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Revisiting democratic civil peace: Electoral regimes and civil conflict

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Revisiting democratic civil peace: Electoral regimes and civil conflict

Abstract

The debate on democratic civil peace has centered on three general claims: democracies have a low risk of civil conflict, autocracies have the same low risk of conflict as democracies, and hybrid regimes have the highest conflict risk. We re-evaluate these claims, emphasizing that previous studies have focused on the aggregate categories of regimes, neglecting the role of particular institutional features. We propose focusing on the electoral qualities of regimes, which constitute the core of democracy, and argue that constraints on electoral contestation generate incentives for opposition to use force. Building on this framework, we distinguish between five regime types according to their electoral features – non-electoral autocracies, single-party autocracies, multi-party autocracies, minimalist democracies, and polyarchies – and specify hypotheses regarding the probability of conflict onset in each. In a global statistical analysis spanning 1817–2006 and employing the new Lexical Index of Electoral Democracy (LIED), we find that polyarchies, characterized by unconstrained contestation, have a lower probability of conflict than any other regime type (although minimalist democracies are only slightly more prone to conflict). Subsequently, we find that single- and multi-party autocracies, characterized by non-competitive elections, are more peaceful than non-electoral autocracies. Our analysis also reveals two factors that are particularly associated with civil peace: the presence of (any form of) elections and minimal electoral competition. Overall, our study underscores the importance of focusing on the central attributes of democracy and sheds new light on the relationship between particular regime features (or types) and civil conflict, thereby contributing to the growing efforts in conflict research to disaggregate political regimes.
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Revisiting democratic civil peace: Electoral regimes and civil conflict
Henrikas Bartusevičius, Department of Political Science, Aarhus University
Svend-Erik Skaaning, Department of Political Science, Aarhus University
Manuscript accepted for publication in the Journal of Peace Research. The final, definitive version of
this paper has been published Journal of Peace Research 55(5), Sep/2018 by SAGE Publications Ltd,
All rights reserved. © Henrikas Bartusevičius and Svend-Erik Skaaning. Link to the published version:
doi: 10.1177/0022343318765607
Abstract
The debate on democratic civil peace has centered on three general claims: democracies have a low risk
of conflict, autocracies have the same low risk of conflict as democracies, and hybrid regimes have the
highest conflict risk. We reevaluate these claims, emphasizing that previous studies have focused on
the aggregate categories of regimes, neglecting the role of particular institutional features. We propose
focusing on the electoral qualities of regimes, which constitute the core of democracy, and argue that
constraints on electoral contestation generate incentives for opposition to use force. Building on this
framework, we distinguish between five regime types according to their electoral features—non-
electoral autocracies, single-party autocracies, multi-party autocracies, minimalist democracies, and
polyarchies—and specify hypotheses regarding the likelihood of conflict in each. In a global statistical
analysis spanning 18172006 and employing the new Lexical Index of Electoral Democracy (LIED),
we find that polyarchies, characterized by unconstrained contestation, have a lower risk of conflict than
any other regime type (although minimalist democracies are only slightly more prone to conflict).
Subsequently, we find that single- and multi-party autocracies, characterized by non-competitive
elections, are more peaceful than non-electoral autocracies. Our analysis also reveals two factors that
are particularly associated with civil peace: the presence of (any form of) elections and minimal
electoral competition. Overall, our study underscores the importance of focusing on the central
attributes of democracy and sheds new light on the relationship between particular regime features (or
types) and civil conflict, thereby contributing to the growing efforts in conflict research to disaggregate
political regimes.
Keywords: democratic civil peace, civil war, armed conflict, political regime, elections, autocracy
Corresponding author: henrikas@ps.au.dk
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Introduction
The proposition that democracy leads to civil peace has generated extensive debate in conflict research
(Hegre, 2014). This debate has centered on three general claims. First, democracies have a low risk of
conflict, as democratic regimes create few political grievances and have institutional means to
accommodate contenders non-violently. Second, autocracies have as low a risk of conflict as
democracies, as autocratic regimes have the means to repress contenders violently. Finally, hybrid
regimes (“anocracies) have the highest conflict risk, as they lack both the established institutions to
accommodate contenders and effective means to repress them. Initially, empirical work provided
considerable evidence to support these claims, suggesting that the democracyconflict relationship
follows an inverted U (Auvinen, 1997; Fearon & Laitin, 2003; Hegre et al., 2001; Henderson & Singer,
2000; Muller & Weede, 1990; Reynal-Querol, 2002). However, subsequent studies have challenged
these claims, showing that anocracies do not in fact have a higher risk of conflict than other regimes
(Trier & Jackman, 2008; Vreeland, 2008).
In view of this, we revisit the debate on democratic civil peace. We note that previous research
has underexplored particular institutional features (see also Fjelde, 2010; Gleditsch & Ruggeri, 2010;
Goldstone et al., 2010). Specifically, previous studies have used indicators representing the overall
level of democracy that do not account for specific qualities of regimes theorized to influence peace;
for example, institutions regulating access to power. We suggest that research on democratic peace
should center on the electoral features of regimes, such as the presence and competitiveness of national
elections, which form the “inescapably sine qua non” of modern democracy (Huntington, 1991: 9).1
Hence, we follow the research tradition adopting a “realistic” understanding of democracy, according
to which democracy is primarily a method that determines access to government power. This
understanding of democracy follows Schumpeter, who defined it as “that institutional arrangement for
arriving at political decisions in which individuals acquire the power to decide by means of a
competitive struggle for the people’s vote” (1976: 269).
1 By emphasizing the electoral qualities of regimes, we do not aim to undermine the importance of other attributes attached
to democracy (e.g., the rule of law). We aim, instead, to promote the disaggregation of regime characteristics and focus on
the mechanisms through which democracy affects peace. However, given the broad agreement about the centrality of
electoral characteristics to democracy and lack of research on their effects on conflict, this aspect should arguably be among
the main foci of research on democracy and peace.
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We suggest that the electoral qualities of regimes are central not only to the concept of
democracy but also to democratic civil peace. To support this claim, we present a theoretical discussion
highlighting the role of electoral contestation (Coppedge, Alvarez & Maldonado, 2008; Dahl, 1971). It
synthesizes four mechanisms through which electoral contestation may influence the incentives for the
opposition to use force. Specifically, constrained electoral contestation can (i) motivate the opposition
to substitute electoral competition with violence, (ii) legitimize the use of anti-government violence,
(iii) “self-select” the opposition recruits into violence, and (iv) hinder the incumbent’s strength.
Building on this framework and extant regime typologies (Diamond, 2002; Howard & Roessler,
2006; Møller & Skaaning 2013), we categorize polities into five “electoral regime” types (political
regimes defined by their electoral characteristics): non-electoral autocracies, single-party autocracies,
multi-party autocracies, minimalist democracies, and polyarchies. Subsequently, we specify hypotheses
on the likelihood of conflict in each.
To shed new light on democracy and civil peace, we employ the new Lexical Index of Electoral
Democracy (LIED) (Skaaning, Gerring & Bartusevičius, 2015). This index simultaneously performs a
classificatory function, each level identifying a unique regime type, and a discriminating function,
distinguishing between different levels of democracy. LIED therefore allows not only assessing
whether democracies are more peaceful than autocracies but also identifying conflict risks in concrete
regime types. Furthermore, spanning 18002013 and including 221 independent polities, LIED has the
most comprehensive coverage among extant indices. This enables us to expand the conventional post-
1945 timespan threefold, to 18172006 (delimited by data on other covariates), substantially widening
the temporal scope of our inferences.
Our analysis demonstrates that polyarchies, characterized by unconstrained electoral
contestation, outperform all other regime types on civil peace. Moreover, we find that hybrid regimes
characterized by at least nominal electoral competition are more peaceful than autocracies without
elections. These findings suggest that democracy—understood in the electoral senserelates to civil
conflict in a negative monotonic way. Our disaggregated analysis also reveals two particular factors
that are most strongly associated with civil peace: the presence of (any form of) elections and minimal
electoral competition.
Altogether, this study contributes to the literature on political regimes and conflict in the
following ways. Conceptually, it underscores that research on democratic civil peace must focus on the
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central attributes of democracy—not correlates of it (e.g. state capacity). Theoretically, it sheds new
light on the mechanisms through which particular regime characteristics, as contrasted to aggregate
categories, can influence conflict. Empirically, it identifies conflict risks in regime types that represent
qualitatively meaningful and ordered categories, generating substantive insights into the relationships
between particular electoral characteristics and conflict.
More generally, our study contributes to an emerging effort to disaggregate political regimes,
arguably a prerequisite for the progress in research on democratic civil peace. In a recent literature
review, Ari, Gleditsch, Hegre, and Wig (2016: 4) noted that
…we know less about the causal mechanisms tying specific aspects of institutions to conflict
outcomes. Disentangling the highly aggregated categories of democracy and
democratization…seems a promising avenue for progress…One potentially fruitful strategy is to
unpack the ‘black box’ of aggregated democracy measures and investigate which regime-type
dimensions are conductive to peace.
While similar calls to disaggregate political regimes have appeared in previous research
(e.g., Gleditsch & Ward 1997), few studies have attempted to address these concerns. One
exception is Gleditsch & Ruggeri (2010).2 Criticizing the use of democracy indices as proxies
of state capacity, they propose an alternative measure and show how it affects civil conflict.
Further, controlling for state capacity, they identify a negative monotonic relationship between
their democracy measure (adjusted Polity Index) and conflict. While the Gleditsch and Ruggeri
study convincingly isolates the effects of state capacity from democracy, it sheds little light on
the actual features of democracy that influence peace. Here, we explicitly pursue this aim:
holding state capacity constant, we investigate the disaggregated features of democracy that
account for democratic civil peace.
2 Other examples include Fjelde (2010) and Goldstone et al. (2010). However, the former exclusively focuses on autocracies
(therefore only covering part of the democracy‒peace nexus), while the latter focuses on regime features that best predict
political instability (without considering their theoretical relevance or centrality to democracy). Also, Goldstone et al. use
subcomponents from Polity Index, aggregating them in a way that prevents the identification of particular institutional
features accounting for conflict.
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Research on political regimes and civil conflict
The democratic civil peace hypothesis has inspired numerous studies on political regimes and civil
conflict (Auvinen, 1997; Dunning, 2011; Fearon & Laitin, 2003; Fjelde, 2010; Gleditsch & Ruggeri,
2010; Goldstone et al., 2010; Hegre et al., 2001; Henderson & Singer, 2000; Muller & Weede, 1990;
Reynal-Querol, 2002). Many have stressed that democracies experience fewer political grievances than
other regimes, as they are less repressive, more politically inclusive, and tolerant. While this does not
imply the absence of societal discontent (as grievances may arise from other sources, e.g., the
economy), fewer political grievances lead to fewer reasons for politically motivated, state-targeted
action (Buhaug, 2006: 696).
Even if grievances arise, democracies can address them non-violently. Democratic institutions
(e.g., elections and legislatures) provide opportunities for contenders to pursue their interests and voice
discontent. While such institutions foster political competition, they offer a major—arguably more
attractive—“substitute” for political violence (Dunning, 2011: 329332; Gleditsch & Ruggeri, 2010:
301); the more competitive the democratic institutions, the less likely that the opposition pursue their
interests violently.
Some scholars have claimed, however, that full autocracies may be just as (or even more)
peaceful than full democracies (Buhaug, 2006; Goldstone et al., 2010). Due to constrained political
competition, corruption, and violations of human rights, autocracies generate more grievances than
democracies, but they can effectively subdue them with force. While democracies can also use force
against their citizens (e.g., to subdue illegal opposition), autocrats can do so more extensively because
they rely less on popular support to remain in power (Hegre, 2014:163).
While full democracies have the means to accommodate contenders and full autocracies possess
the means to repress them, hybrid regimes often lack both, leading to the highest risk of conflict. The
inconsistent nature of such regimes is the culprit. By mixing a level of repression that is not
comprehensive enough to quell the opposition with some degree of political competition that is not
sufficient to fully accommodate the opposition, anocracies both motivate violence and fail to counter it
(Henderson & Singer, 2000: 279280; Muller & Weede, 1990: 627; also Hegre et al., 2001: 33).
Empirical research has tended to support these claims. Numerous studies have shown that full
democracies are least likely to experience conflict (e.g. Gleditsch & Ruggeri, 2010; Hegre et al., 2001),
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others that full autocracies may be as peaceful as full democracies (Buhaug, 2006; Goldstone et al.,
2010). Yet most studies have converged on the finding that anocracies are the most conflict-prone
(Auvinen, 1997; Fearon & Laitin, 2003; Hegre et al., 2001; Henderson & Singer, 2000; Muller &
Weede, 1990; Reynal-Querol, 2002), suggesting that the regime typeconflict relationship follows an
inverted U.
However, Vreeland (2008) has shown that previous research has suffered from an endogeneity
problem: the middle values of Polity Index (Marshall, Gurr & Jaggers, 2016), a proxy of democracy
used by most studies to identify anocracies, by definition partly reflect violence (see also Strand, 2007).
Removing the elements of violence from the index, the middle values seem not to be associated with
conflict. Moreover, Vreeland has shown that substituting the revised Polity Index (“xPolity) with
alternative measures makes little difference: anocracies have no greater risk of conflict than other
regimes (see also Gleditsch & Ruggeri, 2010; Trier & Jackman, 2008).
Yet the results based on xPolity and other graded indicators of democracy suffer more
fundamental problems. To disentangle the anocracyconflict relationship, we must first clearly define
anocracies themselves (Ari et al., 2016: 5). Available indicators of political regimes, however, paint a
different picture: they merely provide a score reflecting the overall level of democracy without linking
specific characteristics to the different levels. While a country with a value of 6 on the Polity scale is
considered more democratic than a 5, this score tells us little about the actual qualitative differences
between the two regimes.
Furthermore, the graded measures of political regimes are aggregates of many sub-components,
and different combinations of values often lead to the same aggregate scores (Cheibub, Gandhi &
Vreeland, 2010; Gleditsch & Ward, 1997). Thus, a country scoring low on competitiveness of
executive recruitment and high on executive constraints might have the same overall score as another
scoring high on competitiveness of executive recruitment and low on executive constraints.
Consequently, such ‘mashup indices’ (Ravallion, 2011) generate heterogeneous pools of autocracies,
democracies, andparticularlyhybrid regimes.
These problems have prevented the identification of the exact regime features associated with
conflict. Fortunately, recent developments in regime data collection have turned towards greater
disaggregation, producing data suitable for our research goal. We present these data in the subsequent
section; we now establish a theoretical link between electoral regimes and conflict.
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Electoral contestation and civil conflict
As emphasized, understanding the relationship between the electoral characteristics of regimes and
civil peace is essential to understanding the democracypeace nexus. This follows from the concept of
democracy, where elections constitute the essential core (Huntington, 1991: 9; Schumpeter, 1976: 269).
The key electoral elements are national elections for the legislature and (directly or indirectly) the
executive, participation of multiple parties/candidates, and uncertainty about the outcome (Przeworski
et al., 2000: 1516). Together with freedom of expression, which supports the meaningfulness of
elections, these elements pertain to what Dahl (1971) has labelled contestation” (see also Coppedge,
Alvarez & Maldonado, 2008). Accordingly, we posit that the arguments linking democracy to conflict
should center on these core features.
Dahl (1971) refers to an additional electoral dimension: inclusiveness (or participation). Here,
however, we exclusively focus on contestation. Variation in inclusiveness is almost absent after 1945,
undermining the relevance of this dimension for understanding contemporary civil conflicts. More
importantly, a unidimensional focus on contestation ensures better alignment between our concepts,
theory, and measures (Coppedge, Alvarez & Maldonado, 2008). Analyzing both dimensions would
involve specifying the theoretical mechanisms pertaining to each, how they interact in producing
conflict, and testing their separate (or interacting) effects in empirical analysis. Here, trading
extensiveness for relevance and parsimony, we exclusively focus on contestation.
Electoral regimes and electoral events
In our framework, political regimes3 are distinguished by the presence/absence of periodic elections
and their competitiveness; i.e., whether opposition groups are allowed to compete in elections, have a
chance of winning, and enjoy freedom of expression. While we use elections to categorize political
regimes (hence, ‘electoral regimes’), we do not focus on the short-term effects of electoral events on
violence. Instead, we focus on the sustained effects of electoral regimes, which affect the behavior of
opposition actors beyond the actual electoral events. For example, if regimes allow periodic electoral
3Political regimesrefer to the sets of formal and informal political institutions regulating the access to political power (see
Mazzuca, 2010).
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competition, opposition actors are incentivized to await elections and pursue their interests non-
violently between them (via political parties, lobbyism, etc.). Conversely, if regimes constrain electoral
competition, opposition actors are dis-incentivized to wait, instead contesting power violently between
elections (see also Harish & Little, 2017).
Studies have shown that electoral events in non-democratic regimes increase the risk of ethnic
civil war (Cederman, Gleditsch & Hug, 2013), recurrence of civil conflict (Brancati & Snyder, 2013),
and small-scale civil violence (Salehyan & Linebarger, 2015). However, these effects have primarily
been attributed to the short-term prospects for mobilization around electoral events (Cederman,
Gleditsch & Hug, 2013: 390; Salehyan & Linebarger, 2015: 26, 30; see also Kuntz & Thompson, 2009:
254), which do not exist between elections. Hence, while electoral events and regimes are intrinsically
related (i.e. the former defines the latter), their immediate and transient effects on peace are likely
different.
In a related study of regime survival, Knutsen, Nygård & Wig (2017) suggest that elections
serve as “focal points” for mobilizing opposition. Mobilization in autocracies constitutes a typical
collective action problem: people are reluctant to express their grievances due to fear of punishment
and lack of knowledge as to whether others share their grievances. The salient political nature and
time-limited character of elections renders overcoming such collective action problems possible,
increasing the prospects of coordinated regime challenge. Yet elections and associated institutions (e.g.
parties and legislatures) also provide information, legitimacy, and means for cooptation for the
incumbents, which, in the longer run, prevent anti-government challenge. In extensive empirical
analysis, Knutsen, Nygård & Wig find that electoral events indeed increase the immediate risk of
regime breakdown, whereas periodic elections stabilize autocracies in the longer term.
Focusing more directly on civil violence, Harish & Little (2017) present a formal model
suggesting a similar pattern. Their model builds on the same assumption that elections generate
favorable opportunities for mobilization, thereby increasing the effectiveness of violent, anti-
government action. Aware of this, the opposition should refrain from using violence between elections
and displace it instead to electoral events. Compared to a baseline without periodic elections (where the
effectiveness of anti-government violence is more constant), long non-electoral periods intersected with
short electoral events should lead to a net positive effect on peace.
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Electoral regimes are thus likely to have separate effects (from electoral events) on conflict. The
likelihood of conflict, however, depends not only on the presence/absence of periodic elections but also
on the actual qualities of regimes.
Electoral regime types and incentives for violence
To explain the electoral regimeconflict relationship, we take the perspective of opposition and focus
on the following mechanisms: (i)substitution,” (ii) legitimacy of anti-government violence, and (iii)
self-selection.” While discussing electoral autocracies, we also consider (iv) how elections and
nominal electoral institutions (parties, legislatures, etc.) can strengthen the incumbents and prevent
anti-government violence. Below, we first introduce the general mechanisms and then elaborate in
detail how they operate in the context of particular regime types.
Non-violent institutional action (e.g., election participation) involves fewer costs than violent
non-institutional action (civil conflict) due to the resources and risks involved in armed conflicts.
Unlike election participation, an armed conflict with a government requires extensive finances, arms,
and recruits, sufficiently motivated to risk injury and death (Hendrix, 2010: 274). Chenoweth &
Stephan (2011: 3239) highlight how violent rebellions face greater obstacles to recruitment—due to
the risks and costs associated with armed conflicton average attracting many times smaller
membership than non-violent campaigns. Hence, we assume that a non-violent institutional action4 is
preferred to a violent non-institutional one when the probability of success of the two actions is at least
on par. We define the success of an opposition action broadly as gaining access to government power
or changing the incumbent’s policies.
The probability of the success of non-violent institutional action should vary positively with
contestation. If incumbents allow electoral competition, non-violent action may be an effective choice,
whereas violent action may be more attractive if incumbents restrict electoral competition. Thus,
‘fighting and voting can be seen as strategic substitutes’(Dunning, 2011: 329), and free competition
should incentivize participation in elections by increasing the opposition’s probability of success of
gaining access to power via electoral means. Further, post-conflict literature highlights how democratic
4 In such contexts, non-violent non-institutional action (e.g., protest) is also an option and actually more likely to succeed
than violence (Chenoweth & Stephan, 2011; Schock, 2005). However, our focus here is on the choice between routine
politics and armed conflict; therefore, we do not address non-violent, non-institutional alternatives to violence.
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institutions mitigate commitment problems among the opposition (e.g. Brancati & Snyder, 2013;
Durant & Weintraub, 2014; Flores & Nooruddin, 2012; Matanock, 2017). When elections occur in
post-conflict settings, ex-warring parties are uncertain about each other’s willingness to comply with
the formal electoral process, resulting in neither side credibly committing to the elections and a higher
risk of conflict recurrence. Such commitment problems can be mitigated by fair electoral competition
(Flores & Nooruddin, 2012: 5612) accompanied by institutions ensuring compliance with elections
(e.g., professionalized bureaucracies, impartial courts, and free media; see Brancati & Snyder, 2013:
82931) or particular electoral design constraining the executive and enabling “the rule of law for
elites” (Durant & Weintraub, 2014: 527). This arguably generalizes to non-post-conflict settings, where
constrained contestation results in uncertainties regarding the respect for electoral outcomes, dis-
incentivizing the opposition from committing to elections and increasing the chance of substitution
with violence.
The probability of the success and costs associated with non-violence/violence also depends on
the legitimacy of anti-government violence. If everyone can pursue interests via the same institutional
means and elections constitute the sole legitimate path to power, violence against incumbents may be
unpopular—and therefore costly and ineffective (Buhaug, 2006: 696; also Cheibub & Hays, 2017: 91).
Conversely, if only particular political actors are allowed to compete for power (e.g., as in single-party
regimes) and electoral competition provides little chance of gaining access to power, anti-government
violence may have popular support and be more likely to succeed. In cases where elections and
legislatures are entirely absent, incumbents cannot even play the “popular legitimacy card,” as there are
simply no institutions for popular representation (Shock, 2005).
When electoral competition is constrained or banned, opposition often operates underground,
which involves multiple barriers that do not exist while joining legal organizations such as political
parties in democracies. Chenoweth & Stephan (2011) discuss such barriers in the context of violent
campaigns, many of which can be generalized to the context of underground activities (violent or not).
Like joining an armed fight, membership in illegal opposition entails higher risks and costs (e.g.,
capture and imprisonment) than membership of legal organizations. Furthermore, given their
clandestine nature, would-be members have limited information about the groups they join, meaning
higher uncertainty (about the size and strength of the group, its goals, etc.). Because of their secret
character, underground groups themselves must follow careful recruitment practices, selecting only
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those with high resolve, reliability, and other qualities pertaining to clandestine activities. Prospective
members must therefore be highly motivated and willing to take risks. Arguably, such qualities are
conductive to violence. Individuals committing to illegal underground groups are likely to be more
risk-taking and less averse to anti-government violence. Thus, compared to legal political
organizations, clandestine opposition groups should be staffed with people more likely to accept and
use political violence, “self-selecting” into conflict.
The discussion above thus suggests a general pattern: constrained electoral contestation
incentivizes opposition actors to use force, implying that the probability of civil conflict is negatively
associated with electoral contestation (H1).
We now detail each of the mechanisms in the contexts of particular regime types, categorized
based on different degrees of contestation. In line with extant typologies of electoral regimes
(Diamond, 2002; Howard & Roessler, 2006; Møller & Skaaning, 2013), we distinguish between five
generic categories: non-electoral autocracies (no elections); single-party autocracies (single-party
elections); multi-party autocracies (multi-party non-competitive elections); minimalist democracies
(multi-party competitive elections); and polyarchies (multi-party competitive elections with freedom of
expression).
As the label implies, non-electoral autocracies hold no national elections (e.g., present-day
Saudi Arabia, Qatar) or postpone them for an unknown length of time (Philippines under Marcos’
martial law, present-day Eritrea). In such contexts, opposition actors are incentivized to use force; yet,
doing so can incur great costs. As electoral institutions are absent, the incumbents must engage the
opposition using other means, usually repression (Davenport, 2007: 490; Fjelde, 2010: 200), which can
take extensive forms, since regime survival rests less on popular support (Hegre, 2014: 163; Schock,
2005: 3132, 4950).
This has led previous research to claim that full autocracies are “peaceful”; however, there is
good reason to doubt this claim. If repression effectively prevented violence, highly repressive regimes
would have little conflict. History reveals this hardly to be the case. The top-10 countries in the
Correlates of War data (elaborated below) with the highest incidence of large-scale civil war (Sudan (N
= 34), Philippines (31), Colombia (29), Burma (27), Indonesia (26), Angola (24), Sri Lanka (22),
Ethiopia (19), Chad (18), and Afghanistan (16)) are/were some of the most repressive in the world.
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Highly repressive states free of conflict do exist (e.g. Saudi Arabia), but such cases are atypical
regarding wealth and state capacity. Unlike the cases above, states like Saudi Arabia can afford a large,
professional security apparatus capable of maintaining order. Indeed, state capacity, backed with a
strong economy, features as key factors preventing anti-government violence in the qualitative
literature (e.g. Bellin, 2004). Large-N studies on political regime and conflict also tend to focus on
state weakness,’ highlighting the role of state capacity in identifying and subduing anti-government
mobilization (e.g. Fearon & Laitin, 2003).
The low likelihood of conflict in full autocracies, as identified in previous research, might
therefore be due to state capacity, a feature that is not a conceptual attribute of democracy (e.g.
Mazzuca, 2010).5 Indeed, we see little theoretical reason why fully autocratic regimes—understood in
the electoral sense—should be peaceful. Given that institutional competition over power is entirely
absent, the incentives to substitute it with violence should be greater and have greater popular support
than in any other regime type. Further, given that political opposition is entirely banned, most regime
contenders must operate underground, attracting members more likely to accept and use anti-
government violence. Thus, we expect that non-electoral autocracies have a higher risk of conflict than
any other electoral regime type (H1a).
The discussion above suggests that H1a should be tested while controlling for state capacity,
but how exactly does state capacity relate to democracyor, more importantly, to electoral features of
regimes—and civil war? Arguably, the choice to introduce elections depends on the incumbents’
capacity to repress opposition. Bellin (2004: 146) and Fjelde (2010: 199) highlight that repression is
rather costly and that only high-capacity states can exclusively rely on it to quell the opposition. If state
capacity is low and resources are insufficient to coerce opponents to “peace,” incumbents must
introduce elections. Likewise, the competitiveness of such elections depends on the incumbents’
capacity to repress: the lower the capacity, the more competitive the election required. Thus, we must
hold state capacity constant to identify the association between electoral regimes and conflict. The
interplay between state capacity and electoral competition is an interesting question in its own right.
5 Previous research on political regime and conflict has controlled for GDP/cap (which partly proxies for state capacity) and
yet found that full autocracies were less prone to violence than anocracies (or even democracies). Virtually all studies
finding such a pattern, however, relied on the problematic Polity Index. Analyses based on xPolity or alternative measures
have not found anocracies to be more violent than other regimes. Indeed, controlling for irregular leader change, a more
direct proxy of state capacity, Gleditsch & Ruggerri (2010) find that democracy is associated with conflict in a negative,
monotonic way (consistent with H1a).
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Yet our focus here is on electoral features of regimes, categories conceptually most central to
democracy.
Civil conflict research often treats electoral autocracies as transitional regimes, but research on
electoral authoritarianism suggests that this regime type is often a deliberate choice aimed at
undermining the opposition and keeping autocrats in power. Regular elections and nominal legislatures
can serve as effective institutional settings to coopt challengers, for example, via spoils allocated
through ‘electedseats (Boix & Svolik, 2013; Gandhi & Przeworski, 2006). Autocrats can also use
electoral campaigns to signal strength: “By rolling out an impressive electoral campaign machinery and
whipping up popular support, the regime credibly signals to (1) the opposition that armed
confrontations are futile and (2) the internal elite that coups will be opposed by numerous supporters”
(Knutsen, Nygård & Wig, 2017: 103; also Cheibub & Hays, 2017). Elections can also help reveal the
strength of challengers (Little 2012) and identify them—and they can then be repressed, discredited, or
coopted (Magaloni 2008: 71). Finally, incumbents can use elections and parties to channel popular
mobilization into regime-supportive activities and to create forums where “political aspirations and
demands from competing factions can be discussed [within regimes’ parties] without challenging the
foundations of the regime” (Fjelde, 2010: 199; also Davenport, 2007: 491; Gandhi & Przeworski,
2006). Altogether, this suggests that nominal democratic institutions can help autocrats to “divide and
rule,” weakening the opposition and preventing anti-government violence.
From the opposition perspective, electoral autocracies can also reduce incentives for violence.
Compared to non-electoral regimes, the spectrum of means to compete over power increases with one
additional choice (Shock 2005: 15). While they do not allow the opposition to gain actual power,
nominal democratic institutions do provide a ‘venue within which discussion/aspirations/activism can
take place—in a sense, it may be the only ‘show in town’, but at least there is a show’ (Davenport,
2007: 490). Elections in autocracies can even result in some degree of popular representation. In
Vietnam, for example, a single-party regime, constituency delegates not only raised issues relevant to
their constituents in the national assembly but also directly questioned the performance of the executive
branch (Malesky & Schuler, 2010).
Additionally, elections and associated institutions, even if only nominal, can improve the
legitimacy of incumbents (Schedler, 2002), thereby undermining support for anti-government violence.
Further, in some (multiparty) electoral autocracies, opposition actors are formally allowed to organize
14
and campaign. Compared to underground groups, legal opposition parties have a more diverse
membership base, which is less likely to accept (or be motivated to use) anti-government violence.
Hence, electoral autocracies should generally be less prone to conflict than non-electoral regimes.
Electoral autocracies come in two basic forms: single-party, where access to power is
constrained by banning opposition parties (e.g. present-day Cuba, Vietnam) and multi-party, where
competition for power is constrained via informal mechanisms such as intimidation, bribery, and
electoral manipulation (e.g., present-day Russia, Zimbabwe). Based on our conceptual framework, we
consider non-electoral autocracies, single-party autocracies, and multi-party autocracies as representing
three different levels of electoral contestation. On this basis, we hypothesize that single-party
autocracies have a lower probability of conflict than non-electoral autocracies (H1b) and that multi-
party autocracies have a lower probability of conflict than single-party autocracies (H1c).
However, the difference in the risk of conflict in single- and multi-party autocracies may not be
substantial. While multi-party autocracies, unlike single-party regimes, allow the opposition to organize
in parties and compete in national elections, thereby reducing incentives for (and delegitimizing) anti-
government violence, electoral competition in multi-party autocracies remains constrained, providing
incentives for (and legitimizing) anti-government violence. Further, formally allowed to organize and
campaign, opposition actors in multi-party autocracies have better opportunities to mobilize (e.g.
Fjelde, 2010: 201). Such opportunities are also greater because multi-party settings provide less
effective institutional context for monitoring, coopting, and repressing the opposition (Davenport,
2007; Fjelde, 2010). Counter-acting mechanisms may therefore be at play, generating similar net
likelihood of conflict in single- and multi-party autocratic regimes.
The only reliable way to reduce the incentives for anti-government violence is, thus, to allow
credible competition over power via non-violent institutional means. In such contexts, citizens are also
less likely to accept violence against a democratically elected government, and opposition actors are
more likely to consist of diverse memberships, less willing to use anti-government violence. Thus, we
hypothesize that regimes with minimally competitive elections have lower probability of conflict than
multi-party autocracies (H1d).
Finally, we expect polyarchies—regimes where freedom of expression strengthens electoral
competition—to have the lowest risk of conflict. In such regimes, citizens can express their preferences
without undue restrictions. This increases the credibility of electoral processes and contestation more
15
broadly, further strengthening the legitimacy of regimes and reducing incentives for violence to a
minimum. Thus, we hypothesize that polyarchies have a lower probability of conflict than any other
electoral regime type (H1e).
Research design
We initially tested the hypotheses in a standard country-year logistic regression. The sample included
all annual observations of states as listed in the LIED dataset (which are based on Gleditsch and
Ward’s list of independent states; see Skaaning, Gerring & Bartusevičius, 2015: 1502). In robustness
checks, we implemented a number of additional analyses, including tests with alternative measures of
the key variables and alternative analysis techniques.
The Lexical Index of Electoral Democracy
To measure electoral regimes, we employed the Lexical Index of Electoral Democracy (LIED)
(Skaaning, Gerring & Bartusevičius, 2015), which allows testing our hypotheses more directly than
other indicators of democracy. LIED exclusively focuses on electoral regimes features and adheres to
the minimalist definition of democracy: ‘regime where leaders are selected through contested elections
held periodically before a broad electorate’ (Skaaning, Gerring & Bartusevičius, 2015: 1495). The
index combines dichotomous indicators of different regime qualities in a systematic fashion, where a
series of necessary and jointly sufficient conditions are arranged in a 7-level ordinal scale: (0) no
elections; (1) no-party/single-party elections; (2) multiparty elections for legislature; (3) multiparty
elections for legislature and executive; (4) minimally competitive, multiparty elections for legislature
and executive; (5) minimally competitive, multiparty elections with full male or female suffrage for
legislature and executive; (6) minimally competitive, multiparty elections with universal suffrage for
legislature and executive.
The second level has very few observations and offers little relevant nuance regarding
theoretical distinctions.6 Hence, we collapsed it with the third level to form the multi-party autocracy
6 This category primarily covers cases with non-competitive multi-party elections for the legislature where the executive is
not accountable to the electoratetypically regimes where a government is appointed by a monarch (rather than an elected
parliament) (e.g. present-day Kuwait, Morocco), and transitional regimes with presidential systems where parliamentary
elections have not yet been followed by executive elections.
16
category. The two highest levels concern electoral inclusiveness. Since we exclusively focus on
contestation, we combined them with the original fourth to form the minimalist democracy category.
The original index does not explicitly account for freedom of expression. One could thus argue
that the highest level potentially covers some hybrid regimes (e.g. Diamond 2002; Schedler 2002). We
therefore introduced an additional category that supplements the criteria for minimalist democracy with
a high degree of respect for freedom of expression. This addition qualifies the competitiveness of
elections and signifies a continuous check on government powers. As such, the index accounts for all
of the aspects of Dahl’s contestation, and includes five categories:
L0 = no elections (non-electoral autocracy)
L1 = no-party or single-party elections (single-party autocracy)
L2 = multiparty elections for legislature and (direct or indirect) executive (multiparty autocracy)
L3 = minimally competitive, multiparty elections for legislature and (direct or indirect)
executive (minimalist democracy)
L4 = minimally competitive, multiparty elections for legislature and (direct or indirect)
executive and extensive freedom of expression (polyarchy)
The coding of L0L2 is clear-cut, as the corresponding features are directly observable;
however, the coding of minimally competitive elections is based on more elaborate rules. LIED follows
the three criteria for contestation outlined by Przeworski et al. (2000: 16): ex-ante uncertainty
(elections are sufficiently free to allow the opposition a chance of winning), ex-post irreversibility (the
winners take office), and repeatability (the electoral regime is not interrupted). However, whereas
Przeworski et al. exclusively rely on government turnover under the same electoral rules as an indicator
of contested elections, LIED also includes information from country-specific sources about voter
intimidation and electoral fraud (Skaaning, Gerring & Bartucevičius 2015: 1501).7
To operationalize freedom of expression, we employed the Global Media Freedom Dataset
(WhittenWoodring & Van Belle, 2017), which distinguishes between three degrees of media freedom,
the highest signifying “criticism of government and government officials is a common and normal part
7 This procedure is similar to that used by Boix, Miller & Rosato (2013). For a detailed account of the coding procedures
and examples, see Møller & Skaaning (2015).
17
of the political dialogue in the mediated public sphere.” For observations with minimally competitive
elections not covered by this dataset, we implemented additional coding based on the same criteria
using country-specific sources.
In contrast to the Polity and Freedom House measures, violent conflict is not directly captured
by any of the LIED components. Civil conflict can influence whether elections take place and reduce
their competitiveness, but minimally competitive elections can co-exist with civil war, as many of the
examples in the dataset signify. Together with the lag structure of our empirical model, the risk of
endogeneity related to this issue is arguably small (at least smaller than in prior research).
LIED combines different features into regime types based on theoretical considerations over the
centrality of particular features to the concept of electoral democracy. This cumulative ordering implies
that the index performs both classificatory (each level connects to a particular combination of regime
features) and discriminating functions (distinguishing between levels). Hence, the modified LIED
allows not only assessing the overall relationship between democracy and conflict but also identifying
the associations between particular configurations of institutional characteristics (e.g., non-competitive
multiparty elections) and conflict.
Outcome variable
LIED covers 18002013, expanding the conventional post-1945 time-span threefold. This allows us to
substantially widen the temporal scope of our inferences and account for factors related to particular
historical periods (due to limited data on other covariates, the final analysis spans 18172006). To
match this scope on the left side of the equation, we employed the data on civil wars (Categories 45)
from the Correlates of War (COW) Intra-State War Data (4.1) (Sarkees & Wayman, 2010). COW
defines civil war as sustained combat between a state government and non-state actor(s) resulting in at
least 1000 battle-related deaths annually and taking place within the state territory. Since we focused on
civil war onset, country-years after the onset year were set to 0 (the data contains new civil war onsets
during ongoing years of other civil wars in the same countries). Following conventions, we also applied
the two-year intermittency rule. The final sample included 282 separate onsets (Table I reports civil
war incidence for different regimes in different periods).
------------------
Table I in here
18
------------------
Control variables
We limited control variables to the likely confounders (i.e. potentially relating to both electoral regimes
and civil war). To avoid missing observations and potential collinearity problems, we only included the
most likely confounders identified in the literature: wealth, economic growth, oil wealth, state capacity,
political regime characteristics unrelated to elections, and instability.
Wealth and economic growth have been linked both to democracy (e.g. Przeworski et al., 2000)
and conflict (e.g. Hegre & Sambanis, 2006). Therefore, we introduced the natural log of GDP/cap and
annual GDP/cap growth (both lagged). Data on GDP/cap came from Bolt & van Zanden (2013). While
theirs is the most complete data on GDP/cap for our analysis period, it contains missing observations.
Therefore, we applied a standard interpolation procedure to impute values between available
observations, increasing the number of observations from 10,125 to 11,479. Excluding interpolated
values from the analysis below does not affect our substantive findings. Furthermore, research has
shown that democracy negatively relates to energy resource wealth, particularly oil, and that oil wealth
positively relates to conflict (e.g. Ross, 2012). We therefore controlled for the total oil income per
capita from Haber & Menaldo (2011) (lagged).
As argued above, the relationship between political regime and conflict can also be confounded
by state capacity. Therefore, we introduced the Composite Index of National Capability (CINC) from
the National Material Capabilities dataset (Singer, 1987) (lagged). CINC is based on the values of total
population, urban population, iron and steel production, energy consumption, military personnel, and
military expenditures. We also used the CINC sub-component: military personnel. This measure
accounts more directly for a state’s military capacity and, by extension, its repressive strength.
The electoral qualities relate to other characteristics of regimes that may confound the
relationship of interest. Therefore, we also included the Polity2 index from the Polity IV project
(Marshall, Gurr & Jaggers, 2016). As some of its sub-components reflect quality of elections and
political competition, Polity2 partly overlaps with LIED.8 Yet Polity2 also captures non-electoral
features of regimes, such as factionalism and constraints on the executive that may confound the
LIEDcivil war relationship.
8 We are aware of potential collinearity issues. Collinearity diagnostics indicate that mean VIF scores = 1.76 (max = 3.68).
Removing Polity2 from the models does not alter our substantive findings.
19
To assess whether the relationship between electoral regimes and conflict is not driven by
changes in electoral regimes, we also introduced a measure of regime change/instability. For the full-
sample analysis, we used a measure indicating whether a country experienced a one-point increase or
decrease in LIED in the preceding three years (alternatively, in the preceding year). For analysis of
post-1945 data, we used democratization and autocratization measures (1- and 3-year versions) from
Cederman, Hug & Krebs (2010).
We also controlled for population size (ln) with data from Singer (1987) and temporal
dependence with cubic polynomials (Carter & Signorino, 2010).9 Robustness tests included other
potential confounders. The Online Appendix provides summary statistics.
While we control for likely confounders, apply fixed effects and time-lags, we cannot entirely
rule out the possibility of recursive effects and omitted variable bias. In OA (Tables OA6OA7 and
Figures OA1OA3), we therefore report an analysis of factors associated with LIED.
Results
Main analyses
Table II reports the main results. We first tested H1, treating LIED as an interval/ratio variable.
Subsequently, we tested H1aH1e, using a ‘dummy-coded’ version of LIED, treating each level as a
separate category.
LIED has a negative, highly significant coefficient when regressed separately.10 The same is
true when LIED is regressed together with the controls. Results also remain similar when using the
alternative measures of capacity and instability described above (not reported here). Turning to the
dummy-coded version of LIED (Model 8), we find that, compared to non-electoral autocracies, all
regime types have significantly lower risk of civil war, with coefficients larger for higher LIED scores.
The coefficient for polyarchy, however, should be treated with caution, as there are only two civil war
onsets in such regimes in the whole sample (addressed below using alternative measures of conflict).
9 To test for model misspecification, we compared standard errors to robust and clustered standard errors of the
specifications discussed below (King & Roberts, 2015), and found no sizable differences.
10 We use “significant” for estimates significant at 10%.
20
Due to combined missing observations among the covariates, Models 78 contain 10,115
observations of a possible 16,153. While such missingness is not untypical (even for post-1945
analyses), we attempted to increase the sample by removing GDP/cap and growth, covariates with most
missing values (note that state wealth is partly controlled for by the remaining CINC). This generated
1,327 additional observations, further strengthening the association between LIED and civil war
(Models 910).
In Models 8 and 10, the base category is non-electoral autocracy. A stronger test of H1aH1e is
a successive comparison of each regime type to one level below. Model 11 shows results with GDP/cap
and growth included back in the block. The coefficients for single-party autocracies, minimalist
democracies, and polyarchies remain significant. In contrast, while significant when compared to the
base category of non-electoral autocracies, the coefficient for multi-party autocracy turns insignificant
when compared to single-party autocracy. Before discussing these results in the next section, we now
turn to robustness tests.
------------------
Table II in here
------------------
Robustness tests
An almost-200-year timespan increases the scope of our inferences and allows ruling out the possibility
that these findings are confounded by idiosyncrasies of particular periods. However, electoral regimes
and their links to conflict are potentially different now than 200 years ago, pointing to potential
heterogeneity problems. To address this, we limited the sample to post-1945.
Table OA2 (appendix) reports the estimates. The coefficient of the interval LIED remains
significant at 0.1% despite the sample size dropping to 6,823 and the number of civil wars from 232 to
134. The estimates for the dummy LIED are similarly in line with previous results. All regimes have
lower risk of civil war than non-electoral autocracies (although the coefficient for single-party
autocracy is now above 10%).
Analyzing post-1945 allows exploring additional confounders. Recent research has identified a
robust relationship between horizontal inequalities and civil conflict (e.g. Cederman, Gleditsch &
Buhaug, 2013). Horizontal inequalities may also be associated with electoral qualities of regimes, as
political and economic discrimination is often maintained by constraining contestation. Therefore, we
21
controlled for horizontal ethno-political inequality—captured by “max discrimination (the relative
demographic size of the largest ethnic group subject to active discrimination)—and horizontal
economic inequality, proxied by “max low ratio (the relative income gap between the poorest group
and the national average). Following previous research, we also controlled for inequality and ethnic
diversity in the total population with Gini coefficient and an ethnic fractionalization index. The four
indices come from Cederman, Gleditsch & Buhaug (2013). The estimates for our key variable
essentially remain the same. All LIED levels also have significant coefficients (the coefficient for
single-party autocracy is now significant at 5%). As previously, a stronger test comparing each regime
type to one level below indicates that all levels, besides L2 (multi-party autocracy), have significant
coefficients.
We subsequently introduced alternative measures of the dependent variable (Table OA3). First,
we substituted the COW civil war with internal war from the UCDP/PRIO Armed Conflict Dataset v.4-
2011, 19462010 (Gleditsch et al., 2002; Themnér & Wallensteen, 2011). The coefficient of the
interval LIED remains negative and significant at 5%. Similarly, all levels of LIED retain negative
signs, although the coefficients for single- and multi-party autocracies are not significant when
compared to the reference category, and the coefficient for polyarchy is not significant compared to
minimalist democracy. Second, we substituted the COW category of civil war with a lower-intensity
armed conflict (from the same UCDP/PRIO dataset). The coefficient of the interval LIED remains
negative and significant, although p = 0.059, and the estimate itself is smaller. This difference
potentially pertains to the fact that regime-related factors affect whole populations, having potential to
cause large-scale violence. Conversely, minor conflicts often concern particular segments of
populations, such as peripheral ethnic groups (e.g., Buhaug, 2006) fighting states over their specific
status (not the status of the states). To assess this claim, we replicated our analysis using the
UCDP/PRIO’s governmental war and found that the coefficient of LIEDcompared to the aggregate
categorybecame considerably larger and more significant (Table OA3, Models 17g19g).
As previously, all levels of the dummy LIED have negative signs. The coefficients for single-
and multi-party autocracies remain insignificant compared to the base category, but the coefficient for
polyarchy attains significance compared to minimalist democracy (polyarchies contain eight onsets of
UCDP/PRIO’s internal war and 14 onsets of minor conflict).
22
We also controlled for time-invariant country-level factors via country-fixed effects. Despite a
two-fold reduction of the sample (analysis of full data dropped 83 polities), the estimates correspond to
the previous results (Tables OA4OA5). The interval LIED is negative and significant in all models but
one. In most specifications, all LIED levels also retain negative signs, although only the coefficient for
minimalist democracy is consistently significant across all specifications.
Discussion
The results support our central expectation that contestation positively relates to civil peace. The
analysis of interval LIED suggests that this relationship is potentially linear, concurring with Gleditsch
& Ruggeri (2010: 303) that once we control for state capacity, democracy relates to civil war in a
negative monotonic way. However, Figure 1 demonstrates that this relationship is more complex than
the linear model suggests. Single-party autocracies have a substantially lower risk of conflict than non-
electoral regimes; however, multi-party autocracies only have a slightly lower risk of conflict than
single-party autocracies. Subsequently, minimalist democracies have substantially lower risk of conflict
than multi-party autocracies. This indicates that the key elements accounting for civil peace are the
presence of (any form of) elections and minimal electoral competition. More generally, these results
demonstrate the usefulness of LIED: it allows us to identify conflict risks in particular regime types and
reveal key electoral features that are associated with civil peace.
-------------------
Figure 1 in here
--------------------
These patterns are consistent with our theoretical claims. If electoral contestation is absent, the
opposition has incentives to use force. Elections and associated institutions—even if non-competitive
apparently reduce such incentives, probably because they offer alternatives to violence, facilitate
autocratic divide-and-rule strategies, and diminish acceptance of anti-government violence. The fact
that multi-party autocracies are only slightly less prone to conflict than single-party regimes indicates
that regimes allowing opposition parties but no genuine competition introduce counteracting
mechanisms that partly cancel out the positive effects on civil peace associated with increased political
openness.
23
Irrespective of their form (single- or multi-party), electoral autocracies therefore appear to be
intrinsically conflict-prone (even if less conflict-prone than non-electoral regimes): civil peace is more
likely to prevail when the opposition has a meaningful chance of gaining power via electoral means.
The less constrained the electoral contestation, the less attractive, costly, and illegitimate anti-
government violence. Polyarchies, where electoral contestation is qualified by high levels of freedom
of expression, are therefore least prone to conflict (although not much less conflict-prone than
minimalist democracies).
As hinted above, non-electoral regimes are highly repressive, and the risk of conflict in such
regimes might therefore not pertain to ‘substitution,’ legitimacy, or ‘self-selection,’ but rather to the
repressiondissent link. Contrary to extant claims in the literature, pervasive repression, coupled with
low state capacity, may not only fail to prevent violence but actually provoke it: “an overwhelming use
of coercive force is a costly strategy with a high risk of backfiring. It depletes bases of support and
strengthens the cause of potential conspirators to depose the dictator” (Fjelde, 2010: 199). Additionally,
repression potentially “increases the costs and decreases the anticipated success of nonviolent relative
to violent resistance” (Rørbæk, 2016: 1), further heightening the risk of conflict. We claim not that
alternative or supplementary mechanisms are implausible, noting only that our research design cannot
adjudicate between causal explanations. Large-N cross-national design allows the identification of
patterns consistent with the theorized claims. Identifying the actual mechanisms driving these patterns,
however, requires scaling down and alternative analytical approaches (e.g. congruence analysis or
process tracing).
Irrespective of the actual mechanism accounting for our findings, the patterns revealed in our
analysis lead us to concur with Hegre et al.: “There is a democratic civil peace” and “[t]he most reliable
path to stable domestic peace in the long run is to democratize as much as possible” (2001: 44). Our
analysis indicates, however, that this path may not be smooth—some moves “up the ladder” of
contestation are more promising than others. Apparently, there are two critical thresholds where the
risk of civil war decreases substantially: one between non-electoral and electoral regimes, the other
between regimes with/without competitive elections.
24
Replication data
All analyses were conducted using Stata 14.2. The dataset and do-file for the empirical analysis in this
article, along with the online appendix, can be found at http://www.prio.org/jpr/datasets.
Acknowledgments
This research was supported by grants from the Danish Council for Independent Research (0602-
02208B) and Innovation Fund Denmark (4110-00002B). We thank the editor, the reviewers, and the
participants of 46th Annual Meeting of the Danish Political Science Association (Vejle, October 2014),
56th Annual Convention of the International Studies Association (New Orleans, February 2015), and
the CODE workshop on ‘Political Repression and Violence’ (Aarhus, March 2016) for valuable
comments. We are particularly thankful to Alexander Taaning Grundholm and Jakob Tolstrup for
scrupulous feedback and insightful suggestions.
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29
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HENRIKAS BARTUSEVIČIUS, b. 1986, PhD (Aarhus University, 2014); assistant professor of
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democracy and the rule of law.
30
Tables
Table I. Cross-tabulation: LIED and Civil War onset—historical periods
Civil war
18171880
19462006
18172006
LIED
0
1
0
1
0
1
0
1
L0
1680
27
809
29
1339
55
3828
111
L1
315
11
579
15
1934
30
2828
56
L2
1175
25
1103
19
1548
40
3826
84
L3
337
3
957
3
1739
23
3033
29
L4
300
0
2056
2
2356
2
31
Table II. Logistic regression estimates of civil war onset: 18172006
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
LIED
-0.34***
(0.05)
-0.21***
(0.06)
-0.20**
(0.07)
-0.21**
(0.07)
-0.21**
(0.07)
-0.30***
(0.09)
-0.30***
(0.09)
-0.43***
(0.08)
L1
-0.41*
(0.20)
-0.47*
(0.18)
-0.41*
(0.20)
L2
-0.37+
(0.20)
-0.56**
(0.18)
0.03
(0.22)
L3
-1.09**
(0.33)
-1.59***
(0.31)
-0.71*
(0.29)
L4
-2.02**
(0.62)
-2.66***
(0.54)
-0.93+
(0.55)
Population
0.27***
(0.03)
0.22***
(0.04)
0.22***
(0.04)
0.21***
(0.04)
0.25***
(0.06)
0.24***
(0.06)
0.24***
(0.06)
0.25***
(0.06)
0.25***
(0.05)
0.26***
(0.05)
0.25***
(0.06)
GDP/cap (ipol)
-0.48***
(0.10)
-0.48***
(0.10)
-0.48***
(0.11)
-0.47***
(0.11)
-0.46***
(0.11)
-0.46***
(0.11)
-0.42***
(0.11)
-0.42***
(0.11)
GDP growth(ipol)
-1.76+
(1.06)
-1.71
(1.06)
-1.70
(1.06)
-1.29
(1.09)
-1.21
(1.08)
-1.17
(1.09)
-1.17
(1.09)
Oil income
-0.03
(0.08)
-0.03
(0.08)
-0.03
(0.08)
-0.03
(0.08)
-0.03
(0.08)
-0.16
(0.12)
-0.14
(0.12)
-0.03
(0.08)
CINC
-2.55
(2.14)
-2.71
(2.18)
-2.53
(2.18)
-2.49
(2.15)
-2.94
(2.03)
-2.74
(2.00)
-2.49
(2.15)
Polity2
0.02
(0.02)
0.02
(0.02)
0.03+
(0.02)
0.02
(0.02)
0.04*
(0.02)
0.03+
(0.02)
Instability(3y)
0.14
(0.16)
0.12
(0.16)
0.12
(0.15)
0.10
(0.15)
0.12
(0.16)
Constant
-5.02***
(0.36)
-1.22
(0.80)
-1.32
(0.81)
-1.14
(0.84)
-1.57+
(0.90)
-1.34
(0.92)
-1.45
(0.93)
-1.73+
(0.94)
-4.51***
(0.51)
-4.58***
(0.51)
N
13637
10664
10528
10223
10205
10115
10115
10115
11442
11442
10115
chi2
263.21
240.71
236.47
233.13
233.45
228.61
229.36
235.96
231.22
242.79
235.96
L1 = single-party autocracy; L2 = multi-party autocracy; L3 = minimalist democracy; L4 = polyarchy. Non-electoral autocracy (L0) is the base category in
Models 8 and 10. In Model 11 the base categories are: L0 for L1; L1 for L2; L2 for L3; and L3 for L4 (resulting in four different constants: -1.73+ (0.94); -
2.13* (0.95); -2.10* (0.95); and -2.82** (1.02), respectively). Standard errors in parentheses. Cubic polynomials not reported. +p<0.10, *p<0.05, **p<0.01,
***p<0.001.
32
Figures
Figure 1. Estimated probabilities (with 95% CI) of civil war onset as a function of interval (upper panel) and
dummy-coded LIED. The estimates are based on Models 9, 14 (upper panels) and 10, 15, holding other
variables at their mean values.
0 .01 .02 .03 .04 .05
01234
LIED
Full sample
0 .01 .02 .03 .04 .05
0 1 2 3 4
LIED
Post-1945
0 .01 .02 .03 .04 .05
01234
LIED
0 .01 .02 .03 .04 .05
0 1 2 3 4
LIED
33
Revisiting democratic civil peace: Electoral regimes and civil conflict
ONLINE APPENDIX
Henrikas Bartusevičius, Department of Political Science, Aarhus University
Svend-Erik Skaaning, Department of Political Science, Aarhus University
34
Table OA1. Summary statistics
N
Mean
SD
Min
Max
COW civil war
16153
.0174581
.1309746
0
1
UCDP/PRIO civil war
8179
.0193178
.1376478
0
1
UCDP/PRIO minor armed conflict
8179
.0346008
.1827777
0
1
LIED
16153
1.815267
1.376021
0
4
Population
13814
8.614745
1.751309
2.197225
14.08632
GDP/capita
10125
7.843521
.9685045
5.313206
10.667
GDP/capita(ipol)
11479
7.694867
1.005517
5.313206
10.667
GDP growth
9878
1.887728
6.331687
-61.47274
86.89957
GDP growth(ipol)
11321
.0172097
.0652825
-.6147274
1.903334
Oil income
13258
.3259811
2.597221
0
78.5888
CINC
13815
.0134944
.0374784
2.43e-07
.3838635
Personnel
13464
3.365309
1.887183
0
9.433564
Polity2
14450
-.8096194
6.993453
-10
10
Instability(3y)
16153
.2123445
.40898
0
1
Instability
16153
.0836996
.2769454
0
1
Democratization(3y)
6479
.0839636
.2773546
0
1
Autocratization(3y)
6479
.0461491
.2098241
0
1
Democratization
6863
.0199621
.1398802
0
1
Autocratization
6863
.0113653
.1060083
0
1
Gini
6744
41.71103
10.60062
15.9
73.9
Fractionalization
7480
.3844273
.282732
.001
.9250348
Max discrimination
7389
.0722347
.1796279
0
.98
Max low ratio
7389
1.197898
.5415661
1
6.773902
35
Table OA2. Logistic regression estimates of civil war onset: 1946–2006
(12)
(13)
(14)
(15)
(16)
LIED
-0.41***
(0.12)
-0.47***
(0.13)
L1
-0.36
(0.25)
-0.54*
(0.27)
-0.54*
(0.27)
L2
-0.54*
(0.27)
-0.64*
(0.29)
-0.10
(0.31)
L3
-1.33**
(0.41)
-1.45***
(0.44)
-0.81*
(0.36)
L4
-2.51***
(0.68)
-2.65***
(0.71)
-1.20*
(0.58)
Population
0.35***
(0.08)
0.34***
(0.08)
0.28**
(0.09)
0.26**
(0.09)
-
GDP/capita
-0.35**
(0.12)
-0.31*
(0.12)
-0.40**
(0.15)
-0.36*
(0.15)
-
GDP growth
-0.01
(0.01)
-0.01
(0.01)
-0.02
(0.01)
-0.02
(0.01)
-
Oil income
-0.02
(0.07)
-0.03
(0.08)
0.31*
(0.14)
0.31*
(0.14)
-
CINC
-16.29*
(7.06)
-14.80*
(6.94)
-17.93*
(7.52)
-16.50*
(7.41)
-
Polity2
0.05*
(0.02)
0.06**
(0.02)
0.07**
(0.02)
0.08**
(0.03)
-
Instability(3y)
-0.01
(0.20)
-0.05
(0.21)
-0.03
(0.21)
-0.07
(0.22)
-
Gini
-0.01
(0.01)
-0.01
(0.01)
-
Fractionalization
0.13
(0.37)
0.12
(0.37)
-
Max discrimination
1.03**
(0.38)
1.02**
(0.38)
-
Max low ratio
0.38**
(0.15)
0.35*
(0.15)
-
Constant
-3.11*
(1.23)
-3.32**
(1.23)
-2.29
(1.48)
-2.24
(1.47)
-
N
6823
6823
6097
6097
-
chi2
113.24
117.94
117.97
122.38
L1 = single-party autocracy; L2 = multi-party autocracy; L3 = minimalist democracy; L4 = polyarchy. Non-electoral autocracy (L0) is
the base category in Models 13 and 15. Standard errors in parentheses. Cubic polynomials not reported. +p<0.10, *p<0.05, **p<0.01,
***p<0.001.
36
Table OA3. Logistic regression estimates of civil war onset: Alternative measures of civil conflict
UCDP/PRIO war
UCDP/PRIO minor
UCDP/PRIO gov.
(17)
(18)
(19)
(20)
(21)
(22)
(17g)
(18g)
(19g)
LIED
-0.28*
(0.13)
-0.18+
(0.10)
-0.41*
(0.17)
L1
-0.38
(0.28)
-0.38
(0.28)
-0.28
(0.22)
-0.28
(0.22)
-0.35
(0.35)
-0.35
(0.35)
L2
-0.22
(0.29)
-0.16
(0.30)
-0.05
(0.22)
0.24
(0.23)
-0.35
(0.38)
-.003
(.39)
L3
-1.14*
(0.45)
-0.92*
(0.37)
-0.66*
(0.33)
-0.61*
(0.27)
-1.57*
(0.61)
-1.22*
(0.50)
L4
-1.78**
(0.65)
-0.64
(0.50)
-1.35**
(0.47)
-0.69*
(0.34)
-2.95**
(0.97)
-1.38+
(0.82)
Population
0.43***
(0.09)
0.41***
(0.09)
-
0.34***
(0.06)
0.32***
(0.07)
-
0.08
(0.12)
0.07
(0.12)
-
GDP/capita
-0.13
(0.14)
-0.11
(0.15)
-
-0.32**
(0.10)
-0.28**
(0.11)
-
-0.11
(0.19)
-0.06
(0.19)
-
GDP growth
0.02
(0.01)
0.02
(0.02)
-
-0.00
(0.01)
0.00
(0.01)
-
0.03
(0.02)
0.03
(0.02)
-
Oil income
0.24+
(0.14)
0.24
(0.15)
-
0.26*
(0.11)
0.26*
(0.11)
-
0.23
(0.15)
0.24
(0.15)
-
CINC
-9.08+
(5.12)
-7.68
(5.04)
-
-7.37+
(3.91)
-6.08
(3.83)
-
1.18
(6.42)
2.08
(5.99)
-
Polity2
0.01
(0.02)
0.03
(0.03)
-
0.02
(0.02)
0.04+
(0.02)
-
0.03
(0.03)
0.05
(0.04)
-
Instability(3y)
0.03
(0.22)
-0.00
(0.22)
-
0.17
(0.16)
0.13
(0.16)
-
-0.21
(0.29)
-0.25
(0.29)
-
Gini
-0.00
(0.01)
-0.00
(0.01)
-
-0.00
(0.01)
-0.01
(0.01)
-
-0.00
(0.01)
-0.00
(0.01)
-
Fractionalization
0.81*
(0.38)
0.76*
(0.39)
-
0.65*
(0.28)
0.61*
(0.28)
-
0.95+
(0.50)
0.88+
(0.50)
-
Max discrimination
0.60
(0.41)
0.65
(0.42)
-
0.44
(0.32)
0.45
(0.33)
-
0.80
(0.51)
0.82
(0.51)
-
Max low ratio
0.18
(0.13)
0.16
(0.13)
-
0.15
(0.11)
0.13
(0.11)
-
-0.73
(0.47)
-0.69
(0.46)
-
Constant
-6.60***
(1.50)
-6.37***
(1.50)
-
-3.76***
(1.09)
-3.63***
(1.09)
-
-2.91
(1.92)
-3.01
(1.90)
-
N
6067
6067
-
6067
6067
-
6067
6067
-
chi2
128.71
134.68
-
156.14
165.46
-
51.66
58.50
-
L1 = single-party autocracy; L2 = multi-party autocracy; L3 = minimalist democracy; L4 = polyarchy. Non-electoral autocracy (L0) is
the base category in Models 18, 21, and 18g. Standard errors in parentheses. Cubic polynomials not reported. +p<0.10, *p<0.05, **p<0.01,
***p<0.001.
37
Table OA4. Logistic regression estimates of civil war onset: Country fixed-effects
(23)
(24)
(25)
(26)
(27)
(28)
(29)
(30)
Analogous to model
7
14
17
20
8
15
18
21
LIED
-0.30**
(0.10)
-0.43**
(0.14)
-0.34*
(0.15)
-0.12
(0.11)
L1
-0.38+
(0.23)
-0.28
(0.32)
-0.24
(0.32)
-0.04
(0.25)
L2
-0.40+
(0.23)
-0.72*
(0.36)
-0.12
(0.35)
0.24
(0.27)
L3
-1.07**
(0.36)
-1.53**
(0.49)
-1.47**
(0.54)
-0.85*
(0.39)
L4
-1.60*
(0.70)
-1.56+
(0.86)
-3.77**
(1.33)
-0.81
(0.61)
Population
-0.08
(0.19)
-0.15
(0.35)
0.86*
(0.37)
0.24
(0.26)
-0.08
(0.19)
-0.16
(0.36)
0.79*
(0.38)
0.19
(0.27)
GDP/capita(ipol)
-0.73**
(0.22)
-0.68**
(0.23)
GDP growth(ipol)
-1.26
(1.09)
-1.32
(1.10)
GDP/capita
0.12
(0.39)
0.34
(0.36)
0.38
(0.27)
0.16
(0.40)
0.33
(0.37)
0.44
(0.28)
GDP growth
-0.02
(0.01)
0.01
(0.01)
-0.00
(0.01)
-0.02
(0.01)
0.01
(0.02)
-0.01
(0.01)
Oil income
0.14
(0.21)
0.06
(0.24)
-0.14
(0.28)
-0.24
(0.24)
0.13
(0.21)
0.06
(0.24)
-0.10
(0.28)
-0.23
(0.25)
CINC
4.01
(5.79)
-69.69
(45.57)
-42.77*
(18.53)
-25.90*
(10.75)
3.57
(5.81)
-69.56
(44.77)
-42.07*
(17.80)
-26.10*
(10.86)
Polity2
0.05**
(0.02)
0.08**
(0.03)
0.02
(0.03)
0.04+
(0.02)
0.06**
(0.02)
0.10**
(0.03)
0.05
(0.03)
0.07**
(0.02)
Instability(3y)
0.22
(0.17)
0.06
(0.23)
0.20
(0.23)
0.32+
(0.17)
0.21
(0.17)
0.05
(0.23)
0.09
(0.24)
0.26
(0.17)
Gini
-0.03
(0.02)
0.04+
(0.02)
0.03+
(0.02)
-0.03
(0.02)
0.05*
(0.02)
0.04*
(0.02)
Max discrimination
-0.06
(0.62)
0.90
(0.69)
0.68
(0.56)
-0.11
(0.63)
0.94
(0.70)
0.69
(0.57)
Max low ratio
0.41
(0.58)
0.09
(0.37)
0.08
(0.35)
0.39
(0.59)
0.02
(0.37)
0.03
(0.35)
N
5600
2418
2641
4002
5600
2418
2641
4002
chi2
49.66
42.96
30.71
60.54
52.42
44.04
40.50
70.45
L1 = single-party autocracy; L2 = multi-party autocracy; L3 = minimalist democracy; L4 = polyarchy. Non-electoral autocracy (L0) is
the base category in Models 2730. Standard errors in parentheses. Cubic polynomials not reported. +p<0.10, *p<0.05, **p<0.01,
***p<0.001.
38
Table OA5. Logistic regression estimates of civil war onset: Country fixed-effects: Comparing LIED levels
(31)
(32)
(33)
(34)
Analogous to model
27
28
29
30
LIED
L1
-0.38+
(0.23)
-0.28
(0.32)
-0.24
(0.32)
-0.04
(0.25)
L2
-0.03
(0.24)
-0.44
(0.38)
0.11
(0.36)
0.28
(0.27)
L3
-0.67*
(0.31)
-0.82+
(0.42)
-1.34**
(0.46)
-1.09***
(0.34)
L4
-0.53
(0.64)
-0.03
(0.80)
-2.31+
(1.25)
0.04
(0.53)
Population
-
-
-
-
GDP/capita(ipol)
-
GDP growth(ipol)
-
GDP/capita
-
-
-
GDP growth
-
-
-
Oil income
-
-
-
-
CINC
-
-
-
-
Polity2
-
-
-
-
Instability(3y)
-
-
-
-
Gini
-
-
-
Max discrimination
-
-
-
Max low ratio
-
-
-
N
-
-
-
-
chi2
-
-
-
-
Standard errors in parentheses. Cubic polynomials not reported. + p < 0.10, * p < 0.05, ** p < 0.01, *** p < 0.001
39
Table OA6. OLS regression estimates of LIED
(35)
(36)
(37)
(38)
(39)
(40)
(41)
(42)
(43)
(44)
Population
-0.05
(0.05)
0.00
(0.05)
0.00
(0.05)
-0.04
(0.05)
-0.05
(0.05)
-0.05
(0.05)
0.00
(0.06)
-0.00
(0.06)
0.00
(0.06)
0.01
(0.06)
GDP/capita(ipol)
0.72***
(0.07)
0.72***
(0.07)
0.81***
(0.06)
0.80***
(0.06)
0.80***
(0.06)
GDP growth(ipol)
0.21
(0.30)
-0.10
(0.24)
-0.10
(0.24)
-0.10
(0.24)
Oil income
-0.12***
(0.02)
-0.12***
(0.02)
-0.12***
(0.02)
-0.21+
(0.11)
-0.22+
(0.11)
-0.22+
(0.11)
-0.22+
(0.11)
CINC
0.79
(1.40)
0.76
(1.40)
-3.07
(2.91)
-2.95
(2.84)
-3.15
(2.96)
-2.48
(2.66)
Instability(3y)
-0.04
(0.06)
-0.09
(0.07)
-0.09
(0.07)
-0.10
(0.07)
-0.10
(0.07)
GDP/capita
0.88***
(0.05)
0.90***
(0.05)
0.89***
(0.05)
0.89***
(0.05)
GDP growth
0.00
(0.00)
0.00
(0.00)
-0.00
(0.00)
-0.00
(0.00)
Gini
0.01*
(0.01)
0.01*
(0.01)
0.01*
(0.01)
0.01*
(0.01)
Fractionalization
0.19
(0.23)
0.24
(0.23)
0.27
(0.23)
Max discrimination
-0.46+
(0.25)
-0.45+
(0.26)
Max low ratio
-0.10
(0.09)
Constant
2.35***
(0.42)
-3.60***
(0.51)
-3.63***
(0.51)
-3.85***
(0.48)
-3.74***
(0.47)
-3.70***
(0.48)
-5.23***
(0.63)
-5.40***
(0.66)
-5.34***
(0.65)
-5.35***
(0.65)
N
13814
10664
10528
10223
10205
10205
6183
6183
6141
6141
R2
0.003
0.282
0.286
0.346
0.346
0.346
0.391
0.392
0.396
0.397
Clustered standard errors on countries in parentheses. + p < 0.10, * p < 0.05, ** p < 0.01, *** p < 0.001
40
Table OA7. Ordered logit regression estimates of LIED
(45)
(46)
(47)
(48)
(49)
(50)
(51)
(52)
(53)
(54)
Population
-0.06***
(0.01)
-0.03*
(0.01)
-0.03**
(0.01)
-0.11***
(0.01)
-0.13***
(0.02)
-0.13***
(0.02)
-0.03+
(0.02)
-0.05*
(0.02)
-0.05*
(0.02)
-0.03
(0.02)
GDP/capita(ipol)
1.30***
(0.02)
1.32***
(0.02)
1.59***
(0.03)
1.58***
(0.03)
1.58***
(0.03)
GDP growth(ipol)
-0.03
(0.27)
-0.46+
(0.27)
-0.46+
(0.27)
-0.47+
(0.27)
Oil income
-0.55***
(0.02)
-0.55***
(0.02)
-0.55***
(0.02)
-0.40***
(0.04)
-0.42***
(0.04)
-0.43***
(0.04)
-0.43***
(0.04)
CINC
0.73
(0.47)
0.70
(0.47)
-4.86***
(1.01)
-4.65***
(1.01)
-4.91***
(1.04)
-3.65***
(1.07)
Instability(3y)
-0.05
(0.05)
-0.14*
(0.06)
-0.15**
(0.06)
-0.16**
(0.06)
-0.16**
(0.06)
GDP/capita
1.56***
(0.03)
1.61***
(0.03)
1.61***
(0.03)
1.62***
(0.03)
GDP growth
0.00
(0.00)
0.00
(0.00)
-0.00
(0.00)
-0.00
(0.00)
Gini
0.02***
(0.00)
0.02***
(0.00)
0.02***
(0.00)
0.02***
(0.00)
Fractionalization
0.43***
(0.09)
0.55***
(0.09)
0.61***
(0.10)
Max discrimination
-0.81***
(0.13)
-0.80***
(0.13)
Max low ratio
-0.18***
(0.05)
N
13814
10664
10528
10223
10205
10205
6183
6183
6141
6141
chi2
44.79
3957.57
3976.53
5098.75
5084.98
5086.02
3175.12
3197.08
3219.94
3235.36
Standard errors in parentheses. + p < 0.10, * p < 0.05, ** p < 0.01, *** p < 0.001
41
Figure OA1. GDP/capita, GDP growth, and oil income by LIED
0 2,000 4,000 6,000 8,000 10,000
GDP/capita (Bolt & van Zanden, 2013)
01234
0 1 2 3
GDP growth (Bolt & van Zanden, 2013)
01234
0 .2 .4 .6 .8 1
Total oil income/capita (Haber & Menaldo, 2011)
01234
42
Figure OA2. CINC, Instability, and Gini by LIED
0 .005 .01 .015 .02 .025
Composite Index of National Capability (Singer, 1987)
01234
0 .05 .1 .15 .2 .25
Instability in last 3 years
01234
0 10 20 30 40
Gini index (Buhaug, Cederman, & Gleditsch, 2014)
01234
43
Figure OA3. Fractionalization, Max discrimination, and Max low ratio by LIED
0 .1 .2 .3 .4 .5
Fractionalization (Buhaug, Cederman, & Gleditsch, 2014)
01234
0 .05 .1 .15
Max discrimination (Buhaug, Cederman, & Gleditsch, 2014)
01234
0 .5 1 1.5
Max low ratio (Buhaug, Cederman, & Gleditsch, 2014)
01234
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