metadata: authors: 0: author: Abu Bader,Suleiman
1: author: Ianchovichina,Elena
count: Middle East and North Africa
docna: 0: docna: Polarization, foreign military intervention,
            and civil conflict
docty: Policy Research Working Paper
subtopic: Conflict and Fragile States,Coastal and Marine Resources,Energy and Natural Resources,Social Cohesion,Armed Conflict
teratopic: Conflict and Development
abstracts: cdata!: In a behavioral model of civil conflict,
            foreign military intervention alters the resources available
            to warring groups and their probability of winning. The
            model highlights the importance of distributional measures
            along with the modifying effect of the intervention for
            conflict incidence. The paper confirms empirically the
            finding in the literature that ethnic polarization is a
            robust predictor of civil war, but it also finds evidence
            that religious polarization is positively and significantly
            associated with civil conflict in the presence of foreign
            military intervention of non-humanitarian and non-neutral
            nature. Such external interventions exacerbate religious
            polarization, leading to high-intensity conflicts in the
            Middle East and North Africa region, but not in the rest of
            the world. These results suggest that, unlike in the rest of
            the world, where civil conflicts are mostly about a public
            prize linked to ethnic polarization, in the Middle East and
            North Africa they are mostly about a sectarian-related
            public prize. The results are robust to allowing different
            definitions of conflict, model specifications, and data time
            spans, and to controlling for other types of foreign
            military interventions.
repnme: repnme: Polarization, foreign military
            intervention, and civil conflict
display_title: Polarization, foreign military
            intervention, and civil conflict
listing_relative_url: /research/2017/11/28190794/polarization-foreign-military-intervention-civil-conflict
topicv3: Rebels, Guerrillas and Insurgents m1326375 2451,Mountains m1326647 1986,Political Violence and Civil War m1326942 739,Political Violence and War m1327310 2462,Military m1505651 3036
publishtoextweb_dt: 2017-11-20T00:00:00Z
historic_topic: Conflict and Development
no_of_pages: 61
author_keys: 0: author_key: 1312523
1: author_key: 453205
model_extractions: WPS8248 Policy Research Working Paper 8248 Polarization, Foreign Military Intervention, and Civil Conflict _Suleiman Abu Bader Elena Ianchovichina_ Middle East and North Africa Region Office of the Chief Economist November 2017
Policy Research Working Paper 8248

# **Abstract**

In a behavioral model of civil conflict, foreign military intervention alters the resources available to warring groups and their probability of winning. The model highlights the importance of distributional measures along with the modifying effect of the intervention for conflict incidence. The paper confirms empirically the finding in the literature that ethnic polarization is a robust predictor of civil war, but it also finds evidence that religious polarization is positively and significantly associated with civil conflict in the presence of foreign military intervention of non-humanitarian and non-neutral nature. Such external interventions exacerbate religious polarization, leading to high-intensity conflicts in the Middle East and North Africa region, but not in the rest of the world. These results suggest that, unlike in the rest of the world, where civil conflicts are mostly about a public prize linked to ethnic polarization, in the Middle East and North Africa they are mostly about a sectarian-related public prize. The results are robust to allowing different definitions of conflict, model specifications, and data time spans, and to controlling for other types of foreign military interventions.

This paper is a product of the Office of the Chief Economist, Middle East and North Africa Region. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at abubader@bgu.ac.il or eianchovichina@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
**Polarization, Foreign Military Intervention, and Civil Conflict**<sup></sup>

**Suleiman Abu Bader**<sup></sup> **and Elena Ianchovichina**<sup></sup>

**JEL classification** : D74, D31

**Keywords** : Conflict, polarization, foreign intervention, Middle East and North Africa.

>  The findings, interpretations, and conclusions expressed in the paper are entirely ours and should not be attributed to the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. We thank Shantayanan Devarajan, Aart Kraay, Bob Rijkers, Alexei Abrahams, and participants in a seminar, organized by the Chief Economist Office of the World Bank’s Middle East and North Africa region, the 11<sup>th</sup> Defense and Security Economics Workshop at Carleton University in Ottawa, Canada, the NBER Conference on the Economics of National Security in Cambridge MA, and the 13<sup>th</sup> Annual Workshop of the Households in Conflict Network in Brussels, Belgium, for useful comments on earlier drafts of the paper.

>  Suleiman Abu Bader is a senior lecturer in the Department of Economics at Ben-Gurion University of the Negev, Israel, E-mail: abubader@exchange.bgu.ac.il.

>  Elena Ianchovichina is a lead economist in the Chief Economist Office, Middle East and North Africa Region, the World Bank, 1818 H Street NW, Washington, DC 20433, USA, Tel: +1 202 458 8910, E-mail: <u>eianchovichina@worldbank.org.</u>
# **I. Introduction**

Civil wars and other types of political violence have grave consequences for human development and global poverty reduction efforts. They disrupt economic activity and investments and destroy human lives and infrastructure, so their effect is usually felt long after peace is restored. The literature on armed insurgencies argues that countries at risk for civil wars tend to be poor (Fearon & Laitin, 2003), politically unstable (Hegre et al., 2001), abundant in lootable resources and unskilled labor (Collier and Hoeffler, 2004), and ethnically polarized (Montalvo and ReynalQuerol, 2005; Esteban, Mayoral and Ray, 2012). Except for the Republic of Yemen, the countries in the Middle East and North Africa do not fit this profile. Following independence, most Arab countries made substantial socioeconomic progress. Nearly all of them achieved middle-income status, reduced extreme poverty, kept vertical economic inequality at moderate levels, and improved access to education and health (Devarajan and Ianchovichina, 2017). Horizontal inequality was moderate as reflected by ethnic and religious polarization levels that were on average below those observed in other regions (Table 1). Following the tumultuous 1950s and part of the 1960s, most of the Arab states remained politically stable between the late 1960s to the early 2000s. Yet, during the same period (from 1965 to 2004), the average incidence of conflict by countries in the MENA region far exceeded the corresponding incidence in the rest of the developing world; it was one and a half times higher than the incidence of civil conflict in SubSaharan Africa, twice the incidence in Asia, and more than three times the incidence in Latin America and the Caribbean (Table 1). The high incidence of civil conflict in these mostly middleincome countries poses a puzzle, the so-called paradox of “political violence in middle-income 2
countries” (Ianchovichina, 2017). This paper explores one potential explanation for this puzzle: the role of non-humanitarian and non-neutral foreign military interventions.<sup>1</sup>

|**Table 1** **Av**|**erages of som**<br>|**e major ind**<br>|**icators (per c**<br>|**ountry per pe**<br>|**riod)**<br>||||
|---|---|---|---|---|---|---|---|---|
||_External_<br>_Intervention_<br>_Int_nh_|_Conflict_<br>_Incidence_<br>_PRIOCW_|_Religious_<br>_Polarization_<br>_RELPOL_|_Ethnic_<br>_Polarization_<br>_ETHPOL_|(1)/(3)<sup>1</sup>|(1)/(4)<sup>2</sup>|(2)/(3)|(2)/(4)|
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|
|MENA|.370|.267|.470|.525|0.79|0.70|0.57|0.51|
|SAFRICA|.166|.179|.701|.537|0.24|0.31|0.26|0.33|
|ASIAE|.095|.136|.507|.458|0.19|0.21|0.27|0.30|
|LAAM|.084|.086|.404|.646|0.21|0.13|0.21|0.13|

Data sources: IMI data (Pearson and Baumann, 1993) for external military interventions of non-neutral and nonhumanitarian type, _Int_nh,_ in (1); PRIO for conflict incidence, _PRIOCW,_ in (2); L’Etat des religions dans le monde and The Statesman’s Yearbook for religious polarization, _RELPOL,_ in (3); WCE for ethnic polarization, _ETHPOL,_ in (4). Note: MENA stands for Middle East and North Africa; SAFRICA is Sub-Saharan Africa; ASIAE is East Asia; and LAAM is Latin America. Columns (5) and (6) display numbers for the incidence of external intervention per unit of religious and ethnic polarization, respectively. Columns (7) and (8) display numbers for the incidence of civil conflicts per unit of religious and ethnic polarization, respectively.

Previous studies of civil war incidence have emphasized different explanatory factors, but virtually all have related civil war to domestic factors and processes. Theoretical studies of internal conflict have focused on grievance-motivated rebellions (Gurr, 1970), the factors creating opportunities for collective action in mobilization (Tilly, 1978), and the role of rents from conflict in promoting support for violence (Collier & Hoeffler, 2004). Many studies have explored the hotly contested link between ethnic and religious diversity and social conflict. Fearon and Laitin (2003) do not find a link between ethnic heterogeneity and conflict, but others insist that ethnic cleavages may increase the risk of conflict (Ellingsen, 2000; Cederman & Girardin, 2007; Montalvo and Reynal-Querol, 2005) and the duration of civil wars (Collier, Hoeffler, and Soderbom, 2004).<sup>2</sup> Arguing that there is less violence in highly homogeneous and highly heterogeneous societies, and more conflict in societies where a large ethnic minority lives side by

> 1 Other explanations for this puzzle, referring specifically to the period after the Arab Spring, are discussed in detail in Ianchovichina (2017).

> 2 Collier et al. (1999) argue that the duration of civil wars is positively, though non-monotonically related to the level of ethnic fractionalization of the warring society. The implication is that polarized societies would generate longer civil wars because the cost of coordinating a rebellion for a long enough period could be prohibitively high in very diverse societies.

3
side with an ethnic majority, Montalvo and Reynal-Querol (2005) show that ethnic polarization,<sup>3</sup> not ethnic fractionalization,<sup>4</sup> is a significant explanatory variable for the incidence of civil war. They conclude that ethnic polarization has a robust and significant explanatory power on civil wars in the presence of other indices of fractionalization and polarization, while the statistical significance of religious polarization depends on the particular specification. Esteban and Ray (2011) formalize theoretically the link between distributional measures and conflict incidence and test these links empirically in Esteban et al. (2012). Assuming no external intervention, they find that all three indices of ethnic distribution – polarization, fractionalization, and the Gini-Greenberg index – are significant correlates of conflict.<sup>5</sup> This literature has largely overlooked the role of transnational factors on conflict incidence (Regan 2010), despite the importance given to these factors in popular accounts of civil wars (McNulty, 1999). The research on interventions has focused on three areas: (i) the effect of foreign intervention on civil war duration; (ii) foreign intervention’s effect on civil war resolution; and (iii) foreign intervention’s effect on peace keeping. Quantitative studies in the first strand of the literature, reviewed in detail by Regan (2010), produce strong evidence that external interventions tend to lengthen civil conflict (Elbadawi and Sambanis, 2000), irrespective of whether they are in the form of direct military involvement, military aid, economic assistance or sanctions, or whether they are designed to be neutral or to favor the government or the opposition (Regan 2000, 2002). Several explanations of this effect have been put forward, with the most popular explanation linked to expected utility (Lake and Rothchild, 1998; Regan, 2002). Foreign intervention provides the

> 3 Polarization measures capture the distance of the group distribution from the bipolar one where the population is split in half into two large groups.

> 4 Fractionalization measures capture the extent of diversity in a country or society.

> 5 This result holds under the assumption that the resources committed by the warring groups come only from individual efforts within countries and that each warring group’s probability of winning equals their population share (Esteban and Ray, 2011).

4
resources necessary for one or both sides to carry out insurgency, which lowers the opportunity cost of participating in the war (Collier and Hoeffler, 2004), potentially making rival groups optimistic about the likelihood of a military victory and creating commitment problems.<sup>6</sup> The latter could arise because the intervention may reduce incentives for the side that benefits from outside assistance to credibly commit to the terms of a peace deal or to reach such a deal because of the greater number of veto players, especially in the case of multiple interventions on different sides of the warring groups (Cunningham, 2004). The second body of this literature finds evidence for the positive effect of foreign interventions that occur once a peace treaty has been signed on the successful resolution of these wars (Walter, 2002; Doyle and Sambanis, 2000; Hartzell, Hoddie, and Rothchild, 2001; Fortna, 2002; and Hartzell and Hoddie, 2003). Zartman (1989) argues that foreign intervention can create a ‘hurting’ stalemate during which both sides calibrate their expected utility and realize that they must negotiate an end to the war sooner rather than later. Foreign intervention can also help overcome information failures that prevent warring factions from reaching a settlement and shortening the duration of the war (Zartman, 1989, 1995; Brown, 1996; Lake and Rothchild, 1998; Doyle, Johnston and Orr, 1997) and help solve commitment (Brown, 1996) and implementation problems (Hampson, 1996). The presence of third-party guarantees reassures combatants that the treaty is credible and alleviates their safety concerns, making post-treaty demobilization possible and credible (Walter, 1994, 1997, and 2002). The third strand of the literature finds that external intervention reduces the risks of war recurrence once a peace deal is reached and implemented (Doyle and Sambanis, 2000; Fortna, 2002). However, only neutral (UN) and multidimensional<sup>7</sup> peacekeeping operations have a positive effect on peace maintenance, according to Doyle and Sambanis (2000). Other types of outside interventions,

> 6 Fearon (2004) and Salehyan (2004) make similar arguments.

> 7 Multidimensional operations include involvement in economic reconstruction, institutional reform and election oversight.

5
including monitoring and observer missions, economic reconstruction/institutional reform, and peace enforcement, appear to have no effect on either the duration of the post-war peace or democratization.

Few studies in the literature explore the question of how foreign interventions influence the incidence of civil wars and the results of these studies are mixed. Albornoz and Hauk (2014) find that interventions by global superpowers such as the U.S. are a sizable driver of domestic conflict, with the risk of civil war increasing under Republican governments and decreasing with the U.S. presidential approval ratings. Cetinyan (2002) finds that external support does not affect civil war incidence, but it influences the terms of settlement in the event conflict occurs. Gershenson (2002) also looks at this issue but in terms of sanctions, not direct military intervention. He finds that strong sanctions can compel the state to engage rebel demands whereas weak sanctions against the state can weaken the rebels’ position. Gleditsch (2007) examines how transnational contagion from neighboring states affects the risk of conflict in a country and concludes that regional factors strongly influence the risk of civil conflict.

This paper explores the effect of foreign military intervention on the incidence and intensity of civil war. Our hypothesis is that non-neutral and non-humanitarian external intervention increases the risk of high-intensity conflict that results in many casualties. The question of how different types of outside military interventions affect the intensity of war is distinctly different from the questions explored in the existing literature on intervention, which focus on war duration effects<sup>8</sup> and not on the causal link between intervention, war incidence and its scale, or how costly a war is in terms of human casualties. This issue is particularly relevant in the context of the increased incidence of high-intensity conflicts in the Middle East and North Africa after the Arab

> 8 Lengthy wars are not necessarily costly in terms of casualties.

6
Spring; the post-Arab Spring civil wars have led to many casualties and massive destruction (Ianchovichina, 2016). The paper focuses on non-neutral and non-humanitarian external interventions because we expect that this particular type of intervention has the potential to disturb the status quo in a country by increasing the incentives of different groups to raise resources for fighting and thus altering the groups’ probability of winning. We also believe that this type of intervention has the highest potential to increase the intensity of fighting and the associated casualties, as external support decreases the rebels’ dependence on local support and therefore their incentives to protect the local population.

**Figure 1 Distribution of Military Intervention Frequency by Type and Region**

<!-- Start of picture text --> 0.40<br>0.35<br>0.30<br>0.25<br>0.20<br>0.15<br>0.10<br>0.05<br>0.00<br>MENA SAFRICA LAAM ASIAE<br>Neutral and humanitarian Non-neutral and non-humanitarian<br><!-- End of picture text --> Data source: IMI data (Pearson and Baumann, 1993).

The global International Military Intervention (IMI) data set, which provides information on events involving foreign military deployment in countries around the world, indicates that there are large differences in the incidence of external military interventions by type and region. Since 1965 the incidence of non-neutral and non-humanitarian interventions has been highest on average in MENA and lowest in Latin America (Figure 1). In Sub-Saharan Africa – the region with the 7
second highest incidence of non-neutral and non-humanitarian interventions – the average prevalence of foreign military interventions was less than half of that observed in MENA. By contrast, neutral and humanitarian interventions appear evenly distributed across regions. Appendix Table 1 provides a complete list of military interventions that have been classified as non-neutral and non-humanitarian in the IMI database and that have been implemented around the world following the end of World War II.

The data suggest that nearly all MENA countries have been the target of military interventions, but the case of Lebanon – a multi-sectarian state – stands out. It illustrates the dynamics between external interventions, the onset of the Lebanese civil war and its intensification. Prior to the war, interventions occurred because following the ‘Black September’ 1970,<sup>9</sup> the Palestine Liberation Organization (PLO) was pushed out of Jordan and established presence in Lebanon, disturbing the balance among different sects in the country. After 1970 interventions occurred in Lebanon in support of the Shia minority, which was pushed out of Southern Lebanon into the urban peripheries of Beirut.<sup>10</sup> These interventions, occurring in the context of shifting population weights, led to increases in sectarian polarization and a struggle for political power, which resulted in a split into pro-Nasser Sunni Muslim camp and pro-Western Christian camp. Eventually, a confrontation erupted between the Lebanese Forces (LF)<sup>11</sup> and the Lebanese National Movement (LNM) and sectarian violence escalated, leading to further interventions in a vicious cycle that grew into a large-scale conflict.

> 9 During the ‘Black September’ conflict, the Jordanian Armed Forces fought with the Palestine Liberation Organization (PLO) and forced it to relocate from Jordan to Lebanon. 10 The ruling Alawite minority in Syria viewed the Shia minority in Lebanon as a counterweight against the Sunni majority of Syria and the Palestinians.

> 11 The LF included the Maronite Christians and the LNM represented a coalition between Druze, Shia, Arab Nationalists, Socialists, Communists and Sunni Militias. The LNM had the support of the PLO.

8
The paper incorporates foreign intervention in a model a la Esteban and Ray (2011). In the model external intervention affects the probability of winning of warring groups<sup>12</sup> and the resources available to them and therefore modifies the horizontal distributional measures. External interventions modify the effect of the distributional measures on the risk of conflict as they alter the balance of power among potential warring groups and therefore the incentives of groups to raise war-related resources. In other words, the revised model tells us that the equilibrium level of conflict depends on the distributional measures of inequality, fractionalization and polarization, modified to reflect the effect of military intervention. The theoretical specification does not indicate the direction and strength of the modifying effect– depending on the type of intervention and the presence of other interventions, it may increase or decrease the risk of conflict or it may have no effect on it.

The theory informs the format of the empirical model, which allows us to estimate empirically the direction and strength of the intervention and its modifying effect. We rely on the global International Military Intervention (IMI) data set for data on different types of external military interventions, the Peace Research Institute of Oslo (PRIO) data set for civil wars, and the databases on ethnic and religious fractionalization used by Montalvo and Reynal-Querol (2005). Our findings are consistent with the results in the literature (Montalvo and Reynal-Querol, 2005; Esteban, Mayoral and Ray, 2012) that ethnic polarization is a robust predictor of civil wars. In addition, we find robust evidence that religious polarization is positively and significantly associated with civil conflict in the presence of non-humanitarian and non-neutral foreign military interventions. Such external interventions exacerbate religious polarization, leading to high-

> 12 The extent to which probabilities shift remains unknown to opponents due to asymmetric information and incentives to dissemble, creating conditions for violence (Fearon 1995).

9
intensity conflicts in the Middle East and North Africa region, but not in the rest of the world. We find no such effect in the case of neutral and humanitarian military interventions.

The remainder of this paper is organized in the following way. Section II presents the theoretical model. Section III discusses the empirical model and data and Section IV presents the main econometric results. We discuss endogeneity issues and robustness checks in Section V and present a summary of findings and concluding remarks in Section VI.

# **II. Theory**

We explore the equilibrium level of conflict attained in a behavioral model in which warring groups choose the amount of resources to commit to a conflict. In the model warring groups can receive external military assistance. This help may be extended for political, economic, or any other reasons and may come in the form of direct military assistance, i.e. a foreign army fighting on behalf of the warring group, or other assistance that alters the groups’ chances of winning.<sup>13</sup> The model developed by Esteban and Ray (2011) defines the link between conflict and measures of inequality and polarization along non-economic identity markers such as ethnicity or religion.<sup>14</sup> These divisions enable groups interested in stoking conflict to channel antagonisms into organized action. This paper argues that external military interventions may deepen perceptions of horizontal divisions and may alter the behavioral incentives of the warring groups to raise warrelated resources. Leaving such influences outside the analysis may therefore overestimate the importance of distributional factors as reasons for civil wars. This paper does not study the motives

> 13 External assistance at one point can also give warring factions the assurance of support at a later time. However, the extent to which intervention alters the probability of winning remains unknown to opponents due to asymmetric information and incentives to dissemble (Fearon 1995).

> 14 Polarization may occur along other identity markers such as political ideas, racial, and/or social views.

10
behind intervention<sup>15</sup> and does not represent explicitly the preferences of the intervening external parties;<sup>16</sup> instead we consider the incentives of the domestic warring factions in the presence of exogenous interventions and in particular how foreign support may affect warring factions’ efforts to raise resources and change their probability of winning.

We consider a country with a population of _N_ individuals belonging to _m_ warring groups. In each group _i_ , there are _Ni_ individuals and _N=∑Ni_ , for _i=1,...,m._ We assume these groups fight over a budget whose per capita value is normalized to unity and that a fraction of it, _λ_ , is available to produce public goods. The winning group enjoys both a public prize,<sup>17</sup> whose value is given by _λ_ , and a private prize, which is given as the remaining fraction of the budget and can be privately divided among the members of the winning group once it gets control over the resources.<sup>18</sup> Using the private good as numeraire, _uij_ is the public goods payoff to a member of group _i_ if a single unit per capita of the optimal mix for group _j_ is produced. Then, the per capita payoff to members of <u>(1−�)</u> the warring group _i_ is ���� + �� _,_ if in case group _i_ wins the war and ���� in case some other group is the winner. We assume that ��� > ��� for all _i_ , _j_ with _i≠j._ This payoff difference defines the “distance” across groups: ��� = ��� −��� _._ Individuals in each group commit resources _r_ to influence the conflict’s outcome. These resources include time, effort, risk, and finance. The income equivalent cost to such expenditure is _c(r)_ where _c_ is assumed to be increasing, smooth, and strictly convex, with _c’(0)=0_ . If _ri(k)_ is the contribution of resources by member _k_ of group _i_ , then _Ri=∑ri(k)_ is the total of all resources

> 15 Foreign interventions may occur for a variety of reasons, some of which may be linked to aspirations for greater economic, political, and ideological influence in a given country.

> 16 The paper focuses on equilibrium conflict, not equilibrium intervention.

> 17 The public prize can be enjoyed by all members of the winning group regardless of its population size and includes political power, control over policy, ability to impose cultural and religious values, among other benefits.

> 18 The private payoff, with a per capita value _μ_ , could be in the form of administrative or political positions, specific tax breaks, and bias in access to resources, among others.

11
mei(k) = DLs pjuiy + pi ~~—>~~ — e(ri(k)) Ui(k) = (1 — a)m(k) + a Diam m ~~2~~ <u>Oj</u> ) Py y =e),, j=l (2)

-A
mm Oo) <u>Gi ij</u> pc'(p) = t=1Luzj=1 Y ~~j~~ Oj ij mm pc'(p); = >, », YjNjNi ~~[=~~ <u>(1-a@)</u> + ani] ~~|~~ <u>(1 -A)</u> + Adi)|. (4) i=1 j=1 ’ i#j
pe'(p) = ~~[HOS ere~~ | + ~~[|~~ ae + afar’ + (1 - Ad 44,

mm i=1 j=1 mm i=1 j=1 m mm i=1 i=1 j=1 j#i mm Fe= > > m7 i=1 j=1 j#i
dij = Uy — Uij dij dij dij pe'(p) = ~~jf meweoeeen - >|~~ + a(AP? +(1—A)F) + ~~a|~~ Fe
If the country is populous (i.e. _N_ is large), as in the baseline case in Esteban and Ray (2011), condition (6) transforms into: This condition suggests that equilibrium per capita conflict in the large country case depends on the extent of fractionalization and polarization, and external intervention has an effect on equilibrium conflict only through its effect on horizontal polarization. If conflict is mostly over a public prize (�= 1), the equilibrium per capita conflict depends only on the polarization measure and the extent to which the intervention polarizes the society. This is consistent with the nature of the public prize, which is linked to the characteristics of the horizontal groups and the individual payoff from it, which is undiluted by one’s own group size. The public prize includes the seizure of political power, the setting of norms, the abolition of certain rights or privileges, the establishment of a religious state, the repression of a language and other public aspects that may lead to contention among horizontal groups. If conflict is mostly over a private prize (�= 0), the equilibrium per capita conflict depends only on the degree of fractionalization and not on polarization and/or external intervention. This is because the private prize is about access to resources (oil or specific material benefits obtained from special positions of power) and the individual payoff of this type of prize is diluted by the group size. In the general case, it is difficult to discern the effect of external intervention on civil conflict incidence without empirical testing, so next we test empirically the association between external military intervention and conflict prevalence.

16
# **III. Empirical investigation: Model and data**

We utilize a logit model for the incidence of civil wars: _P_ ( _PRIOCW it_  )1    _X_ 1 _it_  1  1  _X_ 2 _it_  1  2  _Int_ nhis_    _it_ , (8) in which the independent variables, _X_ 1 _it_  1and _X_ 2 _it_  1 , are the relevant distributional and control variables, respectively; and  _it_ is the error term. The distributional factors and some of the control variables are time invariant; the rest are set at their values in period _t-1_ . The binary explanatory variable, _Int_nhis,_ is 1 if there has been an external military intervention in at least one of the four years preceding period _t_ ( _t-1≤s<t)_ and 0 otherwise. We describe the data for each of these sets of variables next.

We study 137 countries over 1960-2005 and divide the sample into five-year periods so we have a total of 946 observations.<sup>25</sup> For comparison purposes, we first conduct the analysis for the period 1960-1999, considered by Montalvo and Reynal-Querol (2005), but then we estimate the model and test the robustness of the results over the full period up to 2005. We use the Peace Research Institute of Oslo (PRIO) data set for civil wars to construct the endogenous binary variable of civil war incidence, PRIOCW, which is set at 1 if a civil war occurred in a country _i_ in period _t_ and zero otherwise. In the baseline results we focus on intermediate armed conflict (PRIOCW, categories 3 and 4), defined as a contested incompatibility that concerns government and/or territory, where the use of armed force between two parties, of which at least one is the government of a state, results in a minimum of 1,000 deaths over the course of the civil war. In the robustness checks, we also consider low-level conflict (PRIO25) associated with at least 25 deaths,

> 25 The number of observations in a specific empirical model depends on the independent variables included in it, as different variables have different missing observations. In the baseline model, the maximum number of observations is 946.

17
and large scale civil wars (PRIO1000) associated with at least 1,000 per year and per incompatibility (see details in appendix). In the baseline, we consider non-humanitarian and nonneutral military interventions that are likely to be implemented before a civil conflict intensifies and therefore alter the balance of power and the winning probabilities of potential warring groups as discussed in the theory section of this paper.

As in Montalvo and Reynal-Querol (2005), the distributional variables are ethnic polarization ( _ETHPOL_ ), ethnic fractionalization ( _ETHFRAC_ ), religious polarization ( _RELPOL_ ), and religious fractionalization ( _RELFRAC_ ). Montalvo and Reynal-Querol (2005) show that the indices of polarization and fractionalization differ, independent of the data source used in their calculations. We choose the World Christian Encyclopedia (WCE) to obtain the ethno-diversity measure, favoring it to the other two sources: the Encyclopedia Britannica (EB), and the ANM (1964). We do so because according to Montalvo and Reynal-Querol (2005) the most accurate description of ethnic diversity is the one in the WCE. It contains details for each country on the most diverse classification level, which may coincide with an ethnolinguistic family or subfamilies. There are also several sources of data on religious diversity. We adopt the _L’Etat des religions dans le monde_ (ET) data, which are based on a combination of national data sources and the WCE, and provide information on the proportions of followers of Animist and Syncretic cults. Montalvo and Reynal-Querol (2005) consider this to be an important factor for the calculation of indices of religious heterogeneity. Since the data used by Montalvo and Reynal-Querol (2005) and Esteban et al. (2012) do not contain information on the distributional variables for Lebanon, we construct the indexes of religious and ethnic polarization and fractionalization based on data from Encyclopedia Britannica Book of the Year 2001.

18
The group of control variables includes explanatory variables found to influence the incidence of conflict in earlier empirical studies by Fearon and Laitin (2003), Doyle and Sambanis (2000), and Collier and Hoeffler (2002). Fearon and Laitin (2003) argue that GDP per capita is a proxy for the state’s overall financial, administrative, police, and military capabilities. Rebels can expect a higher probability of success in a low-income society with weak state institutions. In addition, a low level of GDP per capita reduces the opportunity cost of engaging in a civil war. The log of real GDP per capita (LGDPC) is set at its value in the previous period in order to reduce the potential endogeneity problem between conflict and the level of real economic activity.<sup>26</sup> The log of the population (LPOP) is also included in the set of control variables and is set at its value in the previous period.<sup>27</sup> Since the usual definitions of civil war always set a threshold in the number of deaths, we control by population as a scale factor. The size of the population can also be considered an additional proxy for the benefits of a rebellion as it measures potential labor income taxation (Collier and Hoeffler, 2002). Fearon and Laitin (2003) also indicate that a large population implies difficulties in controlling what goes on at the local level and increases the number of potential rebels that can be recruited by the insurgents. Mountains ( _MOUNTAINS_ ) are included as well since this terrain can provide safe haven for rebels. Long distances from the center of the state’s power also favor the incidence of civil wars, especially if there is a natural barrier between them, like a sea or other countries, so we include the noncontiguous state ( _NONCONT_ ) variable in the set of control variables. As pointed out by Collier and Hoeffler (2002) the existence of natural resources provides an opportunity for rebellion since these resources can be used to finance the war and increase the payoff if victory is achieved. We measure this dependence using the share of primary commodity exports of GDP ( _PRMEXP_ ) (Collier and Hoeffler, 2002;

> 26 As in Motalvo and Reynal-Querol (2005) we do not use annual data and GDP growth as an explanatory variable due to strong concerns about the potential endogeneity problem between economic growth and conflict. 27 See appendix for data sources for each variable.

19
Montalvo and Reynal-Querol, 2005). Finally, in line with the literature we consider the effect of democracy, measured with the level of democracy using the Polity IV data set score for general openness of the political institutions, transformed into a dummy variable that takes value 1, if the score is greater or equal to 4, and 0 otherwise.

As military interventions for humanitarian and peacekeeping purposes are implemented once civil wars have intensified, we focus only on non-humanitarian and non-neutral military interventions, which may occur before an armed conflict begins and are likely to alter the balance of power and the winning probabilities of potential warring groups leading to armed conflict or the intensification of an existing one, as discussed in the theory section of this paper. We use the data set of International Military Intervention (IMI)<sup>28</sup> to define the intervention variable _Int_nhis_ . This data set records interventions that are purposeful, are the result of conscious decisions of national leaders, and involve “the movement of regular troops or forces of one country inside another, in the context of some political issue or dispute” (Pearson and Baumann, 1993). The data set excludes interventions that involve paramilitaries, government backed militias, private security forces, and other military units that are not part of the regular military of the state. The IMI data set contains a total of 1,243 cases of military interventions which meet these criteria for the period 1946-2005; they have been further classified as neutral, supportive of government or rebels, humanitarian, and other types.<sup>29</sup> This enables us to define external military intervention as a binary variable, _Int_nh,_ which takes the value 1 if there has been at least one intervention in the target country during the four years preceding the current period and the intervention was not neutral and

> 28 The IMI project was established in the late 1960s by Frederic S. Pearson and Robert A. Baumann. Under their guidance, 667 cases of international military interventions spanning the years 1946 to 1988 were coded.  Emizet N. Kisangani and Jeffrey Pickering expanded the IMI collection to 2005. Many studies have been done using the IMI data set, among others are Peksen (2012), Koga (2011), Sullivan and Koch (2009), Pearson et al. (2006), and Pickering and Kisangani (2006).

> 29 For the full list of variables consult the International Military Intervention, 1989-2005 notebook at http://www.researchconnections.org/ICPSR/studies/21282.

20
was not for humanitarian matters. In total, there were 178 intervention years of this kind during the period 1946-2005. The complete list of non-humanitarian and non-neutral military interventions by year, intervening country and target country is shown in Appendix Table 1.

Different regions have relatively similar levels of religious and ethnic polarization, but substantially different frequency of civil conflict and external military interventions, as shown in Table 1. In the context of moderate levels of religious and ethnic polarization, the MENA region stands out with the highest incidence of civil conflict and foreign military intervention of the nonhumanitarian and non-neutral type. Figure 2, which is based on the data of Table 1, shows that countries with high incidence of civil conflict are places with higher than average levels of religious polarization (RELPOL) and external military intervention.

**Figure 2 External Intervention and Civil Conflict Incidence (per Country per Period) at Different Levels of Religious Polarization**

<!-- Start of picture text --> 0.3<br>0.268<br>0.25 0.248<br>0.2173<br>0.195<br>0.2<br>0.191 0.181<br>0.15<br>0.1<br>0.089<br>0.073<br>0.05<br>0<br>Mean-PRIOCW Mean-Intervention<br><!-- End of picture text --> 21
# **IV. Regression Results**

We first replicated the major results of Montalvo and Reynal-Querol (2005), shown in columns (1), (2), and (4) of Table 2. These results point to the significance of ethnic polarization, not fractionalization, as a determinant of conflict. In their specification, which omits the foreign military intervention variable, religious polarization and fractionalization are not significant predictors of conflict. In other words, their results suggest that civil conflict is driven mostly by ethnic strife over public prizes.

# _A. External Intervention and Polarization_

When we include the non-neutral and non-humanitarian external military intervention variable ( _Int_nh_ ), along with the indices of polarization and fractionalization, we find that both the intervention variable and the ethnic polarization index are statistically significant and have the expected positive signs (see columns (3) and (5) of Table 2). This result suggests that, conditional on a given degree of polarization, this type of external military intervention is associated with an increase in the incidence of civil war.<sup>30,31</sup> Expression (6) for the equilibrium per capita conflict in the theory section links the incidence of civil war to the distributional measures modified by the presence of non-neutral and non-humanitarian external military intervention. It suggests that the intervention is associated with conflict through its effects on the distributional measures. In the large country case, given by expression (7),<sup>32</sup> this effect comes through the influence of the intervention on the polarization

> 30 The sample used to estimate regression models (3), (5), (6), and (7) includes observations for Lebanon. Similar results are obtained without Lebanon in the data sample. Results without Lebanon are available upon request from the authors.

> 31 We recognize that there may be reverse causality between intervention and conflict, so we interpret the effect on the intervention variable as a conditional association, rather than a causal relationship. 32 The large country case is also the baseline case in Esteban and Ray (2011).

22
measure. We reflect this by including an interaction term between the external military intervention variable and each of the polarization measures. The results, presented in columns (6) and (7) of Table 2, as well as those presented in columns (6) and (7) of Table 3 for the sample extended up to 2005,<sup>33</sup> suggest that ethnic polarization is a significant determinant of conflict incidence and that foreign intervention exacerbates the relationship between religious polarization and conflict. In other words, religious polarization combined with external military intervention is significantly and positively associated with civil war.

**Table 2 Logit Regressions for the Incidence of Civil Wars (PRIOCW)** **<u>(1965-1999)</u>**

||(1)<sup>1</sup>|(2)<sup>2</sup>|(3)|(4)<sup>3</sup>|(5)|(6)|(7)|
|---|---|---|---|---|---|---|---|
|LGDPPC|-0.28|-0.42*|-0.34|-0.38|-0.28|-0.36|-0.36|
|LPOP|0.34**|0.40**|0.38**|0.44***|0.39***|0.40***|0.40***|
|PRIMEXP|-0.90|-1.07|-1.71|-0.86|-1.77|-1.53|-1.49|
|MOUNTAINS|0.00|-0.00|-0.00|-0.00|-0.00|-0.00|-0.00|
|NONCONT|0.08|0.28|0.35|0.48|0.47|0.41|0.42|
|DEMOCRACY|0.07|0.03|0.11|-0.04|0.08|0.14|0.14|
|ETHFRAC|1.19*|0.17|0.12|0.04|-0.08|-0.35|-0.39|
|ETHPOL||**2.28****|**2.60*****|**2.11*****|**2.38****|**2.59*****|**2.76****|
|RELFRAC||||-4.45|-2.12|-1.89|-1.98|
|RELPOL||||3.28|1.92|1.32|1.36|
|Int_nh|||**1.52*****||1.53***|0.44|0.82|
|Int_nh ˟ RELPOL||||||**1.86**|**1.89***|
|Int_nh ˟ ETHPOL|||||||-0.71|
|Intercept|-5.82**|-6.29**|-7.00***|-7.54**|-7.71***|-7.15**|-7.23**|
|N|850|850|859|850|859|859|859|
|McFadden’s R<sup>2</sup>|0.101|0.123|0.169|0.135|0.176|0.182|0.183|
|McFadden’s Adjusted R<sup>2</sup>|0.079|0.098|0.142|0.104|0.142|0.146|0.144|

1 Refers to column 1 in Table 1 of Montalvo and Reynal-Querol (2005).

2 Refers to column 3 in Table 1 Montalvo and Reynal-Querol (2005).

3 Refers to column 8 in Table 1 of Montalvo and Reynal-Querol (2005).

> 33 We include data up to 2005 by adding one period to the sample employed in Montalvo and Reynal-Querol (2005). We have also added observations for Lebanon, which are not present in their sample. Similar results are obtained with and without Lebanon in the data sample. Results without Lebanon are available upon request from the authors.

23
**Table 3 Logit Regressions for the Incidence of Civil Wars (PRIOCW)** **<u>(1965-2005)</u>**

||(1)<sup>1</sup>|(2)<sup>2</sup>|(3)|(4)<sup>3</sup>|(5)|(6)|(7)|
|---|---|---|---|---|---|---|---|
|LGDPPC|**-0.37***|**-0.52****|**-0.44***|**-0.45***|-0.38|-0.46|**-0.46**|
|LPOP|**0.37****|**0.42****|**0.39****|**0.46*****|**0.39*****|**0.42****|**0.42*****|
|PRIMEXP|0.34|0.31|-0.29|0.25|-0.44|-0.11|-0.08|
|MOUNTAINS|0.01*|0.01|0.01|0.00|0.01|0.01|0.01|
|NONCONT|0.35|0.60|0.63|0.75|0.74|0.68|0.68|
|DEMOCRACY|0.00|0.02|0.12|-0.05|0.08|0.14|0.14|
|ETHFRAC|1.10*|-0.06|0.01|-0.03|-0.06|-0.30|-0.33|
|ETHPOL||**2.34****|**2.47****|**2.13****|**2.24****|**2.42****|**2.55****|
|RELFRAC||||-4.52|-2.56|-2.32|-2.35|
|RELPOL||||3.18*|2.04|1.37|1.38|
|Int_nh|||**1.32*****||**1.33*****|0.02|0.32|
|Int_nh˟ RELPOL||||||**2.16***|**2.19****|
|Int_nh˟ ETHPOL|||||||-0.56|
|Intercept|-5.74**|-6.10**|-6.41**|-7.23**|-7.12***|-6.63***|-6.69***|
|N|937|937|946|937|946|946|946|
|McFadden’s R<sup>2</sup>|0.116|0.138|0.174|0.150|0.179|0.188|0.189|
|McFadden’s Adjusted R<sup>2</sup>|0.097|0.117|0.150|0.124|0.151|0.157|0.155|

1 Column (1) shows results for the specification of Montalvo and Reynal-Querol (2005), shown in column (1) of Table 1 in their paper, with the data set extended to 2005.

2 Column (2) shows results for the specification of Montalvo and Reynal-Querol (2005), shown in column (3) of Table 1 in their paper, with the data set extended to 2005. 3 Column (4) shows results for the specification of Montalvo and Reynal-Querol (2005), shown in column (8) of Table 1 in their paper, with the data set extended to 2005.

# _B. The MENA Effect_

This section investigates the robustness of the results to the inclusion of regional dummies. This way we address the relationship between geographical heterogeneity and civil conflict. In Montalvo and Reynal-Querol (2005) all countries not located in Asia, Sub-Saharan Africa, and Latin America are included in the reference (base) region. The MENA countries therefore are included in the reference region along with all developed countries and the rest of the world. The inclusion of the MENA countries with the base group poses a problem given the substantially higher incidence of civil wars and foreign military interventions in MENA compared with the rest of the world (Table 1). In line with the fact that conflict incidence is higher in MENA than in the rest of the world regions, the coefficient on the MENA dummy is large, positive, and significant, while all other regional dummies remain statistically insignificant (see column (2) of Table 4). Furthermore, the inclusion of MENA reduces the magnitude and significance of the coefficient on 24
the ethnic polarization (ETHPOL) variable; it becomes significant only at the 10% level. As expected, the association between non-neutral and non-humanitarian foreign military intervention variable, Int_nh, and civil conflict is positive and significant in the 3<sup>rd</sup> regression model, shown in column (3) of Table 4. The addition of the interactions of the intervention variable with each of the two polarization indices (RELPOL and ETHPOL) in column (4) of Table 4 suggests that the intervention exacerbates the effect of religious polarization on conflict incidence, but it does not have a similar effect on ethnic polarization.

We explore the channels through which the MENA regional effect translates into higher incidence of civil conflict with the help of alternative specifications of the regression models in columns (5) through (8) of Table 4. In columns (5) and (6) we show results from the regression model with interactions between the regional dummies and the religious and ethnic polarization indices, respectively. In both cases, the MENA dummy loses its significance, the magnitude of its coefficient goes down significantly, and only the interactions of RELPOL with the MENA and the intervention dummy, respectively, remain significant.

Given the different degrees of religious polarization and the incidence of external military interventions across geographic regions, we include a triple interaction term in model (7) that allows us to capture the region-specific dimension of the moderating effect of external intervention on religious polarization. The results show that none of the three variables is significant by itself but the coefficient of the tri-interaction term for MENA is positive, large and highly significant. The interaction terms between the religious polarization and MENA variables and those between the intervention and religious polarization variables are no longer significant too. The final specification in Table 4, shown in column (8), is our preferred specification. It is closest to the specification in Montalvo and Reynal-Querol (2005), shown in column (1), with the difference 25
that we have included the tri-variable interaction between the military intervention dummy, the religious polarization variable, and the MENA dummy.<sup>34</sup> The results with this specification indicate that the index of ethnic polarization is a significant explanatory variable for the incidence of civil war and, in the case of MENA, religious polarization combined with external military intervention is significantly associated with conflict. Similar results are obtained with the sample extended to 2005 (Table 5). The result that ethnic polarization is a significant explanatory variable for war incidence is weakened when the sample is extended and the model proposed by Montalvo and Reynal-Querol (2005) is used and this distributional variable seizes to be significant in the specification with MENA dummy. However, this variable becomes significant at the 5% level in our preferred specification (8).

The magnitude of the interaction effect in nonlinear models does not equal the marginal effect of the interaction term and can be of opposite sign (Ai and Norton 2003). We therefore plot in Figure 3 the predicted probability of intense civil conflict as a function of RELPOL, allowing for shifts in this curve by the two binary variables: Int_nh and MENA, and in figure 4, the marginal effect of Int_nh, differentiating between MENA (MENA=1) and non-MENA (MENA=0) regions. The predicted probability of civil conflict with external intervention in MENA is higher than that in non-MENA countries for any level of RELPOL greater than 0.33 and in both cases the predicted probabilities significantly differ from zero at the 5% significance level (Figure 3). Foreign military interventions of non-neutral and non-humanitarian type increase substantially the predicted probability of these types of conflict in MENA at much lower levels of RELPOL than in the nonMENA case, where substantial differences emerge at the highest levels of RELPOL (Figure 3). In the case of MENA, the marginal effect of external intervention is statistically significant when

> 34 All interaction terms and dummy variables that were insignificant in specification (7) have been dropped from specification (8).

26
RELPOL ranges between 0.32 and 0.59 while in the non-MENA cases, RELPOL needs to be higher, above 0.6 for external intervention to have a statistically significant effect on conflict incidence (Figure 3). At the averages for RELPOL in the data, the estimated marginal effect of intervention in the case of MENA is about 0.25 compared to 0.07 in the non-MENA case.

**Table 4 Logit Regressions for the Incidence of Civil Wars (PRIOCW) in the Presence of Regional Dummies (1965-1999)**

||**(1)**<sup>**1**</sup>|**(2)**<sup>**2**</sup>|**(3)**|**(4)**|**(5)**|**(6)**|**(7)**|**(8)**|
|---|---|---|---|---|---|---|---|---|
|LGDPPC|-0.41*|-0.41|-0.35|-0.40|-0.60*|-0.60*|-0.46|-0.50**|
|LPOP|0.38***|0.45***|0.46***|0.46***|0.54***|0.50***|0.49***|0.39**|
|PRIMEXP|-1.15|-2.19|-2.54|-2.55|-2.67|-2.61|-2.81|-2.22|
|MOUNTAINS|-0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|
|NONCONT|0.09|0.44|0.52|0.42|0.45|0.33|0.39|0.48|
|DEMOCRACY|0.09|0.62|0.56|0.66|0.66|0.64|0.72|0.38|
|ETHFRAC|0.26|0.63|0.41|0.12|0.01|0.21|0.08|0.05|
|ETHPOL|**2.35*****|**1.96***|**2.49****|**2.21***|**2.64****|**2.18****|**2.44****|**2.59****|
|RELFRAC||||-2.81|-1.29|-1.89|-2.37||
|RELPOL||||1.91|-0.88|-0.31|1.30||
|Int_nh|||1.28***|**-0.02**|**0.31**|**0.16**|0.25||
|MENA|**Excluded**|2.44**|2.09**|2.22**|0.31|0.74|1.75*||
|SAFRICA|Included|1.03|1.03|0.81|0.11|-0.59|0.90||
|LAAM|Included|0.49|0.51|0.40|-0.19|-2.45|0.40||
|ASIAE|Included|1.00|0.90|1.27|1.18|1.84|1.57*||
|Int_nh˟RELPOL||||2.50***|2.04*|2.11**|1.69|**1.04**|
|Int_nh˟ETHPOL||||-0.37|-0.59|-0.41|-0.82||
|RELPOL˟MENA|||||**5.55****|**5.17***|||
|RELPOL˟SAFRICA|||||1.84|1.69|||
|RELPOL˟LAAM|||||1.89|0.78|||
|RELPOL˟ASIAE|||||0.49|0.54|||
|ETHPOL˟MENA||||||-0.61|||
|ETHPOL˟SAFRICA||||||0.98|||
|ETHPOL˟LAAM||||||3.72|||
|ETHPOL˟ASIAE||||||-1.22|||
|Int_nh˟RELPOL˟MENA|||||||**3.53***|**5.43*****|
|Int_nh˟RELPOL˟AFRICA|||||||**0.71***|**1.04**|
|Int_nh˟RELPOL˟LAAM|||||||**1.00**||
|Int_nh˟RELPOL˟ASIAE|||||||**-3.08**||
|Intercept|-6.07**|-8.40**|-9.35**|-8.06**|-8.06*|-7.23*|-8.70**|-6.14**|
|<br>N|846|859|859|859|859|859|859|859|
|McFadden’s R<sup>2</sup>|**0.127**|**0.169**|0.203|0.240|0.240|0.245|0.237|0.208|
|McFadden’s Adjusted R<sup>2</sup>|**0.093**|**0.133**|0.165|0.179|0.179|0.173|0.176|**0.175**|

1 Column (1) here is column (2) in Table (5) of Montalvo and Reynal-Querol (2005), who do not have a dummy variable for MENA and include the MENA countries into the reference group.

2 Column (2) here is column (2) in Table (5) of Montalvo and Reynal-Querol (2005), with the addition of MENA dummy to the regression.

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**Table 5 Logit Regressions for the Incidence of Civil Wars (PRIOCW) in the Presence of -** **<u>Regional Dummies (1965 2005)</u>**

||(1)<sup>1</sup>|(2)|(3)|(4)|(5)|(6)|(7)|(8)|
|---|---|---|---|---|---|---|---|---|
|LGDPPC|-0.45*|-0.53*|-0.45|-0.52*|-0.65**|-0.66**|-0.65**|-0.56**|
|LPOP|0.37**|0.44***|0.44***|0.47***|0.53***|0.51***|0.50***|0.37**|
|PRIMEXP|0.11|-1.47|-1.74|-1.46|-1.63|-1.64|-1.64|-1.05|
|MOUNTAINS|0.01|0.01|0.01|0.01|0.01*|0.01|0.01|0.01|
|NONCONT|0.41|0.87|0.90|0.77|0.77|0.68|0.65|0.74|
|DEMOCRACY|0.10|0.60|0.60|0.71|0.69|0.68|0.65|0.32|
|ETHFRAC|0.22|0.38|0.30|-0.04|-0.07|0.01|0.03|0.19|
|ETHPOL|**2.05***|**1.78**|**2.00***|**2.36**|**2.56****|**2.69**|**2.64**|**2.21****|
|RELFRAC|-4.73|-3.93|-3.77|-3.85|-2.49|-2.70|-2.77||
|RELPOL|3.47|3.09|2.93|2.25|0.37|0.46|0.57||
|Int_nh|||1.08***|-0.32|-0.07|**-0.14**|**-0.31**||
|MENA|**Excluded**|**2.49****|**2.27****|**2.37****|0.98|1.71|1.74||
|SAFRICA|Included|0.73|0.83|0.89|0.84|0.60|0.63||
|LAAM|Included|0.17|0.20|0.24|-0.06|-1.89|-1.89||
|ASIAE|Included|1.27*|1.24|1.54******|1.85|2.46|2.46||
|Int_nh˟ RELPOL||||**2.95*****|**2.58****|**2.58****|**2.74*****|**1.47*****|
|Int_nh˟ ETHPOL||||-0.76|-0.92|-0.80|-1.00||
|RELPOL˟MENA|||||3.91|3.92|3.06||
|RELPOLxSAFRICA|||||0.70|0.80|0.72||
|RELPOL˟LAAM|||||1.15|0.44|0.42||
|RELPOL˟ASIAE|||||-0.40|-0.16|-0.36||
|ETHPOL˟MENA||||||-1.28|-1.21||
|ETHPOL˟SAFRICA||||||0.08|0.12||
|ETHPOL˟LAAM||||||2.84|2.85||
|ETHPOL˟ASIAE||||||-1.32|-1.232||
|Int_nh˟RELPOL˟MENA|||||||**2.05****|**4.33*****|
|Intercept|-5.81*|-7.61**|-8.39**|-8.12**|-7.98**|-7.46**|-7.42**|-5.35**|
|N|946|946|946|946|946|946|946|946|
|McFadden’s R<sup>2</sup>|0.154|0.198|0.224|0.238|0.250|0.254|0.257|0.210|
|McFadden’s Adjusted R<sup>2</sup>|0.120|0.162|0.184|0.195|0.198|0.192|0.193|0.185|

1 Column (1) shows results for the specification of Montalvo and Reynal-Querol (2005), shown in column (2) of Table 5 in their paper, with the data set extended to 2005.

28
# **Figure 3 Predicted Conflict Incidence**

<!-- Start of picture text --> 0 .05 .1 .15 .2 .25 .3 .35 .4 .45 .5 .55 .6 .65 .7 .75 .8 .85 .9 .95 1<br>RELPOL<br>MENA=0, Int_nh=0 MENA=0, Int_nh=1<br>MENA=1, Int_nh=0 MENA=1, Int_nh=1<br>1.5<br>1<br>Pr(Priocw) .5<br>0<br><!-- End of picture text --> Note: This graph is based on the results for the coefficients in specification (7) of Table (5) and the variables set at their means.

**Figure 4 Marginal Effect of Non-neutral and Non-humanitarian Intervention by Region**

<!-- Start of picture text --> 0 .05 .1 .15 .2 .25 .3 .35 .4 .45 .5 .55 .6 .65 .7 .75 .8 .85 .9 .95 1<br>RELPOL<br>MENA=0 MENA=1<br>.6<br>.4<br>.2<br>0<br>Effects on Pr(Priocw)<br>-.2<br><!-- End of picture text --> Note: This graph is based on the results for the coefficients in specification (7) of Table (5) and the variables set at their means.

29
**Figure 5 Differences in the Predictive Margins of Non-neutral and Non-humanitarian Intervention by Region**

<!-- Start of picture text --> 0 .05 .1 .15 .2 .25 .3 .35 .4 .45 .5 .55 .6 .65 .7 .75 .8 .85 .9 .95 1<br>RELPOL<br>.5<br>0<br>Contrasts of Pr(Priocw)<br>-.5<br><!-- End of picture text --> Note: This graph is based on the results for the coefficients in specification (7) of Table (5) and the variables set at their means.

Figure 4 displays the difference between the marginal effects of external intervention in MENA and non-MENA countries along with their 95% confidence intervals. The predictive difference between the marginal effects of external intervention on the incidence of civil conflict in MENA and non-MENA regions is statistically significant at the 5% level only when RELPOL varies between 0.32 and 0.53 (Figure 5). Since the average level of RELPOL in MENA is 0.47 and falls in this range, we conclude that the marginal effect of external intervention is much stronger in MENA than in other developing regions. In other words, external intervention of non-neutral and non-humanitarian type worsens polarization along religious lines in MENA, a result which suggests that conflict in the region has been associated with a public prize linked to sectarian norms.

30
# _C. Robustness checks_

The literature makes a distinction between military and non-military foreign interventions (e.g., interventions through diplomacy and trade sanctions), but most studies do not distinguish between different types of external military interventions. This paper focuses on non-neutral and non-humanitarian foreign military interventions (Int_nh), but in this section we turn our attention to another type of foreign military intervention – an intervention that is neutral, i.e. designed not to favor one warring group over another, and that is done for humanitarian reasons. Our hypothesis is that neutral and humanitarian military interventions (NH) are not significantly associated with conflict. We test this hypothesis by including in our model (8) both types of interventions: Int_nh and NH.

**Table 6 Logit Regressions for the Incidence of Civil Wars (PRIOCW)** **<u>(1965-1999)</u>**

||(1)|(2)|(3)|(4)|(5)|(6)|
|---|---|---|---|---|---|---|
|LGDPPC|-0.272|-0.351|-0.355|-0.296|-0.376|-0.380|
|LPOP|0.397***|.0.418***|0.419***|0.453***|0.477***|0.477***|
|PRIMEXP|-1.707|-1.423|-1.380|-2.678|-2.476|-2.428|
|MOUNTAINS|-0.001|-0.002|-0.002|0.004|0.003|0.003|
|NONCONT|0.430|0.355|0.364|0.546|0.372|0.369|
|DEMOCRACY|0.094|0.159|0.152|0.568|0.687|0.683|
|ETHFRAC|-0.054|-0.329|-0.345|0.366|0.123|0.125|
|ETHPOL|**2.450****|**2.672*****|**2.909*****|**2.120****|**2.243****|**2.378****|
|RELFRAC|-2.095|-1.877|-2.055|-2.821|-2.736|-2.854*|
|RELPOL|1.851|1.208|1.290|2.410|1.733*|1.797|
|Int_nh|**1.473*****|0.349|0.770|**1.240*****|-0.222|0.011|
|<br>Int_nh ˟ RELPOL||1.918*|1.943*||**2.428****|**2.433****|
|Int_nh ˟ ETHPOL|||-0.755|||-0.416|
|NH|1.011**|0.741|1.176|0.944*|0.078|0.389|
|NH ˟ RELPOL||0.510|0.510||1.404|1.366|
|NH ˟ ETHPOL|||-0.792|||-0.519|
|MENA||||2.117**|**2.220****|**2.200****|
|ASIA||||1.033|1.271|1.260|
|AFRICA||||0.855|0.875|0.854|
|LAAM||||0.348|0.378|0.356|
|Intercept|-8.030***|-7.497***|-7.618***|-9.758***|-9.246**|-9.275**|
|<br>N|859|859|859|859|859|859|
|McFadden’s R<sup>2</sup>|0.184|0.191|0.192|0.219|0.231|0.231|
|McFadden’s Adjusted R<sup>2</sup>|0.148|0.150|0.145|0.172|0.178|0.173|
The results presented in Table 6 indicate that the inclusion of neutral and humanitarian external military interventions (NH) preserves our findings of significant and positive association between non-neutral and non-humanitarian interventions and conflict. Only in specifications (1) and (4) in Table 6, NH is positively and significantly associated with the incidence of civil war. However, in all other specifications (columns (2), (3), (5), and (6) of Table 6), which feature the interaction of intervention with the polarization measures, neutral and humanitarian external intervention variable is not significant and neither are its interactions with religious and ethnic polarization. This result implies that only non-neutral and non-humanitarian external military intervention modifies RELPOL and only this type of intervention is associated with conflict regardless of the presence of efforts to intervene in a neutral way for humanitarian purposes. Finally, we also test and confirm the robustness of the results to changes in the conflict intensity and the single-equation logit model specifications (Table 7).

**Table 7 Logit Regressions for the Incidence of Civil Wars: Comparing Alternative -** **<u>Definitions of Civil War (1965 2005)</u>**

||**(1)**|**(2)**|**(3)**|**(4)**|**(5)**|**(6)**|**(7)**|**(8)**|
|---|---|---|---|---|---|---|---|---|
|**Dependent Variable**|PRIO25|PRIO25|PRIO25|PRIO25|PRIO1000|PRIO1000|PRIO1000|PRIO1000|
|LGDPPC|**-0.65**<sup>*******</sup>|**-0.50**<sup>*******</sup>|**-0.73**<sup>*******</sup>|**-0.54**<sup>*******</sup>|**-0.59*****|-0.39<sup>**</sup>|**-0.63**<sup>*******</sup>|**-0.47**<sup>*******</sup>|
|LPOP|**0.33**<sup>******</sup>|**0.20**<sup>******</sup>|**0.35**<sup>******</sup>|**0.21**<sup>******</sup>|**0.15**|**0.04**|**0.17**|**0.06**|
|PRIMEXP|-0.35|-0.33|0.02|-0.18|-1.23|-1.67<sup>*</sup>|-0.83|-1.15|
|MOUNTAINS|0.01|0.01|0.01|0.01|0.01|0.01|0.01|0.01|
|NONCONT|0.99<sup>**</sup>|0.75<sup>*</sup>|0.97<sup>**</sup>|0.76<sup>**</sup>|0.93|0.85<sup>*</sup>|0.88|0.79|
|DEMOCRACY|0.30|0.24|0.33|0.24|-0.10|-0.03|-0.06|0.02|
|ETHFRAC|0.23|0.09|0.10|0.04|**0.78**|**0.84**|**0.38**|**0.65**|
|ETHPOL|1.83<sup>**</sup>|**1.41**<sup>******</sup>|**2.2**<sup>**7*****</sup>|**1.82****|2.16*|1.5<sup>8**</sup>|3.34<sup>**</sup>|2.86<sup>**</sup>|
|RELFRAC|||-0.16|-0.58|||1.20|1.03|
|RELPOL|||-0.48|-0.02|||-1.06|-1.08|
|Intnh|1.14<sup>***</sup>|1.29<sup>***</sup>|**1.10**|**1.61**<sup>*****</sup>|**0.90**<sup>*******</sup>|0.69<sup>*</sup>|**1.38**|**1.72**|
|_<br>Dependent variable lag||2.72<sup>***</sup>||2.71<sup>***</sup>||3.05<sup>***</sup>||3.07<sup>***</sup>|
|<br>Intnh˟ RELPOL|||1.70<sup>**</sup>|1.17|||**1.93**<sup>*****</sup>|**1.57**|
|_<br>Intnh˟ ETHPOL|||-1.73|-1.90|||--2.93<sup>*</sup>|-3.64<sup>**</sup>|
|_<br>Intnh˟|3.05<sup>***</sup>|1.23|3.29<sup>***</sup>|1.52*|2.93<sup>***</sup>|2.48<sup>***</sup>|2.82<sup>***</sup>|2.57<sup>***</sup>|
|_<br>RELPOLxMENA|||||||||
|Intercept|-3.20|-2.77<sup>*</sup>|-2.78|-2.57<sup>*</sup>|-2.36|-2.14|-2.69|-2.48|
|<br>N|946|863|946|863|946|863|946|863|
|McFadden’s R<sup>2</sup>|0.196|0.381|0.204|0.385|0.180|0.379|0.195|0.391|
|McFadden’s Adjusted<br>R<sup>2</sup>|0.175|0.357|0.175|0.353|0.146|0.339|0.147|0.337|

32
# **V. Endogeneity issues**

The possible mutual relationship between the dependent variable and two of the explanatory variables raises the issue of endogeneity bias. The real per capita GDP and the external military intervention are two potentially endogenous variables. The risk of conflict is higher in poor countries, but civil conflict also affects real per capita incomes due to damage to infrastructure, loss of labor, skills and productivity, causing erosion in per capita incomes over time. Similarly, conflict can lead to external intervention, but it is also possible that external intervention may lead to conflict. The endogeneity bias is likely to be particularly strong in cases of prolonged and high-intensity civil conflicts because even if civil conflict onset preceded intervention, the intervention may create conditions that intensify and prolong the conflict. This section discusses how we deal with this issue and presents some robustness checks.

Aware of the possible endogeneity with respect to per capita income, Montalvo and Reynal-Querol (2005) and Esteban, Mayoral and Ray (2012) use periods of five years for civil wars and the GDP per capita in the beginning of the period. We adopt their approach of dealing with this source of endogeneity bias.<sup>35</sup> In this section, we develop a strategy for addressing the endogeneity with respect to external military intervention of the non-neutral and non-humanitarian type.

We estimate a version of equation (8) in which we include not only the intervention, Int_nh, but also its interaction with religious polarization, RELPOL:

> 35 Another way to deal with the endogeneity is by adding the lagged value of the dependent variable to the set of the right-hand side variables. Esteban, Mayoral and Ray (2012) added the lagged incidence of war to the list of explanatory variables to lessen the effect of endogeneity. The use of the lagged dependent variable can be effective, however, only in the absence of serial correlations in the errors of the estimated equation.

33
First, we test for endogeneity of the intervention variable and its interaction with RELPOL separately in the cases of MENA and non-MENA countries. As the Durbin-Wu-Hausman endogeneity test statistic shows, we cannot reject the exogeneity null of these two variables in the case of non-MENA countries even at the 10% significance level. However, we reject the null in the case of MENA countries at the 1% significance level. Therefore, we use a linear probability model (LPM) to estimate equation (8.1),<sup>36</sup> while in the case of MENA we employ a two-stage linear probability model (TSLPM). The choice of TSLPM rather than a two-stage logit model is based on the conclusion of Angrist and Kruger (2001) that a linear regression in the first stage generates consistent second-stage estimates in case of an endogenous dummy variable. Moreover, using nonlinear models such as probit or logit to generate fitted values in the first stage for use in the second-stage does not generate consistent estimates unless the nonlinear model happens to be exactly right.

In the first stage, we estimate simultaneously the system of equations (9.1) and (9.2): This system represents a reduced-form specification for the intervention and interaction variables and includes a vector of instruments, X3it. We consider as potential instruments for intervention the number of bordering countries to country _i_ (BORD) and the total length of the border of country _i_ in kilometers (TOTBORD). This choice of variables is motivated by Gleditsch (2007) who finds

> 36 We obtain similar results with the logit.

34
that transnational linkages and attributes of neighboring countries can exert a substantial impact on the risk of conflict. He argues that a country is at a substantially higher risk of civil conflict if it has many transborder groups on its territory or if it is located next to a country in conflict or an authoritarian country. During the period of estimation most MENA countries were authoritarian or fragile and many of them hosted transborder groups, including some located in conflict countries, so the likelihood of non-neutral and non-humanitarian external intervention in a specific country is expected to be linked with the number of bordering countries or alternatively with the length of its border. The F test for excluded instruments confirms the strength of both instruments (BORD and TOTBORD). Since intervention interacts with religious polarization in equation (8.1), we also include as an instrument in equations (9.1) and (9.2) the interaction of the instrument with RELPOL. In the case of MENA, the use of BORD as an instrument interacted with RELPOL results in a predicted value of Int_nh x RELPOL whose coefficient is significant only at the 6% significance level. Therefore, we use the alternative instrument, TOTBORD, along with its interaction with RELPOL, which leads to a significant coefficient on the predicted value of Int_nh x RELPOL at the 1% significance level. The Stock-Wright test for the joint significance of all excluded instruments confirms that we can reject the null that the coefficients on all our instruments are zeros. In addition, the Hansen J test of over-identification confirms the null of absence of correlation between TOTBORD and its interaction with RELPOL and the errors in the incidence-of-civil-conflict equation (8.1). These results convey a good evidence of the strength and suitability of our instruments. In the second stage, we estimate the incidence-of-civil-conflict equation (8.1), using the estimates of intervention and its interaction with RELPOL from the first stage. In the 2<sup>nd</sup> stage the dependent variable is high-intensity conflict (PRIO1000) because of our hypothesis that intervention leads to this type of conflict. Our estimates are efficient for homoscedasticity and robust to heteroscedasticity.

35
Table 8 displays the LPM estimation results for the non-MENA panel in column 2 and the TSLPM estimation results for the MENA countries in columns 3-5.<sup>37</sup> The coefficient of Int_nh in column (2) is negative and significant, while the coefficient of the interaction term Int_nh x RELPOL is positive and highly significant. However, the total effect of Int_nh on conflict is insignificantly different from zero.<sup>38</sup> ETHPOL is highly significant and positive, and the effects of other traditional variables are in line with those obtained in Esteban, Mayoral and Ray (2012).

The results from the first-stage estimation for the MENA panel suggest that the interaction of TOTBORD with RELPOL is a significant determinant of external intervention. This result is in line with the notion that the longer the border of a country in the Middle East the higher the probability of having a transborder ethnic or sectarian group and therefore the higher the probability of external interventions enabled by the presence of a cross-border group. The effect of primary exports on intervention is highly significant and positive in the first-stage estimation, suggesting that in this oil-rich region, external interventions are also driven by a private prize linked to oil resources. The effect of MOUNTAINS is significant and negative as expected because the presence of mountains makes it harder to intervene with boots on the ground. In the secondstage conflict-incidence equation, ETHPOL is an insignificant factor in explaining civil conflict in MENA. The coefficient of the interaction term between predicted intervention and RELPOL is highly significant and positive, which confirms that intervention exacerbates religious polarization and leads to high intensity conflict. Thus, we cannot reject the hypothesis that non-neutral and non-humanitarian intervention is a determinant of civil conflict in MENA. Moreover, it appears that the effects of some of the other exogenous variables (e.g., PRIMEXP and LGDPC) on the

> 37 We apply the STATA option of variance clustering at the country level.

> 38 The total effect is that of the external intervention and its interaction with RELPOL and is measured at means of the variables.

36
incidence of civil conflicts are indirect, occurring either through the intervention variable or its interaction with RELPOL. These results suggest that unlike in non-MENA, where conflicts are mostly about a public prize linked to ethnic polarization, in MENA they are mostly about a public prize linked to sectarian polarization.

**Table 8. Two-Stages Linear Probability Model Panel 1965-2005**

||**LPM**||**TSLPM**||
|---|---|---|---|---|
||**Non-MENA Pane**|**l**|**MENA Panel**||
||Eq. (8.1)<br>(2)|1st stage<br>Eq. (9.1)<br>(3)|1st stage<br>Eq. (9.2)<br>(4)|2nd stage<br>Eq. (8.1)<br>(5)|
|**Dep. Variable**|PRIO1000|Int_nh|Int_nh x<br>RELPOL|PRIO1000|
|LGDPC|-0.054<sup>***</sup>|-0.26|-0.03|0.029|
|LPOP|0.023<sup>***</sup>|-0.09|-0.08<sup>**</sup>|-0.012|
|PRIMEXP|0.048|1.18<sup>***</sup>|0.05|-0.21|
|DEMOCRACY|0.016|0.09|-0.11|-0.27<sup>**</sup>|
|MOUNTAINS|0.001|0.01|0.002<sup>***</sup>|0.005<sup>**</sup>|
|NONCONT|0.084<sup>**</sup>||||
|ETHPOL|0.182<sup>***</sup>|-0.18|0.08|-0.031|
|RELPOL|-0.055|-2.82|-1.69|-0.064|
|TOTBORD||-0.000|-0.000||
|TOTBORD<sup>x</sup>RELPOL||0.0003<sup>**</sup>|0.0003<sup>***</sup>||
|LAAM|0.022||||
|SAFRICA|0.020||||
|ASIAE|-0.017||||
|LGDPxRELPOL||0.18|-0.03||
|PRIMEXPxRELPOL||-1.34<sup>*</sup>|0.30||
|DEMOCRACYxRELPOL||0.51|0.59<sup>*</sup>||
|MOUNTINS*RELPOL||-0.04<sup>***</sup>|-0.03<sup>***</sup>||
|LPOPxRELPOL||0.11|0.12||
|Int_nh|-0.141<sup>**</sup>|||-0.125|
|Int_nh<sup>x</sup>RELPOL|0.424<sup>***</sup>|||1.044<sup>***</sup>|
|Constant|0.008|1.94|1.40<sup>***</sup>|0.010|
|N|824|122|122|122|
|CenteredR<sup>2</sup>||||0.181|
|Durbin-Wu-Hausman Endogeneity<br>2<br>|0.597|4.505<sup>***</sup>|||
|test|||||
|F test of excluded instruments||11.03<sup>***(15%</sup><br>bias)|23.76<sup>***(5%</sup><br>bias)||
|Stock-Wright test for the joint significance<br>ofallexcludedinstruments||||33.48<sup>***</sup>|
|HansenJtest||||5.361|

Notes:<sup>***(15% bias)</sup> and<sup>***(5% bias)</sup> indicate that we can reject the null hypothesis of weak instrument at the 1% significance level, using Stock and Yogo (2005) critical values, allowing respectively for 15% and 5% bias of maximal TSLP relative to the LPM estimator.

37
# **VI. Conclusions**

This paper develops the theory behind the link between polarization, foreign military intervention, and civil conflict. Specifically, in a behavioral model of civil conflict external military interventions alter the resources available to warring groups and their probability of winning. In this case, equilibrium level of conflict depends on the distributional measures, modified by the effect of external intervention. It can be shown that in relatively populous countries, the equilibrium level of conflict depends on the level of polarization modified by the intervention, in the case of conflict over a public prize linked to horizontal divisions, and on the level of fractionalization, in the case of conflict over a private prize.

We test the model empirically and find that ethnic polarization is a robust predictor of civil conflict and that religious polarization is positively and significantly associated with conflict in the presence of non-neutral and non-humanitarian external military interventions. Such external interventions exacerbate religious polarization leading to high-intensity conflicts in the Middle East and North Africa region, but not in the rest of the world. The results are robust to allowing for different definitions of conflict, model specifications, and data time span and to controlling for neutral and humanitarian external interventions, which are not significantly associated with conflict.

It appears that the weak explanatory power of religious polarization on the incidence of civil war found in earlier studies is due to the fact that these studies do not consider the regional heterogeneity and the moderating effect of external military intervention on polarization. These results have important policy implications. They identify non-neutral and non-humanitarian external military intervention as a possible channel for increased risk of high-intensity civil conflict in the Middle East and North Africa. Furthermore, they suggest that unlike in the rest of the world 38
where civil conflicts are mostly about a public prize linked to ethnic divisions, in MENA they are mostly about a sectarian-related public prize. Future work should explore the specific mechanisms through which external military interventions of the non-neutral and non-humanitarian type affect polarization, the formation of horizontal groups contending a prize, and the measurement of overlapping polarization along multiple lines of division. The reliance on the IMI data set restricted the focus of the analysis to non-humanitarian and non-neutral external military interventions that involve the deployment of troops. Future work should look at other types of non-humanitarian and non-neutral types of interventions, including the transfer of funds and other types of support to rebel groups or to governments involved in disputes with rebels.

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