: Dissolution with Conflict .......................................................................................... 12 Model 2: Dissolution without Conflict ..................................................................................... 15 Contextual Factors .................................................................................................................... 18 Government Output Factors...................................................................................................... 18 Case Studies: Variations in Power-Sharing .................................................................................. 20 Tajikistan: 1997 General Agreement on the Establishment of Peace and National Accord .... 20 Yemen: The 2011 Gulf Cooperation Council Agreement ........................................................ 22 Sudan: 2005 Comprehensive Peace Agreement ....................................................................... 25 Conclusions and Policy Recommendations .................................................................................. 28 Take No Action ......................................................................................................................... 28 Increase Access To and Role in International Organizations for GNUs .................................. 29 Strengthen Government Institutions ......................................................................................... 29 Incentivize Multi-Dimensional Power Sharing ........................................................................ 29 Appendix A. Governments of National Unity 1975-2012 ............................................................ 31 Appendix B. Technical Notes ....................................................................................................... 37 Semi-Parametric Model ............................................................................................................ 37 Cox Model ................................................................................................................................ 37 Time-Variant Covariates........................................................................................................... 38 Breslow vs. Efron Method for Approximating Discrete Likelihood of Failure ....................... 38 Frailty ......................................................................................... Error! Bookmark not defined. Appendix C. Model Specifications and Results ........................................................................... 39 References ..................................................................................................................................... 44 List of Tables
Table 1. Data Description ............................................................................................................... 9 Table 2. Predicted Relationship between Covariates and the Hazard Rate of Failure ................. 10 Table 3. Model 1 Dissolution with Conflict Results..................................................................... 12 Table 4. Model 2 Dissolution with Peace Results ........................................................................ 15 Table A1. Database of identified GNUs, Country, Start and End Dates, Dissolution, and
Type of Power-sharing Agreement ............................................................................ 31 Table A2. Listed Citations for Governments of National Unity ................................................... 34 Table C1. Model 1 Failure Results with Coefficients and Confidence Interval ........................... 39 Table C2. Model 2: Success Results with Coefficients and Confidence Interval ........................ 40 Table C3. GNU Summary Statistics by Duration, Model 1: Failure ............................................ 40 Table C4. GNU Summary Statistics by Duration, Model 2: Success ........................................... 41 Table C5. GNU Summary Statistics by Outcome of Interest ....................................................... 41 Table C6. Summary Statistics for Rule of Law Index .................................................................. 41 Table C7. Summary Statistics for Rule of Law Index, continued ................................................ 41 Table C8. Summary Statistics for GDP Growth ........................................................................... 42 Table C9. Summary Statistics for GDP Growth, Continued ........................................................ 42 Table C10. Summary Statistics for Ideological Conflict .............................................................. 42 Table C11. Summary Statistics for Ideological Conflict, Continued ........................................... 42 Table C12. Summary Statistics for Outcome: Stalemate.............................................................. 43 Table C13. Summary Statistics for Outcome: Stalemate, Continued ........................................... 43 List of Figures
Figure 1. Dissolution Outcomes ................................................................................................... 10 Figure 2. Kaplan-Meier Survival Distribution Function: Dissolution with Conflict Model ........ 14 Figure 3. Smoothed Hazard Function, by Median Rule of Law ................................................... 14 Figure 4. Kaplan-Meier Survival Distribution Function: Dissolution without Conflict
Model ......................................................................................................................... 16 Figure 5. Smoothed Hazard Function, by Ideological Conflict .................................................... 17 iv
Foreword
The La Follette School of Public Affairs at the University of Wisconsin−Madison offers a twoyear graduate program leading to a Master of Public Affairs or a Master of International Public
Affairs degree. In both programs, students develop analytical tools with which to assess policy
responses to issues, evaluate implications of policies for efficiency and equity, and interpret and
present data relevant to policy considerations.
Students in the Master of International Public Affairs program produced this report for the U.S.
Government Office of South Asia Analysis. The students are enrolled in the Workshop in
International Public Affairs, the capstone course in their graduate program. The workshop
challenges the students to improve their analytical skills by applying them to an issue with a
substantial international component and to contribute useful knowledge and recommendations to
their client. It provides them with practical experience applying the tools of analysis acquired
during three semesters of prior coursework to actual problems clients face in the public, nongovernmental, and private sectors. Students work in teams to produce carefully crafted policy
reports that meet high professional standards. The reports are research-based, analytical,
evaluative, and (where relevant) prescriptive responses for real-world clients. This culminating
experience is the ideal equivalent of the thesis for the La Follette School degrees in public
affairs. While the acquisition of a set of analytical skills is important, it is no substitute for
learning by doing.
The opinions and judgments presented in the report do not represent the views, official or
unofficial, of the La Follette School or of the client for which the report was prepared.
Melanie Frances Manion
Vilas-Jordan Professor of Public Affairs and Political Science
May 2015
v
Acknowledgments
We offer sincere thanks to everyone who provided assistance and supported this project. We
thank our clients for offering us the opportunity to produce this analysis, and thank them for their
support throughout the project. We especially thank Professor Melanie Manion who was critical
to the production of this report, and for her encouragement and criticism, pushing us to overcome
each of our hurdles with the project. We also want to thank Professor Jon Pevehouse and Simon
Haeder for their help with the methodology and technical aspects of the project. Special thanks to
Karen Faster for her careful review and editorial support. Finally, this project would not have
been possible without the support of the students and staff at the La Follette School of Public
Affairs.
vi
Executive Summary
We conducted research to understand the factors that contribute to the dissolution of
governments of national unity (GNUs), and to what effect these factors contribute to peaceful
dissolution or dissolution with conflict. Opposing groups or elite actors within a country create a
GNU through codifying power-sharing provisions in a settlement that ends or forestall violence.
Very little conclusive or quantitative research exists to support or refute the contention that
GNUs can promote stability for conflict-affected countries. Our report seeks to resolve this
ambiguity by offering evidence-based findings and recommendations for U.S. policy in relation
to GNUs.
We used survival analysis and case studies to determine important conditions underlying GNU
dissolution. Our two outcomes of interest were dissolution without conflict and dissolution with
conflict. We analyzed variation in all GNUs formed from 1975 through 2012, incorporating
measures of heterogeneity, conflict and agreement characteristics, institutional strength,
international involvement, and economic development. Our report examined three case studies—
Yemen, Sudan, and Tajikistan—to clarify the' pathways linking our independent variables with
GNU durability.
Our survival model tested the impact of a variety of contextual characteristics and government
outputs on the likelihood a GNU would dissolve with or without conflict. We found that the type
of conflict preceding the formation of a GNU, the level of fractionalization in the country, the
levels of economic growth, and the institutional strength of a GNU significantly influence the
type of dissolution. A GNU emerging from a preceding conflict that was ideologically motivated
was more likely to dissolve peacefully. Economic growth increased the likelihood a GNU would
dissolve without conflict. Finally, our measure of institutional strength—rule of law—had a large
and positive effect on peaceful dissolution. Our qualitative analysis documented and analyzed
the importance of multi-dimensional power-sharing, including political, economic, military and
territorial power-sharing provisions. It also identified the importance of agreement inclusivity
and implementation—two characteristics that we cannot model quantitatively. With these two
points, we expect agreements that are more fully implemented and do not exclude a major party
will support peaceful transition to more permanent forms of government.
Our findings suggest the U.S. government can play an important role in promoting stability
through GNUs. Regional and international actors have been vital to bringing parties together in
negotiations, facilitating the formation of power-sharing agreements, and supporting the
responsibilities of GNUs. These governments represent an important subset of coalition
governments created during difficult transitional phases in those countries’ histories. The
governments formed through these power-sharing agreements are tenuous and prone to
instability. GNUs have a unique ability to unify past aggressors in a common vision for the
future, and to usher in a new era of peace and stability.
vii
Introduction
Governments of national unity (GNUs) are negotiated, formalized power-sharing agreements
among opposing parties or elites. They include provisions for power-sharing in political,
economic, territorial, and military affairs. GNUs are a subset of coalition governments that form
specifically to end or forestall violence. They are considered temporary or transitional, made in
preparation for elections, the ratification of a new constitution or amendments, or the design and
implementation of new governance institutions. The difficulty of the circumstances under which
GNUs arise (i.e., conflict, political instability, or the credible threat of either), the nature of the
agreements themselves, and the broader sociopolitical and economic context in which they exist
affect their stability.
Research on how GNUs dissolve has extensively employed qualitative case study methodology
to explore and predict the presence and magnitude of factors such as agreement characteristics,
contextual factors, and government output on whether GNUs dissolve into conflict or into more
stable, permanent forms of governance. The diversity of scholarly approaches and varying
emphasis on predictive variables prevents any robust cross-national understanding of GNU
functioning. While the qualitative approach can be instructive, a quantitative study offers a more
generalizable, global picture.
Our objective is to identify variables that impact GNU dissolution, quantify the magnitude, and
then uses three case studies to further characterize how these variables manifest.
To that end, this report:
• synthesizes and analyzes literature relevant to GNUs to understand the contextual
characteristics, agreement power-sharing provisions, and government output attributes
that impact dissolution;
• specifies and estimates a statistical model to determine the magnitude of attribute effects
on dissolution;
• uses case study methodology to further characterize the agreement and implementation
attributes contributing to the dissolution of a GNU; and
• highlights and evaluates policies that the U.S. government might employ to bolster the
stability and peaceful dissolution of a GNU.
Our quantitative analysis of GNUs indicates that the type of conflict preceding the GNU, the
level of fractionalization in the population, economic growth and institutional strength affect the
likelihood a GNU dissolves with or without conflict. Our case studies qualitatively describe how
agreement characteristics and exclusion of major parties in GNU formation and governance
affects how GNUs dissolve. We recommend incorporating this analysis into risk analysis and
other available assessment tools to develop responsive and appropriate policy.
Section I of this report establishes the theoretical background for our analysis. Section II outlines
our data, methodology, and limitations. Section III reports our quantitative results, and Section
IV discusses implications. Section V develops a case selection methodology, identifies three
cases of GNUs, and highlights relevant attributes and outcomes. Section VI discusses the
implications of this study and evaluates policies to enhance the likelihood GNUs dissolve
peacefully.
1
Literature Review
In this project we develop a framework for understanding GNUs and factors contributing to their
peaceful dissolution or their dissolution with conflict. GNUs are negotiated, formal settlements
among opposing parties, groups, or elites that include one or more political, military, economic,
and territorial power-sharing provisions. They are implemented to end or forestall violence, and
are thus temporary in nature. If arrangements succeed, the key outputs are political stability,
more permanent forms of governance, and the absence of conflict. Scholarship related to postconflict power-sharing, post-conflict development, and regime stability is most informative in
identifying relevant factors that enhance durability of these settlements.
This research area lacks clear conclusions for two reasons. First, case studies compose a
substantial portion of GNU research. This methodology identifies the mechanisms of a unique
instance of a unity government, but it is not necessarily generalizable to a larger sample of
GNUs. Second, relevant quantitative analyses produce contradictory conclusions. Researchers
commonly disagree over which factors influence how a GNU dissolves; even when they agree on
variables, their conclusions are often contradictory. Still, the literature coalesces around two
categories of influences: context of the conflict and end-of-conflict agreement, and government
output.
Contextual Factors
We identify three categories of contextual factors: social heterogeneity, the conflict that preceded
the unity government agreement, and the agreement itself.
Social Heterogeneity
While experts frequently explain the link between a society’s heterogeneity and level of political
stability as a positive linear relationship (i.e., greater heterogeneity leads to greater instability),
quantitative analyses have clarified the underlying mechanisms of this relationship.
In comparative politics, heterogeneity describes three subsets of socio-cultural cleavages:
interest-based, ideology-based, and identity-based cleavages (Weiffen and Merkel 2012).
Researchers commonly use two conceptions of heterogeneity to quantify and measure it. The
first, fractionalization, is the most widespread in the literature. Fractionalization increases
linearly with the number of groups; it generally incorporates ethnic, linguistic, and religious
heterogeneity measures in its calculation. The second measure of heterogeneity is polarization.
Esteban and Schneider (2008) describe polarization as the “extent to which the population is
clustered around a small number of distant poles” (Esteban and Schneider 2008, 133). Holding
the distance between groups constant, polarization is maximized in instances with two equally
powerful groups (Alesina et al. 2003, 177). Thus, a single society may lie at opposite ends of
each conceptualization, simultaneously rating low on fractionalization and high on polarization
(or vice versa).
Regardless of conceptualization, peace and stability literature recognizes heterogeneity as an
important determinant of domestic conflict (Ellingsen 2000, 244). Many assume that the linkage
is a simple positive linear relationship: Greater heterogeneity means a higher likelihood of
political instability. However, most quantitative research does not substantiate this claim. Rather,
2
experts find that the relationship is best characterized as an inverted-U curve (Ellingsen 2000). In
other words, as Ellingsen explains, the presence of a few large groups is associated with a higher
risk of conflict, whereas highly diverse and highly homogeneous states face a lower risk of
conflict (Esteban and Schneider 2008, 136). In Ellingsen’s (2000) analysis, conflict results from
a simultaneous identification with one’s own group and a distancing from competing groups.
Taking their analysis a step further, Wieffen and Merkel (2012) argue that heterogeneity does not
inherently lead to cleavages in society (Weiffen and Merkel 2012). For cleavages to occur,
political actors must transform identities into cleavages through politicization, mobilization, and
organization. Their research concludes that heterogeneity harms democratic transition and
consolidation only in cases where identity-based cleavages are politicized and escalated into
violent conflict.
Conflict Characterization
GNUs are created to end an existing conflict or forestall an imminent conflict. Researchers agree
that certain characteristics of the conflict that precedes establishment of a GNU help predict the
stability of post-conflict peace. Indeed, almost all studies include measures of the following
variables: conflict intensity, conflict duration, conflict motivation, and how the conflict ended.
Researchers typically measure conflict intensity by the number of conflict-related deaths
(Binningsbø 2006; Fortna 2004; C. Hartzell and Hoddie 2003; Jarstad and Nilsson 2008; Mattes
and Savun 2009; Werner 1999). Some researchers transform this statistic, using a rate such as
deaths per month or deaths per year throughout the conflict (C. Hartzell, Hoddie, and Rothchild
2001). The two most commonly used conflict datasets—Correlates of War and the Armed
Conflict Dataset—assign values to conflicts based on the level of deaths (e.g., greater than 1000
conflict-related deaths means that the conflict can be classified as a civil war) (Collier, Hoeffler,
and Söderbom 2008). Studies almost unanimously find that the more intense a conflict—that is,
the more conflict-related deaths sustained—the more likely a country will revert to conflict
(Binningsbø 2006; Fortna 2004; C. Hartzell and Hoddie 2003; Jarstad and Nilsson 2008; Mattes
and Savun 2009; Werner 1999). Researchers contend that high casualties create high levels of
distrust and ill-will among parties, which can undermine the stability of any future agreement (C.
A. Hartzell and Hoddie 2007). Thus, undermining the stability would likely also reduce the
likelihood that a GNU would dissolve without conflict.
The second commonly used conflict characterization variable is conflict length (Binningsbø
2006, 2013; Fortna 2004). Most researchers find that the longer the conflict, the more intractable
the disagreement, and therefore the less likely peace will endure.
Researchers also commonly characterize conflicts by type—economic, identity, ideological.
Research shows that power-sharing agreements following an identity conflict are less likely to
last than if the conflict was motivated by other factors, such as economic or distributional
concerns (Collier, Hoeffler, and Söderbom 2008; C. Hartzell and Hoddie 2003). As outlined in
the preceding section, other research has found identity conflicts are “particularly intractable”
and thus are more likely to resume regardless of the strength of the power-sharing agreement
(Kaufmann 2007).
Finally, many researchers find the nature of a conflict’s end is predictive of the subsequent peace
duration (Binningsbø 2006; Binningsbø 2013; Fortna 2004; Mukherjee 2006). If an intrastate
3
conflict ends in decisive victory rather than stalemate, the likelihood of a return to conflict
decreases anywhere from 70 percent to 90 percent (Fortna 2004). Other research goes further,
offering specific peace durations. This research estimates that power sharing agreements
maintain peace for an average of 117 months in cases where the existing government is
victorious, an average of 88 months if the conflict results in an insurgency victory, and an
average of 19 months in cases of stalemate (Mukherjee 2006). An extreme version of this
scholarship argues that the international community should not intervene in intrastate conflicts,
as a definitive internal military victory will lead to a longer-lasting peace (Toft 2006).
Agreement Characterization
Many researchers focus their attention on which provisions of power-sharing agreements
contribute most to the durability of peace.
Researchers often distinguish between different kinds of power sharing: economic, military,
territorial, and political (C. Hartzell and Hoddie 2003; Jarstad and Nilsson 2008; Fortna 2003).
Research differs, however, on the implications of the distinction. Some researchers attribute a
larger effect to some forms of power-sharing than to others. Fortna (2003), for example, finds
that more “costly” forms of power-sharing—such as territorial and military power sharing—
represent a significant sacrifice and therefore indicate a larger commitment, which is positively
related to the durability of peace (Fortna 2003). Elsewhere, Mattes and Savun (2009) find that
only political power sharing is significantly linked to the durability of peace. On the other hand,
some researchers weigh all kinds of power sharing equally (Mattes and Savun 2009). For
example, Hartzell et al. (2001) create a continuous variable between 0 and 4 that captures a total
measure of power sharing. In defending their equal weighting, they argue that the various
incarnations of power sharing are mutually reinforcing; therefore, simply creating a single,
inclusive measure is appropriate (Hartzell, Hoddie, and Rothchild 2001). They find that the more
areas (political, economic, military, and territorial) in which power sharing is instituted, the
longer peace can be expected to last. However, other research directly contradicts this finding
(Jarstad and Nilsson 2008).
Government Output
While the power-sharing literature tends to focus on the contextual factors iterated above, the
regime stability and post-conflict development literature highlights the importance of
government output on the type of dissolution (i.e., with or without conflict). In particular, this
literature finds that a government’s ability to provide public goods—like security, health
infrastructure, rule of law—increases the likelihood of a lasting peace in post-conflict societies.
Indeed, some literature finds that significant public goods investment can strengthen a regime’s
stability by up to 50 percent compared to no investment (Bell 2011).
The category of significant public goods investment offers much more opportunity for policy
makers to assert influence. While characteristics like a society’s heterogeneity cannot be altered,
a government’s policy can be influenced. Therefore, the literature we review is policy-directed
and seeks to determine which government outputs are most associated with a lasting peace.
4
Economic Development
The issues of two-way causality between security and economic growth are problematic for
researchers and policy makers. However, the fact that economic growth leads to a reduction in
the risk of return to conflict is well established. As Collier et al. (2008) summarize, “growth
itself matters”: faster economic growth “directly and significantly reduces” the risk of a return to
conflict (Collier, Hoeffler, and Söderbom 2008). However, the first logical connection—that
investments in security, institutions, and infrastructure lead to economic development and not
vice versa—is difficult to establish. Researchers must keep this two-way causality in mind when
investigating possible policy prescriptions.
International Involvement
Post-conflict states are mostly underdeveloped: Data show that the average post-conflict state
ranks 2.41 on the World Bank’s five-point development scale, far below the Bank’s threshold for
self-sustaining economic development (Collier, Hoeffler, and Söderbom 2008). Thus, postconflict states receive huge amounts of aid in the form of development or peacekeepers. In 2006,
for example, the United States gave more than $26 billion in global Official Development
Assistance to fragile states—states in danger of falling into conflict or were in a post-conflict
stage (Kruk et al. 2010). The literature agrees that post-conflict societies can do more with aid
than other developing countries; in the parlance of the literature, these societies’ absorptive
capacity is “supranormal” (Collier and Hoeffler 2004; Mattes and Savun 2009; Anand 2005).
While all aid experts agree that an informed and highly tailored aid package is necessary in all
contexts, recent scholarship attempts to create general rules about where aid should be directed
(Anand 2005; Kruk et al. 2010).
Peacekeepers are often sent to post-conflict societies when the conflict does not end with a
decisive victor (Fortna 2004). In general, across the many dimensions of “peacekeeping”—
observers, traditional, multi-dimensional—the literature finds that peacekeeping troops are
associated with a reduced risk of a return to conflict (Collier, Hoeffler, and Söderbom 2008;
Fortna 2004; Doyle and Sambanis 2006). While studies agree on the general conclusion, many
argue that peacekeeping operations could benefit from a “recalibration” to improve methods
(Williams 2013).
Researchers also investigate the relationship between third-party enforcers of power-sharing
agreements and the length of peace. The bulk of this research finds that a third-party enforcer
increases the likelihood the GNU will dissolve without conflict, or rather a free and fair election
will occur or a new constitution ratified (C. Hartzell and Hoddie 2003; Mattes and Savun 2009).
Some research, however, directly rejects this finding (Mukherjee 2006). Meanwhile, some
researchers have found that if a third party plays an important role in conflict termination, it is
more likely that one of the parties will believe the subsequent agreement is unfair. Therefore, the
agreement is less likely to last (Werner and Yuen 2005).
Institutional Strength
Institutions are critical in creating the basis for a peaceful society, especially in post-conflict
states. Nation building “templates,” however, are often criticized for containing Western
normative elements, establishing illegitimate or inappropriate institutions (Philp 2009).
Researchers argue that a country’s governance—and thus its formal institutions—must be rooted
in its own normative values (Fukuyama 2010).
5
While endorsements of certain institution-strengthening measures must always be informed and
tailored to a specific society, research finds that institutional characteristics and institutional
efficacy measures such as political inclusion and representation, government accountability, and
rule of law implementation can all increase stability (Eizenstat, Porter, and Weinstein 2010; Le
Van 2011; Fukuyama 2010). This support has positive and prescriptive implications: The
strength of institutions affects whether a GNU dissolution is peaceful or violent; from a policy
perspective, strengthening these institutions is a good investment for stability.
Researchers are also careful to highlight the difference between among (e.g., electoral rules, rule
of law) and informal (e.g., tribal patronage) institutions. Although the implications of either are
difficult to measure in an advanced economy, both forms can be devastating to peace
agreements; indeed, LeVan (2011) describes how this discrepancy contributed to the failure of
coalition governments in Burundi and Rwanda (LeVan 2011).
Security
Unsurprisingly, experts believe increased security helps a country avoid a return to conflict
(Collier, Hoeffler, and Söderbom 2008; Bryden 2013). Of course, the term “security” is very
broad—definitions can range from holding confidence in the government’s ability to ensure
individual property rights to feeling safe when walking to the market. In a post-conflict society,
virtually every definition is applicable. Citizens in these situations are insecure by definition, as
the peace in post-conflict societies is precarious: previously warring parties, organized crime,
and ethnic unrest still pervade, as do the stores of weapons collected throughout hostilities
(Bryden 2013; Collier, Hoeffler, and Söderbom 2008).
Therefore, experts believe that ensuring security in post-conflict societies lies at the “very heart”
of peace building (Bryden 2013). The reasoning is simple enough: If citizens do not need to fear
simply going to the market and carry out other everyday tasks, they can begin to re-establish
their lives and livelihoods. Once livelihoods are re-established, societies can begin a process of
economic development, which, experts agree, helps to maintain peace.
The literature does not agree upon a single way to ensure post-conflict security but rather cites its
general importance. Security offers “confidence” to an economy and therefore allows it to grow,
something which, as expanded on below, is perhaps the most helpful factor in reducing the risk
of conflict reversion (Collier, Hoeffler, and Söderbom 2008).
Infrastructure
There is considerable debate on the most effective allocation of the large amounts of aid flowing
into post-conflict societies. Aid projects to create, rebuild, or support infrastructure have received
great attention by academics studying post-conflict peace (Anand 2005; Haggard and Tiede
2014; Kruk et al. 2010). However, like “security,” “infrastructure” is an extremely broad term
and can mean anything from road mileage per capita to smartphone penetration. Always
cognizant of the implications of aid allocation, the literature attempts to identify specific areas of
infrastructure that, if improved, can help to reduce the risk of reverting to conflict. In other
words, the literature seeks to identify where infrastructure-related aid in post-conflict societies
contributes to greater stability.
6
The first of these areas is healthcare infrastructure, on which, Kruk et al. (2010) note, conflict is
especially hard. During conflict, healthcare infrastructure not only undergoes a loss of physical
capital via the destruction of hospitals, loss of pharmaceuticals, and so forth, but also a loss of
human capital, as many healthcare professionals flee. As a result, at the end of conflict, states
often lack the most basic healthcare necessities. International aid has done a good job of
addressing such emergencies in the short term, but the rebuilding of a more robust healthcare
infrastructure is often lacking. Some experts believe healthcare investments would be “a
promising development opportunity” and thus extremely helpful in reducing the risk of a return
to conflict (Kruk et al. 2010).
Other experts stress the importance of installing a rule of law infrastructure in post-conflict
societies (Fukuyama 2010; Haggard and Tiede 2014). While the logic of this strain of
scholarship is sound, establishing a comprehensive set of laws and carrying out consequences for
violations is difficult to accomplish in practice. As Fukuyama (2010) notes, establishment of a
rule of law infrastructure is extremely costly because, similar to the healthcare industry, it
requires human and physical capital. Additionally, rule of law is not something that can be
transferred from country to country using a template: as Fukuyama (2010) stresses, it must be
thoughtfully implemented, taking into account the post-conflict country’s underlying values.
These values can be drastically different from country to country and even between ethnic
groups within a country. However, progress on this strain of research is advancing. Binningsbø
et al.’s (2012) armed conflict and post-conflict justice dataset affords researchers a meaningful
opportunity to analyze these issues.
Still other experts stress the importance of more traditional conceptions of infrastructure like
roads and bridges (Anand 2005). This strain of scholarship believes that roads and bridges make
governance more efficient, and, in some cases, simply possible. Perhaps more importantly,
significant public goods investment also aids a country’s economic development, as it drastically
reduces transportation costs.
7
Survival Model and Methods
GNU Selection and Dating
We used a strict protocol to identify the start and end dates for each GNU. To determine the start
date, we used negotiated settlement databases to locate the signing of an official agreement. If
we could not find an agreement, we looked for a date when the GNU was internationally
recognized. Failing data availability, we simply used the end of the conflict that preceded GNU
formation. We used archival data to ascertain the date of GNU dissolution, which occurred with
an election, ratification of a new constitution, return to large-scale conflict, or a secondary
settlement setting up further transitional processes. We categorized four outcomes: dissolution
without conflict, dissolution with conflict, transitional agreement for governance, or right
censored (still in existence at the end of 2012).1
We included in our analysis GNUs present from 1975 through 2012 because this period has the
most complete data. Our period of observation also allows us to control for the structure of the
international system that has remained relatively constant since World War II. For many GNUs,
exact dates were difficult to locate and contested, but years were widely agreed upon. Most
variables of theoretical interest are only measured annually. Other studies on peace and stability
in post-conflict countries employ year estimates. This fact supported our decision to use years as
our interval unit. A complete list of GNUs included in this analysis can be found in Appendix A.
Governments of National Unity 1975-2012.
We analyze our GNU dataset to analyze the amount of time between GNU emergence and
dissolution, as well as whether dissolution occurs with or without conflict. Additionally, survival
analysis allows us to identify which factors significantly contribute to dissolution with conflict or
dissolution without conflict.
Data Description
Ninety GNUs existed from 1975 through 2012, representing 311 yearly observations. Summary
statistics for GNUs in our dataset are included in Table 1. We code success as GNUs that
dissolved without conflict (further discussed below) and failure as GNUs that dissolved with
conflict. In our data, 33 GNUs are coded as failures, meaning they dissolved into conflict and
were not replaced immediately by elections and a formal central government or by another
transitional governance agreement.
1
Some GNU observations did not neatly fit these outcomes. Some GNUs were established, dissolved into conflict,
and then were re-established. In these instances, when the conflict lasted less than a year and the GNU agreement
8
Table 1. Data Description
Category
Total
Number of GNUs Observed
90
Years of GNU Existence
311
Median Length of GNUs (Years)
2
Dependent Variable: Dissolution
The dependent or outcome variable in this analysis is GNU “dissolution.” We are interested in
two types of dissolution: dissolution with conflict (failure) and dissolution without conflict
(success). A success outcome includes transition without conflict to a more permanent form of
government, and is observed through peaceful elections, ratification of a new constitution, and
the absence of conflict. We define success this way because focusing on this outcome
distinction—rather than GNU lifespan—allows us to assess which GNUs failed, when they
failed, and why they failed. This method permits a more compelling analysis and lends itself
more to robust policy recommendations.
Additionally, we observed two other outcomes: transition agreements and right censored (or
ongoing as of 2012). These outcomes highlight important considerations about the interpretation
of time in existence of GNUs. Given the transitional or temporary nature of GNUs, longer GNUs
are not necessarily better GNUs, nor do longer GNUs ensure successful transition (i.e., transition
without conflict).
We did not assume that the longer a GNU exists the better it is performing. GNUs are temporary
or transitional by design; therefore a longer-lasting a GNU could indicate an inability to establish
more permanent forms of governance. Therefore, we sought to identify an inflection point in
GNU years in existence after which a GNU becomes more likely to dissolve peacefully.
Additionally, we tested which attributes of the GNU or contextual characteristics make
dissolution with peace more likely.
We observed 90 GNUs for a total of 311 years in existence (known in survival analysis as time at
risk). Figure 1 shows the subjects (countries) and time at risk for each outcome.
9
Figure 1. Dissolution Outcomes
Notes: Subjects are instances of GNUs (one country may have multiple instances of GNUs within the observation time period).
Time at risk is measured in years.
Dissolution
Outcome 1: With Conflict Subjects = 30 Time at Risk = 105
Outcome 2: Without Conflict Subjects = 34 Time at Risk = 140
Outcome 3: Transition Agreement Subjects = 17 Time at Risk = 47
Outcome 4: Right-Censored Subjects = 10 Time at Risk = 69
Independent Variables
When choosing variables to include in our quantitative analysis, we relied on the information
gleaned from our literature review. As such, our independent variables fall into two categories:
contextual characteristics (which include agreement characteristics) and government output.
Table 2 lists the variables, measures, and hypothesized relationship.2
Table 2. Predicted Relationship between Covariates and the Hazard Rate of Failure
Expected Effect
on Success
Expected Effect
on Failure
Fractionalization Score (percentage)
-
+
Intensity (Score 1 to 4 – 4 being most intense)
-
+
Duration (in years)
-
+
Type (political or ideological)
-a
+
Ending (stalemate or decisive victory)
-b
+
Gross Domestic Product (GDP) Growth Rate
+
-
GDP per Capita ( in 2014 US Dollars)
+
-
Agreement Characteristics
Number of Power-Sharing Provisions
+
-
Third-Party Involvement
Presence of Peacekeepers, Aid, and
Development, or Third-Party Facilitation or
Signer of Negotiated Settlement
+
-
Institutional Strength
Rule of Law Strength
+
-
Variable
Measure
Heterogeneity & Population Characteristics
Preceding Conflict Characteristics
Economic Development
Notes: Ideological conflict is expected to have a negative effect, political conflict is expected to have a less negative or no effect; stalemate is
expected to have a negative effect, decisive victory is expected to have no effect or a positive effect.
2
Sources for the dataset are available in the report’s companion dataset and codebook.
10
Limitations
Data availability was a severe challenge for our analysis, and three occurrences of this limitation
were particularly noteworthy. First, our literature review indicated a significant—if
complicated—relationship between the level of corruption and government stability within a
country, but we had no reliable measures to analyze that effect. Therefore, we did not include it
in our model. Second, we could not find reliable covariate data for GNUs in Rhodesia, Palestine,
Serbia, Zanzibar, and Northern Ireland; consequently, we dropped these observations from our
dataset. Finally, the measurement frequency of our variables of theoretical interest required that
we measure the start and end dates of GNUs by year, not by exact dates. We thus potentially
introduce bias to the estimated survival time of each GNU.
Statistical Model
Survival analysis examines the time to dissolution for GNUs included in our study. Survival
analysis predicts, at varying time points, the likelihood of dissolution of a GNU. Additionally,
survival analysis predicts the size of effect and tests the statistical significance of the effect of
each individual covariate on the rate of dissolution. We stratify these results to predict the effect
each covariate has on dissolution without conflict and then dissolution with conflict. Sometimes
our observations shared identical values for a variable. We used stratification in our model to
compensate for repeated values, marking observations with the same values to be included in the
same stratum. This method enables us to develop hazard estimates for each grouping, as opposed
to counting each converging value as a different associative effect with each observation. In
other words, survival analysis tells us which independent variables (e.g., institutional strength,
international involvement, heterogeneity) have the largest impact on dissolution type and how
the likelihood of failure for GNUs changes over time.
Survival Analysis: Cox Proportional Hazards Model
Our basic model predicts when a failure outcome (i.e., dissolution with conflict) will occur and
what factors contribute to failure. Our second model (discussed below) analyzes the likelihood
we observe dissolution without conflict, or success. To determine the failure rate for GNUs, we
construct a survivor function that displays the length of time a GNU lasts before a failure event.
We then provide a framework to predict the likelihood of failure at a given time point for GNUs.
Appendix B. Technical Explanations provides more information on Cox Proportional Hazard
Models.
We use a semi-parametric Cox model to formulate our survival function. Survival analysis
researchers use the Cox model because of its flexibility: unlike other methods of survival
analysis, the Cox model requires less strict assumptions about the shape of the hazard function
and instead allows the data to determine the shape.
Survival Analysis: Kaplan-Meier Estimator
We use Kaplan-Meier estimators to estimate the survival function for GNUs. Kaplan-Meier
estimators measure the probability that a GNU fails after a number of years and the probability
of failing after a particular point in time. The downward sloping, step share of the Kaplan-Meier
estimator represents GNUs failing over time, and the probability of failure for all GNUs still in
existence at each point of time observed. These graphs consider a failure event to be dissolution
with conflict in Model 1, and dissolution with peace in Model 2.
11
Survival Model Results
Model 1: Dissolution with Conflict
The outcome of interest in our first model was dissolution with conflict, which we defined as
failure. Survival analysis first matches GNUs that have the data for our measures of interest to
estimate the shape of the survival function for GNUs that dissolve into conflict. Forty-four
GNUs had sufficient data to create the shape of the hazard function over time and estimate the
effect of the measures on the risk of failure. Of those 44 GNUs, 14 substantiate failures, meaning
they dissolved into conflict. The 44 GNUs lasted a cumulative 137 years from 1975 through
2012. This process provided our estimate of the hazard ratio, which represented the estimated
risk of a failure event for a single GNU at a given time, relative to the rest of the sample, given
that all other measures in the model were held constant. While other methods of reporting are
possible in survival analysis, we chose to report hazard ratios because their values had a
substantial, yet easy-to-understand interpretation: The hazard ratio’s effect on the probability that
a GNU will experience a failure event at a given point in time is 100(Hazard Rate – 1), holding
all else constant. Therefore, positive coefficients indicate an increase in the probability of a
failure event, while negative coefficients indicate a decrease in the probability of a failure event
at a given point in time. Our null hypothesis held that our covariates had no effect on the survival
of GNUs; our alternative hypothesis was a measurable effect. Table 3 displays the estimated
hazard ratios, standard errors, and p-values for the measures in our survival analysis.
Table 3. Model 1 Dissolution with Conflict Results
Variables
Population
Heterogeneity
Measures
Hazard Ratio
P-Value
Fractionalization
1.84
(1.13)
0.31
Number of Power-Sharing Types
1.25
(0.62)
0.65
Presence of Third-Party Enforcer
0.89
(0.68)
0.89
Duration
0.95
(0.07)
0.53
Outcome: Decisive Victory
0.96
(.71)
0.96
Type: Ideological
0.22
(0.18)
0.10
GDP per Capita
0.99
(9.6 x 10-5)
0.17
GDP Growth
1.01
(0.08)
0.90
Rule of Law
12.68
(11.23)
0.004
GNU Agreement
Preceding Conflict
Economic
Development
Institutions
1.62
0.66
(1.65)
Notes: Robust standard errors are reported in parentheses under the hazard ratio.
Log pseudo-likelihood is -23, and the probability we observe values greater than chi-squared is 0.03.
Control
Conflict
We chose to evaluate statistical significance at the 0.05 and 0.1 level. We are less confident in
the nature of the relationship between the covariates in our model and the failure event at the 0.1
level, given the limitations in our sample size and available measures. Results that are significant
12
at the 0.05 level or lower are more likely to indicate a relationship between the covariates and the
failure event.
Hazard ratios are reported in the table above, as they have a more substantive interpretation.
Coefficients for the model report the direction of the relationship between our independent
variables of interest and our dependent variable. However, coefficients do not have a literal
interpretation. This finding was evident especially for our rule of law variable, which itself is an
index that attempts to quantify an already latent measure. We therefore felt hazard ratios better
reflected increases in hazard, as well as indicated the direction of the relationship between
dependent and independent variables. Finally, the variables in our model were also sufficient to
provide control measures that were specified in the literature. See Appendix C. Model
Specifications and Results for a table containing coefficients for each of the models presented in
this paper.
Using the characterization outlined in our literature review, we divided covariates into contextual
characteristics and government output. Only one of the contextual characteristics was significant
in this model at the 0.1 significance level. The risk that a GNU dissolves into conflict when there
is ideological conflict immediately preceding the formation of the government, is 0.22 times
lower than when GNUs are formed following a non-ideological conflict such as political,
economic, or territorial conflicts, holding all else constant.
One “government output” variable was statistically significant. Because the ratio for rule of law
is greater than 1, it indicates that rule of law contributes positively to the rate of failure of GNUs,
an unexpected result. However, when contextualized, this finding was not puzzling. To measure
rule of law we used an index ranging from -2.5 to 2.5. The range represented in our sample, is
from -2.22 to 0.16, with a mean value of -1.08.3 Therefore, in this analysis, an increase in rule of
law’s coefficient actually reflected a decrease in the rule of law score. Given this appropriately
contextualized understanding, we found that, holding all else constant, for every additional point
decrease in the strength of rule of law index, GNUs were about 12.68 times more likely to
dissolve into conflict.
Below we included two figures to aid in understanding the relationship between time and GNU
dissolution with conflict. As is standard in survival analysis, we used the Kaplan-Meier
Cumulative Hazard Estimator to display this relationship. Figure 2 shows the Kaplan-Meier
estimator for all GNUs in this model. The proportional hazard for surviving remained uniform
between events in the estimator, and the curve estimated the survival over time for GNUs before
dissolution. In other words, this graph shows the amount of time that a GNU survived, and, in
each year, the proportion of those GNUs that we expected to dissolve with conflict. Figure 3
elucidates the importance of rule of law; this Kaplan-Meier estimator was broken out to display
the difference in proportional hazard between a median rule of law level and a zero rule of law
level, holding other measures in the model constant.
3
We expected a negative mean value for the rule of law scores represented in our sample. Most GNUs are
established after or during conflict, which affects the capacity and effectiveness of legal institutions. Furthermore,
several GNUs were in developing or least-developed countries, which are generally characterized by weak
institutions and poor rule of law.
13
Figure 2. Kaplan-Meier Survival Distribution Function: Dissolution with Conflict Model
Figure 3. Smoothed Hazard Function, by Median Rule of Law
As shown in Figure 2, the cumulative probability that a GNU will dissolve into conflict increased
each year. Here the vertical axis represents the proportion of GNUs in the sample: as time goes
on (and we move right along the horizontal axis), we witnessed more GNU failures. If every
GNU in this analysis ended during or before 2012, the curve would intersect the horizontal axis
at 18 years (the duration of our longest GNU, Bosnia). However, intersection at the horizontal
axis does not occur because GNUs that were continued past 2012 (i.e., right censored). Figure 3
illustrates the effect of rule of law on the failure of GNUs. As evidenced by the graph’s limited
horizontal breadth, GNUs evaluated based on rule of law data were not likely to survive past five
years. Additionally, the distance between those GNUs with the lowest rule of law levels (the
upper line) and those with a median score (the lower line) showed that a difference in rule of law
level meant rule of law had a significant effect on the hazard rate experienced by GNUs. While
the distance between the lines indicated a difference in the relative risk of failure of a GNU
during each year it exists, the measured distance between GNUs that have a median rule of law
14
and those with the lowest rule of law scores was not a statistically valid measure of the
difference in failure rates.
Model 2: Dissolution without Conflict
Our outcome of interest in Model 2 was dissolution without conflict, that is, a peaceful transition
from the GNU into elections or some formal, permanent central government. Because we used
the same measures in this model as in Model 1, survival analysis performed a “pairing” process
that produced a sample size of 44 GNUs. Fourteen GNUs result in our outcome of interest.4 Our
null hypothesis was that our variables had no effect on peaceful dissolution of a GNU. We used
the same variables in this model as in Model 1 to estimate effects on dissolution without conflict.
Table 4 shows the estimated hazard ratio for each of our measures on GNU success.
Table 4. Model 2 Dissolution with Peace Results
Variables
Measures
Population Heterogeneity
Fractionalization
GNU Agreement
Number of Power-Sharing Types in Agreement
Presence of Third-Party Enforcer
Preceding Conflict
Duration
Outcome: Decisive Victory
Type: Ideological
Economic Development
GDP per Capita
GDP Growth
Institutions
Rule of Law
Control
Conflict
Hazard Ratio
0.27
(0.11)
0.93
(0.45)
1.28
(0.86)
1.09
(0.07)
1.47
(1.02)
4.05
(2.43)
0.99
(4.7 x 10-5)
1.03
(0.01)
0.79
(0.57)
0.65
(0.36)
P-Value
0.001
0.89
0.71
0.21
0.57
0.02
0.16
0.01
0.74
0.44
Notes: Robust standard errors are reported in parentheses under the hazard ratio.
The log pseudo-likelihood is -21.07, and the probability that we observe values greater than chi-squared is 0.02.
Our results indicate that fractionalization, ideological conflict, and GDP growth are statistically
significant at the 0.05 level.5 Within this model, the contextual characteristics of fractionalization
and ideological conflict were statistically significant at the 0.01 and 0.05 levels, respectively.
Our government output measure of GDP growth was also statistically significant at the 0.05
level.
4
With more complete data, the sample of GNUs used to estimate the baseline hazard rate in each model likely
would increase. Better data would improve the specificity of our analysis, as well as expand the time period that
could be analyzed, improving the capacity to project expected results and develop future models to predict the
behavior of GNUs before they have been established.
5
The proportionality test analyzing the explanatory power of the measures included in both Model 1 and Model 2
can be found in Appendix C.
15
Holding all else constant, each additional increase in the level of ethnic, linguistic, and religious
fractionalization within a GNU decreased the likelihood that it dissolved peacefully and
transitioned to a permanent central government. For each additional increase in the level of
fractionalization, a GNU was 0.27 times less likely to dissolve peacefully. This result meant that
GNUs whose populations had extreme levels of heterogeneity were less likely to succeed. Further results indicate that if the conflict preceding GNU formation was ideological in nature, the GNU was 4.05 times more likely to dissolve peacefully, holding all else constant. This
supports the results found in Model 1, that ideological conflict decreases the risk that a GNU will
dissolve into conflict if formed following ideological conflict.
Our final significant variable was GDP growth, a measure of government output. The third
variable that is statistically significant is GDP growth. For each additional percentage point of
yearly GDP growth, a GNU was 1.03 times more likely to dissolve peacefully. Figure 4 is the Kaplan-Meier estimator for Model 2. The estimated line in Figure 4 climbs at a
slower rate than that in Figure 2. This finding indicates that there is less of a change in the risk of
dissolution with peace across time than there is in the risk of dissolution with conflict across
time. That is, the longer a GNU lasts, its risk of dissolution with conflict increases more than its
risk of peaceful dissolution. The curve represents the relative risk of a GNU dissolving into
peace at a given year during its existence.
Figure 4. Kaplan-Meier Survival Distribution Function: Dissolution without Conflict Model
Figure 5 is the Kaplan-Meier estimator for GNUs analyzed in the success model, stratified by
whether the GNU experienced ideological conflict before it was established. Figure 5 shows
when a GNU experienced a preceding conflict that was ideologically driven, it was more likely
to dissolve peacefully than when the preceding conflict was not ideologically driven, (i.e., the
conflict was economically motivated).
16
Figure 5. Smoothed Hazard Function, by Ideological Conflict
17
Discussion of Survival Analysis Results
Our models provided new and substantive evidence to the nascent body of literature on GNUs.
This evidence helped explain variation in GNU dissolution during the 1975-2012 period, and can
hold possible explanatory power for analyzing future GNUs.
As outlined in our literature review, we were interested in two families of variables of
explanation: contextual factors—those that inform the establishment of a GNU—and
government output factors—those that can affect a GNU after it has been established. Our
quantitative analysis found that two contextual factors and two government output factors
significantly impacted GNU dissolution.
Contextual Factors
Our results indicate that a GNU’s likelihood of peaceful dissolution increased when an
ideological conflict—rather than another sort of conflict—preceded the establishment of a GNU.
This finding surprised us. As cited in our literature review, experts believe that identity and
ideological conflicts are particularly intractable, and therefore will likely lead to renewed conflict
if a GNU or other power-sharing agreement is signed.
Additionally, although ideological conflict was not significant in the first model at the .05
threshold, it is approaching significance at the .01 level. Thus, it is possible that further research
and modeling with more nuanced survival analysis model would improve the estimates of the
relationship between ideological conflict and GNU dissolution. While this result is not definitive,
it does indicate that ideological conflict preceding the establishment of a GNU decreases the risk
that a GNU will fail.
Our quantitative finding that ideological conflict contributed to dissolution without conflict is
likely due to ideological conflicts being over-represented in our sample. Additionally,
ideological conflict measured the presence of ideological, identity, or socio-cultural conflict. It is
reasonable to assume that future analysis would be able to assess more accurately the effect of
each of these different types of conflict on the success or failure of GNUs.
Our final statistically significant result in the contextual factors category indicated that higher
levels of fractionalization within a population decreased the chance that a GNU succeeded.
Again, this finding was somewhat at odds with our literature review. Experts believe that low
and high levels of heterogeneity encourage more peaceful and stable governance, while middling
levels lead to more instability and conflict. So, while the finding we identified is consistent with
some prior research conclusions, it contradicted others.
Government Output Factors
The probability a GNU dissolves peacefully may have increased with greater institutional
strength. We used a measure of rule of law to represent the variable of institutional strength. The
rule of law is an index, which makes it impossible to determine the specific level of
improvement needed in various legal institutions to decrease the risk of failure. Therefore, we
cannot distinguish general, individual policies and changes that would increase GNUs ability to
18
enforce rule of law. Our results indicated, however, that rule of law was a significant contributor
to hazard rates experienced by GNUs, indicating the importance of institutional strength to
peaceful dissolution and providing a logical path to possible policy options. This analysis
bolstered previous scholarship in positing a positive association between improvements in
institutional strength and performance and ultimate success of a GNU.
Finally, our analysis indicated that improvements in GDP growth yielded a positive effect on the
expected success of a GNU. This finding was consistent with literature that supports economic
development and its positive effects on a country’s strength, its capacity for institution building,
and other areas. However, as described in the literature review, making causal inferences from
this relationship is difficult. Thus, this finding, above all others, must be considered skeptically.
19
Case Studies: Variations in Power-Sharing
One of the central features of a GNU is the agreement behind its formation. These agreements
institute a framework for the division of power and frequently include political power-sharing,
territorial power-sharing, economic power-sharing, military power-sharing, or a combination of
two or more of these dimensions. To further understand the underlying conditions of successful
GNUs, we explored three case studies to clarify the mechanisms linking peaceful GNU
dissolution and power-sharing arrangements. Number and type of power-sharing dimensions
were chosen as the distinguishing variable because they are not directly tied to the pre-existing
conditions of a state, and it is the variable with the most direct policy implications.
Given the importance of Afghanistan’s current unity government in the policy debate, we used
this agreement as a reference for selecting our three case studies. Afghanistan’s agreement
appeared to only include one dimension of power sharing: political power sharing. The
agreement included the runner-up to the election, the leader of the opposition, and deputies
appointed by the runner-up. They were all involved in the government and the decision-making
process. This inclusion gave these voices more authority than they would otherwise have had,
but failed to include any elements of territorial power sharing, military power sharing, or
economic power sharing. In these other spheres of power, the president retained sole authority
over all matters of importance.
We have selected three cases that are similar to Afghanistan with regard to population
heterogeneity, conflict characterizations, economic development, international involvement, and
institutional strength. The one distinguishing variable was that all three are based on an
agreement along varying dimensions of power sharing. The three cases we selected to analyze in
this report were Tajikistan, Yemen, and Sudan. All of these countries experience low human
development, high levels of corruption, destabilizing rebel groups, and weak institutions.
Tajikistan shares similar population statistics, regional influences, and historical legacies as
Afghanistan. Yemen’s unity government, formed in 2011, only shortly preceded the formation of
Afghanistan’s unity government. Sudan has experienced prolonged conflict, leaving a large
death toll and displacing even more people.
Tajikistan: 1997 General Agreement
on the Establishment of Peace and National Accord
Agreement Analysis
A newly independent country following the collapse of the Soviet Union, Tajikistan has
undergone significant political and economic changes in its path to peace. The weakening Soviet
locus of power and institutions gave rise to escalating patterns of political competition in the
wake of the perestroika period. Tajikistan’s civil war encompassed conflict involving Islamic
fundamentalism, ethnicity, and national identity, but was primarily defined by regional
affiliation. The two main antagonists of the conflict were the Rakhmonov regime, representing
Kulyab Province and the traditional Communist Party Nomenklatura, and the United Tajik
Opposition, which was dominated by the Islamic Rebirth Party whose officials were almost all
from the Garm Valley region (Djalili, Grare, and Akiner 1997). Negotiations between these two
20
parties began in 1993 and occurred in three phases. The two noteworthy outcomes of the first
stage, which lasted about two years, were a ceasefire and prisoner exchange agreement. The
second stage lasted about half a year and ended with no positive outcomes. The third stage was
swift and ended with a resolution of all outstanding issues.
A combination of internal and the external factors accounted for the dramatic shift from deadlock
in negotiations to a series of agreements. The crucial external factors were the role of other
countries in the region. Russia and Iran in particular were major powers influencing Tajikistan
(Nourzhanov and Bleuer 2013). The alignment of interests in having a stable Tajikistan and
avoiding Western involvement helped shift momentum toward a peaceful solution. The territorial
gains of the Taliban in Afghanistan in particular had significant repercussions for Tajikistan.
Afghan refugees exasperated scarce resources, while Tajikistanis and neighboring countries
feared Afghanistan’s conflict would cross the border. Regarding internal factors, before 1996,
leaders of both factions relied heavily on their military commanders and needed to consider the
interests and ideologies of their network of supporters when making decisions. 1996 saw a
worsening economic crisis that created popular unrest (McAuliffe 2006). At the same time,
militants experienced growing war-weariness from years of fighting and an absence of decisive
victories.
The 1997 peace agreement had two main protocols: a one on military issues, the other on
political issues (Abdullaev and Barnes 2001). The military provision provided for the
reintegration, disarmament, and disbandment of armed units of the United Tajik Opposition. It
also called for the reform of government power structures and commissions a Joint Central
Review Board to evaluate and make recommendations with regard to these reforms. The focus,
however, remained on the steps involving the armed opposition forces. This included the
involvement of peacekeeping forces from the Commonwealth of Independent States and the
United Nations Mission of Observers in Tajikistan. These international actors were included to
supervise the registration and storage of weapons and ammunition.
The political protocol adopted the Statute on the Commission on National Reconciliation and
addressed the political issues of import. The first was amnesty; the protocol references a
reciprocal-pardon act as the first political decision that should be made by the commission. Also
called for by the protocol was a new professional Parliament and Central Electoral Commission.
A third provision central to the agreement was the introduction of a quota to provide for a
minimum amount of representation by the United Tajik Opposition into the various structures of
government, including ministries, local government bodies, and judicial and law-enforcement
bodies. The last main aspect was the lifting of all bans and restrictions on activities by political
parties and movements, as well as the mass media. Comparing these two protocols, the military
protocol was the longer and more detailed of the two. However, the political protocol covers
many more issues and was the focal point of the peace process.
Implications
Since the signing of the 1997 agreement, Tajikistan has avoided a return to the devastating
conflict that gripped the country since 1992. Occasional skirmishes with opposition forces that
did not accept the peace agreement have followed it, but meanwhile the government has
continued to extend its authority (International Crisis Group 2001).
21
Regarding military issues, the agreement sought to create a unified national army that
incorporated all of the armed groups that formed during the civil war. Thousands of former
United Tajik Opposition forces were integrated into the new military structures outlined in the
protocols, yet many military commanders have remained independent. Regarding political
issues, the negotiations between the two parties stipulated that 30 percent of posts at all levels of
the government were reserved for former United Tajik Opposition members, yet this deal had not
always been honored, especially at the lower levels (International Crisis Group 2001).
The hoped for turning point stemming from the peace process were elections. In 1999
presidential and parliamentary elections were held, but failed expectations. International
observers widely called the election fraudulent, with opposition candidates initially threatening
to boycott the elections. Ultimately, Rakhmonov was re-elected with Tajikistan largely retaining
the stability secured during the peace negotiations. For the purposes of this analysis, we
categorized Tajikistan’s GNU dissolution as successful, or dissolution without conflict as it did
not devolve into widespread violence. However, the current state of relations between the two
parties can be characterized by high levels of mistrust and controversy over the implementation
of the 1997 agreement and its related protocols (International Crisis Group 2001). Tajikistan’s
dissolution was characterized in our analysis as dissolution without conflict.
Tajikistan’s experience demonstrated the necessity of having an agreement built on military and
political dimensions. Without the disarmament of opposition forces, integration into new military
structures, and general amnesty, the conflict very easily could have returned. Following the
agreement many controversies have arisen, including disputed elections and accusations of the
government’s failure to fully implement its provisions. If more of the opposition groups had not
become part of the government's forces or had retained weapons and ammunition, these
controversies could have erupted into conflict. Even if conflict did not result, conflict would have
been a constant threat, which would have inhibited the stability and development of the country.
The political dimension was equally needed as the primer of negotiations. For Tajikistan, the
most critical part of the negotiations was the political issues; once these issues were resolved, the
military negotiations were easily settled. Without bringing opposition members into the
government and reopening the country to political parties, there would have been no incentive
for the opposition to disarm and disband. Thus, this case study points to the necessity of political
power sharing for an agreement to occur and the necessity of military power sharing for conflict
to be avoided.
Yemen: The 2011 Gulf Cooperation Council Agreement
The 2011 Gulf Cooperation Council Agreement was signed by Yemen’s National Coalition and
the National Council to end hostilities. A stagnant economy, political exclusion, and an armed
insurgency remained after the signing of the agreement. This case study details the agreement
itself, the context of its signing, and the results and implications for theories regarding the
durability of GNUs.
Agreement Analysis
The United States’ war on terror, Saudi Arabia’s fear of instability, and increasing social unrest
within Yemen were three interrelated and crucial factors responsible for Yemen’s recent political
22
history. As a result of the events on September 11, 2001, the Middle East garnered even greater
international attention and concern. In the West, Yemen was viewed as an unstable, corrupt, and
illegitimate nation run by warring tribes (Bonnefoy 2011). The Yemeni government, however,
took significant steps to cooperate with the United States and its allies, changing its policies and
political allegiances, allowing for military bases and administrative offices to be built within its
borders, and President Ali ’Abd Allah Saleh attended the 2004 G8 summit (Bonnefoy 2011).
This shift in policy was followed by significant domestic unrest and terrorist attacks that caused
more casualties in 2010 than in the entire previous decade (Bonnefoy 2011). During this time the
“Believing Youth,” led by the Houthi family—a Muslim armed insurgency known as the Houthi
rebels—had been participating in anti-government demonstrations in Yemen and elsewhere,
clashing with police, and accusing the Saleh administration of violent discrimination (Freeman
2009). The rebels, who have since played a lead role in the events following the 2011 transition
agreement, are a Zaidi Shia insurgent group that have existed in Yemen since 2004, and have
called for the Yemeni government to end its support of the U.S. war on terror.
In November 2011, after months of violent unrest and the stalling of transition talks in Yemen,
President Saleh ended his 33-year reign by transferring power to his deputy, Adb-Rabbu
Mansour Hadi, through a transition agreement (Rashad 2011). Saudi Arabia and the Gulf
Cooperation Council helped facilitate the process of establishing transitional authority. Yet Saudi
Arabia’s role has not been without criticism. Saudi Arabia has aided the Yemeni government in
fighting the Houthi Rebels, helping keep the patronage networks of the Yemeni government
functioning and supportive of Saleh’s rule. When discontent and criticism against Saleh severely
weakened the legitimacy of the regime, Saudi Arabia called for a transitional government (Durac
2012; Haykel 2011; Hill 2011).
The Gulf Cooperation Council agreement was designed to create a GNU in which political,
economic, and military power were shared between Saleh’s party, the General People’s Congress
(GPC) and its opposition, the Joint Meeting Parties. Six Yemeni parties, including the Islamist
Islah Party and the Yemeni Socialist party composed the Joint Meeting Parties. The Gulf
Cooperation Council brokered the agreement with help from Britain and the United States, and it
was signed in the Saudi Arabian capital of Riyadh (Durac 2012). The first stage was to take place
over the course of 90 days, and the second over the course of two years.
The first stage was the most significant in that it contained the majority of protocols that the
Yemen unity government had to enact. The Gulf Cooperation Council agreement called
specifically for the early election of then-deputy Adb-Rabbu Mansour Hadi to the office of
president. It also established the Committee on Military Affairs to be responsible for the
immediate end to all armed conflicts, the removal of all militias from the capital and other cities,
and the reduction of risk of armed conflict in Yemen. Stage one of the agreement also called for
the creation of a Conference of National Dialogue that would engage youth movements in
Yemen, in order to disseminate and explain the agreement, create conversations about the future
of Yemen, and involve youth in Yemen’s political future (“Yemen Transition Agreement, 2012”
2011).
Stage two of the Gulf Cooperation Council agreement called for constitutional reform that, while
ambiguously designed, would address the structure of Yemen’s political system, reform the
electoral process, and implement any constitutional amendments necessary. Last, protocols
23
regarding the further development of a national conversation about violence in South Yemen, the
inclusion of women in politics, human rights, and local government were briefly mentioned
(“Yemen Transition Agreement, 2012” 2011).
Implications
The dissolution of Yemen’s GNU in this analysis was categorized as a failure, or dissolution
with conflict. The GNU failed in Yemen, in part because it failed to address the underlying
factors warranting its creation in 2011: poor agreement implementation and economic
development, insecurity, and exclusion. Two years into the reign of the new GNU, violence
persisted and the economy remained unchanged (Al-Monitor 2013). The insurgency, taking
advantage of public anger toward the government, staged mass protests. These events led to the
march on Sana’a, resulting in the takeover of capital government buildings and forcing the
resignation of Prime Minister Mohammed Basidawa on September 21, 2014. By February 2015
the Houthis had dissolved the government and solidified the collapse of the state (Gasim 2015).
Presently, warring tribes and militias, including Al Qaeda, are active in Yemen. Saudi Arabia,
with logistical support from the United States, has launched an aggressive bombing campaign on
what they assert is a hostile Iranian takeover (Kirkpatrick and Fahim 2015). At the time of the
publication of this report, nothing remains of the 2011 GNU and the conflict shows no sign of
swift cessation.
The transitional government created by the Gulf Cooperation Council agreement failed not only
because it faced a well-organized insurgency, but also because it failed to address the underlying
insufficiency of the governing structures, including the corruption and centralization of Yemen’s
political power, as well as the exclusion of major political actors from the negotiation table.
Neither the Houthi rebels nor Yemen’s youth were included in the agreement process or in the
formation of the transitional plan (Durac 2012). Many say the agreement was a mere
continuation of the old elite-dominated system, and that the old parties had co-opted the protest
movement for their own political gain (Nevens 2011).
The lack of clarity in logistical design and implementation of protocols in the transitional
agreement itself is evidenced by not only its meager length, but also the ability of the formerly
powerful players to negotiate that ambiguity to their advantage. Power-sharing structures were
not altered, and the elite networks that angered many were kept in place. Additionally, while the
agreement did touch on political, economic, and military power sharing, it did so fleetingly,
leaving it to the next administration to interpret the agreement’s protocols and implement them
as it saw fit.
The Yemen case highlights the need for governments to focus on pre-existing components of
political and economic power sharing when forming transitional agreements. Political
settlements like the Gulf Cooperation Council agreement that failed to enact observable changes
both regarding power sharing and government output may function to further exacerbate societal
unrest. In Yemen, real and transformative political change was not achieved, and the basic
demands of the populace were not met. This, in combination with the failure to either include or
eradicate its insurgency, left the 2011 GNU to dissolve into debilitating conflict.
24
Sudan: 2005 Comprehensive Peace Agreement
Agreement Analysis
Following British rule, Sudan fell into a cycle of civil unrest and instability that continues today.
Two civil wars between 1955 and 2005 resulted in millions of civilian casualties, displaced
people, refugees, and significant international intervention. The Comprehensive Peace
Agreement was a bilateral effort by war-weary parties to end to the conflict. The agreement was
signed by Sudan’s National Congress Party , the Government of Sudan, and the Sudan People’s
Liberation Army/Movement, southern Sudan’s leading military and political organization. This
case study discusses the shortcomings of the Comprehensive Peace Agreement and implications
for GNU successful transition to more permanent governance.
The Comprehensive Peace Agreement comprised six agreements signed between 2002 and 2004:
the Protocol of Machakos; the Protocol on Security Arrangements; the Protocol on Wealthsharing; the Protocol on Power sharing; the Protocol on the Resolution of Conflict in Southern
Kordofan/Nuba Mountains and the Blue Nile States; and the Protocol on the Resolution of Conflict
in Abyei. This extensive agreement of more than 200 pages consisted of political, territory,
military, and economic power-sharing arrangements. The goal of the Comprehensive Peace
Agreement was to end conflict and start democratization for a united Sudan (Aalen 2013).
However, many of the provisions of the agreement were never fully implemented (Simmons and
Dixon 2006).
The Protocol of Machakos called for a six-year period during which south Sudan would have
power to govern affairs in its region and participate in the national government, as well as vote in
a referendum to decide Sudan’s unity or South Sudan’s secession in 2011. It made Islamic law
applicable in the north, but not applicable to non-Muslims in the rest of the country. In the
Protocol on Security Arrangements, the Sudan Armed Forces, under the National Congress
Party, and the SPLA agreed to a demobilization, disarmament, and reintegration program as well
as combining soldiers from each to form Joint Integrated Units to be stationed in high-priority,
disputed areas. The wealth-sharing agreement gave responsibility to the national and south
governments for collecting revenue, recognized a dual banking system and separate currencies
until the Central Bank designated a single currency reflecting unity, and allocated 2 percent of oil
revenue to oil-producing states in southern Sudan. The power-sharing agreement included
arrangements such as a 70:30 power split in favor of the National Congress Party in the north
and 70:30 split in favor of the Sudan People’s Liberation Army/Movement in the south; a
bicameral national legislature; and two vice presidents, the first of whom is the chair of the
Sudan People’s Liberation Army/Movement (Simmons and Dixon 2006).
The remaining protocols focused on governance of three critical areas: Abyei, Nuba Mountains
(in the state of Southern Kordofan), and Southern Blue Nile (in the state of Blue Nile). Due to
internal and international pressure, Sudan People’s Liberation Army/Movement representatives
in the Nuba Mountains and Southern Blue Nile gave up many demands. The National Congress
Party and Sudan People’s Liberation Army/Movement were supposed to rotate authority over
Southern Kordofan and Blue Nile, but the party maintained control through the central
government (Simmons and Dixon 2006). Involved parties failed to address certain controversies,
such as disputes over land and natural resources, in the agreement leaving these to be addressed
25
later (Brosché 2009). Furthermore, the Comprehensive Peace Agreement did not address
implementation of the provisions, which was a major failure.
Implications
The Comprehensive Peace Agreement failed to reach the stated goals of ending hostilities and
starting democratization as evidenced by instability (Aalen 2013). This case was categorized in
our analysis as a failure, or dissolution with conflict. Broadly, the agreement process focused too
much on the agreement itself and not enough on implementation. The agreement failed to
incentivize implementation and national unity. One of the major components of the agreement
was the referendum giving the south an exit option (Brosché 2009). The referendum took place
in 2011, and southern Sudanese were overwhelmingly in favor of secession. South Sudan gained
its independence in July 2011 and signed agreements with Sudan in 2012 to establish a positive
framework for relations between the two governments. Like the Comprehensive Peace
Agreement, the 2012 agreement provisions have not yet been fully implemented. The
referendum made disunity a possibility and did not reinforce implementation of the agreement
provisions. There is no incentive to invest in implementation if a party will likely be leaving the
agreement in a few years. If there is an option for a party to exit an agreement, then there can be
no shared vision.
Another example of the agreement’s shortcomings in incentivizing implementation and national
unity is that the agreement only addressed north-south conflict. Due to the fact that only armed
groups were given a voice in the negotiation, the agreement encouraged more violence by
pushing rebel groups to compete for power through military action (Brosché 2009). Remnants of
the Sudan People’s Liberation Army/Movement in the north, as well as other rebel groups,
continued to engage in violent conflict with the Sudanese government, demonstrating the need to
address the relationship between the country center and periphery. Although the agreement did
include some decentralization, because provisions were never fully implemented and there was
little commitment to a shared vision, the agreement was never seen as legitimate and never given
the chance to truly address the relationship between the center and periphery.
Land played an important role in the Comprehensive Peace Agreement. The center-periphery
conflict was not just political, but territorial. Sudan has a long history of economic exploitation
of the periphery by the central government. Much of the disputed land addressed in the
agreement is rich in natural resources. In 2009, 97 percent of South Sudan’s budget came from
oil revenues (Brosché 2009). While the north and south have oil, most of the oil-producing
capacity is in the south. Due to limited infrastructure, the south must rely on the north to ship this
oil for revenue, which enables the north to continue exploiting natural resource wealth. To
sustain the south’s dependency, the north has less incentive to invest in infrastructure in the south
as was part of the agreement. In the literature on power sharing, more power-sharing provisions
(i.e., economic, military, territorial) are proven to strengthen the durability of agreements.
However, this case study points to the necessity of resolving underlying imbalanced power
distribution and using such considerations to inform negotiations.
Without the Comprehensive Peace Agreement the country would likely still be facing a brutal
north-south war, and therefore despite the ongoing instability important lessons can be learned
from Sudan. Exit options discourage implementation of provisions and prevent a shared vision.
Exclusion of key stakeholders and unresolved power imbalances reinforce disunity. Lessons
26
from failed implementation and inadequate incentives must be learned if power sharing is to be
considered a solution for peace in other conflict environments around the world.
27
Conclusions and Policy Recommendations
The stability and proper functioning of countries is in the best interest of the international
system. Costly wars, regional destabilization, loss of life, economic disruption, and the need for
large amounts of aid are a few of the many reasons the international community is an important
stakeholder in the durability and peaceful dissolution of GNUs. Particularly, the United States
has a vested interest in the future of these nations for economic, political, and security reasons.
The survival and case study analyses presented have clarified features of GNUs and the broader
context in which they emerge that affects how they dissolve. As such, the results of our analysis
should be incorporated into risk analysis and other state assessments when GNUs formation is
being considered. Additionally, consideration of the stage in which a GNU is currently at (i.e.,
formation, existence, dissolution) is important in weighing the appropriate policy response.
Our findings can inform policy decisions throughout the GNU establishment timeline. For
example, our analysis of a country’s contextual characteristics can be most helpful from the preGNU establishment perspective: for instance, knowing that GNUs established in the wake of
ideological conflict may result in more successful GNU dissolution, the United States may urge
the establishment of a GNU in these circumstances. Certainly, this information can also help
from a post-establishment perspective. For example, GNUs already established in postideological-conflict countries will be more stable than those in countries where other sorts of
conflicts preceded the GNU. Therefore, intervention and support may not be as great a necessity
in ensuring peaceful dissolution. However, this policy is passive; from a pre-establishment
perspective this finding offers active policy implications.
Providing government services and outputs, like establishing and enacting rule of law, are
important post-GNU establishment intervention and support strategies. United States
policymakers can expect that improving a GNU’s rule of law efficacy can lead to a more
successful dissolution. Therefore, in considering aid packages, the United States can seek to
specifically bolster a country’s rule of law, or explore other institutional strengthening
approaches that may improve the likelihood a GNU, once established, dissolves peacefully.
The policy alternatives offered and evaluated below will be more or less feasible and more or
less effective depending on the time (pre- or post-GNU establishment) in which they are
implemented. Based on the variables identified as significant through our quantitative analysis as
well as the implications of case study findings, this section describes and evaluates four broad
and flexible policy options for the U.S. government.
Take No Action
Given the significant impact contextual factors have on durability, taking no action to enhance or
inhibit peaceful dissolution of GNUs is an attractive and feasible option. Characteristics of
conflict, levels of heterogeneity, and other historical contextual attributes may be beyond the
scope of intervention. More specifically, our analysis demonstrates that while GNUs may
incorporate all four dimensions of power-sharing, full and fair implementation of these
dimensions is difficult to ensure. The absence or exclusion of a major party in negotiations can
doom any agreement before its’ signing. Moreover, intervention in complex conflict zones is
28
politically and financially costly and carries great risk of failure. In light of these issues, some
scholars have advocated taking no action in unstable states. However, competing norms such as
the social costs, economic implications, and potential regional spillover issues may render this
option infeasible.
Increase Access To and Role in International Organizations for GNUs
Involvement of third parties as mediators, economic support, and peacekeepers contributes to the
stability of emergent governance and adherence to peace agreement protocols. However, for
individual state actors, these roles are difficult and costly. Therefore, engaging GNUs in regional
or international organizations spreads cost and risk among players. International organizations
that are seen as legitimate by opposing parties, and that can marshal resources to maintain peace
and enhance government output, can play an important role in peaceful dissolution. Access to
these circles, and support for negotiations and enforcement is important. Additionally, more
diplomatic contact between GNU representatives offers the possibility that problem areas or
potential sources of conflict can be identified at an earlier junction and prevented. Thus opening
these spaces for opposition parties to deliberate, receive support, and ensure enforcement is
feasible and likely effective at creating durable, transitional institutions.
Strengthen Government Institutions
Our analysis implicates the potential role of institutions and government output in maintaining
peace and proper functioning of GNUs once formed. Strong institutions can provide basic
services, ensure security, and signal stability to other countries. They incentivize cooperation
among parties by creating higher consequences for defection. Our analysis uncovered
statistically significant relationships on our institutional strength measure (rule of law), thus
policy that supports institution building, maintenance, and quality improvement is critical. Yet,
similar to the other options, there are high costs and risks to this approach. Additionally, previous
research outlines the difficulty of supporting institution building. There is no template for nation
building, as most state institutions reflect their political culture and historical context. However,
it is feasible to provide strategic support to specific institutions, or act as a supplemental provider
of services in the interim while these entities develop and mature. States can partner with nonstate providers of service and engage GNUs through these organizations.
Incentivize Multi-Dimensional Power Sharing
Our analysis confirms previous findings that the more power-sharing provisions within
negotiated settlements that are implemented, the more likely peace will prevail. By encouraging
the signing of provisions that decentralize power, create broader bases of support, and allow
multiple actors to exert influence in various systems, GNUs are more likely to dissolve
peacefully. Political power sharing is not sufficient; rather power sharing in economic, military,
and territorial affairs has a stronger effect on dissolution type. From the understanding gleaned
by the Tajikistan case, we find that military power-sharing is critical to securing high costs to
defection by former militarized parties.
International actors can facilitate and increase the likelihood of adopting and implementing
multiple power-sharing provisions by providing economic, military, and political incentives.
29
Additionally, negotiated settlements are often mediated by third parties, in which case these
parties may influence the depth of power sharing parties agree to. Thus, this option offers many
strategic and diplomatic routes that may be more feasible than others given the flexibility of
implementation.
30
Appendix A. Governments of National Unity 1975-2012
Table A1. Database of identified GNUs, Country, Start and End Dates, Dissolution,
and Type of Power-Sharing Agreement
P=political, E=economic, M=military, T=territorial. Key to citations is in Table A2; where possible, the actual agreement is cited.
Start End
Type of Power
Country
Description of GNU
Year Year Outcome
Sharing
Afghanistan
Peshawar Accord
1992 1993 Dissolution With Conflict
P, M
Afghanistan
Islamabad Accord
1994 1995 Dissolution With Conflict
P, E, M
Afghanistan
Bonn Agreement
2001 2004 Transition Agreement
P, M
Angola
Gbadolite Declaration on Angola
1989 1990 Dissolution With Conflict
P
Angola
Bicesse Accord
1991 1992 Dissolution With Conflict
P, M
Angola
Lusaka Protocol-GURN
1994 2008 Dissolution Without Conflict P, M, T
Azerbaijan
Bishkek Protocol
1994 1995 Dissolution Without Conflict P, T
Bangladesh
Chittagong Hill Tracts Agreement
1997 2012 Right Censored
P, T, M
Benin
Power-Sharing Agreement
1990 1991 Transition Agreement
P, E, T, M
Bolivia
Megacoalición
1979 1980 Dissolution Without Conflict P
Bolivia
Pact for Democracy
1985 1989 Dissolution Without Conflict P
2005 Elections Won by Movimiento al
Bolivia
2005 2009 Dissolution Without Conflict P
Socialismo
Bosnia
Dayton Accord
1995 2012 Right Censored
P, T, M
Burundi
La Convention de Gouvernement
1994 1996 Dissolution With Conflict
P, E, M
Arusha Peace and Reconcilliation
Burundi
1998 2000 Transition Agreement
P, E, T, M
Agreement for Burundi
Burundi
Arusha Accords
2001 2005 Dissolution Without Conflict P
Result of 1991 Paris Peace Accords-Cambodia
1993 1997 Dissolution With Conflict
P, M
"Supreme National Council"
Cambodia
Power-Sharing Agreement
1998 2003 Dissolution With Conflict
P, E, M
Central African
National Transitional Council
2003 2005 Dissolution Without Conflict P
Republic
Central African
Comprehensive Peace Agreement
2008 2011 Dissolution With Conflict
P, M
Republic
Chad
Transitional Government of National Unity
1979 1980 Dissolution With Conflict
P, T, M
Higher Transitional Council: Agreement
Between Government of Chad and the
Chad
1996 1998 Transition Agreement
P
Movement for Democracy and
Development
Peace Agreement between the Government
Chad
of Chad and the Mouvement pour la
2002 2003 Dissolution With Conflict
P, M
Démocratie et la Justice au Tchad
Chad
Power-Sharing Agreement
2007 2008 Transition Agreement
P, T, M
Chad
Power-Sharing Agreement
2009 2009 Transition Agreement
P, T, M
Colombia
Political Accord with M-19
1990 1990 Dissolution Without Conflict P, M
Common Agenda for the Path to a New
Colombia
1999 2000 Dissolution Without Conflict P, E, T, M
Colombia
Framework Accord for Reconciliation in
Comoros
2001 2001 Transition Agreement
P, E, T, M
Comoros
Comoros
Transitional National Unity Government
2002 2003 Dissolution Without Conflict P
Comoros
Pour la Gestion de la Periode Interimaire
2010 2011 Dissolution Without Conflict P, T
Congo
Libreville Accord
1993 1994 Dissolution With Conflict
P
Accord de Cessez-le-Feu et de Cessation
Congo
1999 2002 Transition Agreement
P, M
des Hostilités
Peace Accord between the Congolese
Congo
2003 2007 Dissolution Without Conflict P, M
Government and the Ninjas
31
Citations
a,b
a,b
a
a
a
a
a
a
c, d, e
f, g
h
i, j
k
l, m
n
a
k, o
p
q
r, s
k, t
u
a
a
q, a
v, w
v
a, x
y
a
z
aa, ab
ac
Country
Côte d’Ivoire
Côte d'Ivoire
Côte d’Ivoire
Croatia
Croatia
Djibouti
Djibouti
DRC
Democratic
Republic of
Congo
El Salvador
Equatorial
Guinea
Fiji
Fiji
Gabon
Guatemala
Guinea
Guinea-Bissau
Guinea-Bissau
Iraq
Kenya
Laos
Lebanon
Lebanon
Liberia
Liberia
Liberia
Liberia
Libya
Madagascar
Madagascar
Maldives
Mali
Mali
Mauritania
Mozambique
Description of GNU
Power-Sharing agreement
Linas-Marcoussis Peace Accords
Ouagadougou Peace Agreement
Third Croation Government, Franjo
Gregurić
Erdut Agreement
Agreement on Peace and National
Reconciliation
General Agreement on Reform and Civil
Concord
Sovereign National Convention
All-Inclusive Agreement on the Transition in
the Democratic Republic of Congo
Chapultepec Peace Accords
GNU under Democratic Party of Equatorial
Guinea Obiang
National Federation Party and Fiji Labour
Party
Coalition Government Between Four
Parties
Power-Sharing Agreement
Agreement on the Implementation,
Compliance, and Verification Timetable for
the Peace Agreements
Ouagadou
Agreement Between the Government of
Guinea Bissau and the Self-Proclaimed
Military Junta
Pact of Stability
Erbil Agreement
Grand Coalition Cabinet-National Accord
and Reconciliation Act
National Assembly
Taif Accord
Doha Agreement on the Results of the
Lebanese National Dialogue Conference
Yamoussoukro I, II, III
Cotonou Agreement
Abuja Agreement and Supplements
Accra Peace Accord
National Transitional Government
High Transitional Authority
National Union Transitional Government
Power-Sharing Agreement
Pacte National Conclu entre le
Gouvernement de la République du Mali et
les Mouvements et Fronts Unifiés de
l’Azawad Consacrant le Statut Particulier du
Nord au Mali
Power-Sharing Agreement
Power-Sharing Agreement
Transitional Government Established by
Adoption of Lusaka Accords
Start
Year
2002
2003
2007
End
Year
2002
2004
2010
Outcome
Transition Agreement
Dissolution With Conflict
Dissolution With Conflict
Type of Power
Sharing
P
P, M
P, M
1991 1992 Dissolution Without Conflict
P
1995 2000 Dissolution With Conflict
P
1994 1999 Dissolution With Conflict
P, E
2000 2005 Dissolution Without Conflict
P
1991 1992 Transition Agreement
P
2002 2006 Dissolution Without Conflict
P, M
1992 1994 Dissolution Without Conflict
P, E, M
2002 2006 Transition Agreement
P
1987 1988 Dissolution With Conflict
P
1999 2000 Dissolution With Conflict
P
1994 1996 Dissolution Without Conflict
P
1996 1999 Dissolution Without Conflict
P, E, T
2010 2010 Dissolution Without Conflict
P, M
1998 1999 Dissolution With Conflict
P, M
2007 2009 Dissolution With Conflict
2010 2011 Dissolution Without Conflict
P, M
P
2008 2012 Right Censored
P
1974 1975 Dissolution With Conflict
1989 1992 Dissolution Without Conflict
P, M
P, M
2008 2009 Dissolution Without Conflict
P
1991
1993
1996
2003
2011
2009
2011
2012
P, M
P
P
P, E, M
P, T
P, E, M
P
P
1992
1994
1997
2006
2012
2010
2012
2012
Right Censored
Transition Agreement
Dissolution With Conflict
Dissolution Without Conflict
Dissolution Without Conflict
Transition Agreement
Right Censored
Right Censored
1991 1992 Dissolution With Conflict
P, T, M
2012 2012 Dissolution With Conflict
2009 2009 Dissolution Without Conflict
P, M
P
1975 1977 Dissolution Without Conflict
P, M
32
Citations
ad
ae, af
ag, af
ah
a
a
a
ai
aj
a, ak
al
am
am
a, an
k, ao, a
a, ap
k, aq
aq
a, ar
a, as
at, au
k, av
a, aw
a
a
a
a
a
a
a
a
a
a, ax
a, ay
az, ba
Country
Mozambique
Nepal
Nepal
Nicaragua
Paraguay
Rwanda
Sierra Leone
Sierra Leone
South Africa
South Africa
Sudan
Sudan
Tajikistan
Tajikistan
Timor-Leste
Togo
Tunisia
Uganda
Uganda
Vanuatu
Yemen
Zimbabwe
Description of GNU
General Peace Agreement for Mozambique
Comprehensive Peace Accord- Transitional
Agreement
Seven Point Agreement-Interim
Government
Tela Accord
Power-Sharing Agreement
Protocol of Agreement on Power-sharing
within the Framework of a Broad-based
Transitional Government between the
Government of the Republic of Rwanda and
the Rwandese Patriotic Front
Abidjan Peace Agreement
Lome Peace Agreement
National Peace Accord
Power-Sharing Agreement
Addis Ababa Agreement
Comprehensive Peace Agreement
Government of National Reconciliation
1997 General Agreement on the
Establishment of Peace and National
Accord and its' related protocols
United Nations Transitional Agreement in
Eastern Timor
President Sharing with Transitional
Government
Government of National Unity
Agreement Between Government of
Uganda and the Uganda National Rescue
Front
Final Peace Agreement
Power-Sharing Agreement
2011 Gulf Cooperation Council Agreement
Power-Sharing Agreement
Start End
Year Year Outcome
1992 1994 Dissolution Without Conflict
2006 2010 Transition Agreement
Type of Power
Sharing
Citations
P, T, M
k, bb
a, bc
P
2011 2012 Right Censored
P, M
1989 1990 Dissolution Without Conflict
1999 2003 Dissolution Without Conflict
P, E, T, M
P
1993 1994 Dissolution With Conflict
P, E, M
1996
1999
1991
1994
1972
2005
1992
P, E, M
P
P, E, T, M
P, E, T, M
P, E, T, M
P, E, T
P
1997
2000
1993
1999
1983
2010
1992
Dissolution With Conflict
Dissolution With Conflict
Transition Agreement
Dissolution Without Conflict
Dissolution With Conflict
Dissolution With Conflict
Dissolution With Conflict
1997 1999 Dissolution Without Conflict
P, M
1999 2002 Transition Agreement
P, T, M
1990 1993 Dissolution With Conflict
P, E, T, M
2011 2011 Dissolution With Conflict
P
2002 2006 Dissolution With Conflict
P, T
2007
1978
2011
2009
P
P
P, E, M
P
33
2008
1979
2012
2012
Dissolution With Conflict
Dissolution Without Conflict
Right Censored
Right Censored
a, bd
be
bf
a, bg
a
a
a, bh
bi
k, bj
bk
bl
bm
bn
bo
bp
bq
br
bs
bt
a
Table A2. Listed Citations for Governments of National Unity
Letter Corresponding Citation for Table A1. List of Governments of National Unity
a
b
c
d
e
f
g
h
I
j
k
l
m
n
o
p
q
r
s
t
u
v
w
y
x
z
aa
ab
ac
International Conflict Research Institute, and Ulster University. 2015. “Conflict Data Service: Peace Agreements.”
http://www.incore.ulst.ac.uk/services/cds/agreements/.
International Conflict Research Institute, Ulster University, and Transitional Justice Institute. 2015. “The Transitional Justice Peace
Agreements Database.” http://www.peaceagreements.ulster.ac.uk/.
United Nations Department of Political Affairs. 2015. “United Nations Peacemaker Database.” http://peacemaker.un.org/.
The Government of the Republic of Benin. 1990. Constitution of the People’s Republic of Benin. International Committee of the Red
Cross. https://www.icrc.org/applic/ihl/ihl-nat.nsf/0/cf2ff43e6cfeb09dc125768e0048233f/$FILE/19243233.pdf/Benin - Constitution.pdf.
Encyclopedia of the Nations. 2015. “Benin - History.” http://www.nationsencyclopedia.com/Africa/Benin-HISTORY.html.
Widner, Jennifer, and Princeton University. 2005. “Constitution Writing & Conflict Resolution: Data & Summaries.”
Slater, Dan, and Erica Simmons. 2013. “Coping by Colluding: Political Uncertainty and Promiscuous Powersharing in Indonesia and
Bolivia.” Comparative Political Studies 46: 1366–93.
Munoz-Pogossian, Betilde. 2008. Electoral Rules and the Transformation of Bolivian Politics. New York: Palgrave Macmillan.
Hudson, Rex A., and Dennis M. Hanratty. 1989. Bolivia: A Country Study. Washington, D.C.: GPO for the Library of Congress.
Fuentes, Federico. 2010. “Government, Social Movements, and Revolution in Bolivia Today.” International Socialist Review, no. 76.
http://isreview.org/issue/76/government-social-movements-and-revolution-bolivia-today.
Bolivia Information Forum. “Social Movements and Trade Unions.” http://www.boliviainfoforum.org.uk/insidepage.asp?page=49&section=3.
Hartzell, Caroline A., and Matthew Hoddie. 2007. Crafting Peace: Power-Sharing Institutions and the Negotiated Settlement of Civil
Wars. University Park, PA: The Pennsylvania State University Press.
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36
Appendix B. Technical Notes
The following has been pulled largely from Cleves et al. (2008) and is a more technical
explanation of the process of survival analysis included in this paper (Cleves 2008).
Survival analysis originated in the health and social sciences as a way to track the success of a
drug or the effects of some treatment over time. Specifically, survival analysis is a time-to-event
method that produces a positive random variable, effectively identifying the time it takes for a
government of national unity to fail (fall to conflict). The survival output helps to identify
relevant correlated determinants that affect the success or failure of a unity government.
In survival analysis, a hazard function predicts the conditional failure rate of GNUs. To construct
the hazard function, we create a survivor function that represents the reverse cumulative
distribution function of T to construct the cumulative density function that is used in the hazard
function to predict the hazard rate. T is a nonnegative random variable that demonstrates the time
before one observes a “failure event” (Cleves et al., 2008, 7). The hazard function is also known
as the intensity function and is the probability that a GNU will fail at any given point within the
interval represented in our data.
S(t) = 1 – F(t) = Pr(T > t)
f(t) = dF(t)/dt = d/dt[1-S(t) = -S’(t)
h(t) = lim Δt-->0 Pr(t + Δt > T > t | T>t)/ΔT = f(t)/S(t)
For our analysis, the hazard rate was such that, the coefficient represented the ratio of the hazard
function that corresponds to a one-unit (1 year) change in the corresponding covariate. This
designation enabled us to estimate the increasing risk of failure for a GNU case in each year. For
example, if the coefficient for the conflict variable was equal to 0.18, then the presence of
conflict within a country’s sovereign borders would equal a 20 percent increase in the hazard
rate, because exp(0.18) = 1.20 (Cleves et al., 2007, 134).
Semi-Parametric Model
There are three main categories of survival analysis: parametric, semiparametric, and
nonparametric. Parametricity refers to the degree of proportionality observed within the data.
Semiparametric is a combination of several separate binary-outcome analyses (Cleves et al.,
2008, 6). Because of the presence of qualitative covariates included in this data set,
semiparametric modeling produced the most accurate estimates. According to Cleves et al.
(2008), when there are no covariates present in the model, the parametric Cox model will
produce estimates that are identical to nonparametric models (6).
Cox Model
The Cox model of survival analysis is a common form of survival analysis and assumes that the
covariates multiplicatively shift the baseline hazard function and has several other benefits
(Cleves et al., 2007, 129). The first benefit of using the Cox model is that it does not require the
estimation of a baseline hazard function, and instead estimates the distribution. Because the
37
intercept is developed from the baseline hazard function, the Cox model has no intercept and
Stata is unable to identify the intercept from the data (Cleves et al., 2007, 134). The model also
has increased flexibility as it does not place any restrictions on the shape of the hazard function
over time. Finally, the Cox model states that the covariates among different independent
variables in the equation do not change over time (Cleves et al., 2007, 132).
L(βldata) = L(analysis 1)L(Analysis 2)....L(Analysis N)
The likelihood function we derived was from each analysis of the time varying covariates and
was adapted to the arguments we made about the nature of GNU dissolution. For instance, if we
decided to group independent variables to test a hypothesis regarding their impact on dissolution
type, the likelihood of failure would have been the sum total of the explanatory variables
specified in the model. In other words, the likelihood function was sensitive to selection.
Furthermore, the weights of importance assigned to the variables we measure directly affect how
we interpreted this survival model output.
Time-Variant Covariates
Time-variant covariates are those independent variables in our analysis that are time-dependent.
This means the value of our time-variant covariates will change within a GNU in a given period
of time. For our model, these included characteristics such as GDP per capita, access to water
and sanitation, corruption, strength of legal rights, and conflict. Time-invariant measures
included agreement characteristics such as the type of power sharing, or the presence of a thirdparty enforcer.
Breslow vs. Efron Method for Approximating Discrete Likelihood of Failure
The proportional hazards model does not assume that ties are possible because it estimates a
continuous hazard. Breslow’s method tends to bias estimates of our coefficients toward zero
when there are large numbers of ties, such as in our analysis.
Efron’s method is still biased toward zero with too many ties, but typically provides more
accurate estimates than Breslow’s. The exact method used in this analysis calculated all possible
orderings and sums the probabilities of each tied event that occurred. This method was useful
due to the imprecise measurements in this analysis, both due to measurement problems and a
lack of data.
38
Appendix C. Model Specifications and Results
Table C1. Model 1 Failure Results with Coefficients and Confidence Interval
The Log-likelihood is -22.55 and the probability that estimates are greater than chi-squared is 0.02.
Confidence Interval
Variables
Measures
Population Heterogeneity
Fractionalization
Number of Power-Sharing Types in Agreement
GNU Agreement
Presence of Third-Party Enforcer
Duration
Preceding Conflict
Outcome: Stalemate
Type: Ideological
GDP per Capita
Economic Development
GDP growth
Institutions
Rule of Law
Control
Conflict
39
Coefficient
0.61
Std. Err: 0.61
0.23
Std. Err: 0.49
-0.12
Std. Err: 0.81
-0.05
Std. Err: 0.08
-0.05
Std. Err: 0.80
-1.52
Std. Err: 0.93
-0.0001
Std. Err: 9.6
x 10-5
0.01
Std. Err: 0.77
2.54
Std. Err: 0.88
0.48
Std. Err: 1.09
Minimum
Maximum
P-Value
-0.58
1.81
0.31
-0.74
1.19
0.65
-1.70
1.47
0.89
-0.01
0.11
0.53
-1.61
1.52
0.96
-3.35
0.30
0.10
-0.00031
0.00006
0.17
-0.14
0.16
0.90
0.82
4.26
0.004
-1.66
2.62
0.66
Table C2. Model 2: Success Results with Coefficients and Confidence Interval
Log-likelihood is -21.07 and the probability our estimates are greater than chi-squared is 0.02.
Variables
Measures
Population Heterogeneity
Fractionalization
Coefficient
-1.30
Std. Err: 0.39
Number of Power-Sharing Types in Agreement
GNU Agreement
Std. Err: 0.49
0.25
Presence of Third-Party Enforcer
Std. Err: 0.67
0.08
Duration
Preceding Conflict
-0.07
Std. Err: 0.07
0.39
Std. Err: 0.69
1.40
Std. Err: 0.60
Outcome: Stalemate
Type: Ideological
95% Confidence Interval
Minimum
Maximum
P-Value
-2.07
-0.53
0.001
-1.02
0.88
.89
-1.07
1.57
0.71
-0.05
0.21
0.21
-0.97
1.74
0.58
0.23
2.57
0.02
1.6 x 10-4
2.7 x 10-5
0.16
0.01
0.05
0.01
-1.64
1.17
0.74
-1.49
0.64
0.44
-0.000065
GDP per Capita
Std. Err: 4.7
x 10-5
Economic Development
0.03
GDP Growth
Institutions
Rule of Law
Control
Conflict
Std. Err: 0.01
-0.23
Std. Err: 0.72
-0.42
Std. Err: 0.54
Table C3. GNU Summary Statistics by Duration, Model 1: Failure
Duration of GNUs
1
2
3
4
5
6
12
15
16
18
Total
Years at Risk of Failure
10
76
33
40
55
36
12
15
16
18
311
Incidence of Failure
0.3
0.24
0.06
0.08
0.04
0.11
0.08
0
0
0
0.11
40
Number of GNUs
10
38
11
10
11
6
1
1
1
1
90
Table C4. GNU Summary Statistics by Duration, Model 2: Success
Duration of GNUs
1
2
3
4
5
6
12
15
16
18
Total
Years at Risk of Failure
10
75
33
40
55
36
12
15
16
18
310
Incidence of Failure
0.3
0.14
0.15
0.08
0.11
0.06
0
0.07
0
0
0.1
Number of GNUs
10
38
11
10
11
6
1
1
1
1
90
Table C5. GNU Summary Statistics by Outcome of Interest
Outcome
Dissolution without Conflict
Dissolution with Conflict
Transition Agreement
Right-Censored
Total
Years at Risk of Failure or Success
109
103
47
52
311
Incidence of Outcome
0.29
0.32
0
0
0.11
Table C6. Summary Statistics for Rule of Law Index
Percentiles
1%
5%
10%
25%
50%
75%
90%
95%
99%
Observed Rule of
Law
-2.07
-1.71
-1.62
-1.43
-1.13
-0.79
-0.49
-0.34
0.01
Smallest
-2.23
-2.07
-1.84
-1.81
Largest
-0.13
-0.01
0.01
0.16
Table C7. Summary Statistics for Rule of Law Index, continued
Observations
Mean
Standard Deviation
Variance
Skewness
Kurtosis
169.00
-1.09
0.44
0.20
0.31
2.72
41
Number of GNUs
31
33
17
9
90
Table C8. Summary Statistics for GDP Growth
Percentiles
1%
5%
10%
25%
50%
75%
90%
95%
99%
Observed GDP
Growth
-32.83
-2.91
-1.21
2.20
4.53
6.81
11.38
16.37
38.00
Smallest
-62.08
-32.83
-15.09
-6.65
Largest
20.74
22.60
38.00
104.48
Table C9. Summary Statistics for GDP Growth, Continued
Observations
165.00
Mean
5.11
Standard Deviation
11.35
Variance
128.71
Skewness
2.78
Kurtosis
45.07
Table C10. Summary Statistics for Ideological Conflict
1%
5%
10%
25%
50%
75%
90%
95%
99%
Percentiles
Smallest
0.00
0.00
0.00
0.00
0.00
1.00
1.00
1.00
1.00
0.00
0.00
0.00
0.00
Largest
1.00
1.00
1.00
1.00
Table C11. Summary Statistics for Ideological Conflict, Continued
Observations
311
Mean
0.36
Standard Deviation
0.48
Variance
0.23
Skewness
0.60
Kurtosis
1.36
42
Table C12. Summary Statistics for Outcome: Stalemate
Percentiles
Smallest
1%
0
0
5%
0
0
10%
0
0
25%
0
0
50%
0
Largest
75%
1
1
90%
1
1
95%
1
1
99%
1
1
Table C13. Summary Statistics for Outcome: Stalemate, Continued
Observations
311
Mean
0.32
Standard Deviation
0.47
Variance
0.22
Skewness
0.75
Kurtosis
1.56
43
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