Inevitable Evil?
A Qualitative Comparative Analysis of Genocide Occurrence and NonOccurrence
Paul Steinheuer
University of Kent, Canterbury
Timothy Williams
Free University, Berlin
Centre for Conflict Studies, Philipps-University, Marburg
Paper presented at the International Studies Association Annual Convention,
San Francisco, 3-6 April, 2013
Abstract:
The relevant genocide literature identifies a host of causes for why and when genocide occurs, with
war, political upheavals such as revolution, autocracy, less interdependent economies and
exclusionary ideologies among the suggested factors. However, much of this evidence relies strongly
on individual cases of genocide, neglecting the important role of comparison between cases and the
relevance of counterfactuals. Harff’s (2003) statistical study began to bridge this gap; however, as a
complex phenomenon there are multiple reasons why different cases of genocide occur, which are
not captured by this statistical approach. By approaching this topic with Qualitative Comparative
Analysis (QCA), this paper aims to apply a different and more suitable methodology to this question
than previous studies. This method allows for the occurrence or non-occurrence of genocide to be
traced back not to the same variables in all cases, but to different combinations of multiple factors,
each coming to a fore in different cases. By using QCA and including counterfactuals in the analysis,
this paper is able to identify both necessary and sufficient conditions for genocide occurrence. The
model identifies several combinations of independent variables which in interaction with each other
have the same effect across several cases, either repeatedly causing genocide or preventing it.
“Genocide is not an inevitable consequence of certain social conditions within a society. There may be extreme
pluralism in a society, with highly antagonistic, polarizing ideologies, division expressed in religion, segregation,
employment, social networks, and political party affiliation, a long history of reciprocal violence, and periods of
highly escalated conflict. Yet the struggle may stop short of genocide.”
- Leo Kuper, 1981 (page 56f.)
1. Introduction
This quote by Leo Kuper is an apt summary of most scholarship in the study of genocide, highlighting
certain factors which facilitate genocide occurrence but shying back from being able to actually label
any of these conditions necessary or sufficient. This paper aims to go beyond the previous literature
and identify constellations of determinants which together can cause genocide. Given the heinous
nature of the crime and the huge impact genocidal killing has had in the 20th century it is of the
utmost importance that social scientists further the endeavour to identify the central determinants
of this phenomenon in order to understand why and when genocides occur. Thus the research
question underlying this paper asks ‘What combinations of factors play together to determine
genocide occurrence?’
In 2003 Barbara Harff published her seminal paper No Lessons Learned from the Holocaust?
Assessing Risks of Genocide and Political Mass Murder since 1955, a statistical analysis of
determinants of genocide occurrence which received wide acclaim. While Harff’s study identified
several key factors which raised the risk of genocide and politicide, genocide is an inherently complex
phenomenon and no one or more causes can be deemed responsible for its outbreak in all cases.
Thus this paper postulates that a better methodology for studying this subject matter would be a
qualitative comparative analysis (QCA) which uses Boolean algebra to identify multiple pathways to
the same outcome with different combinations of variables acting in different cases. With this
method, this paper will provide different profiles of factor combinations which provoke genocide
outbreak, identifying necessary and sufficient conditions. In order to ensure the comparability of this
QCA study with Harff’s previous work, we attempt to use as many of Harff’s variables as possible.
This paper will first clarify some definitorial issues around the concept genocide and politicide, before
presenting a theoretical framework of different determinants emphasised in previous research and
explaining the merits of the chosen QCA approach. Subsequently, our case choice will be explained in
detail, as well as the variable operationalisations, particularly detailing which variable of Harff’s this
study kept, and which were replaced. Finally, the results of the QCA will be presented in a truth table
and expanded in an empirical analysis, before bringing together these results and identifying how
this study has developed the work of Harff and what remains to be researched.
2. What is Genocide? A Contentious Definition of an Elusive Concept
While genocides have been occurring as long as mankind has been living in societies, the term
genocide was not coined until after World War II. Polish jurist and émigré to the United States
Raphael Lemkin combined the Greek word genos (nation, people, race) with the Latin caedere (to
kill), in an attempt to codify in international law the horrors of the Holocaust, in order that they not
be repeated. In 1948, the United Nations General Assembly (1948) – after much discussion and
dilution – passed the Genocide Convention, under which genocide is constituted by
“any of the following acts committed with intent to destroy, in whole or in part, a national, ethnical,
racial or religious group, as such: (a) Killing members of the group; (b) Causing serious bodily or mental
harm to the members of the group; (c) Deliberately inflicting on the group conditions of life calculated
to bring about its physical destruction in whole or in part; (d) Imposing measures intended to prevent
births within the group; (e) Forcibly transferring children of the group to another group.”
This definition, however, is widely criticised by academics, as it proves too exclusive in its target
identification, ignoring victimisation of political, economic and social groups, such as around 300,000
mentally ill and thousands of homosexuals killed during the Holocaust or the 15-20m Soviet citizens
killed as class enemies (Chalk 1989). Furthermore, the UN definition is too inclusive regarding
constitutive means (mental harm, birth prevention, transfer of children), and many posit that a
degree of physical harm should be included to warrant the term genocide. Also, the Convention
neglects the possibility of non-state actors engaging in such actions; finally, while the stipulation of
intentionality is important to the definition, it provides great difficulty empirically. While this final
point has been debated hotly in the research community, it has also been pointed out that “it is not
plausible that a group of some considerable size is victimized by man-made means without anyone
meaning to do it!” (Jonassohn 1992, 21). Nonetheless, when trying to identify cases of genocide and
distinguish them from cases of non-genocide, it can be difficult to pinpoint concrete evidence of
intent.
Due to these obvious shortcomings, academics widely opt for using alternative definitions, although
there are nearly as many definitions as there are authors. One helpful definition is provided by Chalk
and Jonassohn (1990, 26): “a form of one-sided mass killing in which a state or other authority
intends to destroy a group, as that group and membership in it are defined by the perpetrator.” The
advantages of this phrasing are the subjective definition of the victim, one-sidedness of violence, the
stipulation of intentionality, and option for non-state and state actors, most elements not found in
their entirety in other definitions.
However, some authors would not go as far as this and allow victims to be any group a perpetrator
chooses. Thornberry (1991, 68) posits that political groups are formed optionally, not as inevitable
groups and thus should be excluded from the genocide category. So as to include these cases in her
study anyway, Barbara Harff (2003, 58) includes the crime of ‘politicides’, defining genocides and
politicides as “the promotion, execution, and/or implied consent of sustained policies by governing
elites or their agents—or, in the case of civil war, either of the contending authorities—that are
intended to destroy, in whole or part, a communal, political, or politicized ethnic group.” To ensure
the comparability of this study with Harff’s original study, we will remain with this definition;
however, we will subsume both categories of genocide and politicide under a more inclusive term of
genocide, defined to include both the restrictive genocide definition and the extended social,
economic and political categories suggested in politicide. Thus, the term genocide in this paper refers
to the same subject matter as Harff’s genocide and politicide.
3. Why are Genocides and Politicides Expected to Occur? Central Determinants and
Hypotheses
In this section we discuss the main determinants of genocide, as identified in previous research,
particularly the study by Harff (2003), and subsequently deduce preliminary research hypotheses. As
will be discussed in section 4, it would be unwise to include too many variables into the QCA; thus,
this section will also explain which of the theoretically important variables will be included in the
analysis and which will be factored out.
Political Upheaval
The most commonly cited determinant of genocide occurrence is political upheaval (see
Chalk/Jonassohn 1990; Krain 1997; Melson 1992; Rummel 1994; Weitz 2003) and also finds a
prominent position in Harff’s study. Harff (2003, 62) defines political upheaval as “an abrupt change
in the political community caused by the formation of a state or regime through violent conflict,
redrawing of state boundaries, or defeat in international war.” In this context, Melson (1992) and
Krain (1997) emphasise the importance of revolutions, but it is also a category in which
decolonisation would equally be well placed. The logic behind both these is that political upheavals
provide a political opportunity structure which is conducive to starting genocide and in the throes of
political upheaval, reigning elites may feel particularly threatened by certain groups, they believe
could try to exploit the upheaval to topple them. With the constraints of a previous system removed,
the legitimacy of the political community and its identity (including which groups constitute it) can be
called into question (Melson 1992, 21). Political upheaval provides the opportunity to re-define the
demos, the circle of people included as constituents of the state, in a deinstitutionalised setting
(Mann 2005). The empirical founding of this is immense and Harff (2003) finds significant impact of
political upheaval on the risk of genocide occurrence, while Krain (1997) suggests that
extraconstitutional changes (a similar concept) have a significant impact on this likelihood. These
empirical findings suggest that political upheaval should be seen as a necessary and sufficient
condition.
Hypothesis 1: Political upheaval is a necessary and sufficient condition to all genocide occurrences.
War
A further condition often associated with genocide occurrence is the presence of war (Melson 1992;
Rummel 1994; Weitz 2003), and for Krain (1997) a country’s involvement in civil war is the single
most significant determinant of genocide occurrence in his statistical study. Nonetheless, war should
be seen more as a facilitative condition than a determinant, as, logically, it is never strictly the cause
of genocide occurrence: the participation in a war is not a motivation to attempt the destruction of a
part of the population, it merely allows such a destruction to happen, e.g. as other policy options are
closed off or the state becomes increasingly autonomous from other internal social forces (Melson
1992, 19); furthermore, war provides the opportunity to scapegoat certain unwanted groups and
portray them as internal enemies of the state. Due to its purely facilitative nature, however, war will
not feature as a variable in the analysis, as in Harff, but is used to aid in the choice of counterfactual
cases (see section 5).
Pluralistic Societies and Ethnic and Religious Cleavages
Defined as “states with re-existing internal cleavages and real opposition” (Fein 1990, 39), pluralistic
states have often come into existence during the process of colonisation and decolonisation when
multiethnic states emerged as borders were determined arbitrarily by colonial masters (Kuper 1981).
In her paper, Harff (2003) suggests several measures of ethnic and religious cleavages, two of which
will be chosen to be tested here: First, continual political and economic discrimination of a minority
can lead to this group’s political mobilisation, and in turn can lead to repression by the state; in some
circumstances, this repression could escalate into genocide. Only if a spiralling of discrimination is
seen will a genocide occur, although there can be different reasons for such spiralling to occur and
discrimination to intensify. Secondly, if elites are disproportionately from one section of society,
underrepresented groups may challenge this, prompting the elites to frame security and ideology in
communal terms, e.g. advocating racial denigration or exclusion of the other groups. These ethnic
factors, as argued here, could participate in causing genocide where they occur (sufficient), but they
do not seem to present mechanisms which must necessarily be present in all cases, as it is
conceivable that genocide could occur without strong ethnic factors. In her statistical analysis, Harff
found empirical support only for the latter of the two posited connections. In this paper, the primary
analysis will include the last measure of ethnic cleavages focussing on disproportionate ethnic
representation in a country’s elite as this is what Harff found to be most significant. Nonetheless, the
other variable will also be included as a comparison.
Hypothesis 2: Official state discrimination, or biased elite representation are sufficient, although not
necessary for genocide to occur. It is expected that they will have similar impact in the analysis.
Autocratic Regime
Rummel’s (1994) mantra has adapted Lord Acton’s iconic phrase to read ‘Power kills; absolute power
kills absolutely’. In countries with limited and accountable power, democides (as he terms mass
murder by governments of their own citizens) are less likely to happen because of cross pressures
and the associated political culture. This argument can be focused on a more narrow definition of
democracies, in which no one group can become the driving force and there is a democratic culture
which “involves debate, demonstration, and protests as well as negotiation, compromise, and
tolerance” (Rummel 1994, 23). Inversely, autocratic regimes have a free hand at dealing with
disagreeable groups with no other actors constraining their actions or contesting one-sided genocidal
action, suggesting that autocracy is a necessary condition for genocide occurrence. While Harff finds
autocracies to be three-and-a-half times more likely to commit genocide than democracies, Krain
finds no statistical relation. In an effort to test this discrepancy, this variable will be included in the
study. However, one can expect that it only comes to a fore as a sufficient condition in cases in which
there is an exclusionary ideology perpetuated by the elites who then have free hand to act on their
ideology, or in cases of political upheaval, as the autocratic elites must fear losing power and thus
attempt to consolidate their position by drastically changing the playing field, as was evidenced by
Hutu radicals in the 1994 Rwanda genocide. This is not necessarily the case for ethnic cleavages,
however, as the autocratic regime does not necessarily need to see this diversity as negative; rather
political upheaval threatens, and exclusionary ideologies provide a motivation.
Hypothesis 3: The presence of an autocratic regime is necessary for genocide occurrence and could be
sufficient in combination with political upheaval or an exclusionary ideology.
Ideology
Chalk and Jonassohn (1990) posit that modern genocide is implemented as an ideology, selecting
victims according to who they are, and not by what they have or where they are as it was in
premodern genocides. Harff also emphasises the importance of exclusionary ideologies and finds
that they significantly impact the probability of genocide occurrence. She defines an exclusionary
ideology as “a belief system that identifies some overriding purpose or principle that justifies efforts
to restrict, persecute, or eliminate certain categories of people” (Harff 2003, 63). Freeman (1991)
posited that while neither a strong state, nor a pluralistic society were strictly necessary for genocide
occurrence a genocidal ideology is. We disagree that such an ideology should be necessary for
genocide occurrence, as there are several examples of cases in which it is a rational decision due to
internal politics, rather than an ideological impulse that provokes genocide; however, an elite that
subscribes to an exclusionary ideology and has the capacity to follow through, needs no other factors
for genocide to occur. For instance, Mann (2005) demonstrates that the most important genocidal
ideology in modernity has been the ideology of the unified nation-state, from which the victim group
is excluded; this becomes possible because in the process of building a new nation, a new identity
can be created which redefines the demos (citizens of the state) to include only one ethnos (ethnic
sub-group in the country), thus expelling the victim group from the security of citizenship and
opening up the possibility of their destruction. Given the evidence in a breadth of scholarly literature
this variable will also be included in the analysis.
Hypothesis 4: An exclusionary ideology is sufficient for genocide to occur.
Economic and Political Autarky
A variable not commonly mentioned in the genocide literature, but that nonetheless played an
important part in Harff’s analysis is the degree of international involvement and interdependence a
country has. The more interdependent that a country is with others, the less likely they are to choose
genocide as a course of action because the repercussions of international reactions to this move
would hit them harder. On the other hand, this means that relatively isolated states’ leaders will
work on the assumption that they can act without having to fear too strong economic repercussions.
For instance, countries with relatively independent economies will have less to fear from economic
boycotts. This, however, is a facilitative condition that will not cause genocide independently as
there is then no intrinsic motivation for committing genocide. In Harff’s analysis, political
interdependence has no significant impact, while economic interdependence does. In order not to
incorporate too many variables, this QCA will thus include only economic interdependence.
Hypothesis 5: Economic autarky is facilitative for genocide occurrence in some conditions, although it
will have no stand-alone impact.
4. QCA – an Intermediate Method for Multi-Causal Phenomena
The methodology to be used in this paper is Qualitative Comparative Analysis (QCA), popularised in
the social sciences by Charles Ragin (1989; 2008). This method categorises cases by combinations of
factors leading to the occurrence or non-occurrence of the outcome, and reduces these
combinations to the lowest common denominator using Boolean algebra. By executing this reduction
one can show which variables are necessary and which are sufficient for causing the outcome. The
dependent variable can be caused not by the same variable in all cases, but by different
combinations of multiple factors, each coming to a fore in different cases.
QCA is thus an intermediate method between quantitative and qualitative methodologies, as it relies
on the qualitative judgement of the researcher when categorising the cases, but uses a mathematical
technique to categorise and reduce complexity. Its key advantages vis-à-vis statistical analyses are its
ability to cope with multiple pathways to an outcome, each consisting of different combinations of
variables. While statistical analyses pit different variables against each other to establish the variable
with the highest significant impact, QCA follows a conjunctural logic which allows for variables to act
differently in different cases depending on their interaction with other factors. Another key strength,
the importance of the qualitative input of the research when coding the variables, is also its main
weakness. As a set-theoretical method, it can only cope with dichotomous variables, thus losing
much information about the countries being studied and not very well allowing for ambiguous cases
to be coded appropriately, as they must ‘fit the box’. However, there are methodological
developments towards fuzzy set QCA (fsQCA) which allows for a more continuous categorisation.
However, fsQCA cannot work with a dichotomous outcome such as genocide occurrence, so that this
paper will remain with classic QCA, pointing out contentious categorisations. Thus with this method,
this paper hopes to go beyond Harff’s statistical analysis and be able to pinpoint several key
combinations that can lead to the occurrence of genocide.
To carry out a QCA, first all values of variables, both independent and dependent, must be coded
dichotomously for all cases – is this condition present or absent in each case? Next, a so-called ‘truth
table’ is created in which each logical combination of independent variables constitutes one row. For
instance, if a study has three variables A, B and C leading to the outcome E, there will be eight rows
of possible combinations in the truth table. In this example capital letters signal the presence of a
variable, while the symbol ~ before the letter denotes the variable’s absence in the left-hand column
of Figure 1. The asterisk * is to be read as a ‘logical and’, meaning that all these variables must
happen together for the effect to occur. The truth table then assigns to these combinations whether
the outcome is present (E) or not (~E); in most rows this coding is clear, but in some rows there are
cases with diverging outcomes meaning that the researcher must decide whether to include the rows
as present, absent or ambiguous. Ambiguous cases (or ‘Don’t care’ in QCA terms and represented by
a dash -) mean that this particular combination of variables is permitted to be both E and ~E during
the Boolean reduction. Also rows can be excluded from the analysis.
Logical combination
A*B C
A * B * ~C
A * ~B * C
~A * B * C
A * ~B * ~C
~A * B * ~C
~A * ~B * C
~A * ~B * ~C
1
2
3
4
5
6
7
8
Number of cases with Number of cases Classification for QCA
with outcome absent reduction
outcome present
2
E
1
5
~E
4
E
3
E
1
~E
3
~E
2
E
Figure 1: Demonstration QCA truth table
By reducing the cases, one can find two combinations of factors that demonstrate sufficiency for the
outcome to occur: by combining A * B * C and A * ~B * C, one can say that B is irrelevant for the
outcome, but that the presence of A and C together are sufficient. Likewise A * ~B * ~C and ~A * ~B *
~C can be reduced to ~B * ~C. Altogether then the Outcome E can be described as being caused by
the following solution formula, in which + should be read as a ‘logical or’, meaning that either
combination is sufficient for the occurrence of E:
A * C + ~B * ~C
Interestingly, C is an important part of both outcomes, although in one combination it is present and
in the other absent. A statistical regression analysis would not be able to pick up on this and would
most likely discount the influence of C on the outcome, even though it just acts differently in
different combinations. Logically, A * ~B * C and A * ~B * ~C can be reduced to A * ~B also; however,
this brings no extra classification of cases not already covered so is normally excluded from the
results.
5. Model Specification
5.1 Case Selection
Key to any empirical study is selecting the right cases, and in order to avoid any bias in this selection
process (for instance by choosing cases which are a good ‘fit’ with a researcher’s preconceived ideas
of such phenomena and the relevant hypotheses) we have chosen to work from the same list as
Harff (2003). She has compiled a list of 42 cases (Harff 2009a) classified as genocide according to her
definition as explained above and building on the Political Instability Task Force’s (PITF) State Failure
Problem Set which in its updated version today includes all countries in the world from the years
1955-2009.1 However, some of these genocides have occurred with very low absolute fatality
numbers and in order for this study to show the central dynamics leading to genocide occurrence in
general, it will restrict itself to the worst instances of genocide. This is particularly important to be
able to differentiate the cases of genocide clearly from the non-genocides included in the study; in
cases of ‘less extreme’ genocide, there would be a bit of overlap with bloody civil wars in which
civilians are targeted – while these are conceptually different, there is sometimes empirically a
problem in differentiation between them, particularly with low numbers of death. Hence, this
‘extreme case’ approach will highlight the variables which lead to genocide and non-genocide in the
most direct way possible.
This paper thus takes all cases of genocide from Harff’s list which score four or more (out of five) on
the variable DEATHMAG, which signifies a magnitude of at least 64,000 annual deaths, for at least
one year during the genocide. In order to rule out interaction effects over time, each country is only
permitted to be chosen as a case once, with the higher fatality instance being selected. Ultimately
thus there are 11 cases of genocide included, ranging from the 1959 suppression of ‘counterrevolutionary elements of society’ in China to the 1994 genocide in Rwanda.2
Non-genocides conceptually should be cases in which genocide did not occur but in which it is
plausible that they could have. Such ‘counterfactual’ cases are relatively hard to identify reliably, and
the best attempt of this in this paper is to take countries in which – according to the State Failure
Problem Set – an armed conflict (ethnic or revolutionary war) is being fought and then take the
conflicts with the highest number of fatalities, including both combatants and non-combatants. The
logic behind this approach is that most genocides occur in the context of war (one consensus point
within genocide studies), and that this provides a conducive environment for genocide to come
about; this is a context in which it is plausible that genocide could occur, and yet it does not. Again,
to rule out interaction, non-genocides are not selected in a country in which a genocide has occurred
(also in countries with lower magnitude genocides not included in the study), and only one conflict is
included per country. In order to ensure that the same number of cases of genocide and non-
1
Operational guidelines applied by Harff (2003, 58f.) in compiling this list are: 1. Complicity of the state or
contending authorities; 2. Evidence of intent; 3. Victims as members of an identifiable group; 4. “Policies and
practices that cause prolonged mass suffering”; 5. Threat posed to survival of the group by these actions.
2
The case list is Cambodia (1975-1979), Indonesia (1965-1966), Nigeria (1967-1970), Pakistan (1971), Rwanda
(1994), Sudan (1983-2002), Afghanistan (1978-1992), Bosnia (1992-1995), Burundi (1965-1973), China (1959),
Iraq (1988-1991).
genocide are included the threshold is set at more than 5,000 fatalities in the worst year of a conflict,
resulting in 11 cases too.3
5.2 Variables operationalisations
In most key variables’ operationalisation I follow in Harff’s footsteps, taking the data from her model
dataset (Harff 2009b), which is based on the State Failure Problem Set. The QCA model for this paper
features the occurrence of genocide as the dependent variable (coded 1 for occurrence and 0 for
non-occurrence) and five key variables as independent variables. The values of these variables are
selected from the first year of the genocide or non-genocidal conflict (or as close as possible when
data points are missing), in order to avoid reverse causality by which the genocide or non-genocide
itself would impact these variables which are supposed to be determining its outbreak. Here we will
only briefly detail the operationalisation of variables taken from Harff (2003), please see her study
for further details.
Political upheaval (P)
Harff (2009c) operationalises political upheaval (P) using the “the sum of the maximum magnitude of
events in the prior 15 years, including revolutionary wars, ethnic wars, and regime crises” from the
State Failure Problem Set. In the cases included in this study, political upheaval values range from 0
to 33, although two clusters are apparent: value 4 and below, and 9 and above; thus we code
anything as P = 0 if the value is 4 or below, anything of 9 or higher as P = 1, making 7 cases of political
upheaval and 15 with this variable absent.
Exclusionary ideology (I)
Harff (2009c; see also Harff 2003, 63) codes exclusionary ideology herself, as “belief systems that are
articulated by governing elite, and that identify some kind of overriding purpose or principle that is
used to restrict, persecute, or eliminate categories of people who are defined as antithetical to that
purpose or principle.” Hereby, 1 signals the presence of such exclusionary ideologies among the
elites (6 cases), and 0 their absence (16 cases).
Autocratic regime (A)
This indicator of whether a regime is autocratic (1) or non-autocratic (0) is taken from the Polity IV
dataset variable POLITY, which subtracts a country’s autocracy score (scale 0-10) from its democracy
3
The cases are Colombia (1948-1960), Lebanon (1975-1991), Liberia (1989-1993), Mexico (2007 and ongoing),
Nicaragua (1978-1979), Romania (1989), Russia (1994-1996), Tajikistan (1992-1998), Yemen (1962-1970),
Zimbabwe (1972-1979), Chad (1965-1994), Congo-Brazzaville (1997-1999), Croatia (1991-1995).
score (scale 0-10); if POLITY is between -10 and 0, A is coded as 1 (19 cases), otherwise it is coded 0
(3 cases). These data points are again taken from Harff’s dataset.4
Discrimination resulting from ethnic and religious cleavages (D)
Regarding ethnic and religious cleavages and discrimination, Harff (2003) tested several different
variables, although primarily of interest here is only the one which was significant in Harff’s study:
whether elites disproportionately hail from one ethnic group. Nonetheless, another measure
regarding state-level discrimination has also been included in the QCA as an alternative
measurement.
For the main variable of discrimination due to elite ethnicity we differentiate between elite ethnicity
not being salient (0) (5 cases) and ethnicity being salient whereby the political leadership is
representative of a majority or minority communal group or coalition (1) (17 cases). In Harff’s
analysis, she divides the latter category into two; however, in order to dichotimise this variable
appropriately, it is theoretically more plausible to distinguish between whether ethnicity is salient
than between majority and minority representation, then including majority representation with the
non-salient category.
A second variable which was created for the State Failure Problem Set from Minority at Risk data is
official state discrimination. To create a dichotomous variable here, we added the values for active
political discrimination and active economic discrimination of a group together, and then coded any
variable below the average as 0 (14 cases) and above the average as 1 (8 cases). In fact, there were
no values close to the average, making this dichotomisation clearly justifiable.
Economic autarky (E)
Data were missing for most relevant countries in Harff’s dataset, so a new variable was created using
World Bank data. Import and export data were added together (as percentages of the country’s gross
domestic product in the relevant year) to indicate the trade openness of a country. Case were coded
as economically autarkic (1) if their trade percentage was below the average of all cases in our
dataset (12 cases), and as economically interdependent (0) if these trade indicators were above
average (10 cases). Again, no cases are close to the average, making none of the codings
controversial.
4
For the precise coding procedure please see Marshall et al. (2011, 15ff.).
Coding problems
The following variables had no data available in Harff’s dataset (or the alternative sources which
were used) for these specific cases, thus necessitating a manual coding after a qualitative
assessment. None of the five codings is particularly controversial.
Colombia 1948-1960 – exclusionist ideology: The period known as ‘La Violencia’ saw a violent civil
conflict between the Conservative and Liberal parties; the two sides were in a bitter struggle vying
for power, however this was not founded on a belief system that justified the restriction or
elimination of the other side. Each side simply wanted to take power. Thus this variable was coded 0.
Colombia 1948-1960 – discrimination due to elite ethnicity: In ‘La Violencia’ the ethnicity of the elite
was not particularly salient, as the main issue was their social status. While ethnicity did run as a
more or less parallel cleavage (white landowners and indigenous peasants), the conflict itself was not
framed in ethnic but in social and economic terms, thus dictating a coding of 0 for this variable.
Iraq 1988-1991 – economic autarky: This case is coded as economically interdependent (not autarkic
= 0) as the country was vulnerable to outside economic pressure due to its high oil exports. While in
1988 the effects of the Iran-Iraq war (1980-1988) had reduced previously high oil exports and
miscellaneous imports to a lower level, this recovered to a certain degree in 1988.
Lebanon 1975-1991 – economic autarky: The Lebanese economy was extremely vulnerable to
external influence and thus coded as not autarkic (0). As one of the most open economies in the
region it had very high exports and imports.
North Yemen 1962-1970 – economic autarky: The North Yemeni economy has been classified as
autarkic (1) as the country’s economy was characterised by low trade relations with other countries
prior to 1962, with the economy based on feudal relations and an underdeveloped infrastructure,
rendering the economy relatively isolated from the rest of the world.
6. Why do Genocides Occur? Empirical Results from the QCA
Case data
To approach this data with QCA, first each variable must be specified for each of the cases. Figure 2
lists all cases included in this study and their respective values for the relevant variables.5 Purely by
looking at this unsorted table it is plain to see that autocratic regimes (A) are present in all genocide
cases, making them necessary for the outcome of genocide occurrence. However, some cases of non5
The alternative measurement of ethnic discrimination is not featured here, but results will be reported as
necessary during the analysis.
Cambodia
Indonesia
Nigeria
Pakistan
Rwanda
Sudan
Afghanistan
Bosnia and
Herzegovina
Burundi
China
Iraq
Colombia
Lebanon
Liberia
Nicaragua
Russia
Tajikistan
Yemen
Zimbabwe
Chad
CongoBrazzaville
Croatia
Total
Genocide
Political Exclusionist Economic Elite Ethnicity
Occurrence Upheaval
Ideology
Autarky Discrimination
(G)
(P)
(D)
(I)
(E)
1
1
1
1
1
1
1
1
1
1
1
1
0
1
1
1
0
0
1
1
1
1
0
0
1
1
1
1
1
1
1
0
1
1
1
1
0
0
0
1
Autocratic
Regime
(A)
1
1
1
1
1
1
1
1
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
1
1
0
0
0
0
0
0
0
0
0
0
1
1
0
0
0
0
0
0
0
0
0
0
1
1
0
1
0
0
0
0
1
1
0
1
0
1
0
1
0
1
1
0
0
1
0
1
1
1
1
1
1
1
0
1
1
0
1
1
0
1
1
0
13
0
7
0
6
0
12
1
17
1
19
Figure 2: Overview of cases with their respective values on all major included variables.
genocide also occur in autocracies – thus an autocracy is a necessary condition for genocide
occurrence, but not sufficient. In a next step, one can analyse what conditions are sufficient to cause
genocide occurrence. This analysis is the cornerstone of QCA and requires the re-categorisation of
this information into a truth table sorted by combinations of variables.
Truth table
The truth table (Figure 3) has 32 rows to accommodate all possible logical combinations of the
dichotomous variables. Of these theoretical combinations 13 have actual empirical cases, while 19
have no empirical observations; however, this does not mean that these combinations do not
actually exist, but merely that it is not part of this sample. As there is no way of knowing whether this
combination would in reality actually be a genocide or not, combinations of variables with no
empirical cases are coded as ‘don’t cares’ ( - ) meaning that they can take on the property of
genocide or non-genocide during the reduction processes. Of the 13 combinations with empirical
1
~P ~I ~E D A
0
0
0
Elite
Ethnicity
Discrimination
(D)
1
1
4 (1)
0.25
0?
2
~P ~I E D A
0
0
1
1
1
4 (2)
0.5
?
3
PIEDA
1
1
1
1
1
3 (3)
1.0
1
4
~P ~I ~E D ~A
0
0
1
0
0
2 (0)
0.0
0
5
0
0
0
0
0
1 (0)
0.0
0
6
~P ~I ~E ~D
~A
~P ~I ~E ~D A
0
0
0
0
1
1 (0)
0.0
0
7
~P ~I E ~D A
0
0
1
0
1
1 (0)
0.0
0
8
~P I E ~D A
0
1
1
0
1
1 (1)
1.0
1
9
~P I E D A
0
1
1
1
1
1 (1)
1.0
1
10
P ~I ~E D A
1
0
0
1
1
1 (1)
1.0
1
11
P ~I E ~D A
1
0
1
0
1
1 (0)
0.0
0
Combination
Political
Upheaval
(P)
Exclusionist
Ideology
(I)
Economic
Autarky
(E)
Autocratic
Regime
(A)
Cases (of
which G)
Consistency
Outcome G
12
P ~I E D A
1
0
1
1
1
1 (1)
1.0
1
13
P I ~E D A
1
1
0
1
1
1 (1)
1.0
1
14
~P ~I E ~D ~A
0
0
1
0
0
0 (0)
-
15
~P ~I E D ~A
0
0
1
1
0
0 (0)
-
16
~P I ~E ~D ~A
0
1
0
0
0
0 (0)
-
17
~P I ~E ~D A
0
1
0
0
1
0 (0)
-
18
~P I ~E D ~A
0
1
0
1
0
0 (0)
-
19
~P I ~E D A
0
1
0
1
1
0 (0)
-
20
~P I E ~D ~A
0
1
1
0
0
0 (0)
-
21
~P I E D ~A
0
1
1
1
0
0 (0)
-
22
P ~I ~E ~D ~A
1
0
0
0
0
0 (0)
-
23
P ~I ~E ~D A
1
0
0
0
1
0 (0)
-
24
P ~I ~E D ~A
1
0
0
1
0
0 (0)
-
25
P ~I E ~D ~A
1
0
1
0
0
0 (0)
-
26
P ~I E D ~A
1
0
1
1
0
0 (0)
-
27
P I ~E ~D ~A
1
1
0
0
0
0 (0)
-
28
P I ~E ~D A
1
1
0
0
1
0 (0)
-
29
P I ~E D ~A
1
1
0
1
0
0 (0)
-
30
P I E ~D ~A
1
1
1
0
0
0 (0)
-
31
P I E ~D A
1
1
1
0
1
0 (0)
-
32
P I E D ~A
1
1
1
1
0
0 (0)
-
Figure 3: Truth table listing all logical combinations of variables, their empirical frequency and the coding as
used in the analysis. The dash “-“ signifies ‘don’t care’ (meaning that these combinations can be used as either
genocide occurrence or non-occurrence in the reduction algebra), while ? indicates empirically ambiguous
combinations, of which both genocides and non-genocides are to be found in the dataset (in the analysis these
? will be turned to - or 0, as specified).
examples, 11 are clear regarding the outcome and can thus be coded as such. The remaining two
combinations encompass 4 cases each (combinations 1 and 2), and are marked by question marks
(?), as they are not clearly ‘consistent’ and their coding must be discussed in detail. Possible solutions
would be to code them both as 0, so as not to include any non-genocides in the genocide category,
or vice versa as 1 to ensure that all genocides are covered, even if some non-genocides get mixed up
in the categorisation, too. Alternatively, however, the two fields could be excluded completely from
the analysis or marked as ‘don’t cares’, swinging both ways depending on what is needed in the
reduction. For combination 1 it makes sense to code this as 0 as there are three non-genocides in this
category and only one genocide – the one genocide case in this context is Bosnia, which is thus now
coded as non-genocide.6 Combination 2 on the other hand has both two genocides (Pakistan and
Burundi) and two non-genocides (Tajikistan and Chad) and this was run twice with this combination
once excluded and once coded as ‘don’t care’. While there were slight differences in the outcome,
these were relatively small. We here report the results for the combination 2 being excluded
completely from the analysis. Nonetheless, this does mean that the genocide cases of Bosnia,
Pakistan and Burundi will not be able to be explained in this model.
Results and Interpretation
Key determinants of genocide occurrence
As mentioned above, one very central insight from this QCA procedure is that the presence of
autocracy is a necessary condition for the occurrence of genocide. The truth table, however, lets one
also find out further central conditions which are sufficient for genocide occurrence, that is that the
presence of this combination will always lead to the outcome, although not all instances of the
outcome will be caused by this combination. When the data from Figure 3 is reduced according to
the principles of Boolean algebra (see section 4), one receives the following formula:
Solution 1: P * D * A + I * E * A
Substantively this means that genocide occurs in autocratic countries in which either there is political
upheaval combined with an elite whose ethnicity is salient, or there is an exclusionary ideology
combined with an autarkic economy. Which cases are covered by these combinations are listed in
Figure 4, along with their consistency and coverage scores. Consistency scores indicate how good a
fit a particular combination is, that is how many non-genocides are also described by this term.
Coverage scores show how many of the genocide cases can be explained by this solution – raw
scores detail how many cases are covered by this combination, while unique coverage means the
cases which are explained only by this combination. To a certain degree, there is a trade-off between
the consistency and coverage scores, as a solution with a higher consistency (thus explaining only the
phenomenon itself and less ‘other cases’ too) will possibly not be able to explain the same amount of
breadth as a very inclusive solution which explains all cases but also includes some non-genocides
6
As it is controversial coding Bosnia as a non-genocide, the analysis was also run with this combination coded
as ‘don’t care’; the results were nearly identical, the only difference being that in the more parsimonious
solution A *D was a combination, and was not interchangeable with P * D and E * D. This is a small difference
given that the cases covered are identical. Also, on alternative coding for this case please see footnote 7 below.
Cases covered
Cambodia,
Indonesia, Nigeria,
Rwanda, Sudan, Iraq
I*E*A
Cambodia,
Indonesia, Sudan,
Afghanistan, China
Solution coverage: 0.727
P*D*A
Raw coverage
Unique coverage
Consistency
0.545
0.273
1.0
0.455
0.182
1.0
Solution consistency: 1.0
Figure 4:Solution 1 case coverage and consistency by combinations
too. The consistency scores of 1 in this case, however, indicate that there are no non-genocides
occurring with these combinations of variables, thus making these combinations truly sufficient for
causing genocide occurrence. The score for overall coverage is explained by the exclusion of Pakistan
and Burundi, and with the re-coding of Bosnia as 0. Thus these three cases are not explained by this
conjunctural solution.
Both the combinations are substantively plausible. First, an autocratic system with elites whose
ethnicity is particularly salient which comes into a time of political upheaval is susceptible to
genocide, as these elites will want to try and cling to their position of power in the upheaval by
mobilising along ethnic lines. This mobilisation can then easily lead to a demonisation of the ethnic
group which the elites fear could take over power and the subsequent call for their elimination. A
prime example of this combination is the 1994 genocide in Rwanda in which the autocratic Hutu
majority government (in which their Hutu ethnicity was certainly salient) feared that it would lose
power through the monumental changes happening in the country, most specifically through the
power-sharing agreement which was being signed in the Arusha Accords. This agreement would have
given the Tutsi ethnic group significant powers in government, thus causing Hutu radicals to mobilise
along ethnic lines against this agreement and against the Tutsis as a whole. This attempt to retain
power during a political upheaval underlines the dynamics of this combination very well.7
While the P * D * A emphasises the motivational structure that can lead some elites to pursue
genocide as a strategy, I * E * A also incorporates the importance in some cases of an opportunity
structure which is conducive to genocide. This second combination – again in an autocratic regime –
7
A very similar situation was present in Bosnia in 1992 in the context of the dissolution of Yugoslavia. The
autocratic regime had elites whose ethnicity was certainly salient, however, according to Harff’s dataset Bosnia
was not in a context of political upheaval in 1992. Even if the situation in Bosnia does not match the State
Failure Problem Set definition of political upheaval, it can well be argued that Bosnia was undergoing a severe
and unsettling transition which, as in Rwanda, caused elites to mobilise along ethnic lines to sustain their
power. In order to stay consistent with Harff’s analysis, this value for political upheaval was not changed, but
an alternative coding would lead to a fit on this case to, and thus also higher coverage scores.
is based on the interplay between an exclusionary ideology and economic autarky, with the
exclusionary ideology suggesting the motivation for genocide, while the lack of economic ties
provides a conducive environment for this plan to be executed. A country with few economic ties has
several key advantages for a genocidally inclined elite: first, it has relatively little to fear from
economic sanctions by other countries, as these will not impact the overall economy very strongly;
second, as countries seldom intervene militarily in other countries purely out of humanitarian
compassion, powerful countries are less inclined to attempt prevention of the genocide militarily as
they have few economic interests in the genocidal country.
An alternative, more parsimonious solution
The data can, however, also be reduced to an alternative format. Solution 2 tries to reduce the data
to as few variables as possible. While this provides a more parsimonious presentation of the data, it
lacks some of the causal insights of the above suggestion:
Solution 2: I + P * D + P * ~E
This solution provides three alternatives which are each sufficient for causing genocide. First, the
presence of an exclusionary ideology is enough to cause genocide; second, political upheaval in a
polity in which elite ethnicity is salient; third, political upheaval in a context of economic
interdependence (lack of economic autarky). The cases covered and their coverage and consistency
are listed in Figure 5. However, P * D could be replaced with either A * D or E * D as these all cover
the same cases equally, with the same consistency and coverage scores.
Compared with Solution 1, it is striking that the variable A is missing from all three combinations. This
is not necessarily surprising, however, as an autocratic regime is a necessary condition, but by no
means must it be a sufficient condition. The presence of an exclusionary ideology, however, is
sufficient, as only cases of genocide have such ideologies; given the essence of such ideologies, this is
also substantively plausible. Also, the second combination of variables (P * D) is similar to above,
following the same logic of emphasising the salience of elite ethnicity in the context of political
upheaval. The final combination, however, is substantively different with genocide being caused by
political upheaval combined with a country which is interdependent economically. While this could
be argued along the lines that trade openness allows for an easier flow of weapons, this is certainly
not the central dynamic in the two cases it purports to explain (Rwanda and Iraq) and it must be said
that they are both much better explained by other combinations of variables.8
8
While millions of machetes were imported into Rwanda prior to the genocide, this cannot be seen as the
central dynamic leading to genocide. This was merely an action as part of the preparations for the genocide
which was caused by other, much more substantial reasons.
I
P*D
P * ~E
Cases covered
Raw coverage
Unique coverage
Consistency
Cambodia,
Indonesia, Sudan,
Afghanistan,
China, Iraq
Cambodia,
Indonesia,
Nigeria, Rwanda,
Sudan, Iraq
Rwanda, Iraq
0.545
0.182
1.0
0.545
0.091
1.0
0.182
0.0
1.0
Solution coverage: 0.727
Solution consistency: 1.0
Figure 5: Solution 2 case coverage and consistency by combinations
Altogether, the more parsimonious Solution 2 does not appear to actually simplify our
understanding of genocide occurrence, with the confusing role of P * ~E and the interchangeable
status of P * D, A * D or E * D; moreover, the slightly more complex combinations in Solution 1 also
pay homage to the important role of the necessary condition of the presence of an authoritarian
regime. Thus, the best presentation of the results of the QCA in this paper remain P * D * A + I * E *
A.
Alternative operationalisation of ethnic discrimination
As expounded on in the theoretical section, there are several different ways in which ethnic diversity
can impact genocide occurrence. The variable used above measured whether the ethnicity of elites
was salient, but the QCA was conducted also with variables measuring the occurrence of state-led
political and economic discrimination. This variable resulted in the same results as described above
even though in Harff the variable remained insignificant. This demonstrates that the quantitative
methods used previously could not pick up on similar effects that were only demonstrated using
QCA’s conjunctural logic.
Determinants of genocide non-occurrence
It is also interesting to look into what causes can be seen as sufficient and necessary for genocide not
to occur in a country. By again looking at the table in Figure 2, one can say that the absence of an
exclusionary ideology (~I) is a necessary condition, as all cases lack such ideologies, but it is not
sufficient as there are several genocidal cases without exclusionary ideologies. While the absence of
political upheaval is nearly a necessary condition, there is one case (Colombia) in which political
upheaval occurs without resulting in genocide. Thus, this cannot be a necessary condition. Figure 6
Political
ExcluEconomic
Elite
Auto- Cases (of Consistency
Upheaval sionist
Autarky Ethnicity cratic which ~G)
(P)
Ideology
(E)
Discrim- Regime
(I)
ination (A)
(D)
1 ~P ~I ~E D A
0
0
0
1
1
4 (3)
0.75
2 ~P ~I E D A
0
0
1
1
1
4 (2)
0.5
3 PIEDA
1
1
1
1
1
3 (0)
0.0
4 ~P ~I ~E D ~A
0
0
0
1
0
2 (2)
1.0
5 ~P ~I ~E ~D ~A
0
0
0
0
0
1 (1)
1.0
6 ~P ~I ~E ~D A
0
0
0
0
1
1 (1)
1.0
7 ~P ~I E ~D A
0
0
1
0
1
1 (1)
1.0
8 ~P I E ~D A
0
1
1
0
1
1 (0)
0.0
9 ~P I E D A
0
1
1
1
1
1 (0)
0.0
10 P ~I ~E D A
1
0
0
1
1
1 (0)
0.0
11 P ~I E ~D A
1
0
1
0
1
1 (1)
1.0
12 P ~I E D A
1
0
1
1
1
1 (0)
0.0
13 P I ~E D A
1
1
0
1
1
1 (0)
0.0
14 ~P ~I E ~D ~A
0
0
1
0
0
0 (0)
15 ~P ~I E D ~A
0
0
1
1
0
0 (0)
16 ~P I ~E ~D ~A
0
1
0
0
0
0 (0)
17 ~P I ~E ~D A
0
1
0
0
1
0 (0)
18 ~P I ~E D ~A
0
1
0
1
0
0 (0)
19 ~P I ~E D A
0
1
0
1
1
0 (0)
20 ~P I E ~D ~A
0
1
1
0
0
0 (0)
21 ~P I E D ~A
0
1
1
1
0
0 (0)
22 P ~I ~E ~D ~A
1
0
0
0
0
0 (0)
23 P ~I ~E ~D A
1
0
0
0
1
0 (0)
24 P ~I ~E D ~A
1
0
0
1
0
0 (0)
25 P ~I E ~D ~A
1
0
1
0
0
0 (0)
26 P ~I E D ~A
1
0
1
1
0
0 (0)
27 P I ~E ~D ~A
1
1
0
0
0
0 (0)
28 P I ~E ~D A
1
1
0
0
1
0 (0)
29 P I ~E D ~A
1
1
0
1
0
0 (0)
30 P I E ~D ~A
1
1
1
0
0
0 (0)
31 P I E ~D A
1
1
1
0
1
0 (0)
32 P I E D ~A
1
1
1
1
0
0 (0)
Combination
Outcome G
1?
?
0
1
1
1
1
0
0
0
1
0
0
-
Figure 6: Truth table for genocide non-occurrence. See Figure 3 for details.
shows the truth table for this analysis, which is an inversion of the truth table for genocide
occurrence in Figure 3, with the variable values remaining, just the cases and consistency and
outcome changing.
Using this data for genocide non-occurrence results in following combinations – Solution 3 is again
the more complex version, with more variables per combination but less combinations in total, and
Solution 4 is more parsimonious9:
Solution 3: ~D * ~I + ~E * ~I * ~P
Solution 4: ~D * ~I + ~E * ~P + ~I * ~P + P * ~D + ~A
Solution 3 and 4 tell us first that if elite ethnicity (D) is not salient and an exclusionary ideology (I) is
not present, then genocide will not occur; this fits the theoretical arguments above, as there is no
motivation for elites to identify a specific group for eradication if ethnicity is not salient in
governance and there is no respective ideology. Likewise, if a country that is not in a time of political
upheaval either lacks an exclusionary ideology or is economically interdependent with the rest of the
world, then genocide will not occur. Particularly the latter is an opportunity-centric argument,
demonstrating that economic ties have an inhibitive effect, and also that without political upheaval
there is little room for elites to launch a genocidal campaign in the absence of a prevalent
exclusionary ideology. However, genocide will only certainly not occur in the context of political
upheaval when ethnicity is not an issue in the elites of a country. Finally, democracy is a guarantor of
genocide avoidance.
Evaluation of the hypotheses
Hypothesis 1: Political upheaval is a necessary and sufficient condition to all genocide occurrences.
The influence of political upheaval was not as conclusive as expected, considering its prominent
position in the literature. In combination with ethnic discrimination and an authoritarian setting, it
poses a sufficient condition. However, with only six of eleven cases of genocide occurring in the
context of political upheaval, it is certainly not a necessary condition. As explained in footnote 7 this
could partly be due to coding deficiencies in the original dataset.
Hypothesis 2: Official state discrimination, or biased elite representation are sufficient, although not
necessary for genocide to occur. It is expected that they will have similar impact in the analysis.
This variable’s impact was adequately predicted as it did not turn out to be necessary for genocide
occurrence but was sufficient in combination with political upheaval.
9
Solution 3’s coverage is 0.818 and its consistency is 0.9, meaning that some genocides are wrongly predicted
as non-genocides according to this solution (consistency), but that more than 4 in 5 non-genocides can be
accurately forecasted. The coverage in Solution 4 is 1.0 and thus predicts every case of non-genocide, however,
the consistency is lower at 0.786, thus making nearly every fourth prediction of non-genocide actually a
genocide case.
Hypothesis 3: The presence of an autocratic regime is necessary for genocide occurrence and could be
sufficient in combination with political upheaval or an exclusionary ideology.
The role of autocratic regimes was accurately predicted as necessary by the theory and the
predictions for sufficiency were correct, although not specific enough: Autocracy is sufficient for
genocide occurrence in combination with political upheaval (when ethnic discrimination is present
too) and an exclusionary ideology combined with autocracy is also sufficient (along with economic
autarky).
Hypothesis 4: An exclusionary ideology is sufficient for genocide to occur.
This hypothesis can also be seen as fulfilled, as it was the only factor which singularly caused
genocide occurrence on its own but was not present in any cases of non-occurrence.
Hypothesis 5: Economic autarky is facilitative for genocide occurrence in some conditions, although it
will have no stand-alone impact.
Finally, this variable’s impact was underestimated to a certain degree as it went beyond merely a
facilitative effect showing itself to be a sufficient condition for genocide occurrence in combination
with an exclusionary ideology in an autocratic system. Given that autocracy is necessary for genocide
occurrence and an exclusionary ideology is sufficient on its own, however, this does undermine the
importance of this variable’s impact. Also, contrary to the theory, in combination with political
upheaval this variable’s influence is shown to be sufficient in its absence. Altogether then, the impact
of economic autarky is mixed and would need closer inspection.
7. Conclusion and Outlook
The aim of this paper was to look into the research question of why genocides occur and what
combinations of factors play together to determine this occurrence, and further this research agenda
by applying a different methodology to any previous studies. Using the conjunctural and
combinatorial logic of Qualitative Comparative Analysis (QCA) this paper examined 22 cases of
genocide and non-genocide. The analysis of the truth table revealed that the presence of an
authoritarian regime is necessary for genocide to occur, and that the presence of an exclusionary
ideology is sufficient. Furthermore, the following combinations of factors are sufficient in causing
genocide:
P * D * A + I * E * A.
All genocidal countries are authoritarian, but those regimes which are led by elites whose ethnic
affiliation is salient to politics will experience genocide if they then encounter political upheaval as
the governing elites will try to maintain power by mobilising along ethnic lines. Also, in an autocratic
regime which is economically autarkic genocide will occur when there is also the presence of an
exclusionary ideology.
While these results are plausible and insightful, how do they compare to the benchmark for this
paper, Harff’s (2003) statistical paper on genocide and politicide occurrence? Harff identifies six
variables that impact the likelihood of genocide occurrence with a certain degree of statistical
significance. In order of their substantive effect, measured as an odds ratio, the variables that effect
a higher risk of genocide are: autocracy (A in this study), prior genocide, low trade openness (E), the
ruling elite coming from an ethnic minority (D), exclusionary ideology (I) and political upheaval (P).
Only prior genocide was not tested here, as this was precluded by the way the sample was drawn.
While this paper has found support for Harff’s work that these identified variables are important, it
goes beyond this and actually specifies in which contexts which variables come to fruition, and what
combinations will prove lethal. It is important to remember that the majority of the data used here,
was the same as used by Harff, in order to ensure the comparability of the two studies. A major step
forward from Harff’s study is that this paper has demonstrated that autocracy is a necessary
condition, not merely a very high risk. Furthermore, it has not played the different variables off
against each other for the highest impact of an individual variable. Instead this paper has examined
how the variables interact and combine with each other in different unique conditions.
This paper has shown that QCA provides a helpful methodological approach to the study of genocide
and it should certainly become more widely used throughout peace and conflict research. Although
QCA is often portrayed as a method for datasets which are too large for simple qualitative
comparisons and too small for viable statistical analyses, it is also possible to use QCA with large
numbers of cases, as these are all still categorised by combinations in the truth table. The higher the
number of cases, the higher the threshold should be for coding something as a particular outcome,
but this will also facilitate picking up on outliers. Thus, while this study has already demonstrated
considerable progress in understanding genocide occurrence, future research could be conducted
with an expanded case set and with expanded tests for robustness and varying cut-off points for
classification, all procedures which would have gone beyond the scope of this paper. Furthermore,
future research could include better operationalisations of certain key variables which were not
applied here, as this paper wanted to remain as close to the Harff original study to enhance
comparability. For instance, a better measure for political upheaval or discrimination due to ethnic
pluralism could be employed. Lastly, future research should also go beyond crisp set QCA as used
here and embrace fuzzy set QCA – this would only be possible with a new dataset as the State Failure
Problem Set codes genocide dichotomously, whereas fuzzy set QCA requires more a nuanced
attribution of set membership.
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