World Development Vol. 78, pp. 1–12, 20160305-750X/� 2015 Published by Elsevier Ltd.

www.elsevier.com/locate/worlddevhttp://dx.doi.org/10.1016/j.worlddev.2015.09.004

Oil and Civil Conflict: Can Public Spending Have a Mitigation Effect?

CRISTINA BODEAa, MASAAKI HIGASHIJIMAb,c and RAJU JAN SINGHd,*

aMichigan State University, USAbEuropean University Institute, ItalycWaseda University, Tokyo, Japan

dThe World Bank, Washington, DC, USA

Summary. — This paper explores the conditions under which public spending could minimize violent conflict related to oil wealth. Pre-vious work on the resource curse suggests that oil can lead to violent conflict because it increases the value of the state as a prize orbecause it undermines the state’s bureaucratic penetration. On the other hand, the rentier state literature has long argued that oil mightprovide states with resources to deliver public and private goods, and stabilize political regimes. The empirical evidence to settle theseconflicting predictions is limited. This paper argues that the effect of oil on civil conflict is conditional on the size of government expen-diture and the allocation of government spending for welfare or the military. To test these hypotheses, logit models of conflict onset areused and a global sample of 148 countries from 1960 to 2009 is examined. Higher levels of military spending are found to be associatedwith lower risks of both minor and major conflict onset in countries rich in oil and gas. By contrast, in countries with little oil or gasresources, increases in military spending are associated with a higher risk of conflict. Welfare expenditure is associated with a lower riskof small-scale conflict, irrespective of the level of oil revenue. However, general government spending does not appear to have any robustmitigating effects. Consistent with the focus in the more recent literature to disentangle the average effect of natural resources, these re-sults nuance the conditions under which there may be a resource curse. The results point to what governments can do with resourcerevenues to mitigate conflict risk.� 2015 Published by Elsevier Ltd.

Key words — civil conflict, natural resources, oil, public spending, military spending, welfare spending

*This research was part of the World Bank’s Africa Regional Studies. The

authors are grateful to Massimiliano Cali, Richard Damania, Shantayan

Devarajan, Francisco Ferreira, Maelan Le Goff, Philip Keefer, Stuti

Khemani, Auguste Kouame, Bryan Land, Magda Lovei, Anand Rajaram,

and Carolina Renteria for their helpful comments, as well as to the

participants of the Workshop on Conflict at the Department of Political

Science at Michigan State University and to three anonymous referees.Final revision accepted: September 13, 2015.

1. INTRODUCTION

The last decade has seen significant oil and gas discoveries.Ross (2012), for instance, reports that during the period 1998–2006 19 new countries, mostly low and middle-income, havebecome oil and gas exporters. At the same time, many of thesestates have experienced political violence, in particular rav-aging civil wars. This link between natural resources and con-flict outbreak has been identified by numerous studies (Collier& Hoeffler, 2004a, 2004b; Fearon, 2005; Fearon & Laitin,2003; Humphreys, 2005; Lujala, 2010; Lujala, Gleditsch, &Gilmore, 2005; Ross, 2006a, 2006b). Ross (2012) warns thatthe inflow of oil revenue into mainly poor nations is likelyto spread further the oil curse in the form of lack of democracyand civil conflict. While other causal mechanisms have beensuggested (Humphreys, 2005; Ross, 2006a, 2006b), such nega-tive outcomes can also be linked to features of oil revenue—non-tax based, unstable, and secretive—that limit the abilityand incentive of governments to spend such revenue in a pro-ductive manner (Ross, 2006a, 2006b).In this paper, we study the conditions under which the pat-

terns of public spending may mitigate the risk of violentdomestic conflict arising from the resource curse. Some recentresearch suggests that more government spending either ingeneral or specifically for welfare and the military may reducethe risk of civil conflict onset (Basedau & Lay, 2009; Fjelde &de Soysa, 2009; Hegre & Sambanis, 2006; Taydes & Peksen,2012). While oil wealth has begun to be considered in thestudy of civil conflict as an important source of revenue forgovernments, there has not been a systematic analysis ofwhether oil-rich countries can increase public spending or alterthe particular allocation of such spending to social sectors orthe military as a way to mitigate the risk of conflict. This paperlinks the literature on public spending and conflict, on the onehand, and that connecting natural resources and conflict, onthe other.

1

We use time-series cross-section data (148 countries, 1960–2009) to test the hypothesis that the effect of oil on civil conflictis conditional on the size of government expenditure and theallocation of government spending. Our dependent variableis the onset of minor and major armed conflict (Gleditschet al., 2002). The empirical estimations show that in oil andgas rich countries both minor and major conflicts are less likelywhen military spending is high. In contrast, in countries withlittle natural resources, increases in military spending are asso-ciated with a higher risk of conflict. Increased spending on edu-cation, health, or social security is associated with a lower riskof small-scale conflict, irrespective of the level of oil revenue.On the other hand, higher levels of general government expen-diture do not appear to have any robust mitigating effects.The paper proceeds as follows: the next section reviews

work on natural resources and conflict; Section 3 discussesthe literature on public spending and conflict; Section 4 derivestestable hypotheses; Section 5 presents the data and our empir-ical strategy; Section 6 describes the results; and the final sec-tion concludes.

2. NATURAL RESOURCES AND CONFLICT

A significant amount of research examines the reasons whysome countries experience violent civil conflict. Previous work

2 WORLD DEVELOPMENT

points to rebel motivation coming from grievance and injustice(Cederman, Weidmann, & Gleditsch, 2011; Gurr, 1970;Wimmer, Cederman, & Min, 2009) or economic opportunityand greed (Collier and Hoeffler, 1998, 2004a, 2004b). Otherparts of the literature emphasize the characteristics of the stateand the different facets of state capacity (Buhang & Rød, 2006;Fearon & Laitin, 2003; Hendrix, 2010; Thies, 2010).The literature on the resource curse is very prominent and

natural resources have been argued to influence conflictthrough similar channels (de Soysa, 2002, 2007; Dixon,2009; Fearon & Laitin, 2003; Lujala, 2010; Ross, 2004a,2012).1 Two groundbreaking papers, Collier and Hoeffler(2004a) and Fearon and Laitin (2003), both show that wealthin natural resources increases the probability of civil waronset. Collier and Hoeffler (2004a) suggest that naturalresources finance rebel groups and thus lower opportunitycosts for rebellion. On the other hand, Fearon and Laitin(2003) emphasize the fact that oil producers tend to haveweaker state apparatuses, which makes it difficult for govern-ments to sustain efficient conflict prevention, a conclusionsupported by Humphreys (2005). In addition, Fearon andLaitin (2003), Englebert and Ron (2004), Fearon (2005), andBesley and Persson (2009) argue that natural resources swellthe state’s coffers and thus increase the value of the state,which is then more likely to induce conflicts over the state asa ‘‘prize”.The negative effect identified by the resource curse literature,

however, may be related in particular to oil and not to naturalresources in general. Fearon and Laitin (2003) and Fearon(2005) find no robust support for the role of primary commodi-ties in civil conflict onset. This view is supported by de Soysaand Neumayer (2008) who show that even when looking at awider range of natural resources, only hydrocarbons affect civilwar onset. Finally, Ross (2004a) reviews 14 quantitative studiesof the resource–conflict link. He concludes that primary com-modities as a whole cannot be robustly linked to either civilwar onset or duration. Only oil-exporting countries seem tobe particularly prone to civil war onset. This finding is sup-ported by another meta-analysis conducted by Dixon (2009).On the other hand, research has long suggested that oil

might provide states with resources to deliver public or privategoods and stabilize political regimes, be they democracies ordictatorships. Considerable work suggests that naturalresource rents can, in fact, bring stability to the state–societyrelationship (Basedau & Lay, 2009; Beblawi & Luciani,1987; Fjelde, 2009; Mahdavy, 1970; Morrison, 2009; Ross,2012; Smith, 2004). Bueno de Mesquita, Smith, Siverson,and Morrow (2003) point out that government spending deci-sions are strategic responses aimed at maintaining power.Regimes can offset oil-related or other conflict risks by gener-ous and large-scale distributional policies, and as a result grie-vances are less likely to emerge. A large security sector,financed by oil money, also helps to render rebellion more dif-ficult.More specifically, Ross (2001) argues that oil wealth has two

mechanisms through which governments provide goods thatreduce social pressures against the government. First, naturalresource wealth allows governments to buy off citizens usinglow tax rates and patronage (a ‘‘rentier effect”). The secondis a ‘‘repression effect”: natural resources allow governmentsto strengthen the military and security forces to maintainsocial order.2 Along the same lines, Smith (2004) andMorrison (2009) both show that natural resources or non-tax revenues tend to increase political stability by prolongingregime durability. Ulfelder (2007) and, more recently,Wright, Franz, and Geddes (2014) also find that autocracy

and individual autocratic leaders are more durable in naturalresource rich countries.For instance, proceeds from oil allowed Yemen elites to buy

peace for a while. Oil rents in Yemen are argued to have beenused to buy tribal, military and bureaucratic allegiancesthrough state jobs, contracts or subsidized fuel, assuring polit-ical stability (World Bank, in press). Spending on defense wasalso widely seen as key sources of patronage. Senior militaryofficers would allegedly use the salaries of ‘‘ghost” soldiersand the sale of military equipment and fuel to bolster theirincomes. This system which characterized Yemeni politicsfor the 30 years before 2011 collapsed partly as a result ofthe decline in oil production, resulting in a substantial reduc-tion in the resources available for sharing since the early 2000s.Competition increased among Yemen’s elites over a shrinkingpool of resources, breeding instability.The ‘‘rentier state” and the resource curse arguments thus

offer conflicting predictions, and the literature has examinedpossible background factors that may condition the effect ofoil on conflict. For instance, Humphreys (2005) finds thatthe presence of oil production significantly increases the likeli-hood of civil war in weak states and may lower conflict risk instrong states. Fjelde (2009) finds that oil wealth tends to mit-igate civil war risk if political corruption is high enough tohelp buy off oppositions and placate restive groups by provid-ing patronage in exchange for political loyalty.In a paper most closely related to ours, Basedau and Lay

(2009) find that oil wealth (when controlling for oil depen-dence) reduces the risk of conflict onset. Their work on a smallsample of countries with high average dependence on oil rev-enues shows that, comparatively, the countries rich in oil canmaintain peace because they engage in larger scale distributionand spend more on the military. The analysis is based, how-ever, on a simple comparison of country values to sample medi-ans for 27 oil dependent countries (after 1990) and mayoverlook important differences among countries. A more rigor-ous approach taking into account the possible non-linearitiesmentioned by Basedau and Lay (2009) and the endogeneityissues that plague many of the existing studies would be neededto understand better the possible mitigation effect of publicspending on the risk of conflict onset related to oil.

3. PUBLIC SPENDING AND CONFLICT

Until recently the empirical research has paid surprisinglittle attention to the relationship between the nature of publicspending and civil conflict. Azam (1995) uses a game theoret-ical model that explicitly links redistributive policy adopted bystates with domestic peace, pointing out the importance ofgovernments’ spending decisions in preventing violent conflict.However, following work by Collier and Hoeffler (1998,2004a, 2004b) and Fearon and Laitin (2003), theory andempirical work have mainly centered on whether rebel motiva-tion and state weakness, rather than government spendingdecisions, contribute to explaining the onset of violentconflict.3

The interest in government spending and its connection tocivil conflict has resurfaced, however. Several recent studiesexplore directly the impact of public spending on civil waronset. This work emphasizes specific types of spending includ-ing (1) general government spending, (2) social spending suchas education, health and social security, or (3) military spend-ing. For general government spending, Fjelde and de Soysa(2009) provide evidence indicating that higher governmentexpenditure enables governments to effectively buy off

OIL AND CIVIL CONFLICT: CAN PUBLIC SPENDING HAVE A MITIGATION EFFECT? 3

opposition and increase the welfare of marginalized groups.This has the potential to increase the status quo stakes ofkey social actors, as well as reduce grievance and inequity,thus reducing the appeal of violent challenges to power fromboth elites and the broader population.Studies on the impact on conflict of spending allocations to

specific sectors are also emerging. Taydes and Peksen (2012)find that higher welfare spending reduces the risk of civil con-flict. They argue that spending resources on social welfarepolicies leads to loyalty and support from citizens, whichincreases the difficulty of rebel recruitment. Through welfarepolicies that influence positively the living standards of citi-zens, governments can outspend the opposition, helping gainsupport from broad segments of the population, co-opt polit-ical opposition, and decrease the incentives for organizing arebellion. Taydes and Peksen also argue that social spendingpromotes economic development, thereby raising further theopportunity cost of rebellion.Authors have documented a number of cases where cash

transfer programs were introduced to improve national cohe-sion (Moss, Lambert, & Majerowicz, 2015). Mexico launched,for instance, its Progresa program in part to address the rootsof the 1990s Chiapas uprising, while the rapid expansion ofArgentina’s Jefes y Jefas de Hogar attempted to defuse ten-sions stemming from rising unemployment. Kenya extendedcash transfers to promote stability following the political vio-lence that rocked the country in 2008. Similarly, SierraLeone’s and Nepal’s interventions are argued to have beendesigned to promote social cohesion and contribute to peaceprocesses.Other work focuses more specifically on individual items of

government social spending such as education. The majorityof recent work identifies a benefic effect: the level of educationspending has been argued to have a positive impact on pre-venting civil war onset by mitigating relative deprivationamong citizens (Thyne, 2006), increasing opportunity costsfor the youth to take up arms (Collier & Hoeffler, 2004a),and nurturing social stability and people’s generosity (Lipset,1959). Thyne (2006) posits two key mechanisms throughwhich education spending lowers the risk of civil conflictonset. First, by investing state resources in education, govern-ments can send a strong signal toward citizens that the govern-ment is trying to improve their lives. Thus, educationalinvestment reduces grievance, which contributes to lowingthe risk of civil war. Second, he suggests that education pro-motes social cohesion by encouraging students to cultivateinterpersonal skills and thus learn how to resolve disputespeacefully. Such social cohesion enables the country to achieveeconomic and social stability, which lessen the incidence ofviolent conflicts. In a similar vein, Barakat and Urdal (2009)examine how greater level of educational attainment lowersthe risk that large male youth bulges are associated with vio-lent conflict. The argument is that education raises the oppor-tunity cost for male youth (the key suppliers of rebel labor) toengage in violent conflict.4

Military spending is also an important aspect of state capac-ity to pacify violent conflict via coercion and policing. Thebasic argument is that the strength of the military can bothdeter insurgency and repress it while in infancy. Fearon andLaitin (2003) suggest that ‘‘most important for the prospectsof a nascent insurgency, however, are the government’s policeand military capabilities and the reach of government institu-tions into rural areas.”5 Empirically, Hegre and Sambanis’(2006) sensitivity analysis shows that the size of military per-sonnel tends to be negatively and robustly correlated with civilwar onset. Yet Collier and Hoeffler (2004b) and Taydes and

Peksen (2012) find no effect of military spending on civil waronset, and the opposite is also suggested: Henderson andSinger (2000) argue that because higher military expenditurecrowds out social spending, economic growth and investment,subsequent citizens’ grievance is more likely to be linked withinsurgency and thus fuel violent conflict.

4. HYPOTHESES

The literature reviewed earlier suggests that governmentspending in general and specific allocations to welfare or mil-itary spending may reduce the risk of civil conflict onset (‘‘therentier state” view). Yet, states with oil revenues appear ingeneral to have experienced more civil conflict (‘‘the oil curse”perspective). There is thus a need to clarify the hypothesesbehind the relationships linking oil revenue, public spending,and risk of conflict onset to understand better this seemingcontradiction. The manner in which the government uses nat-ural resource revenue can affect significantly the rebels’ view ofrewards and costs from violent conflict. Against this back-drop, the government has several options to use the country’snatural resource wealth.A first use is predatory. This involves spending such non-tax

resources literally as rents or private goods for members of asmall inner circle, including a country’s top leader. Oil wealthin this case is consumed by members of a small, privilegedgroup with access to leaders’ favors, often siphoned in privateforeign bank accounts or spent on luxury goods. Bratton andvan de Walle (1994) argue that leaders in such personalistregimes simply aim to ‘‘acquire personal wealth and status.”Most of the revenues from the country’s natural resourcesgo into the leader’s own pockets without significant distribu-tion through party organizations or the legislature (Gleason,2010).6 Leaders’ monopoly of economic wealth in suchregimes may increase the risk of civil conflict, because suchdominance of wealth enhances the value of the state as a prize,which increases the appeal to take up arms. Gandhi andVreeland (2004) find that predatory dictatorships, that is,dictatorships without institutions such as legislatures andparties are more likely to experience civil war.An alternative option would be to use oil resources for

broad-based patronage, including spending on social orwelfare public goods and on the security apparatus. Thegovernment would in this case use oil wealth to providepatronage more broadly to powerful groups across society,placate the opposition and generally increase the inclusivenessof the power base of the state through a strategy of co-optation.Revenues from natural resource may also be spent on publicgoods such as infrastructure, education, sanitation, pension orunemployment benefits, all of which benefit citizens at large.Finally, the government may use oil wealth to strengthen thesecurity apparatus including the military and police. In consoli-dated democracies, where there is significant oversight over thebudget, increasing military expenditure provides public goodsfor citizens in the form of domestic and international security.In mixed regimes and autocracies, on the other hand, militaryspending is primarily used as investment in repression, aspatronage to regime loyalists, or direct rents to the military toprevent possible coup attempts (Collier & Hoeffler, 2005).Using natural resources to provide patronage, public goods

or security through public government spending can increasethe opportunity cost of rebellion in various ways. First, bymaking public spending commitments the government cansend a signal to potential rebel groups that the governmentcares about the general population and has made spending

4 WORLD DEVELOPMENT

commitments that are hard to retract at a later date.7 Suchcommitments may include public goods. As Thyne (2006) sug-gests, ‘‘investment in domestic institutions is one way in whichthe government can signal that it cares about the population.This can be done in a variety of ways, such as increasedspending for water sanitation, securing basic health needs, orproviding a strong system of education”. Alternatively, publicspending commitments of oil revenue may be on patronage(construction contracts, public employment, or transfers)and used to ‘‘retain allegiance and integrate broader segmentsof the population into the power base of the regime” (Fjelde &de Soysa, 2009).8 The corruption implied by patronage maycontribute to economic stagnation and inequality. However,oil-based rents funneled through political corruption areshown to strengthen regimes and reduce the risk of civil con-flict (Fjelde, 2009; Smith, 2004). As noted earlier, the role ofrents and, implicit corruption is also emphasized by the origi-nal literature on the rentier state (Beblawi & Luciani, 1987;Mahdavy, 1970) and argued to provide vital resources toruling elites.In oil-rich countries, the signaling function and public nat-

ure of spending commitments can be even more importantthan in oil-poor countries. Such public commitments onspending by the government can work to lower rebel percep-tion about the value of the state as a prize going to small elite.Because oil resources are non-tax revenue, it is generally diffi-cult for citizens and rebels to figure out how much oilresources the government has and how much the ruling elitescan siphon out of the public coffers (Ross, 2012). Rebels mayoverestimate the value of the state. Signaling through the pro-vision of visible public goods can thus lower rebels’ expecta-tions of grabbing a high state prize following a successfulinsurgency. This should result in fewer incentives to take uparms, and more readiness to cooperate with the government.Even if large parts of government spending is directed towardpatronage rather than public goods, large public budgetspending can signal quite powerfully and openly the numberand sizes of groups that are likely to support the regime inplace and oppose a rebel challenge (Bratton & van de Walle,1997; Fjelde & de Soysa, 2009).This discussion leads to the following hypothesis: A larger

size of public spending in oil-rich countries is associated with alower risk of violent conflict onset (H1).In addition to the public signal sent by government spending

(versus predatory spending), using oil resources to specificallyincrease military expenditure is another strategy that govern-ments can adopt to avoid violent challenges. By financing boththe police and military, improving military equipment andadding personnel, the government is better able to deter andoverpower rebellious attempts. As previous work suggests, incountries with strong security forces, it simply becomes moredifficult for rebel leaders to militarily challenge the incumbentgovernment (Hegre & Sambanis, 2006). In addition, the secu-rity apparatus supported through high military spending mayguarantee a better enforcement of the rule of law and personalsecurity to citizens, increasing the political support for thegovernment in place.Some caveats apply, nevertheless, to the argument that

investment in the military deters rebellion or increases per-sonal security. Larger military budgets may not generate effi-ciency and loyalty, but may be a result of leaders bribing themilitary to keep them from staging a coup (Acemoglu,Robinson, & Verdier, 2004; Belkin & Schofer, 2003; Keefer,2010). Many countries at risk of civil war face other risks(Bodea & Elbadawi, 2007; Roessler, 2011; Svolik, 2009) andstacking the military with loyalists or ethnic group members,

shuffling, arresting, or executing high-ranking officers, or cre-ating multiple and overlapping units that are suspicious ofeach other can undermine the quality of the military forcesand make these regimes even more vulnerable. Increasingspending on the military can also have additional negativeeffects on development and popular grievance. Allocatingmore to the military may crowd out spending on social andwelfare policies (Henderson & Singer, 2000) and reduce eco-nomic growth (Knight, Loayza, & Villanueva, 1996).In oil-rich countries, the significant financial resources avail-

able to the state can mitigate these crowding-out effects. Oilwealth allows the government to honor their obligations tothe security apparatus and minimize the risk of the military‘‘quitting, striking, or using their arms against citizens”(Keefer, 2008), minimizing grievance both from the militaryrank-and-file and from the population. Thus, the rentier effectmay dominate the resource curse for countries with a signifi-cant amount of oil revenues.9

Following the discussion, we have a second hypothesis:Military spending in oil-rich countries is associated with a lowerrisk of violent conflict onset (H2).Finally, by increasing the amount of social spending includ-

ing expenditures in infrastructure, education, health and socialsecurity, the government could reduce grievance and garnerpolitical support from its citizens, increasing opportunity costsfor rebel recruitment. As Taydes and Peksen (2012) succinctlynote, ‘‘in return for productive social welfare policies, politicalleaders gain public loyalty, compliance, and support; (. . .) Thesecond and more indirect connection emphasizes the role ofsocial spending in promoting economic development, decreas-ing the impact of poverty, and undermining the opportunitystructure for rebellion.”10 Expansion in educational opportu-nities, health care spending, and social safety nets in the formof pensions and unemployment benefits all enable citizens tohave alternative options other than participating in insurgentactivities (Collier & Hoeffler, 2004a).In oil-rich countries with significant available resources, a

strategy of co-optation and public goods provisions can bean effective spending strategy. Basedau and Lay (2009) citelarge-scale distribution of resources or free health care andeducation in oil abundant countries as strategies to mitigatethe resources curse. They find that all but one of the oilabundant countries in their sample of 27 (net) oil-exportingcountries engage in above average distributional policies.11

In addition, Taydes and Peksen (2012) find an average mitigat-ing effect of welfare spending on conflict. Again, oil-producingcountries may face less of a resource constraint and increasingwelfare spending would imply fewer opportunities costs. Inthis context, one could expect a more potent mitigating effectof welfare spending on conflict risk in oil-rich countries.A third hypothesis follows: Social spending (education,

health and social security) in oil-rich countries is associated witha lower risk of violent conflict onset (H3).

5. DATA AND METHODOLOGY

(a) Dependent variable

Several data sources have been used for armed conflict,explaining in part the different results found in the literature.There are four major datasets: (1) Armed Conflict Dataset(ACD) from the Uppsala Conflict Data Program PRIO(Gleditsch et al., 2002); (2) Fearon and Laitin (2003); (3)Sambanis (2004); and (4) the Correlates of War, or COW(Sarkees and Wayman, 2010). All four use a threshold of1,000 battle deaths to define a civil war. The UCDP/PRIO

OIL AND CIVIL CONFLICT: CAN PUBLIC SPENDING HAVE A MITIGATION EFFECT? 5

dataset also codes minor armed conflicts of at least 25 battledeaths per year. These competing measures differ in relationto when to code the start, what counts as a war, and how totreat breaks in violence. Also, the datasets in Fearon andLaitin (2003) and Sambanis (2004) have a more limited cover-age, ending before 2000.To measure the onset of violent conflict, we use the Armed

Conflict Dataset (ACD) for years 1960–2009 (Gleditsch et al.,2002, version 4.1.) to generate a dichotomous variable thattakes the value of one in years with a new conflict onset andzero otherwise. This dataset has become the standard refer-ence for cross-country analyses of conflict determinants. Themajority of the recent studies have tended to use this source.Furthermore, along with major armed conflict, PRIO alsocodes the onset of minor armed conflicts as those above 25battle deaths per year. These smaller conflicts provide arelevant complement to the much rarer full blown civil wars.Adding these minor conflicts should assist in estimating thedeterminants of rare events such as conflict onset. FollowingRoss (2012), we regard a conflict as a new conflict onset if itoccurs two years after the previous conflict. The ACD definesviolent conflict as ‘‘a contested incompatibility that concernsgovernment and/or territory where the use of armed forcebetween two parties, of which at least one is the governmentof a state, results in at least 25 battle-related deaths”(UCDP/PRIO, 2012). As mentioned above, we also use the1,000 battle-related deaths threshold to measure the onset ofmajor civil conflict.

(b) Key independent variables: natural resources and publicspending

(i) Oil revenue

To operationalize oil revenue, we follow Ross (2012) anduse his oil–gas value per capita.12 The data measure the valueof oil and gas production per capita, multiplying the amountof oil gas production in a country with current oil and gasprices. These data have advantages over other measures thatscale oil production to GDP or exports, both of which canbe driven down by risk of civil war. More importantly, it givesa sense of the size of the oil wealth available to the governmentfor spending.13

(ii) General government spending

We use general government final consumption expenditurerelative to GDP (WDI). This includes all government current

Table 1. Variations in spending among

Total government spending HighLow

Military spending HighLow

Education spending HighLow

Health spending HighLow

Social security spending HighLow

Note: Countries are defined as oil abundant if oil–gas value per capdollars). Countries are oil producers if oil–gas value per capita radollars). Each spending item is regarded as high if it is above the

expenditures for purchases of goods and services (includingcompensation of employees). It also includes expenditure onnational defense and security, but excludes government mili-tary expenditures.

(iii) Military spending

The Correlates of War Project (COW) provides informationon total military expenditure that we scale by total popula-tion.14

(iv) Welfare spending

This variable includes total health, social security andeducation expenditures relative to GDP. Missing observationsin the welfare-spending variable, especially in developingcountries, is an important issue that may pose difficulties ininterpreting results. Therefore, we use an imputed welfare-spending variable provided by Taydes and Peksen (2012)based on Stata’s ICE multiple imputation procedure. Theprocedure specifically imputes missing observations based onthe pattern of the observed values of the non-missing variablesand creates a completed dataset.15

Table 1 shows descriptive statistics on oil revenue and publicspending based on data for all countries except westerndeveloped democracies. We group oil-rich countries in twocategories: oil abundant countries (more than 996 dollars ofoil–gas value per capita, or above the 90th percentile forRoss’ (2012) oil–gas value per capita in the sample of non-western countries); and oil producing countries (oil gas valueper capita is between 109 and 996 dollars, or the range between75th and 90th percentiles). We further classify countriesaccording to whether they are low or high on various categoriesof public spending (the cut point is the mean). The classifica-tion of countries in the tables is based on national means,which are computed by taking within-county means over time.There is a remarkable variation in the pattern of govern-

ment spending in countries with significant oil revenue. Noclear pattern appears to emerge. Oil abundant countries canhave high ratios of government spending to GDP (average21.29%; examples include: Russia, Equatorial Guinea, SaudiArabia, Kuwait, Bahrain, Qatar, Oman, Brunei) or moremodest ones (average 12.3%; examples include: Trinidad,Venezuela, Gabon, United Arab Emirates, Turkmenistan).Similarly, significant resources in oil abundant countries canbe directed to the military (average of 7.85% of military spend-ing to GDP; examples include: Bahrain, Brunei, Iraq, Kuwait,Libya, Oman, Qatar, Russia, Saudi Arabia, United Arab

oil-rich countries: average spending

Oil abundant Oil producer

21.29% (8.17) 18.2% (6.0)12.3% (6.0) 12.12% (3.11)

7.85% (9.09) 4.69% (4.27)0.97% (1.12) 1.09% (0.76)

5.51% (2.11) 5.52% (1.57)3.44% (1.08) 3.15% (1.43)

2.69% (1.05) 3.32% (1.32)1.86% (0.92) 1.37% (0.82)

4.78% (2.48) 3.6% (2.08)0.55% (0.62) 1.0% (0.97)

ita (Ross, 2012) ranges above the 90 percentile (more than 996nges between the 75 and 90 percentiles (between 109 and 996mean.

6 WORLD DEVELOPMENT

Emirates) or military spending can be much less prominent(average 0.97%; examples include: Equatorial Guinea, Gabon,Trinidad, Turkmenistan, Venezuela). The average differencebetween high and low spenders on welfare is less impressivebut it exists. Oil abundant countries that allocate significantresources to social security spend on average 4.7% of GDP(Kuwait), while those that allocate little spend on average0.55% of GDP (e.g., Bahrain, Equatorial Guinea, Gabon,Iraq, Libya, Oman, Qatar, Saudi Arabia, Trinidad, UnitedArab Emirates, Venezuela). Education spending shows similarpatterns, with some oil abundant countries spending above themean for developing countries (average 5.51%; examplesinclude: Brunei, Kuwait, Saudi Arabia, Trinidad, Venezuela),while other spend below that mean (average 3.44%; examplesinclude: Bahrain, Gabon, Iraq, Libya, Oman, Qatar, Russia,United Arab Emirates).

(c) Control variables

Along the lines of Fearon and Laitin (2003), our model alsoincludes a range of control variables, capturing the variety offactors possibly explaining conflict. All time-varying variablesare lagged one year. All models include the following vari-ables: the logged income per capita to control for the ‘‘state’soverall financial, administrative, police, and military capabili-ties” (Fearon & Laitin, 2003). This variable also captures theargument that there exist fewer grievances in a society withhigher levels of income; the log of the country’s populationto control for ‘‘the number of potential recruits to an insur-gency at a given level of income” (Fearon & Laitin, 2003);noncontiguous territory, because if a country has a territorialbase separated from the state’s center due to geography, rebelgroups could find it easier to take up arms; a country’s democ-racy score: a more democratic country should be less likely toexperience violent conflict because political rights and civil lib-erties are guaranteed in democracies so that people find iteasier to resolve conflict through non-violent means16;political regime instability: unstable regimes signal a weakenedstate capacity, leading to an increase in the risk of violent chal-lenges to government power; ethnic and religious fractional-ization captures the notion that civil wars are more frequentin heavily heterogeneous societies. Ethnically or religiouslydivided societies may face strong grievances, which increasesthe risk of violent conflict; and a dummy variable for ongoingwar: if a country is in a violent conflict with another group, otherrebel groups may find it easier to challenge the government.17

(d) Empirical model and econometric issues

Our dependent variable is the dichotomous indicator forconflict onset and empirical estimations are logit models withrobust standard errors, that include the duration of peaceyears (or years since independence) and cubic splines to con-trol for time dependence (Beck, Katz, & Tucker, 1998). To testour conditional hypotheses, we use interaction terms betweenthe measure of oil value and measures of broad public spend-ing and the specific spending items described above. Similar toprevious work, all time-varying variables are lagged one year.While previous studies are influential, the cross-country

empirics they are based on have not always taken fullyaccount of cross-country heterogeneity or the likely endogene-ity between conflict and its determinants. The endogeneity biasmay arise from measurement errors, omitted variables orpotential reverse causality between the risk of conflict onsetand our variable of interest, public spending. It is possible,for instance, that education enrollment drops as a civil warapproaches because people flee their homes in anticipation

of fighting. Likewise, expenditures may drop before an insur-gency as the government diverts resources from social expen-ditures to the military in order to defend itself. Studies ofconflict onset typically address this problem by lagging theexplanatory variables so that conflict onsets in a given yearare explained by the values on the explanatory variables inthe previous year. However, it is possible that problems withreverse causality appear before t � 1.To take account of unmeasured regional effects, all estima-

tions include regional dummies as in Fearon and Laitin(2003) for Asia, the Americas, Africa, and Europe (the MiddleEast being the reference region). Random effects are alsoadded to the logit models. Because the dependent variable isbinary, fixed effects would drop all the countries that do notexperience any conflict over the period of study. Yet, at thesame time, it may be the case that the effect of interactionsmay differ systematically due to country specific conditions,even after the inclusion of our control variables. Therefore,as an alternative, we include country-level random effects toaccount for the likelihood that each country may have differ-ent effects with regard to the interaction term.Finally, to further test our results for military spending—as

shown below, these are the most robust statistically significantresults—we also consider instrumental variable (IV) estima-tions. Following Collier and Hoeffler (2004a, 2004b), we usefour instrumental variables: military spending in neighboringcountries relative to home country’s GDP, a Cold Wardummy, current engagement in international war, and timepassed since the last international war after WWII.18 Collierand Hoeffler (2004b) suggest that current civil war risk in acountry is unlikely to affect the average level of military spend-ing in all neighboring countries, the demise of the Cold Warera, the country’s decision to wage an international war orits history of joining international conflict. International riv-alry and the risk of international war are key determinantsof decisions to spend on the military as was the cold war(Fordham & Walker, 2005). We expect therefore that the vari-ables proposed by Collier and Hoeffler (2004b) are good can-didates for instruments. These exclusion restrictions may fail,however, given some evidence of civil conflicts spreading intoneighboring countries and their contribution to regional con-flict. As a robustness test, therefore, we verify whether ourresults hold when we exclude the military spending of neigh-bors and international conflict from our list of instruments.19

6. RESULTS

Tables 2 and 3 report our key results. We show the resultsfor both minor and major conflict onsets. We include thespending items in distinct models because these variableseither overlap (general spending and spending allocations onmilitary and welfare) or are complements (spending alloca-tions). As part of our robustness tests, we discuss alternativespecifications. The coefficients on the control variables havebroadly the expected signs. Political instability increases therisk of both minor and major conflicts. More populous coun-tries also face a higher chance of civil conflict. The estimatedcoefficient for states with noncontiguous territory is positiveand consistent with Fearon and Laitin (2003). Ethno-linguistic fractionalization (ELF) increases the risk of minorconflict, while it does not appear to be associated with majorconflicts. Democracy reduces the risk of large-scale conflict,while it has an ambiguous effect on minor conflicts. Finally,economic development, operationalized as income per capitais not predicting civil conflict in our models.

Table 2. Conditional effect of oil wealth on conflict onset

Model 1Minor conflict

onset

Model 2Major conflict

onset

Model 3Minor conflict

onset

Model 4Major conflict

onset

Model 5Minor conflict

onset

Model 6Major conflict

onset

Oil–gas value per capita (1,000 USD) 0.17 �0.52 0.20 �0.08 �0.08 0.11(0.124) (0.381) (0.149) (0.236) (0.166) (0.481)

Government expenditure 0.0156 0.0036(0.014) (0.025)

Gov expenditure * oil �0.0131* 0.01(0.008) (0.016)

Military expenditure per capita 0.0012*** 0.002***

(0.0003) (0.0004)Military expenditure * oil �0.001*** �0.001***

(0.0004) (0.0003)Welfare expenditure �0.109*** �0.005

(0.0340) (0.038)Welfare expenditure * oil �0.0003 �0.054

(0.0175) (0.069)ELF 1.609*** 0.508 1.508*** 0.517 1.484*** 0.198

(0.479) (0.952) (0.435) (0.928) (0.506) (0.927)Religious fractionalization �0.704 0.672 �0.23 0.603 �0.3 0.621

(0.455) (0.712) (0.499) (0.814) (0.538) (0.794)Political instability 0.686*** 0.715** 0.741*** 0.739*** 0.792*** 0.708**

(0.186) (0.300) (0.171) (0.285) (0.215) (0.285)Non contiguity 1.166*** 1.286* 1.171*** 1.325** 1.293*** 1.989***

(0.377) (0.680) (0.330) (0.595) (0.281) (0.571)Polity IV 0.0375 �0.115** 0.0258 �0.127*** 0.0529* �0.108**

(0.026) (0.048) (0.023) (0.042) (0.031) (0.044)Logged population 0.362*** 0.417*** 0.348*** 0.397*** 0.219*** 0.338***

(0.067) (0.110) (0.061) (0.093) (0.074) (0.112)Logged GDP per capita �0.00887 0.155 �0.0915 0.0254 �0.286* �0.295

(0.095) (0.123) (0.099) (0.133) (0.156) (0.239)Constant �12.43*** �14.46*** �11.61*** �13.59*** �6.015*** �10.15***

(1.540) (2.330) (1.300) (2.002) (2.107) (3.335)Psedo R squared 0.126 0.114 0.123 0.118 0.14 0.13Log pseudolikelihood �611.51 �253.83 �692.3 �288.59 �503.73 �247.60Wald Chi2 355.51*** 98.17*** 414.25*** 125.25*** 175.81*** 83.69***

Observations 5,190 5,190 5,618 5,618 4,108 4,108

Note: ***p < 0.01, **p < 0.05, *p < 0.1. The estimation method is logistic regression. In Models 1, 3 and 5, the dependent variable is the onset of minorconflict (more than 25 deaths), whereas Models 2, 4, and 6 set the onset of major conflict (more than 1,000 deaths) as the dependent variable. Models 5 and6: Welfare spending based on imputed data available from Taydes and Peksen (2012). Regional dummies, half-decade dummies, peace years and cubicsplines are included in all models. Country clustered standard errors in parentheses.

OIL AND CIVIL CONFLICT: CAN PUBLIC SPENDING HAVE A MITIGATION EFFECT? 7

General government spending is not robustly associatedwith a lower risk of conflict. Models 1 and 2 in Table 2 presentthe estimation results for oil revenue interacted with generalgovernment spending. While the results in Table 2 (Model 1)indicate a negative and statistically significant coefficient (atthe 10% level) in the case of minor conflict onsets, this resultdoes not hold for major conflicts (Model 2) or once randomeffects are included (Table 3, Models 7 and 8). Hypothesis 1does not appear to hold, whereby governments are able to mit-igate the increased risk of conflict onset related to oil revenueby signaling their willingness to use this revenue not just fortheir own enrichment, but also to reward their supportersand signal to would-be rebels the size of their coalition.Military spending, on the other hand, appears to have a mit-

igating effect both on major and minor conflict onsets. Models3 and 4 in Table 2 report coefficients from estimations thatinclude the interaction between oil–gas value per capita andmilitary spending per capita. The negative and statistically sig-nificant coefficients on the interaction terms show that higherlevels of spending on the military in oil-rich countries are asso-ciated with lower risks of minor and major conflicts. Theseresults remain unchanged even when random effects are

included (Table 3, Models 9 and 10) or when we use instru-mental variables (Table 3, Models 13 and 14), and supportour Hypothesis 2.In logit models the substantive effect of a particular indepen-

dent variable depends on the levels of all other variables. Tofacilitate the interpretation of the interaction between oil–gasvalue per capita and military spending per capita, Figure 1shows the predicted probability of minor conflicts at lowand high oil–gas value per capita for increasing levels of mili-tary spending using the estimation results from Model 3. Ver-tical lines show the 95% confidence interval around thepredicted probabilities. These predicted probabilities rangebetween 0 and 1 by definition, with all the variables kept attheir observed mean with the exception of the two that arevarying (military spending and oil/gas production).20

At low levels of military spending per capita, if anything, theproduction of oil and gas tends to increase the risk of violentconflict. The dotted line (no oil and gas production) is belowthe continuous line (high oil and gas production). In oil andgas rich economies, however, this increase in risk of small-scale conflict can be mitigated and even reversed withhigher levels of military spending. Moving along the military

Table 3. Additional analysis: logit models of conflict onset

Model 7

Minorconflict

onset

Model 8

Major conflict

onset

Model 9

Minor conflict

onset

Model 10

Major conflict

onset

Model 11

Minor conflict

onset

Model 12

Major conflict

onset

Model 13

Minor conflict

onset

Model 14

Major conflict

onset

Random effects Random effects Random effects Instrumental variables

Oil–Gas Value per capita (1,000 USD) 0.17 �0.48 0.16 �0.02 �0.14 0.28 0.0002 0.00003

(0.22) (0.99) (0.18) (0.41) (0.39) (0.72) (0.0002) (0.0002)

Government expenditure 0.0156 0.0209

(0.0157) (0.0318)

Gov expenditure * oil �0.01 0.00

(0.0151) (0.0427)

Military expenditure per capita 0.00118** 0.00201** 0.0016*** 0.0018***

(0.001) (0.001) (0.000) (0.001)

Military expenditure * oil �0.001* �0.00132* �0.0012** �0.001**

(0.0006) (0.0008) (0.0005) (0.0005)

Welfare expenditure �0.119*** �0.00763

(0.0372) (0.053)

Welfare expenditure * oil 0.0014 �0.0782

(0.0475) (0.117)

ELF 1.609*** 0.951 1.547*** 0.825 1.482*** 0.533 1.727*** 0.169

(0.429) (0.922) (0.465) (0.874) (0.551) (0.895) (0.527) (0.990)

Religious fractionalization (0.704) 1.117 �0.178 0.865 �0.202 0.836 �0.717 �0.121

(0.493) (1.280) (0.529) (1.178) (0.625) (1.233) (0.483) (0.868)

Political instability 0.686*** 0.730** 0.791*** 0.793** 0.862*** 0.715** 0.626*** 0.653**

(0.192) (0.352) (0.189) (0.326) (0.224) (0.349) (0.195) (0.314)

Non contiguity 1.166*** 1.272** 1.179*** 1.310** 1.368*** 2.189*** 1.250*** 1.902**

(0.310) (0.640) (0.327) (0.611) (0.403) (0.694) (0.374) (0.861)

Polity IV 0.0375 �0.112** 0.0292 �0.123*** 0.0614* �0.0923* 0.0216 �0.129**

(0.028) (0.045) (0.026) (0.041) (0.032) (0.049) (0.029) (0.051)

Logged population 0.362*** 0.543*** 0.354*** 0.521*** 0.209** 0.428** 0.346*** 0.412***

(0.070) (0.175) (0.071) (0.163) (0.086) (0.169) (0.061) (0.113)

Logged GDP per capita �0.00887 0.0355 �0.0757 �0.0865 �0.304** �0.477* �0.138 0.0447

(0.096) (0.204) (0.098) (0.196) (0.151) (0.275) (0.109) (0.173)

Constant �12.43*** �17.69*** �12.18*** �16.66*** �6.321*** �12.09*** �11.35*** �15.17***

(1.60) (3.73) (1.64) (3.44) (2.24) (4.01) (1.47) (2.77)

Log pseudolikelihood �611.51 �250.65 �691.5 �284.82 �502.76 �244.41 �550.05 �229.46

Wald Chi2 153.81*** 36.27*** 121.44*** 42.06*** 100.27*** 35.20*** 448.61*** 106.16***

Observations 5,190 5,190 5,618 5,618 4,108 4,108 4,884 4,884

Note: ***p < 0.01, **p < 0.05, *p < 0.1. Models 9–14: Random effect models. Models 11 and 12: Welfare spending is imputed using Taydes and Peksen’s(2012) data. Models 13 and 14: Following Collier and Hoeffler (2004b), military spending per capita is instrumented by neighbors’ military spending, thecold war dummy, current engagement in international war, and past engagement in international war in the period since 1945. The ongoing war variable(only for minor conflict onset), regional dummies, half-decade dummies, peace years, and cubic splines are included.

Predicted probability of conflict onset

Figure 1. The effect of military spending on conflict at different levels of oil–gas value.

Note: Predicted probability of minor conflict onset using Model 3. The vertical lines show the 95% confidence interval around the predicted probabilities of conflict.

8 WORLD DEVELOPMENT

OIL AND CIVIL CONFLICT: CAN PUBLIC SPENDING HAVE A MITIGATION EFFECT? 9

spending per capita scale (from zero to 1,500 dollars per cap-ita), the predicted probability of conflict onset not only returnsto the low level when both oil/gas production and militaryexpenditure are set at zero, but falls below it and movestoward zero. On the other hand, for economies not endowedwith oil or gas, a similar increase in military spending is asso-ciated with continuously higher risks of conflict. In addition,the confidence intervals for the predicted probability of minorconflict do not overlap and the size of military spendingincreases: for military spending greater than about 600 percapita US dollars (about 55% of the observations for oil-richcountries), the confidence intervals do not overlap. In addi-tion, for major conflicts, a pattern similar to Figure 1 emerges(see online Appendix B). In this case, however, the downwardslope for oil and gas rich economies is less pronounced.These non-linearities may explain at least in part the diverg-

ing results observed in the literature. For oil-poor countrieswith limited resources, military spending could be perceivedas crowding out more important spending, fueling citizen grie-vance and possibly leading to higher risk of conflict. As coun-tries become richer in oil and can tap more resources, theymay be less constrained and military spending can take placewithout crowding out other expenses. Furthermore, as thesegovernments grow richer they may represent more attractiveprizes, and would need larger military budgets to fend offunwanted claims on their treasury, either through patronageor military action. In addition, signaling and patronage seemto prevail over any possible loss of efficiency in the militaryapparatus. The results presented here suggest that, in oil andgas rich economies, spending on repression, patronage toregime loyalists, or direct rents to the military to prevent pos-sible coup attempts offsets any undermining in the quality ofthe armed forces. Oil-rich governments appear to have beenable to spend on the military and contain the increased riskof conflict onset related to oil resources, while not becomingmore vulnerable to other threats.Finally, higher welfare spending seems to be associated with

a lower risk of minor conflict, but not of major conflict. Forminor conflicts, the results from Models 5 (Table 2) indicatea negative and statistically significant coefficient for the levelof welfare spending. The coefficient of the interaction termwith the oil–gas value per capita is not statistically significant,however, a Wald test of joint statistical significant rejects thathypothesis that welfare spending, oil–gas per capita and theirinteraction term are jointly statistically insignificant. Theinclusion of random effects does not change these results(Table 3, Model 11). In the online Appendix E we show thepredicted probability of minor conflicts when varying welfarespending for oil poor (oil gas value per capita at zero) and oil-rich countries (oil gas value per capita at the 95th percentile).We find that, regardless of the value of oil and gas production,higher welfare spending reduces the risk of minor conflict.These results suggest that the reduction in minor conflict riskassociated with higher levels of spending on education, health,and social protection is independent from the oil–gas value.For major conflict we cannot find a statistically significanteffect of welfare spending.

(a) Robustness

Our main finding is that spending on the military in oil-richcountries reduces the risk of conflict. To further probe therobustness of this finding, we carry out the following addi-tional empirical tests: (1) other combinations of instrumentalvariables; (2) relevant sample restrictions; (3) additional con-trol variables and alternative model specification; and (4) use

of the logged oil–gas variable based on Ross (2012) modelof oil and conflict.Although our instrumental variables are based on Collier

and Hoeffler (2004a), Collier and Hoeffler (2004b), some ofthe instruments may be affected by the dependent variable.For instance, civil wars in bordering countries may be associ-ated with decisions on the level of military spending (Phillips,in press). If so, the level of military spending observed inneighboring countries may be influenced by the risk of civilconflict onset in the home country. Likewise, an ongoing inter-national war may encourage rebel groups to take up armsbecause an international conflict may weaken the state. Tocheck for this problem, we exclude military spending inneighboring countries as well as current engagement in aninternational war from the list of instrumental variables andre-estimate the IV models. The results do not change for bothminor and major conflicts (online Appendix F).21

We also check whether the interaction effect of militaryspending and oil remains robust across various sample restric-tions. First, we exclude countries that have another ongoingviolent conflict because countries under a civil conflict maybe more likely to face insurgency by other rebel groups. Sec-ond, we exclude democracies and use only observations forautocracies and anocracies because decisions to spend rev-enues from natural resources may be more likely to be gearedtoward public goods in democracies. Third, we include onlyoil-producing countries that produce more than 109 dollarsper capita of oil and gas (the 75th percentile). Since our theo-retical focus is about the spending decisions of oil-producingcountries, limiting our sample to countries that have naturalresources may be more appropriate to test our hypotheses.Fourth, we exclude rich western countries from our samplebecause these countries have rarely experienced violent conflictin the period under study. Fifth, we include only the periodafter 1970 when oil companies started to be nationalized.According to Andersen and Ross (2014), this nationalizationprovided governments with greater and more direct access tooil revenues for distributive purposes. Our results for bothminor and major conflicts are robust across all these samplerestrictions (online Appendix G).Furthermore, we use two additional control variables not

included in our baseline models—ethnic exclusion (Wimmeret al., 2009: percentage of excluded population relative to totalpopulation) and mountainous terrain (Fearon & Laitin, 2003).Only the coefficient of ethnic exclusion in the major conflictmodel is statistically significant, although the two variablesin the other models had expected positive sign, and their inclu-sion does not change the baseline results for both minor andmajor conflict onsets. Spending allocations on both the mili-tary and welfare have also been included in the same modeland our key findings remain unchanged for both minor andmajor conflicts (the online Appendices H and I).

7. CONCLUSION

If natural resources increase the risk of violence in a country,are there ways for the government to change this course ofevents? Previous work on the resource curse suggests, on theone hand, that oil can lead to violent conflict because itincreases the value of the state as a prize or because it undermi-nes the state’s bureaucratic penetration. On the other hand, therentier state literature has long argued that oil might providestates with resources to deliver public and private goods andstabilize political regimes. This paper proposes to reconcilethe tension between these two major strands of the literature.

10 WORLD DEVELOPMENT

Contributing to this ongoing debate in the study of civil war,our paper sheds light on one key aspect of governments’ polit-ical decisions: the allocation of natural resource wealth, in par-ticular oil wealth, for various public spending items. Thepacifying role of public spending in oil-rich countries may bedue to a signaling effect of spending, showing potential rebelsthe size of the coalition they would be facing; a reduction ofgrievance; or a deterrent effect due to a greater security appa-ratus.The statistical analysis presented in this paper confirms that

the association between natural resources and conflict is not afatality. The pattern of public spending could play a role. Themain contribution of this paper is to show that higher levels ofmilitary spending in oil-rich countries are associated withlower risks of both minor and major conflict. This mitigatingeffect is all the more potent when oil revenue grows larger. Asthese resources grow in importance, larger military budgetsmay be called for either for repression, patronage to regimeloyalists, or direct rents to the military to prevent possiblecoup attempts. At low levels of oil revenue, however, theopportunity costs of military expenditure in terms of foregonealternative spending may fuel grievance. Higher levels of mil-itary expenditure are in this case associated with higher risk ofconflict.The results also confirm that higher spending in education,

health, and social protection is associated with a lower risk

of minor conflict. We find, however, that this effect is indepen-dent from the level of oil revenue and could be more effectivethan military spending in reducing conflict risk for countriesnot well-endowed with natural resources. While unable to pre-vent full-scale wars, higher spending on public services forwhich the citizen’s care could be enough to reduce grievance,foster a government’s legitimacy, and reduce the risk ofsmall-scale conflict. Finally, higher levels of general govern-ment spending are not robustly associated with a lower riskof conflict in both oil-rich and oil-poor countries.These results uncover interesting non-linearities in the rela-

tion between conflict, natural resources (oil and gas in thiscase), and public spending that could explain partly the diver-gent results presented in the literature and call for furtherinvestigation. First, while general government spending doesnot seem to have any effect on conflict risk, patronage usuallygoes through construction contracts or civil service employ-ment. Examining the association between higher investmentbudgets or higher wage bills and the risk of conflict may yielddifferent results. Furthermore, citizens may care more aboutactual improvements in public service delivery than higherpublic spending. Signaling without delivering the actual ser-vice may backfire and fuel grievance. Examining the possiblerole of improving education or health outcomes in reducinggrievance and conflict risk could also be a fruitful venue forfuture research.

NOTES

1. For an exhaustive literature review, see Ross (2006a) or Humphreys(2005). Brunnschweiler and Bulte (2009) and Cotet and Tsui (2013) findthat oil dependence and, respectively, oil reserves, have no statisticallysignificant association with the risk of civil conflict.

2. While these views are supported by Andersen and Ross (2014),particularly for years after the 1970s, Haber and Menaldo (2011) contestthem.

3. In contrast, the importance of distributive politics is thoroughlyrecognized in studies of democratization and regime survival (Acemoglu &Robinson, 2006; Bueno de Mesquita et al., 2003; Ross, 2001).

4. Education, however, may not always lead to civil peace. Rapidexpansion of education in developing countries may increase the numberof the high educated to the level where the market cannot absorb them, sothat it fuels violent conflict (Huntington, 1968; Oyefusi, 2010). Lange andDawson (2010) and Lange (2012) also argue that education is more likelyto fuel violent conflict, especially ethnic violence in countries with ethnicdivisions, ineffective political institutions and/or low incomes. Anextensive review is in Ostby and Urdal (2010).

5. Previous studies have mainly focused on the duration of violentconflict. A key argument is that because the strong military can defeatrebel groups more easily, it contributes to shortening duration of conflict(DeRouen & Sobek, 2004; Mason & Fett, 1996; Mason, Weingarten, &Fett, 1999). There is also evidence to the contrary, however(Balch-Lindsay & Enterline, 2000).

6. Such personalist dictatorships are not a rare occurrence, as Gandhiand Przeworski (2007) show: 35% of dictatorships have no political partiessupporting them.

7. In Cameroon, a key response from the Biya administration followingcoup attempts in 1983–84 was populist spending policies on education andthe youth that revolted in Yaounde, as well as on ethnic groups that

supported the regime during the coup attempts. This spending continuedeven after international oil prices dropped (Gauthier & Zeufach, 2011).

8. Oil has been long linked to the provision of patronage (Beblawi &Luciani, 1987; Gelb, 1988).

9. Theoretically, governments can be presumed to want to reduce the riskof civil conflict, which may lead to increases in spending allocations to themilitary in anticipation of violence. Empirically we use an instrumentalvariable strategy to mitigate the risk of endogeneity.

10. In the development literature there is a debate about whether publicspending and its specific allocation helps achieve economic growth(Devarajan, Swaroop, & Zou, 1996; Easterly & Rebelo, 1993).

11. Bahrain, Norway, Brunei, Oman, Qatar, Gabon, Saudi Arabia,Kuwait, UAE, Libya; the exception is Equatorial Guinea.

12. The data are from http://dvn.iq.harvard.edu/dvn/dv/mlross (ac-cessed 03/14/2013).

13. We use both logged and non-logged oil variables in our analyses. Formodels using non-logged oil variable, one may suspect that results aredriven by a handful of outliers. Yet, this is not the case. Excluding outliersthat have more than 10,000 dollars oil–gas value per capita from themodels does not change the main results. In Tables 1 and 2, we report theresults using the non-logged oil variable without excluding outliers. InAppendix C, we show results using the logged oil variable, includingreplications of the results of Ross (2012). Our results are robust to usingthe log of the oil–gas value per capita variable.

14. COW reports total military spending in US dollars without specify-ing the exchange rate, making it problematic to scale these data usingGDP numbers from another source. We thus prefer scaling militaryspending by total population.

OIL AND CIVIL CONFLICT: CAN PUBLIC SPENDING HAVE A MITIGATION EFFECT? 11

15. Appendix D shows a list of countries included in both the imputedand the original data.

16. Following Vreeland (2008), we also recode Polity IV score to avoidpossible endogeneity.

17. Income per capita comes from Penn World Tables and WorldDevelopment Indicators, supplemented with per capita energy con-sumption. Population size is based on World Bank World Develop-ment Indicators. We do not control for recent independence becausefor some of our specifications data are only available post 1960.Democracy is based on Polity IV (�10 to 10). For political instability,we follow Fearon and Laitin (2003) and use a dummy variable forcountry/years that had a three or greater change on the Polity IVregime index in any of the three years prior to the country-year inquestion.

18. We also include neighboring countries’ military spending relative totheir own GDP and our results do not change. We do not use Collier andHoeffler’s (2004b) country level of democracy as a fifth instrument,because this variable is included in most models of civil conflict.

19. Besides the exogenous instruments, the same set of control variablesis included in the second model as featured in the first model. To avoid theWooldridge (2002) forbidden regression, the predicted interaction betweenmilitary spending and oil wealth comes from a similar model that alsoincludes the interaction of predicted military spending and oil wealth.

20. The distribution of the oil–gas variable is highly skewed toward zero(more than 50% of the observations in the sample have zero or negligibleoil and gas production) so we show the probability of conflict for countrieswith no oil and countries rich in oil, i.e., for values of the oil–gas value percapita variable at the 95th percentile. These are plausible values. Aroundthe 95 percentile for the oil–gas value per capita are most countries that weusually consider as petro states: Trinidad, Venezuela, Russia, Azerbaijan,Norway, Equatorial Guinea, Gabon, Angola, Algeria, Libya, Iran, Iraq,Saudi Arabia, Kuwait, Bahrain, Qatar, UAE, Oman, Turkmenistan,Kazakhstan, and Brunei.

21. Specifically, we use three alternative combinations of instrumentalvariables: (1) the three instruments excluding the level of military spendingin neighboring countries, (2) the three instruments excluding the currentengagement in an international war, and (3) only two instrumentsexcluding both.

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APPENDIX A. SUPPLEMENTARY DATA

Supplementary data associated with this article can befound, in the online version, at http://dx.doi.org/10.1016/j.worlddev.2015.09.004.

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