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Why Do Some Oil Exporters Experience Civil War But Others Do Not?
A Qualitative Comparative Analysis of Net Oil-Exporting Countries
Paper prepared for presentation at the SGIR 7th Pan-European Conference on IR, Stockholm,
9-11 September 2010
Matthias Basedau & Thomas Richter1
German Institute of Global and Area Studies (GIGA)
According to quantitative studies, oil seems to be the only resource that is robustly linked to
civil war onset. However, recent debates on the nexus of oil and civil war have neglected two
major considerations: there are a number of historically peaceful oil-rentier states, and there
have been few efforts to explain why some oil-exporting countries have experienced civil war
and others have not. Methodologically, the debate has been dominated by research using
either quantitative methods or case studies, with little genuine medium-N comparison. This
paper aims to fill this gap by studying the conditions of civil war onset among net oil
exporters using (crisp-set) Qualitative Comparative Analysis (csQCA), a technique best used
to study samples between 10 and 50 cases. QCA is also more suited to identifying necessary
and sufficient conditions. At the same time, this technique looks at country-specific
configurations but outperforms case studies in yielding generalizable results. Considering a
sample of 44 net oil exporters between 1970 and 2008, we test pertinent factors such as the
abundance (per capita) and dependence of oil, settlements of excluded ethnic groups in oil
reserve areas and outside protection. The results point to a combination of necessary and
sufficient conditions that has been largely ignored until now: although low rents per capita
and a lack of outside protection are necessary conditions for civil war onset among oilexporting countries, a combination of high dependence and low abundance sufficiently
explains the onset of civil war.
1
German Institute of Global and Area Studies, Neuer Jungfernstieg 21, 20354 Hamburg, Germany; Matthias
Basedau is at the Institute of African Affairs, [email protected]; Thomas Richter is at the Institute of
Middle East Studies, [email protected].
1
1.
Introduction2
According to a large body of quantitative literature, oil seems to be robustly linked to the
onset of civil war3 (Ross 2004a; Hegre und Sambanis 2006; Dixon 2009). However, recent
debates on the nexus of oil and civil war have neglected two major considerations: there are a
number of historically peaceful oil-rentier states, and there have been few efforts to explain
why some oil-exporting countries have experienced civil war and others have not.
Methodologically, the debate has been dominated by research using either quantitative
methods or case studies, with little genuine medium-N comparison.
This paper aims to fill this gap, researching why some oil-exporting countries experience civil
war while others do not using a relatively new methodological approach: (crisp-set)
Qualitative Comparative Analysis (csQCA), a technique best used to study samples between
10 and 50 cases. QCA is also more suited to identifying necessary and sufficient conditions
than most existing quantitative techniques. At the same time, this technique looks at countryspecific configurations but outperforms case studies in yielding generalizable results.
The paper proceeds as follows. We first review the literature on the resource-conflict link,
pointing to specific deficiencies. We then outline our general empirical strategy, starting with
a short introduction to csQCA. Subsequently, we present our dependent variable (civil war)
and our independent variables (oil abundance, oil dependence, overlap of ethnic exclusion and
oil reserves, and outside protection), which are then tested using a sample of 44 net oil
exporters between 1970 and 2008. After outlining our empirical strategy, we perform the
analysis and discuss the results. Finally, we draw conclusions and highlight opportunities for
future research.
2.
2.1
Literature Review
Theoretical Approaches
Collier and Hoeffler’s (2004; initially 1998) influential work on ‘greed and grievance’ has
inspired many studies on the link between resources and conflict. Collier and Hoeffler (2004)
argue that an abundance of primary commodities increases the likelihood of civil war onset by
2
We are grateful to Georg Strüver for excellent research assistance.
If not indicated otherwise, civil war denotes an armed conflict (UCDP/PRIO-definition) that has produced at
least 1,000 battle-related deaths in a given year (see Gleditsch, Wallensteen, und Eriksson 2002).
3
2
providing the opportunity for armed rebel activity and the related motive of ‘greed’ rather
than by spurring conflict-promoting grievances, such as the political and economic
deprivation experienced by, for instance, ethnic or religious groups. These ideas have been
further developed, extended and modified in the literature. Generally, natural resources can
promote violence through three major causal mechanisms (Humphreys 2005; Ross 2004b; see
also Le Billon 2008).
1) Motivation to take up arms may result from resource-related grievances, such as ecological
damage or the withholding of resource revenues; costs and benefits relating to resources are
the driving forces of conflict.
2) Resources also provide the opportunity for conflict by making rebellion or warfare in
general financially (or militarily) feasible, particularly through the “lootability” of resources.
3) Resources may make indirect mechanisms work, directly providing neither motive or
opportunity but exerting a detrimental influence on other areas such as state institutions (the
‘weak state’) and socio-economic development (‘Dutch disease’), which in turn makes civil
war more likely.
All of these mechanisms involve numerous contextual conditions, particularly resourcespecific conditions (Ross 2008; Basedau 2005). In fact, ‘resources’ are a fairly imprecise
concept. They have several characteristics that may influence their impact on peace and war.
Among these characteristics are the resource type (oil, diamonds or other) and the mode of
extraction, which affects the feasibility of rebellion. As Le Billon (2001; see also Auty 2001)
notes, the exploitation of so-called ‘distant’ and ‘diffuse’ resources such as alluvial diamonds,
timber or drugs can hardly be controlled by the central government. Hence, rebels can ‘loot’
them more easily than deep-shaft gems or off-shore oil, which would require sophisticated
technical know-how.4
Moreover, a country’s resource dependence and abundance are not identical (Ross 2006, 266;
De Soysa 2002, 8-9). Dependence means that rents from resources are the most important
source of income relative to other value-adding activities, whereas abundance or wealth refers
4
Such ‘point’ resources are more likely to trigger power struggles over the control of the central state or, if
concentrated in certain, presumably peripheral regions (referred to as ‘point’ and ‘distant’ regions), secessionist
uprisings (Le Billon 2001, 31).
3
to the absolute resource rents available in per capita terms (or relative to global reserves or
production). It can be easily illustrated that the values of these two variables may differ
substantially.5
Dependence and abundance have different implications for the likelihood of civil war.
Resource dependence may be especially violence-enhancing at higher levels. Countries are
vulnerable to price shocks, which in turn create economic crisis and (thus) make conflict more
likely (Basedau und Lay 2009). Moreover, resources may foster the onset of internal conflict
only in economies with a monolithic structure that offers limited alternative income sources.
In contrast, higher resource abundance per capita will probably foster peace when
governments employ particular distributive policies.
According to rentier state theory (Mahdavy 1970; Luciani 1987; Smith 2004; Snyder und
Bhavnani 2005), which has been largely disregarded in the debate over the resource-conflictlink, governments can use resource revenues for costly policies such as large-scale redistributional schemes and security apparatuses, buying off potential dissidents or effectively
suppressing rebellion. In contrast, in motivating mechanisms of grievance, as mentioned
above, material distribution and repression work in the opposite direction, creating a profound
challenge to the resource-conflict link suggested by the conventional wisdom of the existing
literature.
Whether or not high rents will be available depends not only on output but also on input as
part of resource governance. Careful management of the resource sector may include effective
taxation structures (Snyder und Bhavnani 2005) and private rather than state ownership
(Luong und Weinthal 2006). Moreover, rent income often disappears into the pockets of the
elite or multinational companies. Important resource-specific conditions also include the
external structure of demand. Powerful importing countries may be ready to intervene
militarily, either directly or by supporting warring factions. All of these conditions have been
declared to constitute a ‘key research agenda’ (Collier und Hoeffler 2005, 627).
5
Nigeria and Saudi Arabia, for instance, were almost equally dependent on oil exports in 2002; these exports
accounted for 38.9% and 38.5% of their GDPs, respectively. However, had governments decided to pay out the
proceeds from oil exports to their citizens, Nigerians would have been given a mere US$ 140, whereas Saudi
Arabian citizens would have earned US$ 2.715.
4
The likelihood of conflict may also depend on non-resource-specific characteristics such as
the general level of development, relations between identity groups, geographical and
demographical factors and the general quality of state institutions as well as elite behavior. All
of these conditions may affect the likelihood of violence independent of resources. Hegre and
Sambanis (2006) have empirically identified non-resource-related conditions such as
population size, income level and growth and rough terrain as robust correlates of major civil
war. However, more importantly, resource- and non-resource specific conditions are likely to
interact (Ross 2008; Basedau 2005). In a resource-dependent economy, wealth is mainly
derived from resource income. The relationships between identity groups will be affected
when resources are discovered in a region that differs from the rest of the country or when the
region in question does not get a fair share of the revenues but instead has to suffer from
ecological or socio-economic stress connected to resource production.
2.2
Results from Quantitative Studies
A multitude of quantitative studies has tried to demonstrate that natural resources increase the
risk of civil war onset. The results vary. Ross (Ross 2004a) has analyzed 14 quantitative
studies of the resource-conflict link and finds that primary commodities as a whole cannot be
robustly linked to civil war onset or duration. According to his conclusions, the type of
resource definitely matters. Whereas no study under review by Ross can establish a
relationship between agricultural commodities and violence, ‘lootable’ resources such as
narcotics, timber and (alluvial) diamonds seem to influence the duration of a conflict,
although they do not make the onset of civil war more likely (Lujala, Gleditsch, und Gilmore
2005).6 Studies differ in their conclusions regarding whether diamonds cause or sustain civil
war (Le Billon 2008, 352). Only oil-exporting countries seem to be particularly prone to civil
war onset (Ross 2006). Further studies question the notoriety of oil in this respect: Smith
(2004) finds a positive effect of oil dependence on regime stability and peace in developing
countries. According to Hegre and Sambanis (2006, 531), only oil exports (and not production
or other resources) are marginally robustly linked to minor armed conflict. Others (Fearon
und Laitin 2003; Fearon 2005) have concentrated their criticism on the opportunity or
feasibility mechanism and propose that the oil-violence nexus works through a weak state
mechanism (see Ross 2006, 290-291) or can be attributed to the effects of a ‘sparse networks’
mechanism (Humphreys 2005).
6
They find that secondary diamonds are positively linked to the onset of ethnic civil wars only, whereas primary
diamonds lower the risk of civil war onset and duration.
5
Recent studies have found evidence that some of the rentier mechanisms are present within oil
states in particular. Fjelde (2009) finds that the interaction of high levels of corruption and
appropriable resources (oil wealth) reduces the conflict proneness of a country by offsetting
the destabilizing effect of resource abundance. According to Basedau and Lay (2009), oil
dependence increases the risk of civil war onset, creating a U-shaped relationship, whereas
high levels of abundance (as indicated by an inverted U-shape relationship) are apparently
used to engage in large-scale distribution and the establishment of a huge and effective
security apparatus.7 Brunnschweiler and Bulte (2009) have also tested both resource
dependence and abundance and find that resource abundance reduces the likelihood of civil
war onset, whereas dependence seems to be a result rather than a cause of civil war.
2.3
Results from Comparative Studies (Small & Medium N)
Methodologically, research on the onset of civil war is dominated by quantitative studies
employing mostly logistic regressions. Although there are numerous case studies that provide
country-specific evidence on the resource-conflict link, genuinely comparative perspectives
are rare. In particular, medium-N studies are very much missing from this field. There are
some edited volumes and monographs that compare several pertinent cases (Basedau und
Mehler 2005; Collier und Sambanis 2005; Oliveira 2007). A comparison of three diamond
producers (Sierra Leone, Ghana and Guinea) by Snyder and Bhavnani (2005) shows that
modes of extraction, the tax base from resource production and spending patterns – as already
suggested in the theoretical section above – help to influence the complex relationship
between natural resources and civil war.
One of the few systematic small-to-medium-N studies in this debate is Ross (2004b). Ross
explicitly and exclusively tests a number of causal mechanisms potentially leading to civil
war onset using 13 cases in which resources and conflict are “most likely” interrelated. He
finds evidence of neither the opportunity (‘looting’) nor motive (‘grievances’) mechanisms for
creating conflict, but he does find evidence of separatism in two cases (Sudan, Indonesia) and
of two other mechanisms in three cases (Congo Republic: “future booty”; DRC: foreign
7
The U-shaped relationship suggests that very low and very high levels of dependence are linked to a greater
likelihood of civil war, whereas medium levels of dependence make civil war onset less likely. They find an
inverse U-shaped relationship between abundance and the likelihood of civil war: states with medium levels of
abundance are the most war-prone, whereas very low and high levels of abundance are related to a lesser
likelihood of civil war onset.
6
intervention; Sierra Leone: foreign intervention and future booty). Empirical support for the
mechanisms at work increases with conflict duration, particularly for “looting” (in all but two
cases), although some of the mechanisms have shortened the wars. However, the sample
cannot explain differences in violence given the rather constant dependent variable, as frankly
admitted by the author himself (Ross 2004b, 49).
A study by Basedau and Lay (2009) uses both logistic regression and a medium-N analysis
that concentrates on 27 highly dependent net oil exporters to isolate the possible effects of
abundance and material rewards that may explain the absence or presence of civil war onset.
According to this analysis, abundant income from resources is apparently used to engage in
large-scale distribution and the establishment of a huge and effective security apparatus. In
addition, oil-abundant states often enjoy protection from abroad, suggesting that international
influence may not only spur conflict but also contribute to internal peace.
A paper by Wegenast and Basedau (2009) tests a medium-N sample of 17 highly ethnically
fragmented, low-income, and resource-rich countries (a strategy used to keep important
contextual conditions constant) and attempts to look more closely at individual cases. The
findings lend support to the assumption that the combination of ethnic exclusion and resource
availability (here, oil and diamonds) renders civil war onset very likely. Basedau and
Wegenast’s (2009) medium-N study of Africa’s 15 main oil and diamond producers confirms
these results. According to these findings, the existence of high dependence and minorities at
risk in producing regions strongly increase the likelihood of civil war. Lower income from
resources per capita and substantial production of lootable resources in peripheral regions are
apparently necessary conditions for civil war.
2.4
Preliminary Conclusion
Three observations from previous research on the nexus of material resources and civil war
onset seem important for our paper: First, oil (and oil exports) is the only resource that is
more or less robustly connected to civil war. Secondly, relatively little effort has been
invested in explaining the variation within the group of oil-exporting countries. The relatively
few studies on this subject that exist suggest that certain resource-specific characteristics (e.g.,
abundance and dependence) and the relation of resources to the ethnic diversity of a country,
for instance, might be potential factors. Finally, research strategies other than quantitative
approaches or single case studies are extremely rare. In particular, medium-N analyses are,
7
with a few exceptions, virtually absent from the field of conflict studies. To the best of our
knowledge, no study has ever tried to investigate the oil-conflict link via formal
configurational methods such as csQCA using a medium-N sample.
3.
A Short Introduction to Crisp Set QCA (csQCA)
Qualitative Comparative Analysis (QCA) or Configurational Comparative Analysis, as it has
recently been (re)named (Rihoux und Ragin 2009, bd. 51), is a relatively new formal data
analysis technique that is “… concerned with the systematic matching and contrasting of
cases to establish common causal relationships by eliminating all other possibilities” (BergSchlosser u. a. 2009, 2). Introduced by the sociologist Charles Ragin (Ragin 1987) during the
late 1980s and developed further during the last two decades (Ragin 1994; Ragin 2000), QCA
has become an interesting complement to prevailing statistical approaches within macrocomparative research (Grofman und Schneider 2009). However, as already mentioned, to the
best of our knowledge, QCA has rarely been used as a data analysis technique within the field
of peace and conflict studies.8
Although it can be argued that QCA attempts to combine the advantages of qualitative (caseoriented) and quantitative (variable-oriented) techniques, it is better suited to comparing an
intermediate number of cases (medium-N) than are most quantitative, statistically oriented
methods. From a qualitative perspective, QCA is useful because it still allows a closer look a
different kinds of cases; it does not level down case characteristics to an average degree
within a given sample as statistical techniques usually do. From a quantitative perspective,
QCA permits to analyze the influence of more than one or two variables on a single outcome
or event, without getting lost into case specifics.
As a data analysis technique, QCA systematically combines the method of agreement and the
method of difference9 – the two famous principles of J.S. Mill’s logic of comparison – in
order to identify necessary10 and sufficient11 conditions (independent variables) or
8
The only application we know of is (Clément 2004), and she deals more with state failure than with civil war.
The method of agreement eliminates all similarities but one. The method of difference establishes the absence
of a common cause if all other circumstances are identical (Berg-Schlosser u. a. 2009).
10
A condition is defined as necessary if it must be present for a certain outcome to occur (Ragin 1987, 99).
However, necessary conditions might be present even the outcome does not occur.
11
A condition is defined as sufficient if by itself it can produce a certain outcome (Ragin 1987, 99). Sufficient
conditions are not present if the outcome does not occur.
9
8
combinations of conditions in relation to a certain outcome (the dependent variable).12 QCA’s
two basic questions are therefore as follows: which conditions (or which combination of
conditions) are necessary for a certain outcome to occur, and which conditions (or which
combination of conditions) are sufficient for a certain outcome to occur? As a result, QCA has
the ability to unravel causally complex structures like equifinality, multifinality, and
asymmetric causality (Grofman und Schneider 2009, 662). Whereas standard statistical
techniques give prominence to the net effect of single variables, QCA is used to detect
different and sometimes overlapping conjunctions of configurations or conditions that may all
led to the same outcome (Ragin 2008, 176-189).
Boolean algebra13 is used to analyze truth tables in which cases are pictured according to the
binary values of their conditions and respective outcomes.14 An uppercase letter represents the
“1” value for a given binary condition or an outcome, whereas the lowercase letter represents
the “0” value for that binary condition or outcome. A hyphen “-“ represents the “don’t care”
value for a given binary condition or outcome, meaning that it can be either present or
absent.15 In crisp set QCA, there are two main Boolean operators used. The logical “AND” is
symbolized by the “*” multiplication sign and the logical OR is represented by the “+”
addition symbol. To establish a connection between the conditions and the outcome, arrows
are used. An arrow to the right “” signifies a sufficient relationship between conditions and
outcome, whereas an arrow to the left “” symbolizes a necessary relationship.
Moreover (and this is really the heart of the matter of using QCA as a data analysis
technique), Boolean minimization is used to reduce empirical complexity. In the words of
Charles Ragin, “If two Boolean expressions differ in only on causal condition yet produce the
same outcome, then the causal condition that distinguishes the two expressions can be
considered irrelevant and can be removed to create a simpler, combined expression” (Ragin
1987, 93).
12
Please note that QCA applicants usually refer to independent variables as conditions and to dependent
variables as outcomes. We will exclusively use this terminology from now on.
13
Boolean algebra was developed in the mid-nineteenth century by the mathematician and logician George
Boole and is based on logical rather than numeric characters. For a detailed introduction to this technique as used
in QCA, see Ragin 1987, 85-102; Rihoux und De Meure 2009.
14
Because we use only crisp set QCA (csQCA) in this paper, other versions (like, for instance, multi-value QCA
(mvQCA) and fuzzy-set QCA (fsQCA)) are not be examined here. For mvQCA, see Cronqvist 2005; Cronqvist
und Berg-Schlosser 2009 and for fsQCA, see especially Ragin 2000.
15
It is important to note that the hyphen is not an intermediate value between 1 and 0.
9
Consider the example of two states that have high degrees of primary commodities per GDP
(sxp) and experienced negative growth during a given time period (gy1) but significantly
differ in their population size (pop) – one with more than 20 million inhabitants and one with
just only 1 million. Also assume that in both countries, a civil war started to take place
(onset). Table 1 shows the corresponding truth table.
Table 1: A simple binominal Truth Table used for csQCA
Country
Sxp
Gy1
Pop
Onset
A
1
0
1
1
B
1
0
0
1
Expressed in Boolean language, this truth table can be written as:
SXP*gy1*POP + SXP*gy1*pop ONSET16
Following the rule described above, Boolean minimization allows the replacement of these
two terms with a single, simpler expression because the population size turns out to be
irrelevant to the onset of civil war.
SXP*gy1 ONSET
As a result of Boolean minimization, more parsimonious expressions are created that show
combinations or configurations of conditions that together form a sufficient condition for the
occurrence of a certain outcome (Rihoux und De Meure 2009, 34-39). As part of these
configurations, the initial single condition operates as a so-called INUS factor (an insufficient
but necessary part of a condition that is itself unnecessary but sufficient for the outcome)
(George und Bennett 2005; Mahoney 2008). These are causally relevant factors that are
almost always overlooked when standard statistical techniques are applied (Grofman und
Schneider 2009, fn. 4).
16
Read this expression as indicating that the presence of many primary commodity exports relative to GDP,
combined with negative GDP growth and a large population, OR the presence of many primary commodity
exports relative to GDP, combined with negative GDP growth and a small population, are sufficient for civil war
onset.
10
There exists a shared consensus among experts on csQCA that a good configurational analysis
will present at least three technical components (Wagemann und Schneider 2007; Grofman
und Schneider 2009): the truth table, the solution formulas and measures of fit like coverage
and consistency. The truth table presents the data to be analyzed, showing the conditions (the
independent variables) as columns, the cases as rows and the value of the outcome (the
dependent variable). However, the cases are not always confined to a single row but are rather
grouped together if they are associated with a single combination of conditions with the same
outcome. Using Boolean language, the solution formula shows the causally relevant
conditions linked to the outcome, as already explained above.
Coverage and consistency are basic measures of fit (Ragin 2006). The consistency of a
sufficient condition measures the proportion of instances of this condition – coded as either 1
or 0 in csQCA – that overlap with the given value of the outcome – also coded as either 1 or 0
– in relation to the total number of cases with the same value for this condition. The higher the
consistency level of a condition, the closer it is to being a consistently sufficient condition of
the outcome. Furthermore, coverage will exist only when conditions are sufficiently
consistent to be regarded as sufficiently explaining the outcome (Grofman und Schneider
2009, 665).17 The coverage of a sufficient condition indicates the proportion of the outcomes
that are explained by this condition. It is then the number of cases in which Y is present
simultaneous to X (as the consistently sufficient condition or configuration of conditions)
relative to all cases with Y.
4.
Empirical Analysis
4.1
Sample Selection
Because we are mainly interested in explaining civil war onset and peace among petroleumproducing countries, our base sample consists of all countries that were net oil exporters for at
least one year between 1970 and 2008, the period for which reliable data is available (the base
sample).18 To exclude pure oil traders like Singapore, for instance, we also excluded all those
17
Please note that in csQCA, as we have introduced it in this paper, the level of consistency of a single condition
or a configuration of conditions must always be 1.000000 or 100 per cent.
18
The data are taken from UN comtrade (SITC Rev. 1,33) online: http://comtrade.un.org/db/default.aspx, (access
2010-06-29).
11
countries with no proven reserves of mineral fuels using the PRIO Petrodata (subsample1).19
Following Ross (2006), we further reduced our sample size, only keeping those countries with
non-trivial amounts of oil production: that is, countries with more than $100 per capita in
rents per year from exporting oil and gas in at least one year between 1970 and 2008.20 This
two-step sample selection procedure leaves us with 44 petroleum-producing countries
(subsample2).21
4.2
Outcome (Dependent Variable): Civil War
The dependent variable or the outcome is the onset of civil war, which is operationalized
using UCDP/PRIO definitions and data (Gleditsch, Wallensteen, und Eriksson 2002).
According to the definition by UCDP/PRIO, an armed conflict is 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 at least 25 battle-related deaths.”
We define a civil war as any armed conflict that has caused at least 1,000 battle-related deaths
in a given year. We positively coded “civil war onset” for a country when at least one such
conflict began or if an ongoing conflict or a new episode of a conflict caused at least 1,000
battle-related deaths during at least one year. All other constellations, including those
featuring armed conflicts with fewer than 1,000 victims, were coded as not experiencing civil
war onset (cf. Appendix 2 - Codebook at the end of this paper for more details). On this basis,
there are 30 cases in the sample that have not experienced civil war onset and 14 cases in
which at least one civil war has broken out between 1970 and 2008.
4.3
Conditions (Independent Variables)
Because we aim to provide the most parsimonious explanations possible, we restrict our
independent variables to four pertinent conditions22, two of which are novel in civil war
research. (see for more coding details and data sources, Appendix 2 at the end of this paper).
19
Data are from PRIO/CSCW: Petroleum Dataset v. 1.2, online:
http://www.prio.no/CSCW/Datasets/Geographical-and-Resource/Petroleum-Dataset/, (access 2010-04-20).
20
Data are from the World Bank Adjusted Net Saving Data Center: Oil and Gas Rents, online:
http://siteresources.worldbank.org/INTEEI/1105643-1115814965717/21683431/oil_and_gas_rents.xls, (access
2008-11-05).
21
A list of all three samples can be found in Appendix 1 at the end of this paper.
22
Limiting our analysis to four conditions inevitably raises the question of why we use these and not others. As
already mentioned, QCA is best used with limited number of factors explaining a certain outcome. Having
selected these four conditions does not mean that we are completely ruling out others that might be important. In
particular, non-resource-specific conditions such as state strength might be included in future research. However,
some potentially influential conditions were excluded based on theoretical considerations. For instance, because
12
Dependence: As discussed in section 2.1, greater dependence on oil might make civil war
more likely. High levels of dependence indicate that oil is the main source of wealth in a
country, which may have a number of harmful consequences that may indirectly increase the
risk of civil war or, using the classification of section 2.1, may serve as a proxy for the
indirect mechanism(s): such dependence makes countries vulnerable to price shocks in the
world oil market. Dependence on an export commodity such as oil fosters a rent-seeking
mentality and, resultantly, weaker institutions and governance. Finally, in an economy
dependent on oil, it is also more likely that economic conflict will centre on this very
commodity. Dependence on oil is certainly the most conventional measure of resources in the
resource-conflict literature and has been employed in many, if not most, quantitative studies
(cf. for an overview Ross 2004a). We measure dependence on oil (dependence5) using the
ratio of available fuel exports to GDP. To minimize endogeneity problems, we use the mean
between 1970 and the year before the possible civil war onset according to the above
definition. If no civil war begins, the mean for the whole period of investigation is calculated.
Because csQCA requires binary-coded conditions, we had to select a cut-off point. Looking at
the actual distribution of the values in the sample, we see that 0.15 (indicating that 15% of the
GDP consists of fuel exports) emerges as a sort of ‘natural’ threshold range because no
country shows this or similar values (for the distribution of dependence5, see Appendix 3 at
the end of this paper). We used this value to create a new binary variable dependence5_015.
All values below this point have been coded as 0 and all values equal to and above as 1.
Abundance: As also previously discussed, dependence and abundance must not be confused
(see section 2.1). According to our understanding, oil abundance indicates what oil rents are
available per capita. The per capita measure is particularly useful because it allows us to
proxy the capacity of governments to employ peace-buying rentier mechanisms, thus testing
possible motivation mechanisms and providing a proxy for state capacity. Large-scale
distributional policies and an effective security apparatus are extremely expensive, and
income must be considered in relation to population size. We measure abundance in oil and
gas (rentpc3) as the average of oil and gas rents per capita between 1970 and a possible civil
war onset (or, if no war occurs, until 2008). Data on estimated income from these rents come
oil is a less lootable resource than diamonds, we do not include an indicator of lootability or any proxy for the
opportunity mechanism in a narrow sense.
13
from the World Bank Data on adjusted net savings.23 For abundance, we were able to identify
a pertinent threshold. Variable pre-testing identified a cut-off-point of $440 per capita from
rents above which no civil war began (see the Appendix 4 at the end of this paper for the
distribution of rentpc3 in relation to ucdpintens3). Similar as with dependence, we used this
value to create a new binary variable rentpc3_440. All values below this point have been
coded as 0 and all values equal to and above as 1.
Overlap: Conflicts like those in Nigeria (Biafra, Niger Delta), Indonesia (Aceh) or (southern)
Sudan illustrate that the interaction of ethnic and/or regional heterogeneity and oil reserves
might be a particularly dangerous combination, though this condition has rarely been tested.
The combination of resources and a shared group identity facilitates mobilization and
provides a significant motive for uprising (motive mechanisms). This risk might increase if
groups are already politically or otherwise aggrieved. Furthermore, resources may contribute
to ethnic insurgency by supplying the necessary financial means for armed rebellions
(opportunity mechanism). We therefore created a third variable that captures whether oil
reserves are located in areas where ethnic groups settle that are excluded from the central
political framework in a given country. To measure this overlap, we used PRIO data on the
location of oil reserves (Lujala, Gleditsch, und Gilmore 2005) and matched them to georeferenced data from the Ethnic Power Relations Data (see Wucherpfennig u. a. 2010). We
positively coded for overlap of ethnic exclusion and resource endowment (overlap2) when
overlap between the settlement of an excluded group and oil location could be identified
within the period of investigation or, in the case of civil war onset, before the outbreak of civil
war. If the area in which the excluded group was settled covered the entire state territory, we
did not code this as an overlap. All other constellations were also rated as 0. Because this
procedure required subjective visual assessment, we performed inter-subjective coding via a
group of three different independently functioning coders.
Outside protection: External variables have been rarely used in studies of the resourceconflict link. Because oil is probably the most strategic resource in the world today, it attracts
interest that may also include a military dimension. External powers may be ready to
intervene militarily or to support warring factions within a given ‘oil country’ to secure a
23
Data can be found at http://go.worldbank.org/3AWKN2ZOY0 (access, 2008-11-05). Please note that rents
(rents3) include both oil and gas rents, not just oil.
14
supply of ‘black gold’. However, this is not to say that oil-exporting countries only face
threats from abroad. On the contrary, many oil-producing countries have established close
relations with internationally powerful countries, which are most often also large oil
importers. The most well known example is certainly the ‘special relationship’ between the
US and Saudi Arabia, in which the latter provides oil to the former and receives a security
guarantee in return. We thus created a fourth variable to measure outside protection
(outsideprotection). We consider substantial outside protection to exist if the net oil exporter
in question hosts a permanent military base of a permanent UNSC member country (US,
British, Chinese, French, or Russian military bases) which we coded as 1.24 We defined a
military base as a (relatively permanent) facility with regular combat forces (not just an
airfield or depots). Military bases were only counted as outsideprotection when there was a
military presence before the onset of civil war and not – as in Afghanistan or Iraq – as a result
of an external military invasion.
4.4
Model and Expectations
We use the following model (1) to test for the necessary and sufficient conditions of civil war
onset and peace using crisp set QCA.
(1)
ucdpintens3 = f (rentpc3_440, dependence5_015, overlap2, outsideprotection)
The four variables “dependence”, “abundance”, “overlap” and “outside protection” form a
specific risk profile. According to our theoretical assumptions, the greatest risk of civil war
should be found in countries that are A) highly dependent on oil, B) experience low oil
abundance, C) feature a geographical overlap between oil reserves and excluded ethnic groups
and D) do not enjoy outside protection. In contrast, we should expect that countries that are a)
not dependent on oil, b) enjoy a great abundance of rents, c) do not have a geographical
overlap between excluded ethnic groups and oil reserves and d) possess the protection by a
powerful outsider will not experience civil war.
24
In the case of the UNSC members themselves, outside protection was only positively coded when there were
military bases from other UNSC members. For instance, China and Russia, both without any foreign military
bases do not have outside protection according to our understanding.
15
5.
5.1
Empirical Analysis Using Crisp Set Qualitative Comparative Analysis (csQCA)
The Truth Table
Table 2 below shows the truth table based on model (1) for a dataset of 44 net oil-exporting
countries with at least $100 per capita rent during at least one year between 1970 and 2008
(subsample2). There are 16 possible configurations combining four binominal conditions (24
= 16). Strictly speaking, only 4 of these do not represent cases from our dataset. In other
words, there are 4 different theoretically possible configurations that are not represented
among net oil exporters.
Two of the 16 possible configurations – which together represent 8 cases – have led to civil
war onset. As row number 1 shows, Algeria, Angola, Azerbaijan, Congo, Iran, Nigeria and
Russia are part of the same configuration: they experienced the onset of at least one civil war
between 1970 and 2008. Additionally, Yemen also underwent a civil war but is part of
another configuration (row number 3). As highlighted in Table 2, both configurations
represent high-risk profiles as previously expected in section 4.4. Furthermore, there are 9
different configurations including 26 cases in which no civil war has broken out.
Additionally, there is one configuration (row number 2) that includes 10 contradictory cases
(C).25 This configuration includes those net oil exporters with low abundance (per capita rents
below US$440), a low degree of dependence (below 0.15), no outside protection, and overlap
in terms of the location of oil reserves and a settlement populated by an excluded political
group. Whereas in Colombia, Indonesia, Iraq, Peru, Sudan, and Syria, a civil war broke out
between 1970 and 2008, there was no civil war in Argentina, Bolivia, Malaysia, or Mexico
during that time. Because of its contradicting outcomes, this configuration had to be excluded
from the csQCA analysis. We will eventually discuss the importance and relevance of this
configuration in the concluding section of this paper.
25
Please note that this configuration represents less than 25% of cases. In turn, this means that our model
explains more than 75% of the cases in the sample. This rate is far above the degree of variance that is usually
explained via common quantitative regressions.
16
Table 2 – Truth Table: ucdpintens3 = f (rentpc2_440, dependence5_015, overlap2, outsideprotection)
Row
Cases
No of
cases
rentpc2_440
dependence5_015
overlap2
outsideprotection
ucdpintens3
consistency of
ucdpintens3=1
1
Algeria, Angola, Azerbaijan, Congo, Iran, Nigeria, Russia
7
0
1
1
0
1
1.00
2
Argentina (0), Bolivia (0), Colombia (1), Indonesia (1), Iraq (1),
Malaysia (0), Mexico (0), Peru (1), Sudan (1), Syria (1)
10
0
0
1
0
C
0.60
3
Yemen
1
0
1
0
0
1
1.00
4
Kazakhstan
1
1
1
1
0
0
0.00
5
Oman, Libya, Trinidad & Tobago, Turkmenistan, Venezuela
5
1
1
0
0
0
0.00
6
Cameroon, Egypt, Papua New Guinea, Tunisia
4
0
0
0
0
0
0.00
7
Gabon, Kuwait, Saudi Arabia
3
1
1
1
1
0
0.00
8
Ecuador
1
0
0
1
1
0
0.00
9
Australia, Côte d'Ivoire, Denmark, Netherlands, UK, Vietnam
6
0
0
0
1
0
0.00
10
Bahrain, Brunei, Qatar, United Arab Emirates
4
1
1
0
1
0
0.00
11
Canada
1
1
0
1
1
0
0.00
12
Norway
1
1
0
0
1
0
0.00
13
-
0
0
1
1
1
-
0.00
14
-
0
0
1
0
1
-
-
15
-
0
1
0
0
0
-
-
16
-
0
1
0
1
0
-
-
Please note: We have highlighted high risk conditions in this table. For instance row no.1 has 4 highlighted cells – this is a configuration with the highest risk of civil war onset. In
contrast to that in row no.12 none of the cells is highlighted – this is a configuration with the lowest risk of civil war onset.
C indicates that a contradictory outcome exists for this configuration. The numbers in brackets after the countries in this row indicate the corresponding outcome.
17
5.2
Identifying Necessary Conditions of Civil War Onset and Peace26
A condition is defined as necessary if it must be present for a certain outcome to occur (Ragin
1987, 99). Thus, tests for necessity attempt to verify whether a condition is always present if a
certain outcome occurs. However, necessary conditions might also be present if the outcome
does not occur.27
Table 3 – Test results for necessary conditions for UCDPINTENS3 (civil war onset) 28
Conditions tested:
Consistency29
Coverage30
RENTPC3_440
0.000000
0.000000
rentpc3_440
1.000000
0.482759
DEPENDENCE5_015
0.571429
0.380952
dependence5_015
0.428571
0.260870
OVERLAP2
0.928571
0.565217
overlap2
0.071429
0.047619
OUTSIDEPROTECTION
0.000000
0.000000
outsideprotection
1.000000
0.500000
There are two necessary conditions for civil war onset, as shown by the consistency levels of
1.000000 in Table 3. All countries that experienced civil war onset feature rents per capita
below $440 (rentpc3_440) and do not have a military base affiliated with a permanent UNSC
member on their territory. Additionally, spatial overlap between the settlement of politically
excluded groups and oil reserves within a given country only marginally fails the test for
necessity. It is interesting to note that this result only occurs because of the inclusion of
Yemen. If overlap2 for Yemen had been coded as 1, the consistency level of OVERLAP2
would have been 1.000000 instead of 0.928571.
26
Please note that unlike in the case of the tests for sufficiency, the cases that are part of the configuration with
contradicting outcomes in the truth table (row 1 in Table 2) will be included in the tests for necessity.
27
For the tests measuring necessity, we have used the software fs/QCA 2.5, which can be downloaded at
http://www.u.arizona.edu/~cragin/fsQCA/software.shtml (Access, 2010-18-07).
28
As previously explained, uppercase letters represent the “1” value for a given binary condition or outcome,
whereas lowercase letters represent the “0” value for that binary condition or outcome. This means that for
instance “RENTPC3_440” represents all cases coded with 1 that have an average rent per capita above $440,
whereas “rentpc3_440” represents all cases coded with 0 that have an average rent per capita below $440.
29
The consistency value of a necessary condition indicates the degree to which this condition overlaps with a
particular outcome relative to all cases with the same outcome. If a given condition is present in all cases with
the same outcome, the consistency value will be 1.000000, indicating that this is a necessary condition.
30
Coverage of a necessary condition indicates the overlap between a condition and an outcome relative to all
cases with the same condition. Coverage therefore measures the proportion of instances in which the condition
arises that is necessarily explained by the outcome.
18
Of the two necessary conditions of civil war, the absence of outside protection
(outsideprotection) has slightly higher coverage (0.500000) than a low level of per capita
rents (rentspc3_440). Only 48.29 % (0.482759) of the cases that exhibit the latter condition
have experienced civil war onset. If both of these conditions are taken together, we see that if
at least one is present in a country, there is roughly a 50% chance that a civil war will break
out. However, if OVERLAP2 had not marginally failed the test for necessity, countries with
this characteristic would be the most likely to experience civil war of all those within our
sample of 44 net oil-exporting countries.
Table 4 – Test results for necessary conditions for ucdpintens3 (absence of civil war)
Conditions tested:
Consistency
Coverage
RENTPC3_440
0.500000
1.000000
rentpc3_440
0.500000
0.517241
DEPENDENCE5_015
0.433333
0.619048
dependence5_015
0.566667
0.739130
OVERLAP2
0.333333
0.434783
overlap2
0.666667
0.952381
OUTSIDEPROTECTION
0.533333
1.000000
outsideprotection
0.466667
0.500000
Unlike in necessity tests for civil war onset, there is no necessary condition for peace (or the
absence of civil war), as indicated by the presence of consistency values below 1.000000 in
Table 4 for the 8 different values of the 4 binominal conditions tested in our sample.
Taken together – on a more technical level – the solution formula for the necessary conditions
for civil war onset reads as follows:
(2)
rentpc3_440 + outsideprotection  UCDPINTENS3 31
31
Read this expression as indicating that low levels of per capita rents OR a lack of outside protection
necessarily lead to civil war onset.
19
This formula means that an average level of per capita rents below $440 or the absence of a
military base associated with a permanent UNSC member are independent of each other
necessary conditions for civil war onset in net oil-exporting countries.
5.3
Identifying Sufficient and INUS Conditions of Civil War onset and Peace
A condition is defined as sufficient if it can independently produce a certain outcome (Ragin
1987, 99). Thus, tests for sufficiency attempt to verify whether a condition always leads to the
same outcome (although sufficient conditions, unlike necessary conditions, are not
(necessarily) present if the outcome occurs). In addition, INUS conditions are insufficient but
necessary parts of a condition that is itself unnecessary to but sufficient for the outcome to
occur.32
As previously pointed out (cf. section 3 of this paper), Boolean minimization is used in
csQCA to test for sufficient conditions to produce a certain outcome and to seek the most
parsimonious solution formulas including INUS conditions. This Boolean operation, however,
presupposes that each possible logical configuration is covered by at least one real-world
case. Logical remainders, as logically possible configurations that are not represented through
empirical cases in the dataset, constrain this quest for parsimonious solutions.33 In the next
two sections, we therefore present two results of Boolean minimization: one without using
logical remainders and the second including logical remainders. We call the latter the
parsimonious solution and the former the complex solution.
5.3.1 Civil war onset (UCDPINTENS3)
A csQCA-test for sufficiency using the outcome of civil war onset (UCDPINETNS3)
excluding logical remainders yields the following complex solution:
(4)
rentpc3_440*DEPENDENCE5_015 *outsideprotection UCDPINTENS3
solution coverage: 0.571429
unique coverage: 0.571429
solution consistency: 1.000000
32
For the following tests of sufficiency, the software TOSMANA 1.3.1.0 has been used. See
http://www.tosmana.net (Access, 2010-13-07) for more information.
33
See Table 2 for more details. There are 4 logical remainders in our truth table (rows 13, 14, 15, and 16).
20
This solution means that low rents per capita, high dependence and a lack of outside
protection together sufficiently explain the onset of civil war in net oil-exporting countries in
our sample. Taken separately, each factor forms an INUS condition of civil war onset. This
solution is valid without any simplifying assumptions regarding logical remainders and
explains (as indicated by the solution and unique coverage values) more than 57% (7 out of
12) of the cases of civil war onset in the dataset.34
To find a parsimonious solution, logical remainders are included in the test for the sufficiency
of civil war onset. Formula (5) reports the most parsimonious explanation that we could
develop using our dataset:
(5)
rentpc3_440*DEPENDENCE5_015 UCDPINTENS3
solution coverage: 0.571429
unique coverage: 0.571429
solution consistency: 1.000000
This solution reveals that low per capita rents and high dependence are together a sufficient
explanation for civil war onset. Taken separately, the two conditions form INUS conditions.
However, this parsimonious solution is only valid if one assumes that all 4 of the logical
remainders in Table 2 are associated with the onset of civil war in reality.
5.3.2 No onset of civil war (ucdpintens3)
After having tested for sufficient conditions of civil war onset, formula (6) summarizes the
results of the csQCA-test for sufficiency using no civil war onset as an outcome. In a first step
– similar to the tests in the previous section – the complex solution is presented; later, we also
show a parsimonious solution formula.
34
The Appendix 5 at the end of this paper provides a more detailed overview on this.
21
A csQCA-test for sufficiency using the absence of civil war (ucdpintens3) as our outcome
yields the following complex results:
(6)
RENTPC3_440*DEPENDENCE5_015 +
rentpc3_440*dependence_015*overlap2 +
dependence5_015*OUTSIDEPROTECTION
ucdpintens3
solution coverage: 0.866667
solution consistency: 1.000000
As indicated by this solution formula, there are three different (causal) pathways to peace (the
absence of civil war) in the net oil-exporting countries. All three pathways are combinations
of at least two conditions. Each pathway sufficiently explains the absence of civil war for a
varying number of cases. The coverage of each of the three different sufficient explanations is
reported in Table 5.35 High rents per capita (RENTSPC3_440) together with high dependence
(DEPENDENCE5_015) sufficiently explain peace in 43 % of the cases, whereas low rents per
capita (rentpc3_440), low dependence (dependence_015) and no overlap between politically
excluded groups and oil reserves (overlap2) sufficiently explain only 33 % of peaceful cases.
Additionally, low dependence (dependence5_015) and the existence of a military base
affiliated with a permanent UNSC member (OUTSIDEPROTECTION) are a sufficient
combination of INUS conditions in 30 % of the cases in which civil war does not break out.
Table 5 – Coverage of solution formulas for the absence of civil war excluding logical remainders36
Raw Coverage37
Unique coverage38
No of countries
explained
RENTPC3_440 *
DEPENDENCE5_015
rentpc3_440*
dependence5_015*
overlap2
dependence5_015 *
OUTSIDEPROTECTION
0.433333
0.433333
0.333333
0.133333
0.300000
0.100000
13
6
9
35
See the Appendix 7 at the end of this paper for more details.
A (C) indicates membership in a contradicting configuration, cf. also Table 2. These cases are not explained
by sufficient or INUS conditions.
37
Raw coverage indicates the proportion of cases explained by this sufficient condition or combination of
conditions.
38
Because a typical characteristic of csQCA is the existence of overlapping causal pathways (so that a single
case may be explained by more than one causal pathway), unique coverage points to the proportion of cases that
are uniquely explained by this sufficient condition or combination of conditions.
36
22
In addition, Boolean minimization involving the four logical remainders39 reveals the
following parsimonious solution:
(7)
RENTPC3_440 + dependence5_015*overlap2 + OUTSIDEPROTECTION
ucdpintens3
solution coverage: 0.866667
solution consistency: 1.000000
This solution formula is only valid if one assumes that all of the 4 previously mentioned
logical remainders, as shown in rows 13, 14, 15 and 16 of the truth table in Table 2, lead to
the absence of civil war onset (ucdpintens3).
Table 6 – Coverage of solution formula for the absence of civil war including logical remainders
0.500000
0.200000
dependence5_015*
overlap2
0.366667
0.133333
15
6
RENTPC3_440
Raw Coverage
Unique coverage
No of countries
explained
OUTSIDEPROTECTION
0.533333
0.033333
16
Like the complex solution, the parsimonious solution formula (7) shows that there are three
different combinations of conditions that sufficiently explain the absence of civil war. Two
pathways are explained by single sufficient conditions: high rents per capita (RENTPC3_440)
and outside protection (OUTSIDEPROTECTION). The third pathway is a combination of
low dependence (dependence5_015) with no overlap between politically marginalized groups
and oil reserves (overlap2). Each pathway sufficiently explains the absence of civil war for a
varying number of cases (see Table 6). However, a number of cases are explained by more
than one of these pathways.40 The coverage of each of the three different sufficient
explanations is also reported in Table 6. High rents per capita (RENTPC3_440) sufficiently
explain peace in 50 % of the cases, while low dependence (dependence_015) and a lack of
overlap between politically excluded groups and oil reserves (overlap2) only sufficiently
explain 36 % of peaceful cases. Outside protection (OUTSIDEPROTECTION) is the pathway
that explains most of the cases in which civil war does not break out in the sample (53 %).
Unique coverage refers to those cases that are uniquely explained by the given pathway. It is
39
40
For logical remainders, see rows number 13, 14, 15 and 16 in the truth table on page 17.
See Appendix 8 at the end of this paper for more details.
23
here where high rents per capita are proven to be a superior sufficient explanation of the
absence of civil war onset. The rentier mechanism uniquely explains 20 % of the cases in
which civil war does not break out. This figure is far above the unique coverage values of the
two other sufficient explanations.
6.
Conclusion
According to quantitative studies, oil seems to be the only resource that is robustly linked to
civil war onset. However, recent debates on the nexus of oil and civil war have neglected two
major considerations: there are a number of historically peaceful oil-rentier states, and there
have been few efforts to explain why some oil-exporting countries have experienced civil war
and others have not. Methodologically, the debate has been dominated by research using
either quantitative methods or case studies, with little genuine medium-N comparison. This
paper aims to fill this gap by studying the conditions of civil war onset among net oil
exporters, using (crisp-set) Qualitative Comparative Analysis (csQCA) to identify necessary
and sufficient conditions for the onset of civil war in 44 net oil-exporting countries. To the
best of our knowledge, this paper contains the first attempt to look at the oil-conflict link
using this methodology.
Our findings show that a certain level of abundance in terms of rents per capita (below
$440)41 and a lack of outside protection (with no military base present that is associated with a
permanent UNSC member) are both independently necessary conditions for the onset of civil
war in oil-exporting countries. Moreover, we have also isolated high dependence and low
abundance as INUS conditions of civil war onset. Taken together, along with the factor
indicating the absence of outside protection, these factors sufficiently explain the onset of
civil war.
Unlike with civil war onset, we have found no necessary conditions for the non-occurrence of
(major) civil war. We interpret this result as evidence supporting the assumption that there are
many more configurations that will lead to peace than configurations that will lead to civil
war onset. In other words, peace is still the most likely status, even for petroleum-rich
countries, and this is true for a variety of reasons.
41
Strictly speaking, the level of abundance is below $440 rents per capita and above $100 rents per capita
because we have restricted our sample so that it includes only those cases with non-trivial amounts of oil exports
(see also Section 4.1, Sample Selection, on page 11).
24
We have also found three major pathways that sufficiently explain the non-occurrence of civil
war. High rents per capita are the most wide-ranging single condition in this context. 13 of 30
cases with this outcome in the sample are sufficiently explained by this condition. A military
base owned by a UNSC member and a combination of low dependence and a lack of overlap
between politically excluded groups and oil reserves are two alternative factors or sets of
factors that are sufficient to prevent the outbreak of a (major) civil war. These sorts of results
are rarely found in the existing comparative literature on civil war.
We must note that our model explains only 8 out of 14 cases of (major) civil war onset. Six
cases feature a configuration or ‘risk profile’ (cf. row 2 in Table 2) that is connected with
contradictory outcomes. Out of the 10 countries in this configuration, there are 4 that have
experienced no onset of civil war in addition to 6 cases with civil war onset. Although these
10 cases do not present a substantial limitation to our model – the explained variance in
regression analyses is commonly much lower42 – this inconsistency certainly calls for future
research. One preliminary observation is that all countries that belong to the configuration in
row 2 of Table 1 have indeed experienced minor civil war (below the threshold of 1,000
battle-related deaths). It is possible that this configuration is prone to this kind of violence.
Moreover, the contradictory configuration includes low dependence as one of its conditions,
which may suggest that oil is less important for these economies on the whole and thus that
non-resource-specific conditions play a bigger role. Methodologically, these and related
hypotheses could be tested through additional QCA analyses and particularly using qualitative
controlled comparison, such as by comparing selected pairs of cases.43
In more technical terms, (a) contradicting configuration(s) may indicate that the model we
have used is under-specified. However, increasing the number of variables in csQCA models
does not come without costs. Based on the analytical logic of QCA, there is a trade-off
between the number of conditions included in the model and the number of potential logical
remainders given the constant number of historical cases. The more binary-coded conditions,
the exponentially higher the number of theoretically possible configurations. Given the
42
As we have previously noted (see fn 24), we interpret the proportion of cases belonging to a contradictory
configuration as a major measure of model fit in csQCA. From this perspective, our model sufficiently explains
more than 75% of the cases in the sample.
43
There are two sets of cases that look promising for such a comparison. The first is a set of four Latin-American
countries (Colombia and Peru, which have experienced civil war, and Argentina and Bolivia, which have not).
The second set covers two cases from Southeast Asia (Malaysia and Indonesia).
25
usually static number of historical cases, it is very likely then that the number of logical
remainders will increase as well.44 A high number of logical remainders, however, limits the
opportunities for Boolean minimization and increases the need to use more simplifying
assumptions to identify the most parsimonious solution.
7.
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8.
Appendix
Appendix 1 - Sample
Base sample:
All countries between 1970-2008
with at least a single year of netexports of mineral fuels (SITC
Rev1 3).45
Cases: 62
Afghanistan
Algeria
Angola
Antigua and Barbuda
Argentina
Australia
Azerbaijan
Bahamas, The
Bahrain
Barbados
Belarus
Benin
Bhutan
Bolivia
Brunei Darussalam
Bulgaria
Cameroon
Canada
Cape Verde
China
Colombia
Congo, Rep.
Cote d'Ivoire
Denmark
Ecuador
Egypt, Arab Rep.
Gabon
Ghana
Indonesia
Iran, Islamic Rep.
Iraq
Kazakhstan
Kuwait
Sub-sample 1:
Sub-sample 2:
Base sample plus proven reserves
Sub-sample 1 plus at least $ 100
of mineral fuels (crude oil and
per capita rents from production of
natural gas) according to PRIO
mineral fuels for at least one year47
Petrodata (V1.2.)46
Cases: 54
Afghanistan
Algeria
Angola
Argentina
Australia
Azerbaijan
Bahrain
Belarus
Benin
Bolivia
Brunei Darussalam
Bulgaria
Cameroon
Canada
China
Colombia
Congo, Rep.
Cote d'Ivoire
Denmark
Ecuador
Egypt, Arab Rep.
Gabon
Ghana
Indonesia
Iran, Islamic Rep.
Iraq
Kazakhstan
Kuwait
Cases: 44
Algeria
Angola
Argentina
Australia
Azerbaijan
Bahrain
Bolivia
Brunei Darussalam
Cameroon
Canada
Colombia
Congo, Rep.
Cote d'Ivoire
Denmark
Ecuador
Egypt, Arab Rep.
Gabon
Indonesia
Iran, Islamic Rep.
Iraq
Kazakhstan
Kuwait
45
Data are from UN comtrade (SITC Rev. 1,33), online: http://comtrade.un.org/db/default.aspx, (access 201006-29).
46
Data are from PRIO/CSCW: Petroleum Dataset v. 1.2, online:
http://www.prio.no/CSCW/Datasets/Geographical-and-Resource/Petroleum-Dataset/, (access 2010-04-20).
47
Data are from World Bank/Adjusted Net Saving Data Center: Oil and gas rents, online:
http://siteresources.worldbank.org/INTEEI/1105643-1115814965717/21683431/oil_and_gas_rents.xls, (access
2008-11-05).
30
Libya
Lithuania
Malaysia
Mexico
Mozambique
Netherlands
Nigeria
Norway
Oman
Papua New Guinea
Peru
Qatar
Russia
Saudi Arabia
Seychelles
Singapore
Somalia
South Africa
Sudan
Syria
Trinidad and Tobago
Tunisia
Turkmenistan
United Arab Emirates
United Kingdom
Venezuela, RB
Vietnam
Yemen, Rep.
Zimbabwe
Libya
Lithuania
Malaysia
Mexico
Mozambique
Netherlands
Nigeria
Norway
Oman
Papua New Guinea
Peru
Qatar
Russia
Saudi Arabia
Somalia
South Africa
Sudan
Syria
Trinidad and Tobago
Tunisia
Turkmenistan
United Arab Emirates
United Kingdom
Venezuela, RB
Vietnam
Yemen, Rep.
-
Libya
Malaysia
Mexico
Netherlands
Nigeria
Norway
Oman
Papua New Guinea
Peru
Qatar
Russia
Saudi Arabia
Sudan
Syria
Trinidad and Tobago
Tunisia
Turkmenistan
United Arab Emirates
United Kingdom
Venezuela, RB
Vietnam
Yemen, Rep.
-
31
Appendix 2 - Codebook
Variable
Label
Description
Sources
ucdpintens3
1: if at least 1,000 battle-related deaths in
a given year for the first time between
1970 and 2008 (new civil war onset, or
new episode of civil war or ongoing
conflict)
0: all other constellations
.: n/a
UCDP/PRIO Armed Conflict
Dataset v.4-2009, 1946 –
2008, online:
http://www.pcr.uu.se/researc
h/UCDP/
data_and_publications/datase
ts.htm, 20.4.2010.
rentpc348
Mean of available oil and gas rents in $
per capita between 1970 and the year
before ucdpintens3 = 1; otherwise mean
over the whole period (1970-2008)
World Bank/Adjusted Net
Saving Data Center: Oil and
gas rents, online:
http://siteresources.worldban
k.org/INTEEI/11056431115814965717/21683431/oi
l_and_gas_rents.xls,
5.11.2008.
- World Bank: World
Development Indicators
online, 20.4.2010 (population
data).
rentpc3_440
1: value of rentpc3 equal and above $ 440
0: value of rentpc3 below $ 440
Mean of the ratio of available fuel exports
to GDP, 1970 and the year before
ucdpintens3 = 1; otherwise mean over the
whole period (1970-2008)
Based on values of
rentpc3.
1: value of dependence5 equal and above
0.15
0: value of dependence5 below 0.15
1: If settlement of excluded group(s) and
resource locations overlap in general or in
the case of civil war before the onset of
civil war or the onset of the first new
episode of an old civil war (Overlap only
if the settlements of the group do not cover
the whole/very large parts of the country.)
0: all other constellations
.: n/a
Based on values of
dependence5.
1: if UNSC members maintain a military
Existence of US, British,
Dependence5
Dependence5_015 49
overlap2 50
outsideprotection
- World Bank/Adjusted Net
Saving Data Center: Oil and
gas rents, online:
http://siteresources.worldban
k.org/INTEEI/11056431115814965717/21683431/oi
l_and_gas_rents.xls,
5.11.2008.
- World Bank: World
Development Indicators
online, 20.4.2010 (population
data).
Coded on the basis of
GeoEPR, online:
separate maps by 3
http://dvn.iq.harvard.edu/dvn/
different coders.
dv/epr, 21.4.2010.]
EPR categories for
excluded groups:
powerless, discriminated,
regional
autonomy/seccionist
autonomy
Based on our own
48
Please note that in order to calculate rentpc3 for Angola we have used the episode of civil war onset in 1998
instead of the original onset in 1975, which coincides with the first year of Angola in the dataset (year of national
independence).
49
Due to the lack of data on oil and gas exports or the lack of GDP data dependence5 has a number of missing
values (Azerbaijan, Mozambique, Russia, Sudan and Yemen). However, due to our country expertise we
estimated the values of dependence5_015 as follows: Azerbaijan = 1; Russia = 1; Sudan = 0; Yemen = 1.
50
Bahrain, Brunei and Qatar are not covered by EPR data. Therefore we decided to code all three cases as 0.
32
base employed with regular combat forces
in the country
0: no bases (also permanent UNSC
members with no base of another
permanent UNSC member and troops of
UNSC members which entered the
country due to an internal or external
conflict)
.: n/a
French, Russian or
Chinese military bases
which employ regular
combat forces
(paramilitary units,
border guards, military
advisers, logistic unites
are not coded as 1)
investigations.
Appendix 3 – Distribution of dependence5_015
distribution of dependence5
0,6500
0,6000
0,5500
0,5000
0,4500
0,4000
0,3500
0,3000
0,2500
0,2000
0,1500
0,1000
0,0500
0,0000
-1
0
1
33
Appendix 4 – Distribution of ucdpintens3 versus rentpc3
ucdpintens3 versus rentpc3
12000
11000
10000
9000
8000
7000
6000
5000
4000
3000
2000
1000
0
-1.0
0.0
1.0
2.0
Appendix 5- Coverage of the complex solution for civil war onset excluding logical remainders
rentpc3_440*
DEPENDENCE5_015*
outsideprotection
0.571429
0.571429
X
X
X
Raw Coverage
Unique coverage
Algeria
Angola
Azerbaijan
Colombia (C)
X
Congo
Indonesia (C)
X
Iran
Iraq (C)
X
Nigeria
Peru (C)
X
Russia
Sudan (C)
Syria (C)
Yemen
X
Please note: C denotes that cases belong to a configuration with contradiction outcome even though the have
experienced an onset of civil war. These cases are not explained by sufficient or INUS conditions.
Appendix 6 - Coverage of the parsimonious solution for civil war onset including logical remainders
rentpc3_440*
DEPENDENCE5_015
Raw Coverage
Unique coverage
Algeria
0.571429
0.571429
X
34
Angola
X
Azerbaijan
X
Colombia (C)
Congo
X
Indonesia (C)
Iran
X
Iraq (C)
Nigeria
X
Peru (C)
Russia
X
Sudan (C)
Syria (C)
Yemen
X
Please note: C denotes that cases belong to a configuration with contradiction outcome even though the have
experienced an onset of civil war. These cases are not explained by sufficient or INUS conditions.
Appendix 7 – Coverage of the complex solution for no onset of civil war excluding logical reminders51
0.433333
0.433333
rentpc3_440*
dependence5_015*
overlap2
0.333333
0.133333
13
6
RENTPC3_440 *
DEPENDENCE5_015
Raw Coverage
Unique coverage
No of countries
explained
Argentina (C)
Australia
Bahrain
Bolivia (C)
Brunei
Cameroon
Canada
Cote d'Ivoire
Denmark
Ecuador
Egypt
Gabon
Kazakhstan
Kuwait
Libya
Malaysia (C)
Mexico (C)
Netherlands
Norway
Oman
Papua New Guinea
Qatar
Saudi Arabia
Trinidad and Tobago
Tunisia
Turkmenistan
United Arab
United Kingdom
Venezuela
Vietnam
dependence5_015 *
OUTSIDEPROTECTION
0.300000
0.100000
9
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
51
A (C) indicates membership into a contradicting configuration, cf. also Table 2. These cases are not explained
by sufficient or INUS conditions.
35
Yemen
X
Please note: C denotes that cases belong to a configuration with contradiction outcome even though the have
experienced no onset of civil war. These cases are not explained by sufficient or INUS conditions.
Appendix 8 – Coverage of the parsimonious solution for no onset of civil war including logical reminders
0.500000
0.200000
dependence5_015*
overlap2
0.366667
0.133333
15
6
RENTPC3_440
Raw Coverage
Unique coverage
No of countries
explained
Argentina (C)
Australia
Bahrain
Bolivia (C)
Brunei
Cameroon
Canada
Cote d'Ivoire
Denmark
Ecuador
Egypt
Gabon
Kazakhstan
Kuwait
Libya
Mexico (C)
Netherlands
Norway
Oman
Papua New Guinea
Qatar
Saudi Arabia
Trinidad and Tobago
Tunisia
Turkmenistan
United Arab Emirates
United Kingdom
Venezuela
Vietnam
Yemen
OUTSIDEPROTECTION
0.533333
0.033333
16
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Please note: C denotes that cases belong to a configuration with contradiction outcome even though the have
experienced no onset of civil war. These cases are not explained by sufficient or INUS conditions.
36